Renal care readiness and gaps in early detection of sickle cell nephropathy in children in North Kivu Province, Democratic Republic of the Congo: an exploratory cross-sectional study

Renal care readiness and gaps in early detection of sickle cell nephropathy in children in North Kivu Province, Democratic Republic of the Congo: an exploratory cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Renal care readiness and gaps in early detection of sickle cell nephropathy in children in North Kivu Province, Democratic Republic of the Congo: an exploratory cross-sectional study Mupenzi Mumbere, Charles Kahindo Kangitsi, Victor Kambale Malengera, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8630909/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract Background Sickle cell nephropathy is a common and progressive complication of sickle cell disease in children and a major contributor to early morbidity and long-term chronic kidney disease. Although early renal screening is essential to prevent irreversible damage, its implementation remains limited in resource-constrained settings. This study assessed healthcare provider readiness for the early detection and management of sickle cell nephropathy in North Kivu Province, Democratic Republic of the Congo. Methods We conducted an exploratory cross-sectional study among medical and paramedical healthcare providers involved in the care of children with sickle cell disease. Data were collected using a structured electronic questionnaire evaluating knowledge, attitudes, practices, and diagnostic availability related to renal screening. Composite scores were constructed for these domains, and factors associated with adequate renal care readiness were examined using multivariable logistic regression. Results Two hundred providers were included. Adequate knowledge was observed in 50.5% of participants, while only 21.0% demonstrated favorable attitudes. Reported practices were poor, with good practice identified in only 4.1% of respondents. Diagnostic availability was limited (mean score 39.8 ± 23.5), particularly in primary and secondary facilities. Overall renal care readiness was suboptimal, and adequate diagnostic availability emerged as the main independent determinant. Key barriers included recurrent shortages of diagnostic supplies, financial constraints, and high workload, whereas standardized protocols and institutional support were reported as facilitators. Conclusions Despite moderate knowledge levels, early renal screening for children with sickle cell disease is insufficiently implemented in North Kivu. Health system capacity, especially access to essential diagnostic tools, is central to effective renal care readiness. Strengthening diagnostic availability, standardizing care pathways, and reinforcing targeted training may substantially improve early detection and prevention of kidney disease in resource-limited settings. Sickle cell nephropathy Early renal screening Healthcare provider readiness Diagnostic availability North-Kivu Democratic Republic of the Congo Introduction Sickle cell disease (SCD) is one of the most prevalent inherited hemoglobinopathies worldwide, affecting millions of individuals and disproportionately burdening sub-Saharan Africa, where more than 80% of affected children are born ( 1 ). Despite significant improvements in survival over recent decades, particularly in high-income countries, SCD remains associated with substantial morbidity and early mortality in low-resource settings. This disparity is largely driven by limited access to comprehensive care, delayed diagnosis of complications, and constrained health system capacity ( 2 ). Among the chronic complications of SCD, renal involvement (commonly referred to as sickle cell nephropathy (SCN)) represents a major yet often under-recognized contributor to long-term morbidity beginning in childhood ( 3 , 4 ). Sickle cell nephropathy encompasses a spectrum of functional and structural renal abnormalities that may appear early in life and progress insidiously. These include glomerular hyperfiltration, impaired urinary concentrating ability, microalbuminuria, hypertension, and, in advanced stages, chronic kidney disease (CKD) and end-stage kidney failure ( 3 , 5 ). Pediatric renal manifestations are frequently asymptomatic, allowing kidney damage to progress silently for years before clinical detection. Once overt proteinuria or reduced glomerular filtration rate becomes apparent, renal injury is often irreversible and associated with poor outcomes. Consequently, early identification of renal involvement in children with SCD is critical to prevent or delay progression to CKD and its associated complications ( 6 , 7 ). Current international and regional guidelines emphasize the importance of systematic renal screening in children with SCD. Recommended measures include regular blood pressure monitoring, annual screening for albuminuria, and periodic assessment of kidney function ( 8 , 9 ). Early detection enables timely implementation of preventive and therapeutic interventions, such as optimization of hydration, early initiation of hydroxyurea therapy, and the use of angiotensin converting enzyme inhibitors /angiotensin receptor blockers (ACEI/ARB) in selected cases ( 10 , 11 ). These strategies have been shown to reduce proteinuria, slow the progression of renal disease, and improve overall outcomes in children with SCD ( 11 , 12 ). However, the successful implementation of these recommendations depends not only on clinical knowledge but also on the availability of diagnostic tools, standardized clinical pathways, and adequately trained healthcare providers (HCPs) ( 13 ). In many low- and middle-income countries (LMIC), including those in the Democratic Republic of the Congo (DRC), the translation of evidence-based recommendations into routine clinical practice remains inconsistent. Healthcare systems often face structural constraints such as limited laboratory capacity, shortages of essential diagnostic tests, lack of standardized operating procedures (SOP), and insufficient opportunities for continuing professional training. In this context, HCPs may possess adequate theoretical knowledge and positive attitudes toward early renal screening yet remain unable to implement recommended practices consistently. Understanding the interplay between provider-related factors and system-level constraints is therefore essential for identifying realistic and sustainable strategies to improve renal care for children with SCD ( 14 – 18 ). While several studies have explored knowledge, attitudes, and practices related to general SCD management, relatively few have focused specifically on renal complications, and even fewer have addressed early screening for SCN in pediatric populations ( 19 – 22 ). Moreover, data from the DRC are particularly scarce, despite the high prevalence of SCD and the significant burden of kidney disease in the region ( 23 – 25 ). Existing studies often emphasize patient-level outcomes, leaving a critical gap in understanding HCP readiness and health system preparedness to deliver effective renal preventive care. Addressing this gap is essential for informing policy decisions, guiding capacity-building initiatives, and improving long-term renal outcomes for children with SCD. North Kivu Province in the DRC represents a setting where these challenges are particularly pronounced. The region is characterized by a relatively high burden of SCD, limited diagnostic infrastructure, and heterogeneous healthcare delivery across urban and rural settings ( 18 , 26 ). Despite these constraints, HCPs play a central role in the early identification and management of renal complications in children with SCD. Evaluating their readiness to implement recommended renal screening practices offers valuable insight into existing gaps and potential leverage points for intervention. Importantly, the challenges observed in North Kivu are not unique and reflect broader issues faced by many resource-limited settings globally. The present study aimed to assess renal care readiness for the early detection and management of SCN in children in North Kivu Province by evaluating HCPs’ knowledge, attitudes, practices, and diagnostic availability. By identifying determinants of adequate renal care readiness and highlighting key barriers and facilitators to implementation, this study seeks to generate actionable evidence to inform strategies for strengthening early renal screening and preventive care. The findings are intended to contribute not only to local improvement efforts but also to the broader discourse on optimizing pediatric nephrology care for children with SCD in low-resource settings worldwide. Methods Study design and setting To address these gaps, we conducted a quantitative, exploratory cross-sectional study with descriptive and analytical components among HCPs working in North Kivu Province, eastern DRC. The study was observational in nature and involved no intervention or modification of participants’ clinical behaviors or practices. Data collection was carried out between 16 October and 30 November 2025. The study included healthcare facilities across all levels of care (primary, secondary, and tertiary) and all types of structures (public, faith-based, and private), in both urban and non-urban settings. Study population The study population consisted of medical and paramedical HCPs actively working in health facilities in North Kivu Province and potentially involved in the screening, follow-up, or management of SCD in children and/or its renal complications. Medical staff included general practitioners and medical specialists, while paramedical staff comprised nurses and laboratory technicians/medical biologists. Eligibility criteria Inclusion criteria Participants were eligible if they: were members of the medical or paramedical workforce practicing in North Kivu Province; were aged 18 years or older; provided free and informed consent to participate through electronic confirmation. Exclusion criteria Participants were excluded if the responses to their questionnaires were: incomplete; or internally inconsistent based on predefined coherence checks. Sample size calculation The primary objective was to estimate the proportion of HCPs with an adequate level of knowledge, attitudes, and practices (KAP score ≥ 70) regarding the management of SCN in children. Sample size was calculated using Cochran’s formula for estimating a proportion in an assumed infinite population. A conservative expected proportion of 50% was used in the absence of prior regional estimates, with a 95% confidence level (Z = 1.96) and an absolute precision of 7%. A design effect of 1.0 was assumed due to light stratification by professional category, level of care, and geographic zone. To account for anticipated non-response in an online survey context, a conservative response rate of 50% was applied, yielding a minimum recruitment target of 196 respondents. This approach was chosen to maximize statistical power and ensure adequate precision. Ultimately, 200 valid responses were included in the final analysis. Sampling strategy Because the exact size of the eligible population with internet access was unknown, a non-probabilistic quota sampling strategy was adopted. Quotas were defined according to three key stratification variables: professional category (physicians, nurses, laboratory staff), level of care (primary, secondary, tertiary), and geographic zone (urban versus non-urban). Participant inclusion occurred on a first-come, first-served basis until both the overall target of valid questionnaires (≥ 196) and minimum stratum-specific quotas were approached. Despite repeated targeted reminders, some predefined quotas could not be fully achieved, particularly among paramedical staff and certain levels of care. Data collection procedures Data were collected using a pretested structured, self-administered electronic questionnaire developed in French and deployed via the KoboCollect platform. The survey link was disseminated through institutional communication channels and professional WhatsApp groups across health zones in North Kivu Province. Weekly reminders were issued by the principal investigator throughout the data collection period. To ensure data completeness, all questionnaire items were configured as mandatory within KoboCollect, preventing submission unless all questions were answered. Upon completion of data collection, the dataset was exported to Microsoft Excel (Microsoft 365) for initial processing. A manual data-cleaning process was then conducted to verify internal consistency and identify anomalous response patterns. Following this process, the dataset was frozen and constituted the definitive version used for all statistical analyses, with no further modifications permitted to preserve data integrity and reproducibility. Study variables and operational definitions Knowledge score (K) Knowledge was assessed using 23 items addressing key aspects of SCD and SCN, including diagnostic principles, early renal screening strategies, indications for ACEI/ARBs, hydroxyurea use, referral criteria, renal risk factors, and the role of cystatin C. Items were formatted as true/false questions with an additional “I do not know” option. Correct responses were scored as 1, while incorrect or “I do not know” responses were scored as 0. The knowledge score was calculated as the percentage of correct answers and ranged from 0 to 100. Scores were categorized as adequate (≥ 70), intermediate (50–69), or insufficient (< 50). Attitudes score (A) Attitudes toward early renal screening were measured using 12 Likert-scale items ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). Negatively worded items were reverse-coded to ensure consistent score orientation. Individual attitude scores were computed as the mean Likert score and standardized to a 0-100 scale using the formula: A = ((mean Likert score − 1) / 4) × 100 . Scores were categorized as favorable (≥ 70), neutral (50–69), or unfavorable (< 50). Internal consistency was assessed using Cronbach’s alpha, with values ≥ 0.70 considered acceptable. Practices score (P) Practices related to renal screening and management were evaluated using 13 items assessing the frequency of recommended clinical actions. Frequency responses (“never,” “rarely,” “sometimes,” “often,” “always”) were coded as 0, 25, 50, 75, and 100, respectively. Binary items were coded as 100 for recommended practice and 0 otherwise. The practices score was calculated as the arithmetic mean of item scores and ranged from 0 to 100. Scores were categorized as good (≥ 70), moderate (50–69), or poor (< 50). Internal consistency was evaluated using Cronbach’s alpha. Composite indices A global KAP index was constructed as a weighted composite score: KAP = 0.40 × K + 0.30 × A + 0.30 × P . The index was categorized as adequate (≥ 70), intermediate (50–69), or insufficient (< 50). For multivariable analyses, KAP was dichotomized using a threshold of 50% to ensure sufficient category sizes. A Diagnostic Availability Index (DAI) was created based on the availability of essential diagnostic tools for early renal screening. Additional composite indices assessed therapeutic practices (TPI) and the implementation of standard operating procedures (GI-SOP), each normalized to a 0-100 scale. Independent variables Independent variables included sociodemographic, professional, and structural characteristics of HCPs and their working environments. These comprised sex, age group, years of professional experience, professional category, level and type of health facility, and geographical setting (urban versus rural/peri-urban). Statistical analysis Statistical analyses were performed using R software (version 4.5.2) and Microsoft Excel (Microsoft 365). In addition, the artificial intelligence tool ChatGPT (version 5.2) was used to support manuscript drafting and to assist in the selection of appropriate methodological and analytical approaches. Categorical variables were summarized using frequencies, percentages, and 95% confidence intervals (CI) calculated with the Wilson method. Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR), as appropriate. Normality was assessed using the Shapiro-Wilk test and visual inspection of distributions. Group comparisons were conducted using non-parametric tests (Mann-Whitney U or Kruskal-Wallis) as distributions were non-normal. Multivariable logistic regression was used to identify factors independently associated with insufficient operational performance (GI-SOP < 50%). Variables with p < 0.20 in univariable analyses were considered for multivariable modeling. Adjusted odds ratios with 95% confidence intervals were reported, and statistical significance was set at p < 0.05. Ethical considerations The study protocol was approved by an independent Ethics Committee, the “Comité d’Ethique du Nord-Kivu”. Participation was voluntary and based on electronic informed consent. Data were anonymized at the point of collection and stored on password-protected systems accessible only to authorized researchers. Results Study flow and participant inclusion A total of 212 questionnaires were submitted through the electronic data collection platform during the study period. After data cleaning, 12 questionnaires (5.7%) were excluded due to major internal inconsistencies. Consequently, 200 questionnaires (94.3%) were retained for the final descriptive and analytical analyses. Sociodemographic and professional characteristics of participants The final sample included 200 HCPs. Most participants were male (155/200, 77.5%; 95% CI 71.2–82.7), while 43 (21.5%; 95% CI 16.4–27.7) were female and 2 (1.0%) did not report sex. The majority were aged 30–39 years (40.5%) or 40–49 years (38.0%) (Table 1 ). Table 1 Sociodemographic and contextual characteristics of respondents (N = 200) Variable Category n (%) 95% CI Sex Male 155 (77.5) 71.2–82.7 Female 43 (21.5) 16.4–27.7 Undetermined 2 (1.0) 0.3–3.6 Age group (years) 30–39 81 (40.5) 33.9–47.4 40–49 76 (38.0) 31.6–44.9 ≥ 50 26 (13.0) 9.0-18.4 18–29 17 (8.5) 5.4–13.2 Professional category General practitioner 109 (54.5) 47.6–61.3 Other medical specialties 53 (26.5) 20.9–33.0 Nurse A1 13 (6.5) 3.8–10.8 Pediatrician / Pediatric resident 12 (6.0) 3.5–10.2 Laboratory technician 5 (2.5) 1.1–5.7 Medical biologist 4 (2.0) 0.8-5.0 Midwife 2 (1.0) 0.3–3.6 Nurse A0 2 (1.0) 0.3–3.6 Level of health facility Secondary 89 (44.5) 37.8–51.4 Primary 64 (32.0) 25.9–38.8 Tertiary 47 (23.5) 18.2–29.8 Geographical setting Urban 128 (64.0) 57.1–70.3 Rural/peri-urban 72 (36.0) 29.7–42.9 Regarding professional category, medical doctors accounted for 87.0% of participants, including general practitioners (54.5%), other medical specialties (26.5%), and pediatricians or pediatric residents (6.0%). Paramedical staff represented 13.0%, mainly nurses and laboratory personnel. Participants were predominantly employed in secondary-level facilities (44.5%), followed by primary-level (32.0%) and tertiary-level institutions (23.5%). Most respondents practiced in urban settings (64.0%), while 36.0% were based in rural or peri-urban areas (Table 1 ). Knowledge related to sickle cell nephropathy Knowledge was calculated for all 200 participants. The mean (SD) knowledge score was 70.0 (17.7), with a median (IQR) of 73.9 (56.5–82.6) and a range of 26.1–100 (Table 2 ). When categorized, 101 participants (50.5%; 95% CI 43.6–57.4) demonstrated adequate knowledge, 71 (35.5%; 95% CI 29.2–42.3) had intermediate knowledge, and 28 (14.0%; 95% CI 9.9–19.5) had insufficient knowledge (Table 3 ). Item-level analysis showed that while general concepts of SCD and renal involvement were widely recognized, important gaps persisted in technical aspects of early renal screening, including interpretation of estimated glomerular filtration rate (eGFR), the clinical utility of cystatin C, and indications for ACEI/ARBs (Additional file 1). Attitudes toward early renal screening Attitude was also available for all 200 participants. The mean (SD) attitude score was 61.7 (10.1), with a median (IQR) of 60.4 (54.2–68.8) and a range of 37.5–89.6 (Table 2 ). Only 42 participants (21.0%; 95% CI 15.9–27.2) demonstrated favorable attitudes, whereas the majority exhibited neutral attitudes (141/200, 70.5%; 95% CI 63.8–76.4). Seventeen participants (8.5%; 95% CI 5.4–13.2) had unfavorable attitudes (Table 3 ). Despite widespread acknowledgment of the importance of early renal screening, negative or hesitant attitudes were frequently associated with perceived financial constraints, limited laboratory capacity, and prioritization of acute hematologic or infectious complications over asymptomatic renal involvement (Additional file 2). Reported clinical practices related to renal screening Practice was calculated for 169 participants, reflecting the applicability of practice-related items. The mean (SD) practice score was 35.9 (19.9), with a median (IQR) of 34.6 (21.2–50.0) and a range of 0.0-94.2 (Table 2 ). Only 7 participants (4.1%; 95% CI 2.0-8.3) achieved good practice scores. Thirty-eight (22.5%; 95% CI 16.8–29.4) demonstrated moderate practices, while the vast majority, i.e. 124 participants (73.4%; 95% CI 66.2–79.5), had poor practices (Table 3 ). At the item level, recommended actions such as annual urine dipstick testing, routine blood pressure measurement, periodic assessment of kidney function, and documentation of renal findings were inconsistently implemented, particularly in primary and secondary healthcare facilities (Additional file 3). Table 2 Description of scores and indices Score / Index n Mean (SD) Median (IQR) Min-Max p-value (Shapiro-Wilk) Knowledge score (K, %, items 1–23) 200 70.0 (17.7) 73.9 (56.5–82.6) 26.1–100.0 0.0000 Attitude score (A, %, items 24–35) 200 61.7 (10.1) 60.4 (54.2–68.8) 37.5–89.6 0.1960 Practice score (P, %, items 37–49) 169 35.9 (19.9) 34.6 (21.2–50.0) 0.0-94.2 0.0056 Global KAP score (%, composite) 169 57.3 (11.7) 57.9 (49.4–64.3) 29.5–87.6 0.7137 Diagnostic Availability Index (DAI, %) 200 39.8 (23.5) 37.5 (25.0–50.0) 0.0-100.0 0.0000 Therapeutic Practice Index (TPI, %) 169 39.9 (20.5) 37.5 (25.0-56.2) 0.0-93.8 0.0855 Global SOP Implementation Index (GI-SOP, %) 169 39.8 (17.9) 37.5 (28.1–50.0) 4.7–95.3 0.0020 Table 3 Categorization of knowledge, attitude, and practice scores Knowledge score (N = 200) Category n % 95% CI Adequate knowledge 101 50.5 43.6–57.4 Intermediate knowledge 71 35.5 29.2–42.3 Insufficient knowledge 28 14.0 9.9–19.5 Attitude score (N = 200) Category n % 95% CI Favorable attitudes 42 21.0 15.9–27.2 Neutral attitudes 141 70.5 63.8–76.4 Unfavorable attitudes 17 8.5 5.4–13.2 Practice score (N = 169) Category n % 95% CI Good practices 7 4.1 2.0-8.3 Moderate practices 38 22.5 16.8–29.4 Poor practices 124 73.4 66.2–79.5 Diagnostic availability and composite renal care readiness The DAI showed substantial limitations across facilities. Among the 200 participants, the mean (SD) DAI score was 39.8 (23.5), with a median (IQR) of 37.5 (25.0–50.0) and a range of 0-100 (Table 2 ). The global KAP score had a mean (SD) of 57.4 (11.7) and a median (IQR) of 57.5 (49.3–64.8) (Table 2 ), indicating an overall intermediate level of renal care readiness. The global SOP implementation index (GI-SOP) further highlighted operational gaps, with a mean (SD) of 39.8 (17.9) and a median (IQR) of 37.5 (28.1–50.0) (Table 2 ). Lower DAI and GI-SOP scores were predominantly observed in primary and secondary care facilities. Factors associated with adequate renal care readiness In bivariate analyses, the global KAP score did not vary significantly by sex or years of professional experience. In contrast, higher KAP scores were observed among pediatricians or pediatric residents compared with general practitioners (p = 0.004), and among respondents working in tertiary facilities compared with primary and secondary facilities (p = 0.003). KAP scores were also higher in urban than in rural or peri-urban settings (p = 0.019). Diagnostic availability was strongly associated with the global KAP score, with higher scores among respondents reporting a diagnostic availability index ≥ 50% (p < 0.001). Higher knowledge and favorable attitude scores were both significantly associated with higher global KAP scores (p < 0.001). No significant differences were observed according to the type of health facility (Table 7 ). Table 7 Global KAP score (%) according to respondent characteristics Variable Category n Mean (SD) Median (IQR) p-value Sex Male 131 57.6 (11.9) 57.9 (50.4–64.1) 0.825 Female 36 56.6 (11.2) 57.3 (49.2–65.3) Other/Prefer not to say 2 52.8 (12.2) 52.8 (48.5–57.1) Professional category General practitioner 97 55.1 (10.4) 56.3 (48.5–62.5) 0.004 Other medical specialties 37 59.2 (13.0) 59.7 (50.7–70.3) Pediatrician / Resident 12 68.5 (10.3) 67.7 (61.3–75.5) Nurse / Midwife 14 54.8 (11.6) 55.6 (49.2–61.3) Laboratory staff / Medical biologist 9 62.0 (11.6) 66.8 (56.6–71.7) Years of experience ≥ 10 years 81 56.4 (11.7) 57.8 (48.4–63.2) 0.760 ≤ 5 years 48 58.1 (9.9) 58.0 (51.0-65.6) 6–9 years 40 58.3 (13.6) 56.3 (48.1–67.2) Level of facility Secondary 74 56.9 (11.8) 58.5 (50.1–63.7) 0.003 Primary 58 54.2 (10.0) 55.8 (48.4–60.9) Tertiary 37 63.1 (12.1) 64.3 (54.1–71.7) Type of facility Public 75 55.2 (11.8) 55.6 (47.6–62.9) 0.225 Faith-based private 60 60.3 (11.7) 59.9 (53.4–67.7) Private 22 56.1 (12.3) 59.5 (49.0-63.1) Other 10 57.3 (7.8) 58.0 (51.8–61.4) NGO 2 60.9 (2.7) 60.9 (60.0-61.8) Geographical setting Urban 104 59.0 (11.6) 60.0 (51.3–65.7) 0.019 Rural / peri-urban 65 54.7 (11.3) 55.4 (46.8–61.4) Diagnostic availability index < 50% 106 54.6 (11.3) 55.9 (47.5–62.0) 0.000 ≥ 50% 63 61.9 (10.9) 61.6 (54.0-68.3) Knowledge score ≥ 70% Yes 87 64.9 (8.4) 63.1 (59.3–70.6) 0.000 No 82 49.3 (9.1) 49.3 (43.2–55.2) Attitude score ≥ 70% No 132 55.1 (10.8) 55.9 (48.4–62.2) 0.000 Yes 37 65.1 (11.6) 65.6 (59.8–74.8) In bivariate analyses, the TPI did not differ by sex or years of professional experience. Higher TPI scores were observed among pediatricians or pediatric residents compared with general practitioners (p = 0.007), and among respondents working in tertiary facilities compared with primary and secondary facilities (p < 0.001). TPI scores were higher in urban than in rural or peri-urban settings (p = 0.018). Higher diagnostic availability (≥ 50%) and higher knowledge scores (≥ 70%) were both associated with higher TPI values (p = 0.003 and p = 0.005, respectively), whereas attitude scores were not significantly associated with the TPI. No significant differences were observed according to the type of health facility (Table 8 ). Table 8 Therapeutic Practice Index (TPI, %) according to respondent characteristics Variable Category n Mean (SD) Median (IQR) p-value Sex Male 131 39.5 (21.5) 37.5 (23.4–54.7) 0.659 Female 36 41.9 (15.4) 39.1 (30.5–53.9) Other/Prefer not to say 2 32.8 (42.0) 32.8 (18.0-47.7) Professional category General practitioner 97 34.9 (18.3) 34.4 (21.9–46.9) 0.007 Other medical specialties 26 46.0 (22.4) 48.4 (29.7–59.4) Pediatrician / Resident 23 48.4 (23.7) 53.1 (32.8–64.1) Nurse / Midwife 14 42.6 (16.5) 43.8 (32.0-55.5) Laboratory staff / Medical biologist 9 50.7 (20.8) 56.2 (34.4–68.8) Years of experience ≥ 10 years 81 38.7 (21.7) 34.4 (25.0-53.1) 0.656 ≤ 5 years 48 41.0 (18.1) 40.6 (30.5–56.2) 6–9 years 40 40.9 (21.0) 39.1 (24.2–56.2) Level of facility Secondary 74 37.8 (19.7) 37.5 (22.7–52.3) 0.000 Primary 58 34.4 (17.6) 34.4 (21.9–49.2) Tertiary 37 52.9 (21.1) 56.2 (34.4–65.6) Type of facility Public 75 35.2 (20.3) 34.4 (18.8–53.1) 0.058 Faith-based private 60 45.5 (21.5) 40.6 (31.2–62.5) Private 22 37.6 (16.7) 34.4 (28.9–49.2) Other 10 45.6 (16.0) 43.8 (38.3–58.6) NGO 2 42.2 (24.3) 42.2 (33.6–50.8) Geographical setting Urban 104 43.1 (20.6) 40.6 (28.1–56.2) 0.018 Rural / peri-urban 65 34.7 (19.3) 34.4 (21.9–46.9) Diagnostic availability index < 50% 106 36.0 (18.1) 34.4 (21.9–50.0) 0.003 ≥ 50% 63 46.5 (22.5) 46.9 (31.2–62.5) Knowledge score ≥ 70% Yes 87 44.2 (20.8) 46.9 (28.1–59.4) 0.005 No 82 35.3 (19.1) 34.4 (21.9–46.9) Attitude score ≥ 70% No 132 38.9 (19.6) 37.5 (25.0-53.1) 0.191 Yes 37 43.5 (23.2) 46.9 (25.0-59.4) In bivariate analyses, the GI-SOP did not differ by sex or years of professional experience. Higher GI-SOP scores were observed among pediatricians or pediatric residents compared with general practitioners (p = 0.001), and among respondents working in tertiary facilities compared with primary and secondary facilities (p < 0.001). GI-SOP scores were also higher in faith-based private facilities than in public and private secular facilities (p = 0.011), and in urban compared with rural or peri-urban settings (p < 0.001). Diagnostic availability was strongly associated with IG-SOP, with substantially higher scores among respondents reporting a diagnostic availability index ≥ 50% (p < 0.001). Higher knowledge scores (≥ 70%) were associated with higher GI-SOP values (p = 0.002), whereas attitude scores were not significantly associated (p = 0.053 (Table 9 ). Table 9 Global SOP Implementation Index (IG-SOP, %) according to respondent characteristics Variable Category n Mean (SD) Median (IQR) p-value Sex Male 131 39.0 (18.0) 35.9 (26.6–48.4) 0.151 Female 36 43.5 (16.4) 44.5 (31.2–51.6) Other/Prefer not to say 2 32.0 (34.3) 32.0 (19.9–44.1) Professional category General practitioner 97 35.5 (15.8) 32.8 (25.0-43.8) 0.001 Other medical specialties 26 44.7 (20.4) 45.3 (31.2–54.3) Pediatrician / Resident 23 50.0 (19.8) 48.4 (36.7–63.3) Nurse / Midwife 14 36.5 (13.3) 38.3 (27.0-44.9) Laboratory staff / Medical biologist 9 51.7 (15.7) 50.0 (42.2–62.5) Years of experience ≥ 10 years 81 39.5 (19.8) 37.5 (26.6–51.6) 0.789 ≤ 5 years 48 38.6 (14.0) 35.9 (29.3–48.4) 6–9 years 40 42.0 (18.2) 40.6 (27.7–51.6) Level of facility Secondary 74 38.6 (16.8) 36.7 (28.1–50.0) 0.000 Primary 58 32.8 (12.3) 32.8 (23.8–43.8) Tertiary 37 53.5 (20.1) 51.6 (35.9–68.8) Type of facility Public 75 35.2 (17.9) 31.2 (24.2–45.3) 0.011 Faith-based private 60 46.4 (18.2) 43.0 (32.8–60.9) Private 22 36.7 (12.6) 35.9 (28.5–43.4) Other 10 41.6 (16.2) 41.4 (35.9–48.8) NGO 2 43.0 (16.6) 43.0 (37.1–48.8) Geographical setting Urban 104 43.9 (18.0) 41.4 (30.9–53.5) 0.000 Rural / peri-urban 65 33.3 (15.6) 31.2 (25.0-42.2) Diagnostic availability index < 50% 106 30.5 (11.2) 30.5 (23.4–39.1) 0.000 ≥ 50% 63 55.6 (15.8) 53.1 (43.8–65.6) Knowledge score ≥ 70% Yes 87 44.3 (18.4) 40.6 (31.2–53.1) 0.002 No 82 35.1 (16.0) 32.8 (25.0-44.9) Attitude score ≥ 70% No 132 38.5 (17.4) 35.9 (26.6–48.8) 0.053 Yes 37 44.7 (18.9) 43.8 (29.7–60.9) In multivariable logistic regression analysis, diagnostic availability emerged as the dominant determinant of renal care readiness. Participants working in settings with low diagnostic availability (DAI < 50%) had a markedly higher likelihood of insufficient implementation of standard operating procedures (GI-SOP < 50%), compared with those in settings with adequate diagnostic capacity (DAI ≥ 50%) (adjusted OR 35.23; 95% CI 11.76-105.55; p < 0.001) (Table 4 ). This strong association remained robust in sensitivity analyses using Firth’s penalized logistic regression, which yielded a more conservative but still highly significant estimate (adjusted OR 25.95; 95% CI 9.45–71.25; p < 0.001), confirming the central role of diagnostic availability in shaping renal care readiness. After adjustment, individual-level factors such as sex, knowledge level, and attitudes were not independently associated with adequate renal care readiness (Table 4 ). Table 4 Determinants of insufficient GI-SOP performance (GI-SOP < 50%) Explanatory variable Adjusted OR 95% CI p-value Sex (Female vs Male) 0.45 0.14–1.43 0.175 Years of experience (≤ 5 vs ≥ 10) 0.95 0.28–3.22 0.940 Years of experience (6–10 vs ≥ 10) 0.77 0.24–2.49 0.660 Primary facility vs secondary/tertiary 3.82 1.24–11.74 0.019 Rural/peripheral vs urban setting 2.10 0.70–6.26 0.185 Diagnostic availability index < 50% vs ≥ 50% 35.23 11.76-105.55 < 0.001 Knowledge score < 70% vs ≥ 70% 1.49 0.54–4.10 0.436 Attitude score < 70% vs ≥ 70% 1.25 0.40–3.91 0.703 Obstacles and facilitators to early renal screening Participants consistently reported several major obstacles to the implementation of systematic renal screening, including lack of reagents and diagnostic supplies, poor integration of renal screening into routine care pathways, insufficient clinical supervision, and financial barriers affecting both facilities and patients (Table 5 ). Conversely, facilitating factors included the availability of standardized protocols, motivation of HCPs, and institutional or partner support, particularly from non-governmental organizations and SCD programs. These facilitators were more frequently reported in tertiary-level facilities and settings with external technical support (Table 6 ). Table 5 Barriers to the implementation of systematic screening for sickle cell nephropathy (N = 200) Barrier n % 95% CI (Wilson) Lack of equipment and reagents 168 84.0 78.3–88.4 Lack of training 161 80.5 74.5–85.4 Absence of management protocols 136 68.0 61.2–74.1 High cost of tests 119 59.5 52.6–66.1 Lack of supervision 67 33.5 27.3–40.3 Lack of patient/parent interest 44 22.0 16.8–28.2 Workload 17 8.5 5.4–13.2 Other 17 8.5 5.4–13.2 Lack of electricity 16 8.0 5.0-12.6 Table 6 Facilitators of appropriate management of sickle cell nephropathy (N = 200) Facilitator n % 95% CI (Wilson) Continuing professional training 188 94.0 89.8–96.5 Regular supply of consumables 151 75.5 69.1–80.9 Support programs for patients with sickle cell disease 149 74.5 68.0–80.0 Inclusion in clinical protocols 142 71.0 64.4–76.8 Interprofessional collaboration 120 60.0 53.1–66.5 Clinical supervision 105 52.5 45.6–59.3 Institutional support 95 47.5 40.7–54.4 Team motivation 82 41.0 34.4–47.9 Other 12 6.0 3.5–10.2 Discussion Main findings This study provides one of the first comprehensive assessments of HCP readiness for the early detection and management of SCN in children in the province of North-Kivu, eastern DRC. Despite a relatively high proportion of participants demonstrating adequate knowledge of SCN, and generally favorable or neutral attitudes toward early renal screening, the implementation of recommended practices was markedly limited. Diagnostic availability emerged as a central determinant of effective renal care readiness, highlighting a critical disconnect between knowledge and practice driven primarily by structural and system-level constraints. A key finding of this study is the progressive decline observed across the knowledge-attitude-practice continuum. While half of the participants achieved adequate knowledge scores, only a small minority reported good renal screening practices. This discrepancy underscores that knowledge alone is insufficient to ensure the implementation of preventive renal care measures in children with SCD, particularly in resource-limited settings. Instead, the translation of knowledge into practice appears to be heavily dependent on diagnostic capacity, institutional support, and standardized care pathways. Comparison with existing literature Our findings are consistent with reports from other LMICs, where gaps between recommended standards of care and real-world practice in SCD management have been widely documented. Previous studies conducted in sub-Saharan Africa have shown that while HCPs often recognize the importance of screening for chronic complications, routine implementation remains inconsistent, especially for asymptomatic conditions such as early kidney disease ( 14 , 15 , 20 , 27 – 32 ). However, most existing studies have focused on general aspects of SCD management, with limited emphasis on renal complications and early nephropathy screening. Compared with studies from higher-resource settings, the low frequency of routine renal screening reported by our responders contrasts sharply with recommendations and practices in pediatric sickle cell programs where systematic blood pressure monitoring, annual albuminuria testing, and periodic assessment of kidney function are standard components of care ( 33 – 37 ). These differences likely reflect disparities in diagnostic infrastructure, availability of laboratory tests, and access to continuing professional education rather than differences in provider awareness alone ( 38 ). Importantly, our findings suggest that the barriers identified in North Kivu are not unique but are representative of broader challenges faced by health systems in similar contexts. Health system constraints and diagnostic availability One of the most important contributions of this study is the identification of diagnostic availability as a key driver of renal care readiness. Low scores on the diagnostic availability index were strongly associated with inadequate implementation of renal screening practices. This finding highlights the central role of basic diagnostic resources (such as urine testing materials, creatinine assays, and blood pressure monitoring devices) in enabling early detection of kidney involvement in children with SCD. In settings where diagnostic tools are scarce or inconsistently available, HCPs may deprioritize renal screening in favor of managing acute complications perceived as more immediately life-threatening ( 39 ). This dynamic likely contributes to delayed identification of kidney disease and missed opportunities for early intervention( 40 , 41 ). Strengthening diagnostic capacity at the primary and secondary care levels may therefore represent a high-impact strategy for improving pediatric renal outcomes in SCD, even in the absence of advanced nephrology services ( 42 – 46 ). Implications for early prevention of chronic kidney disease The low levels of reported renal screening practices observed in this study have important implications for the prevention of CKD in children with SCD. Early renal abnormalities, such as microalbuminuria and hypertension, often precede overt kidney dysfunction by several years. Failure to detect these early changes may result in progression to irreversible kidney damage, with long-term consequences extending into adulthood ( 47 ). In contrast, in high-income countries, early renal screening and prevention of CKD in children with SCD are routinely embedded within standardized care pathways and supported by robust diagnostic infrastructures. Regular blood pressure monitoring, annual screening for albuminuria, periodic assessment of kidney function, and confirmatory testing for persistent microalbuminuria are widely implemented as part of comprehensive sickle cell follow-up programs. These practices are reinforced by clear clinical guidelines, electronic medical records facilitating longitudinal monitoring, and multidisciplinary care models involving pediatric nephrologists, hematologists, and primary care providers ( 48 , 49 ). Our findings suggest that targeted interventions focusing on diagnostic availability, standard operating procedures, and provider support could substantially improve early detection of SCN ( 3 ). Integrating renal screening into routine sickle cell follow-up protocols, alongside simplified algorithms adapted to resource-limited settings, may help bridge the gap between knowledge and practice ( 32 , 50 ). Furthermore, expanding access to continuing medical education with a specific focus on pediatric nephrology could reinforce provider confidence and promote more consistent implementation of screening recommendations ( 51 , 52 ). Obstacles and facilitators to implementation Participants in this study identified multiple barriers to the implementation of early renal screening, including recurrent stock-outs of diagnostic reagents, financial constraints affecting both healthcare facilities and patients, high workload, and limited clinical supervision. These obstacles are consistent with findings from other LMICs, where deficiencies in supply chains, limited laboratory capacity, and competing clinical priorities have been repeatedly reported as major impediments to the delivery of guideline-recommended kidney care, particularly for chronic and often asymptomatic conditions such as early SCN ( 53 – 55 ). Previous studies conducted in sub-Saharan Africa have similarly shown that, even when HCPs are aware of recommended screening strategies, the absence of basic diagnostic tools (such as urine dipsticks, serum creatinine assays, or standardized reporting systems) substantially limits the translation of knowledge into practice ( 56 – 58 ). High patient volumes and staff shortages further exacerbate this gap, leading to a prioritization of acute and life-threatening complications over preventive renal monitoring. In this context, our findings reinforce the notion that inadequate renal care readiness is primarily driven by structural and organizational constraints rather than individual provider deficits ( 2 , 40 , 59 , 60 ). Conversely, several facilitators to implementation were identified. The availability of standardized protocols, institutional commitment, and external partnerships (particularly with non-governmental organizations and structured SCD programs) could be associated with improved implementation of renal screening practices. Similar facilitators have been described in other resource-limited settings, where protocol-driven care models, task standardization, and external technical or financial support have been shown to enhance adherence to recommended screening and follow-up practices ( 16 , 61 , 62 ). Importantly, studies evaluating implementation strategies in LMICs suggest that integrating renal screening into existing chronic care platforms (such as sickle cell clinics or pediatric follow-up programs) can mitigate the impact of resource constraints by streamlining workflows and reducing additional workload ( 63 , 64 ). Our findings align with this evidence and suggest that leveraging existing institutional and partnership-based support structures may represent a pragmatic and scalable approach to strengthening pediatric renal care in low-resource environments. Taken together, these results underscore that improving renal care readiness requires interventions that extend beyond individual training and target health system strengthening. Ensuring reliable access to essential diagnostic tools, reinforcing supervision and clinical governance, and embedding renal screening into routine SCD care pathways are likely to be critical for achieving sustainable improvements in the early detection and management of SCN. Strengths and limitations of the study This exploratory study has several strengths. It is among the first to focus specifically on early renal screening for SCN in children within a low-resource setting, using a comprehensive framework that integrates knowledge, attitudes, practices, and diagnostic availability. The inclusion of HCPs across multiple levels of care and geographic zones enhances the relevance and generalizability of the findings within similar contexts. However, several limitations should be acknowledged. The cross-sectional design precludes causal inference, and practices were self-reported, which may be subject to social desirability bias. Additionally, although the study included a broad range of HCPs, some professional categories were underrepresented, potentially limiting subgroup analyses. Finally, the study did not assess patient-level renal outcomes, which would be valuable for linking provider readiness to clinical impact. Implications for policy and practice The findings of this study underscore the need for integrated strategies to improve early renal screening for children with SCD in resource-limited settings. Policy efforts should prioritize the availability of essential diagnostic tools at peripheral healthcare facilities, the development and dissemination of simplified renal screening protocols, and the integration of pediatric nephrology content into continuing professional education. By addressing both provider-related and system-level barriers, health systems may improve early detection of SCN and reduce the long-term burden of CKD. Conclusions In conclusion, this study demonstrates that while HCPs in North Kivu Province generally possess adequate knowledge and relatively positive attitudes toward early renal screening in children with SCD, substantial gaps persist in practical implementation. Diagnostic availability and health system capacity play a pivotal role in determining renal care readiness. Strengthening diagnostic resources, standardizing care pathways, and supporting HCPs through targeted training and institutional support are essential steps toward improving early detection and prevention of kidney disease in this vulnerable population. Abbreviations A Attitude score ACEI Angiotensin-Converting Enzyme Inhibitor ARB Angiotensin Receptor Blocker CKD Chronic Kidney Disease DAI Diagnostic Availability Index DRC Democratic Republic of the Congo eGFR Estimated Glomerular Filtration Rate GI-SOP Global SOP Implementation Index HCP Healthcare Provider IQR Interquartile Range K Knowledge score KAP Knowledge, Attitudes, and Practices LMIC Low- and Middle-Income Countries P Practices score SCD Sickle Cell Disease SCN Sickle Cell Nephropathy SD Standard Deviation SOP Standard Operating Procedure TPI Therapeutic Practice Index Declarations Ethics approval and consent to participate The study protocol was reviewed and approved by the “Comité d’Ethique du Nord-Kivu” (CENK) (approval reference number: N° 50/CENK/2025). The study was conducted in accordance with the principles of the Declaration of Helsinki. Participation was voluntary, and electronic informed consent was obtained from all participants prior to questionnaire completion. Consent for publication Not applicable. This manuscript does not contain any individual person’s data in any form. Competing interests The authors declare that they have no competing interests. Authors’ information (optional) MM is a pediatrician with a research interest in sickle cell disease, pediatric nephrology, and health system strengthening in resource-limited settings. Funding Although this study did not receive any specific financial support from public, commercial, or not-for-profit funding agencies, the authors gratefully acknowledge the “Centre de Diagnostic et de Recherche Biomédicale du Nord-Kivu” (CDRB/NK) for its institutional and logistical support, particularly in providing office facilities and internet access that facilitated data management, analysis, and manuscript preparation. Author Contribution MM conceptualized the study, designed the methodology, supervised data collection, and drafted the original manuscript.MM, KKC and KMV performed data analysis and interpretation.All authors critically reviewed the manuscript for important intellectual content and approved the final version. Acknowledgements The authors would like to thank all HCPs who participated in the study, as well as the health facility managers who facilitated data collection. Data Availability The datasets generated and/or analysed during the current study are not publicly available due to inability to secure an adequate data repository but are available from the corresponding author on reasonable request. References Adigwe OP, Onoja SO, Onavbavba G. A Critical Review of Sickle Cell Disease Burden and Challenges in Sub-Saharan Africa. J Blood Med. 2023;14:367. Obeagu EI, John A. Health equity in sickle cell disease: overcoming barriers to care in marginalized communities. 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Supplementary Files Additionalfile1.Knowledgescorebyitem.docx Additionalfile2.Respondentsattitudestowardscreeningforsicklecellnephropathy.docx Additionalfile3.Respondentspracticesrelatedtoscreeningforsicklecellnephropathy.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 28 Mar, 2026 Reviews received at journal 23 Feb, 2026 Reviews received at journal 21 Feb, 2026 Reviews received at journal 19 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers invited by journal 12 Feb, 2026 Editor invited by journal 20 Jan, 2026 Editor assigned by journal 20 Jan, 2026 Submission checks completed at journal 20 Jan, 2026 First submitted to journal 18 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8630909","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":588735316,"identity":"945e1e5c-329b-457c-9f41-1c42e63b235f","order_by":0,"name":"Mupenzi Mumbere","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYPACCSDmATFsgJix8QApWtJAWhqI0cIA03IYzMSrRXdG7sHHBX8sog2unT34uKLivN3a9sNAW2psonFpMbuRl2w8g0cid8PtvGTDM2duJ287kwjUciwttwGnlhwzaR4JkJYcM8nGttvJZgeAWhgbDuPTYv6bxwCsxfxn479zyWbnHxLUYsbMkwCxhbGx4YCd2Q1Ctpx5lyzNc0AidybQL5INx5ITzG4AbUnA55fjuQc/8/ypy+27nXvwY0ONnb3Z+fSHDz7U2ODUAo0OBEgEq0zAqRyLFnu8ikfBKBgFo2BEAgDuqGa37ei9JAAAAABJRU5ErkJggg==","orcid":"","institution":"Université Catholique du Graben","correspondingAuthor":true,"prefix":"","firstName":"Mupenzi","middleName":"","lastName":"Mumbere","suffix":""},{"id":588735317,"identity":"56682eab-0857-4619-b116-21a5a2941aca","order_by":1,"name":"Charles Kahindo Kangitsi","email":"","orcid":"","institution":"Université de Goma","correspondingAuthor":false,"prefix":"","firstName":"Charles","middleName":"Kahindo","lastName":"Kangitsi","suffix":""},{"id":588735318,"identity":"15bd2e5e-2194-4e1e-a329-e4ee37063dbc","order_by":2,"name":"Victor Kambale Malengera","email":"","orcid":"","institution":"Université Catholique du Graben","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"Kambale","lastName":"Malengera","suffix":""},{"id":588735319,"identity":"4b3cbca8-5d95-4125-ba96-ba27cc22cf01","order_by":3,"name":"Zaccharie Lwanzo Sindikubyo","email":"","orcid":"","institution":"Centre de Diagnostic et de Recherche Biomédicale du Nord-Kivu","correspondingAuthor":false,"prefix":"","firstName":"Zaccharie","middleName":"Lwanzo","lastName":"Sindikubyo","suffix":""},{"id":588735320,"identity":"6818be9c-d1df-4ee5-9b5b-49bedc7cd171","order_by":4,"name":"François Katsuva Mbahweka","email":"","orcid":"","institution":"Université Catholique du Graben","correspondingAuthor":false,"prefix":"","firstName":"François","middleName":"Katsuva","lastName":"Mbahweka","suffix":""},{"id":588735321,"identity":"c04c5988-864e-47d8-ad81-399c32a9ec88","order_by":5,"name":"Zaccharie Tsongo Kibendelelwa","email":"","orcid":"","institution":"Université Catholique du Graben","correspondingAuthor":false,"prefix":"","firstName":"Zaccharie","middleName":"Tsongo","lastName":"Kibendelelwa","suffix":""}],"badges":[],"createdAt":"2026-01-18 11:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8630909/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8630909/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102382123,"identity":"f962299b-c907-4a85-940e-6adfe644f166","added_by":"auto","created_at":"2026-02-11 06:57:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2325303,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8630909/v1/beb5f427-7f0d-46c0-92cb-9bc74ee71827.pdf"},{"id":102382084,"identity":"fecb2600-26a9-4d51-ad87-a792e90cd8b7","added_by":"auto","created_at":"2026-02-11 06:57:39","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":30459,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.Knowledgescorebyitem.docx","url":"https://assets-eu.researchsquare.com/files/rs-8630909/v1/2a7632c71650a04e9fbc1861.docx"},{"id":102382120,"identity":"14c52578-2515-425f-a610-7187cf5d55d0","added_by":"auto","created_at":"2026-02-11 06:57:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29145,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.Respondentsattitudestowardscreeningforsicklecellnephropathy.docx","url":"https://assets-eu.researchsquare.com/files/rs-8630909/v1/368b27f125dc50d6d8109821.docx"},{"id":102382061,"identity":"a9a36b11-03dd-4803-9150-25c0fe74e28e","added_by":"auto","created_at":"2026-02-11 06:57:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":29831,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile3.Respondentspracticesrelatedtoscreeningforsicklecellnephropathy.docx","url":"https://assets-eu.researchsquare.com/files/rs-8630909/v1/7cfac9d2818b2a6b93d95c91.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Renal care readiness and gaps in early detection of sickle cell nephropathy in children in North Kivu Province, Democratic Republic of the Congo: an exploratory cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSickle cell disease (SCD) is one of the most prevalent inherited hemoglobinopathies worldwide, affecting millions of individuals and disproportionately burdening sub-Saharan Africa, where more than 80% of affected children are born (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite significant improvements in survival over recent decades, particularly in high-income countries, SCD remains associated with substantial morbidity and early mortality in low-resource settings. This disparity is largely driven by limited access to comprehensive care, delayed diagnosis of complications, and constrained health system capacity (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Among the chronic complications of SCD, renal involvement (commonly referred to as sickle cell nephropathy (SCN)) represents a major yet often under-recognized contributor to long-term morbidity beginning in childhood (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSickle cell nephropathy encompasses a spectrum of functional and structural renal abnormalities that may appear early in life and progress insidiously. These include glomerular hyperfiltration, impaired urinary concentrating ability, microalbuminuria, hypertension, and, in advanced stages, chronic kidney disease (CKD) and end-stage kidney failure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Pediatric renal manifestations are frequently asymptomatic, allowing kidney damage to progress silently for years before clinical detection. Once overt proteinuria or reduced glomerular filtration rate becomes apparent, renal injury is often irreversible and associated with poor outcomes. Consequently, early identification of renal involvement in children with SCD is critical to prevent or delay progression to CKD and its associated complications (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Current international and regional guidelines emphasize the importance of systematic renal screening in children with SCD. Recommended measures include regular blood pressure monitoring, annual screening for albuminuria, and periodic assessment of kidney function (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Early detection enables timely implementation of preventive and therapeutic interventions, such as optimization of hydration, early initiation of hydroxyurea therapy, and the use of angiotensin converting enzyme inhibitors /angiotensin receptor blockers (ACEI/ARB) in selected cases (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). These strategies have been shown to reduce proteinuria, slow the progression of renal disease, and improve overall outcomes in children with SCD (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, the successful implementation of these recommendations depends not only on clinical knowledge but also on the availability of diagnostic tools, standardized clinical pathways, and adequately trained healthcare providers (HCPs) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn many low- and middle-income countries (LMIC), including those in the Democratic Republic of the Congo (DRC), the translation of evidence-based recommendations into routine clinical practice remains inconsistent. Healthcare systems often face structural constraints such as limited laboratory capacity, shortages of essential diagnostic tests, lack of standardized operating procedures (SOP), and insufficient opportunities for continuing professional training. In this context, HCPs may possess adequate theoretical knowledge and positive attitudes toward early renal screening yet remain unable to implement recommended practices consistently. Understanding the interplay between provider-related factors and system-level constraints is therefore essential for identifying realistic and sustainable strategies to improve renal care for children with SCD (\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile several studies have explored knowledge, attitudes, and practices related to general SCD management, relatively few have focused specifically on renal complications, and even fewer have addressed early screening for SCN in pediatric populations (\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Moreover, data from the DRC are particularly scarce, despite the high prevalence of SCD and the significant burden of kidney disease in the region (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Existing studies often emphasize patient-level outcomes, leaving a critical gap in understanding HCP readiness and health system preparedness to deliver effective renal preventive care. Addressing this gap is essential for informing policy decisions, guiding capacity-building initiatives, and improving long-term renal outcomes for children with SCD.\u003c/p\u003e \u003cp\u003eNorth Kivu Province in the DRC represents a setting where these challenges are particularly pronounced. The region is characterized by a relatively high burden of SCD, limited diagnostic infrastructure, and heterogeneous healthcare delivery across urban and rural settings (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Despite these constraints, HCPs play a central role in the early identification and management of renal complications in children with SCD. Evaluating their readiness to implement recommended renal screening practices offers valuable insight into existing gaps and potential leverage points for intervention. Importantly, the challenges observed in North Kivu are not unique and reflect broader issues faced by many resource-limited settings globally.\u003c/p\u003e \u003cp\u003eThe present study aimed to assess renal care readiness for the early detection and management of SCN in children in North Kivu Province by evaluating HCPs\u0026rsquo; knowledge, attitudes, practices, and diagnostic availability. By identifying determinants of adequate renal care readiness and highlighting key barriers and facilitators to implementation, this study seeks to generate actionable evidence to inform strategies for strengthening early renal screening and preventive care. The findings are intended to contribute not only to local improvement efforts but also to the broader discourse on optimizing pediatric nephrology care for children with SCD in low-resource settings worldwide.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo address these gaps, we conducted a quantitative, exploratory cross-sectional study with descriptive and analytical components among HCPs working in North Kivu Province, eastern DRC. The study was observational in nature and involved no intervention or modification of participants\u0026rsquo; clinical behaviors or practices. Data collection was carried out between 16 October and 30 November 2025. The study included healthcare facilities across all levels of care (primary, secondary, and tertiary) and all types of structures (public, faith-based, and private), in both urban and non-urban settings.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe study population consisted of medical and paramedical HCPs actively working in health facilities in North Kivu Province and potentially involved in the screening, follow-up, or management of SCD in children and/or its renal complications. Medical staff included general practitioners and medical specialists, while paramedical staff comprised nurses and laboratory technicians/medical biologists.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eEligibility criteria\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eInclusion criteria\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticipants were eligible if they:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003ewere members of the medical or paramedical workforce practicing in North Kivu Province;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003ewere aged 18 years or older;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eprovided free and informed consent to participate through electronic confirmation.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExclusion criteria\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticipants were excluded if the responses to their questionnaires were:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eincomplete; or\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003einternally inconsistent based on predefined coherence checks.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample size calculation\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe primary objective was to estimate the proportion of HCPs with an adequate level of knowledge, attitudes, and practices (KAP score\u0026thinsp;\u0026ge;\u0026thinsp;70) regarding the management of SCN in children. Sample size was calculated using Cochran\u0026rsquo;s formula for estimating a proportion in an assumed infinite population. A conservative expected proportion of 50% was used in the absence of prior regional estimates, with a 95% confidence level (Z\u0026thinsp;=\u0026thinsp;1.96) and an absolute precision of 7%. A design effect of 1.0 was assumed due to light stratification by professional category, level of care, and geographic zone.\u003c/p\u003e\u003cp\u003eTo account for anticipated non-response in an online survey context, a conservative response rate of 50% was applied, yielding a minimum recruitment target of 196 respondents. This approach was chosen to maximize statistical power and ensure adequate precision. Ultimately, 200 valid responses were included in the final analysis.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling strategy\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBecause the exact size of the eligible population with internet access was unknown, a non-probabilistic quota sampling strategy was adopted. Quotas were defined according to three key stratification variables: professional category (physicians, nurses, laboratory staff), level of care (primary, secondary, tertiary), and geographic zone (urban versus non-urban). Participant inclusion occurred on a first-come, first-served basis until both the overall target of valid questionnaires (\u0026ge;\u0026thinsp;196) and minimum stratum-specific quotas were approached. Despite repeated targeted reminders, some predefined quotas could not be fully achieved, particularly among paramedical staff and certain levels of care.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eData collection procedures\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eData were collected using a pretested structured, self-administered electronic questionnaire developed in French and deployed via the KoboCollect platform. The survey link was disseminated through institutional communication channels and professional WhatsApp groups across health zones in North Kivu Province. Weekly reminders were issued by the principal investigator throughout the data collection period.\u003c/p\u003e \u003cp\u003eTo ensure data completeness, all questionnaire items were configured as mandatory within KoboCollect, preventing submission unless all questions were answered. Upon completion of data collection, the dataset was exported to Microsoft Excel (Microsoft 365) for initial processing. A manual data-cleaning process was then conducted to verify internal consistency and identify anomalous response patterns. Following this process, the dataset was frozen and constituted the definitive version used for all statistical analyses, with no further modifications permitted to preserve data integrity and reproducibility.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy variables and operational definitions\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eKnowledge score (K)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eKnowledge was assessed using 23 items addressing key aspects of SCD and SCN, including diagnostic principles, early renal screening strategies, indications for ACEI/ARBs, hydroxyurea use, referral criteria, renal risk factors, and the role of cystatin C. Items were formatted as true/false questions with an additional \u0026ldquo;I do not know\u0026rdquo; option. Correct responses were scored as 1, while incorrect or \u0026ldquo;I do not know\u0026rdquo; responses were scored as 0. The knowledge score was calculated as the percentage of correct answers and ranged from 0 to 100. Scores were categorized as adequate (\u0026ge;\u0026thinsp;70), intermediate (50\u0026ndash;69), or insufficient (\u0026lt;\u0026thinsp;50).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAttitudes score (A)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAttitudes toward early renal screening were measured using 12 Likert-scale items ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 5 (\u0026ldquo;strongly agree\u0026rdquo;). Negatively worded items were reverse-coded to ensure consistent score orientation. Individual attitude scores were computed as the mean Likert score and standardized to a 0-100 scale using the formula:\u003c/p\u003e \u003cp\u003e \u003cem\u003eA = ((mean Likert score\u0026thinsp;\u0026minus;\u0026thinsp;1) / 4) \u0026times; 100\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eScores were categorized as favorable (\u0026ge;\u0026thinsp;70), neutral (50\u0026ndash;69), or unfavorable (\u0026lt;\u0026thinsp;50). Internal consistency was assessed using Cronbach\u0026rsquo;s alpha, with values\u0026thinsp;\u0026ge;\u0026thinsp;0.70 considered acceptable.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePractices score (P)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePractices related to renal screening and management were evaluated using 13 items assessing the frequency of recommended clinical actions. Frequency responses (\u0026ldquo;never,\u0026rdquo; \u0026ldquo;rarely,\u0026rdquo; \u0026ldquo;sometimes,\u0026rdquo; \u0026ldquo;often,\u0026rdquo; \u0026ldquo;always\u0026rdquo;) were coded as 0, 25, 50, 75, and 100, respectively. Binary items were coded as 100 for recommended practice and 0 otherwise. The practices score was calculated as the arithmetic mean of item scores and ranged from 0 to 100. Scores were categorized as good (\u0026ge;\u0026thinsp;70), moderate (50\u0026ndash;69), or poor (\u0026lt;\u0026thinsp;50). Internal consistency was evaluated using Cronbach\u0026rsquo;s alpha.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eComposite indices\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA global KAP index was constructed as a weighted composite score:\u003c/p\u003e \u003cp\u003e \u003cem\u003eKAP\u0026thinsp;=\u0026thinsp;0.40 \u0026times; K\u0026thinsp;+\u0026thinsp;0.30 \u0026times; A\u0026thinsp;+\u0026thinsp;0.30 \u0026times; P\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe index was categorized as adequate (\u0026ge;\u0026thinsp;70), intermediate (50\u0026ndash;69), or insufficient (\u0026lt;\u0026thinsp;50). For multivariable analyses, KAP was dichotomized using a threshold of 50% to ensure sufficient category sizes.\u003c/p\u003e \u003cp\u003eA Diagnostic Availability Index (DAI) was created based on the availability of essential diagnostic tools for early renal screening. Additional composite indices assessed therapeutic practices (TPI) and the implementation of standard operating procedures (GI-SOP), each normalized to a 0-100 scale.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eIndependent variables\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIndependent variables included sociodemographic, professional, and structural characteristics of HCPs and their working environments. These comprised sex, age group, years of professional experience, professional category, level and type of health facility, and geographical setting (urban versus rural/peri-urban).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatistical analyses were performed using R software (version 4.5.2) and Microsoft Excel (Microsoft 365). In addition, the artificial intelligence tool ChatGPT (version 5.2) was used to support manuscript drafting and to assist in the selection of appropriate methodological and analytical approaches.\u003c/p\u003e \u003cp\u003eCategorical variables were summarized using frequencies, percentages, and 95% confidence intervals (CI) calculated with the Wilson method. Continuous variables were described using means and standard deviations (SD) or medians and interquartile ranges (IQR), as appropriate. Normality was assessed using the Shapiro-Wilk test and visual inspection of distributions.\u003c/p\u003e \u003cp\u003eGroup comparisons were conducted using non-parametric tests (Mann-Whitney U or Kruskal-Wallis) as distributions were non-normal. Multivariable logistic regression was used to identify factors independently associated with insufficient operational performance (GI-SOP\u0026thinsp;\u0026lt;\u0026thinsp;50%). Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in univariable analyses were considered for multivariable modeling. Adjusted odds ratios with 95% confidence intervals were reported, and statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e The study protocol was approved by an independent Ethics Committee, the \u0026ldquo;Comit\u0026eacute; d\u0026rsquo;Ethique du Nord-Kivu\u0026rdquo;. Participation was voluntary and based on electronic informed consent. Data were anonymized at the point of collection and stored on password-protected systems accessible only to authorized researchers.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStudy flow and participant inclusion\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA total of 212 questionnaires were submitted through the electronic data collection platform during the study period. After data cleaning, 12 questionnaires (5.7%) were excluded due to major internal inconsistencies. Consequently, 200 questionnaires (94.3%) were retained for the final descriptive and analytical analyses.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic and professional characteristics of participants\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe final sample included 200 HCPs. Most participants were male (155/200, 77.5%; 95% CI 71.2\u0026ndash;82.7), while 43 (21.5%; 95% CI 16.4\u0026ndash;27.7) were female and 2 (1.0%) did not report sex. The majority were aged 30\u0026ndash;39 years (40.5%) or 40\u0026ndash;49 years (38.0%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and contextual characteristics of respondents (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155 (77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71.2\u0026ndash;82.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.4\u0026ndash;27.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndetermined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u0026ndash;3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81 (40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.9\u0026ndash;47.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.6\u0026ndash;44.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0-18.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral practitioner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109 (54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.6\u0026ndash;61.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther medical specialties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.9\u0026ndash;33.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse A1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.8\u0026ndash;10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePediatrician / Pediatric resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.5\u0026ndash;10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaboratory technician\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1\u0026ndash;5.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedical biologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8-5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMidwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u0026ndash;3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse A0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3\u0026ndash;3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of health facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89 (44.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.8\u0026ndash;51.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.9\u0026ndash;38.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.2\u0026ndash;29.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographical setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.1\u0026ndash;70.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural/peri-urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.7\u0026ndash;42.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRegarding professional category, medical doctors accounted for 87.0% of participants, including general practitioners (54.5%), other medical specialties (26.5%), and pediatricians or pediatric residents (6.0%). Paramedical staff represented 13.0%, mainly nurses and laboratory personnel. Participants were predominantly employed in secondary-level facilities (44.5%), followed by primary-level (32.0%) and tertiary-level institutions (23.5%). Most respondents practiced in urban settings (64.0%), while 36.0% were based in rural or peri-urban areas (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eKnowledge related to sickle cell nephropathy\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eKnowledge was calculated for all 200 participants. The mean (SD) knowledge score was 70.0 (17.7), with a median (IQR) of 73.9 (56.5\u0026ndash;82.6) and a range of 26.1\u0026ndash;100 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen categorized, 101 participants (50.5%; 95% CI 43.6\u0026ndash;57.4) demonstrated adequate knowledge, 71 (35.5%; 95% CI 29.2\u0026ndash;42.3) had intermediate knowledge, and 28 (14.0%; 95% CI 9.9\u0026ndash;19.5) had insufficient knowledge (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eItem-level analysis showed that while general concepts of SCD and renal involvement were widely recognized, important gaps persisted in technical aspects of early renal screening, including interpretation of estimated glomerular filtration rate (eGFR), the clinical utility of cystatin C, and indications for ACEI/ARBs (Additional file 1).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eAttitudes toward early renal screening\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAttitude was also available for all 200 participants. The mean (SD) attitude score was 61.7 (10.1), with a median (IQR) of 60.4 (54.2\u0026ndash;68.8) and a range of 37.5\u0026ndash;89.6 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOnly 42 participants (21.0%; 95% CI 15.9\u0026ndash;27.2) demonstrated favorable attitudes, whereas the majority exhibited neutral attitudes (141/200, 70.5%; 95% CI 63.8\u0026ndash;76.4). Seventeen participants (8.5%; 95% CI 5.4\u0026ndash;13.2) had unfavorable attitudes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite widespread acknowledgment of the importance of early renal screening, negative or hesitant attitudes were frequently associated with perceived financial constraints, limited laboratory capacity, and prioritization of acute hematologic or infectious complications over asymptomatic renal involvement (Additional file 2).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eReported clinical practices related to renal screening\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePractice was calculated for 169 participants, reflecting the applicability of practice-related items. The mean (SD) practice score was 35.9 (19.9), with a median (IQR) of 34.6 (21.2\u0026ndash;50.0) and a range of 0.0-94.2 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOnly 7 participants (4.1%; 95% CI 2.0-8.3) achieved good practice scores. Thirty-eight (22.5%; 95% CI 16.8\u0026ndash;29.4) demonstrated moderate practices, while the vast majority, i.e. 124 participants (73.4%; 95% CI 66.2\u0026ndash;79.5), had poor practices (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAt the item level, recommended actions such as annual urine dipstick testing, routine blood pressure measurement, periodic assessment of kidney function, and documentation of renal findings were inconsistently implemented, particularly in primary and secondary healthcare facilities (Additional file 3).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of scores and indices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScore / Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin-Max\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value (Shapiro-Wilk)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge score (K, %, items 1\u0026ndash;23)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.0 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.9 (56.5\u0026ndash;82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.1\u0026ndash;100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude score (A, %, items 24\u0026ndash;35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.7 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.4 (54.2\u0026ndash;68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5\u0026ndash;89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1960\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePractice score (P, %, items 37\u0026ndash;49)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.9 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.6 (21.2\u0026ndash;50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0-94.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlobal KAP score (%, composite)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.3 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.9 (49.4\u0026ndash;64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.5\u0026ndash;87.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic Availability Index (DAI, %)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.8 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.5 (25.0\u0026ndash;50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0-100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTherapeutic Practice Index (TPI, %)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.9 (20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.5 (25.0-56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0-93.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlobal SOP Implementation Index (GI-SOP, %)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.8 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.5 (28.1\u0026ndash;50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.7\u0026ndash;95.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eCategorization of knowledge, attitude, and practice scores\u003c/em\u003e Knowledge score (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdequate knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.6\u0026ndash;57.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntermediate knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.2\u0026ndash;42.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsufficient knowledge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9\u0026ndash;19.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section4\"\u003e \u003ch2\u003eAttitude score (N\u0026thinsp;=\u0026thinsp;200)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFavorable attitudes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.9\u0026ndash;27.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutral attitudes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.8\u0026ndash;76.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnfavorable attitudes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003ePractice score (N\u0026thinsp;=\u0026thinsp;169)\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGood practices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0-8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate practices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8\u0026ndash;29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoor practices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.2\u0026ndash;79.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic availability and composite renal care readiness\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe DAI showed substantial limitations across facilities. Among the 200 participants, the mean (SD) DAI score was 39.8 (23.5), with a median (IQR) of 37.5 (25.0\u0026ndash;50.0) and a range of 0-100 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe global KAP score had a mean (SD) of 57.4 (11.7) and a median (IQR) of 57.5 (49.3\u0026ndash;64.8) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating an overall intermediate level of renal care readiness. The global SOP implementation index (GI-SOP) further highlighted operational gaps, with a mean (SD) of 39.8 (17.9) and a median (IQR) of 37.5 (28.1\u0026ndash;50.0) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLower DAI and GI-SOP scores were predominantly observed in primary and secondary care facilities.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with adequate renal care readiness\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn bivariate analyses, the global KAP score did not vary significantly by sex or years of professional experience. In contrast, higher KAP scores were observed among pediatricians or pediatric residents compared with general practitioners (p\u0026thinsp;=\u0026thinsp;0.004), and among respondents working in tertiary facilities compared with primary and secondary facilities (p\u0026thinsp;=\u0026thinsp;0.003). KAP scores were also higher in urban than in rural or peri-urban settings (p\u0026thinsp;=\u0026thinsp;0.019). Diagnostic availability was strongly associated with the global KAP score, with higher scores among respondents reporting a diagnostic availability index\u0026thinsp;\u0026ge;\u0026thinsp;50% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Higher knowledge and favorable attitude scores were both significantly associated with higher global KAP scores (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were observed according to the type of health facility (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGlobal KAP score (%) according to respondent characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.6 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.9 (50.4\u0026ndash;64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.6 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.3 (49.2\u0026ndash;65.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther/Prefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.8 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.8 (48.5\u0026ndash;57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral practitioner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.1 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.3 (48.5\u0026ndash;62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther medical specialties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.2 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.7 (50.7\u0026ndash;70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePediatrician / Resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.5 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.7 (61.3\u0026ndash;75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse / Midwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.8 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.6 (49.2\u0026ndash;61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaboratory staff / Medical biologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.0 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.8 (56.6\u0026ndash;71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.4 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.8 (48.4\u0026ndash;63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.1 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.0 (51.0-65.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.3 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.3 (48.1\u0026ndash;67.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.9 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.5 (50.1\u0026ndash;63.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.2 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.8 (48.4\u0026ndash;60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.1 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.3 (54.1\u0026ndash;71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.2 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.6 (47.6\u0026ndash;62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFaith-based private\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.3 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.9 (53.4\u0026ndash;67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.1 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.5 (49.0-63.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.3 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.0 (51.8\u0026ndash;61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.9 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.9 (60.0-61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographical setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.0 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.0 (51.3\u0026ndash;65.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural / peri-urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.7 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.4 (46.8\u0026ndash;61.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic availability index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.6 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.9 (47.5\u0026ndash;62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.9 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61.6 (54.0-68.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.9 (8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.1 (59.3\u0026ndash;70.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.3 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.3 (43.2\u0026ndash;55.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.1 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.9 (48.4\u0026ndash;62.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.1 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.6 (59.8\u0026ndash;74.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn bivariate analyses, the TPI did not differ by sex or years of professional experience. Higher TPI scores were observed among pediatricians or pediatric residents compared with general practitioners (p\u0026thinsp;=\u0026thinsp;0.007), and among respondents working in tertiary facilities compared with primary and secondary facilities (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). TPI scores were higher in urban than in rural or peri-urban settings (p\u0026thinsp;=\u0026thinsp;0.018). Higher diagnostic availability (\u0026ge;\u0026thinsp;50%) and higher knowledge scores (\u0026ge;\u0026thinsp;70%) were both associated with higher TPI values (p\u0026thinsp;=\u0026thinsp;0.003 and p\u0026thinsp;=\u0026thinsp;0.005, respectively), whereas attitude scores were not significantly associated with the TPI. No significant differences were observed according to the type of health facility (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTherapeutic Practice Index (TPI, %) according to respondent characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.5 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5 (23.4\u0026ndash;54.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.9 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.1 (30.5\u0026ndash;53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther/Prefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.8 (42.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.8 (18.0-47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral practitioner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.9 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (21.9\u0026ndash;46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther medical specialties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.0 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.4 (29.7\u0026ndash;59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePediatrician / Resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.4 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.1 (32.8\u0026ndash;64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse / Midwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.6 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.8 (32.0-55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaboratory staff / Medical biologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.7 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.2 (34.4\u0026ndash;68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.7 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (25.0-53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.0 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.6 (30.5\u0026ndash;56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.9 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.1 (24.2\u0026ndash;56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.8 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5 (22.7\u0026ndash;52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.4 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (21.9\u0026ndash;49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.9 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.2 (34.4\u0026ndash;65.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.2 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (18.8\u0026ndash;53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFaith-based private\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.5 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.6 (31.2\u0026ndash;62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.6 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (28.9\u0026ndash;49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.6 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.8 (38.3\u0026ndash;58.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.2 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.2 (33.6\u0026ndash;50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographical setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.1 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.6 (28.1\u0026ndash;56.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural / peri-urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.7 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (21.9\u0026ndash;46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic availability index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.0 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (21.9\u0026ndash;50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.5 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.9 (31.2\u0026ndash;62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.2 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.9 (28.1\u0026ndash;59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.3 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.4 (21.9\u0026ndash;46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.9 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5 (25.0-53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.5 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.9 (25.0-59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn bivariate analyses, the GI-SOP did not differ by sex or years of professional experience. Higher GI-SOP scores were observed among pediatricians or pediatric residents compared with general practitioners (p\u0026thinsp;=\u0026thinsp;0.001), and among respondents working in tertiary facilities compared with primary and secondary facilities (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). GI-SOP scores were also higher in faith-based private facilities than in public and private secular facilities (p\u0026thinsp;=\u0026thinsp;0.011), and in urban compared with rural or peri-urban settings (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Diagnostic availability was strongly associated with IG-SOP, with substantially higher scores among respondents reporting a diagnostic availability index\u0026thinsp;\u0026ge;\u0026thinsp;50% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Higher knowledge scores (\u0026ge;\u0026thinsp;70%) were associated with higher GI-SOP values (p\u0026thinsp;=\u0026thinsp;0.002), whereas attitude scores were not significantly associated (p\u0026thinsp;=\u0026thinsp;0.053 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGlobal SOP Implementation Index (IG-SOP, %) according to respondent characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.0 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.9 (26.6\u0026ndash;48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.5 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.5 (31.2\u0026ndash;51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther/Prefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.0 (34.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.0 (19.9\u0026ndash;44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral practitioner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.5 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.8 (25.0-43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther medical specialties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.7 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.3 (31.2\u0026ndash;54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePediatrician / Resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.0 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.4 (36.7\u0026ndash;63.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse / Midwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.5 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38.3 (27.0-44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLaboratory staff / Medical biologist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.7 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.0 (42.2\u0026ndash;62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.5 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5 (26.6\u0026ndash;51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.6 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.9 (29.3\u0026ndash;48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;9 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.0 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.6 (27.7\u0026ndash;51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.6 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.7 (28.1\u0026ndash;50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.8 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.8 (23.8\u0026ndash;43.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.5 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.6 (35.9\u0026ndash;68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.2 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.2 (24.2\u0026ndash;45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFaith-based private\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.4 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.0 (32.8\u0026ndash;60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.7 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.9 (28.5\u0026ndash;43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.6 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.4 (35.9\u0026ndash;48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.0 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.0 (37.1\u0026ndash;48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographical setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.9 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.4 (30.9\u0026ndash;53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural / peri-urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.3 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.2 (25.0-42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic availability index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.5 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.5 (23.4\u0026ndash;39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.6 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.1 (43.8\u0026ndash;65.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.3 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.6 (31.2\u0026ndash;53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.1 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.8 (25.0-44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude score\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.5 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.9 (26.6\u0026ndash;48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.7 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.8 (29.7\u0026ndash;60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn multivariable logistic regression analysis, diagnostic availability emerged as the dominant determinant of renal care readiness. Participants working in settings with low diagnostic availability (DAI\u0026thinsp;\u0026lt;\u0026thinsp;50%) had a markedly higher likelihood of insufficient implementation of standard operating procedures (GI-SOP\u0026thinsp;\u0026lt;\u0026thinsp;50%), compared with those in settings with adequate diagnostic capacity (DAI\u0026thinsp;\u0026ge;\u0026thinsp;50%) (adjusted OR 35.23; 95% CI 11.76-105.55; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis strong association remained robust in sensitivity analyses using Firth\u0026rsquo;s penalized logistic regression, which yielded a more conservative but still highly significant estimate (adjusted OR 25.95; 95% CI 9.45\u0026ndash;71.25; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming the central role of diagnostic availability in shaping renal care readiness.\u003c/p\u003e \u003cp\u003eAfter adjustment, individual-level factors such as sex, knowledge level, and attitudes were not independently associated with adequate renal care readiness (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDeterminants of insufficient GI-SOP performance (GI-SOP\u0026thinsp;\u0026lt;\u0026thinsp;50%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExplanatory variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex (Female vs Male)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.14\u0026ndash;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of experience (\u0026le;\u0026thinsp;5 vs\u0026thinsp;\u0026ge;\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026ndash;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears of experience (6\u0026ndash;10 vs\u0026thinsp;\u0026ge;\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026ndash;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary facility vs secondary/tertiary\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.24\u0026ndash;11.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRural/peripheral vs urban setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.70\u0026ndash;6.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnostic availability index\u0026thinsp;\u0026lt;\u0026thinsp;50% vs\u0026thinsp;\u0026ge;\u0026thinsp;50%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.76-105.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge score\u0026thinsp;\u0026lt;\u0026thinsp;70% vs\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.54\u0026ndash;4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitude score\u0026thinsp;\u0026lt;\u0026thinsp;70% vs\u0026thinsp;\u0026ge;\u0026thinsp;70%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.40\u0026ndash;3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eObstacles and facilitators to early renal screening\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticipants consistently reported several major obstacles to the implementation of systematic renal screening, including lack of reagents and diagnostic supplies, poor integration of renal screening into routine care pathways, insufficient clinical supervision, and financial barriers affecting both facilities and patients (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversely, facilitating factors included the availability of standardized protocols, motivation of HCPs, and institutional or partner support, particularly from non-governmental organizations and SCD programs. These facilitators were more frequently reported in tertiary-level facilities and settings with external technical support (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBarriers to the implementation of systematic screening for sickle cell nephropathy (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarrier\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI (Wilson)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of equipment and reagents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.3\u0026ndash;88.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74.5\u0026ndash;85.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsence of management protocols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.2\u0026ndash;74.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh cost of tests\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.6\u0026ndash;66.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of supervision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.3\u0026ndash;40.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of patient/parent interest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.8\u0026ndash;28.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorkload\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4\u0026ndash;13.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLack of electricity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.0-12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFacilitators of appropriate management of sickle cell nephropathy (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacilitator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI (Wilson)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinuing professional training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.8\u0026ndash;96.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular supply of consumables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.1\u0026ndash;80.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupport programs for patients with sickle cell disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.0\u0026ndash;80.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInclusion in clinical protocols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.4\u0026ndash;76.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterprofessional collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.1\u0026ndash;66.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical supervision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.6\u0026ndash;59.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitutional support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.7\u0026ndash;54.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeam motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.4\u0026ndash;47.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.5\u0026ndash;10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study provides one of the first comprehensive assessments of HCP readiness for the early detection and management of SCN in children in the province of North-Kivu, eastern DRC. Despite a relatively high proportion of participants demonstrating adequate knowledge of SCN, and generally favorable or neutral attitudes toward early renal screening, the implementation of recommended practices was markedly limited. Diagnostic availability emerged as a central determinant of effective renal care readiness, highlighting a critical disconnect between knowledge and practice driven primarily by structural and system-level constraints.\u003c/p\u003e\u003cp\u003eA key finding of this study is the progressive decline observed across the knowledge-attitude-practice continuum. While half of the participants achieved adequate knowledge scores, only a small minority reported good renal screening practices. This discrepancy underscores that knowledge alone is insufficient to ensure the implementation of preventive renal care measures in children with SCD, particularly in resource-limited settings. Instead, the translation of knowledge into practice appears to be heavily dependent on diagnostic capacity, institutional support, and standardized care pathways.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section3\"\u003e \u003ch2\u003eComparison with existing literature\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur findings are consistent with reports from other LMICs, where gaps between recommended standards of care and real-world practice in SCD management have been widely documented. Previous studies conducted in sub-Saharan Africa have shown that while HCPs often recognize the importance of screening for chronic complications, routine implementation remains inconsistent, especially for asymptomatic conditions such as early kidney disease (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29 CR30 CR31\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, most existing studies have focused on general aspects of SCD management, with limited emphasis on renal complications and early nephropathy screening.\u003c/p\u003e \u003cp\u003eCompared with studies from higher-resource settings, the low frequency of routine renal screening reported by our responders contrasts sharply with recommendations and practices in pediatric sickle cell programs where systematic blood pressure monitoring, annual albuminuria testing, and periodic assessment of kidney function are standard components of care (\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). These differences likely reflect disparities in diagnostic infrastructure, availability of laboratory tests, and access to continuing professional education rather than differences in provider awareness alone (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Importantly, our findings suggest that the barriers identified in North Kivu are not unique but are representative of broader challenges faced by health systems in similar contexts.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e \u003ch2\u003eHealth system constraints and diagnostic availability\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOne of the most important contributions of this study is the identification of diagnostic availability as a key driver of renal care readiness. Low scores on the diagnostic availability index were strongly associated with inadequate implementation of renal screening practices. This finding highlights the central role of basic diagnostic resources (such as urine testing materials, creatinine assays, and blood pressure monitoring devices) in enabling early detection of kidney involvement in children with SCD.\u003c/p\u003e \u003cp\u003eIn settings where diagnostic tools are scarce or inconsistently available, HCPs may deprioritize renal screening in favor of managing acute complications perceived as more immediately life-threatening (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). This dynamic likely contributes to delayed identification of kidney disease and missed opportunities for early intervention(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Strengthening diagnostic capacity at the primary and secondary care levels may therefore represent a high-impact strategy for improving pediatric renal outcomes in SCD, even in the absence of advanced nephrology services (\u003cspan additionalcitationids=\"CR43 CR44 CR45\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eImplications for early prevention of chronic kidney disease\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe low levels of reported renal screening practices observed in this study have important implications for the prevention of CKD in children with SCD. Early renal abnormalities, such as microalbuminuria and hypertension, often precede overt kidney dysfunction by several years. Failure to detect these early changes may result in progression to irreversible kidney damage, with long-term consequences extending into adulthood (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn contrast, in high-income countries, early renal screening and prevention of CKD in children with SCD are routinely embedded within standardized care pathways and supported by robust diagnostic infrastructures. Regular blood pressure monitoring, annual screening for albuminuria, periodic assessment of kidney function, and confirmatory testing for persistent microalbuminuria are widely implemented as part of comprehensive sickle cell follow-up programs. These practices are reinforced by clear clinical guidelines, electronic medical records facilitating longitudinal monitoring, and multidisciplinary care models involving pediatric nephrologists, hematologists, and primary care providers (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOur findings suggest that targeted interventions focusing on diagnostic availability, standard operating procedures, and provider support could substantially improve early detection of SCN (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Integrating renal screening into routine sickle cell follow-up protocols, alongside simplified algorithms adapted to resource-limited settings, may help bridge the gap between knowledge and practice (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Furthermore, expanding access to continuing medical education with a specific focus on pediatric nephrology could reinforce provider confidence and promote more consistent implementation of screening recommendations (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eObstacles and facilitators to implementation\u003c/h3\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eParticipants in this study identified multiple barriers to the implementation of early renal screening, including recurrent stock-outs of diagnostic reagents, financial constraints affecting both healthcare facilities and patients, high workload, and limited clinical supervision. These obstacles are consistent with findings from other LMICs, where deficiencies in supply chains, limited laboratory capacity, and competing clinical priorities have been repeatedly reported as major impediments to the delivery of guideline-recommended kidney care, particularly for chronic and often asymptomatic conditions such as early SCN (\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrevious studies conducted in sub-Saharan Africa have similarly shown that, even when HCPs are aware of recommended screening strategies, the absence of basic diagnostic tools (such as urine dipsticks, serum creatinine assays, or standardized reporting systems) substantially limits the translation of knowledge into practice (\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). High patient volumes and staff shortages further exacerbate this gap, leading to a prioritization of acute and life-threatening complications over preventive renal monitoring. In this context, our findings reinforce the notion that inadequate renal care readiness is primarily driven by structural and organizational constraints rather than individual provider deficits (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConversely, several facilitators to implementation were identified. The availability of standardized protocols, institutional commitment, and external partnerships (particularly with non-governmental organizations and structured SCD programs) could be associated with improved implementation of renal screening practices. Similar facilitators have been described in other resource-limited settings, where protocol-driven care models, task standardization, and external technical or financial support have been shown to enhance adherence to recommended screening and follow-up practices (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eImportantly, studies evaluating implementation strategies in LMICs suggest that integrating renal screening into existing chronic care platforms (such as sickle cell clinics or pediatric follow-up programs) can mitigate the impact of resource constraints by streamlining workflows and reducing additional workload (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Our findings align with this evidence and suggest that leveraging existing institutional and partnership-based support structures may represent a pragmatic and scalable approach to strengthening pediatric renal care in low-resource environments.\u003c/p\u003e\u003cp\u003eTaken together, these results underscore that improving renal care readiness requires interventions that extend beyond individual training and target health system strengthening. Ensuring reliable access to essential diagnostic tools, reinforcing supervision and clinical governance, and embedding renal screening into routine SCD care pathways are likely to be critical for achieving sustainable improvements in the early detection and management of SCN.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations of the study\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis exploratory study has several strengths. It is among the first to focus specifically on early renal screening for SCN in children within a low-resource setting, using a comprehensive framework that integrates knowledge, attitudes, practices, and diagnostic availability. The inclusion of HCPs across multiple levels of care and geographic zones enhances the relevance and generalizability of the findings within similar contexts.\u003c/p\u003e \u003cp\u003eHowever, several limitations should be acknowledged. The cross-sectional design precludes causal inference, and practices were self-reported, which may be subject to social desirability bias. Additionally, although the study included a broad range of HCPs, some professional categories were underrepresented, potentially limiting subgroup analyses. Finally, the study did not assess patient-level renal outcomes, which would be valuable for linking provider readiness to clinical impact.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec36\" class=\"Section3\"\u003e \u003ch2\u003eImplications for policy and practice\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe findings of this study underscore the need for integrated strategies to improve early renal screening for children with SCD in resource-limited settings. Policy efforts should prioritize the availability of essential diagnostic tools at peripheral healthcare facilities, the development and dissemination of simplified renal screening protocols, and the integration of pediatric nephrology content into continuing professional education. By addressing both provider-related and system-level barriers, health systems may improve early detection of SCN and reduce the long-term burden of CKD.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn conclusion, this study demonstrates that while HCPs in North Kivu Province generally possess adequate knowledge and relatively positive attitudes toward early renal screening in children with SCD, substantial gaps persist in practical implementation. Diagnostic availability and health system capacity play a pivotal role in determining renal care readiness. Strengthening diagnostic resources, standardizing care pathways, and supporting HCPs through targeted training and institutional support are essential steps toward improving early detection and prevention of kidney disease in this vulnerable population.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAttitude score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACEI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-Converting Enzyme Inhibitor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin Receptor Blocker\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCKD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDAI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiagnostic Availability Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDRC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDemocratic Republic of the Congo\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eeGFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstimated Glomerular Filtration Rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGI-SOP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlobal SOP Implementation Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealthcare Provider\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile Range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eK\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKnowledge score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKnowledge, Attitudes, and Practices\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLMIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow- and Middle-Income Countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePractices score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSickle Cell Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSCN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSickle Cell Nephropathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Operating Procedure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTherapeutic Practice Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The study protocol was reviewed and approved by the \u0026ldquo;Comit\u0026eacute; d\u0026rsquo;Ethique du Nord-Kivu\u0026rdquo; (CENK) (approval reference number: N\u0026deg; 50/CENK/2025). The study was conducted in accordance with the principles of the Declaration of Helsinki. Participation was voluntary, and electronic informed consent was obtained from all participants prior to questionnaire completion.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable. This manuscript does not contain any individual person\u0026rsquo;s data in any form.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAuthors\u0026rsquo; information (optional)\u003c/h2\u003e \u003cp\u003eMM is a pediatrician with a research interest in sickle cell disease, pediatric nephrology, and health system strengthening in resource-limited settings.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eAlthough this study did not receive any specific financial support from public, commercial, or not-for-profit funding agencies, the authors gratefully acknowledge the \u0026ldquo;Centre de Diagnostic et de Recherche Biom\u0026eacute;dicale du Nord-Kivu\u0026rdquo; (CDRB/NK) for its institutional and logistical support, particularly in providing office facilities and internet access that facilitated data management, analysis, and manuscript preparation.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMM conceptualized the study, designed the methodology, supervised data collection, and drafted the original manuscript.MM, KKC and KMV performed data analysis and interpretation.All authors critically reviewed the manuscript for important intellectual content and approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003e The authors would like to thank all HCPs who participated in the study, as well as the health facility managers who facilitated data collection.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to inability to secure an adequate data repository but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdigwe OP, Onoja SO, Onavbavba G. 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Kisangani M\u0026eacute;dical. 2023;13(2):658\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNgonde ACM, Fina JPL, Burgueno E, Lukanu PN. Knowledge and practices of sickle cell disease among healthcare providers in Kinshasa, Democratic Republic of the Congo. Afr J Prim Health Care Fam Med. 2023;16(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson LA, Camanda J, Chocolate F, D\u0026rsquo;Ambruoso L, Lohfeld L, Airewele G et al. Knowledge, Attitudes, and Practices Towards Sickle Cell Anaemia Among Healthcare Professionals in Cabinda Province, Angola. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDruye AA, Agyare DF, Akoto-Buabeng W, Zutah J, Offei FO, Nabe B, et al. Healthcare Professionals\u0026rsquo; Knowledge, Attitudes, and Practices in the Assessment, and Management of Sickle-Cell Disease: A Meta-Aggregative Review. 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J Am Soc Nephrol. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAeddula NR, Bardhan M, Baradhi KM. Sickle Cell Nephrop StatPearls Publishing. 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtaga KI, Saraf SL, Derebail VK. The nephropathy of sickle cell trait and sickle cell disease. Nat Rev Nephrol. 2022;18(6):361\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlly M, Balandya E. Current challenges and new approaches to implementing optimal management of sickle cell disease in sub-Saharan Africa. Semin Hematol. 2023;60(4):192.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJawabreh B, Khatib S, Hamdan M. A qualitative study of nephrologists\u0026rsquo; perspectives on implementing a nephrology rapid response model for acute kidney injury. BMC Nephrol. 2025;26(1):534.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeale EP, Middleton J, Lambert K. Barriers and enablers to detection and management of chronic kidney disease in primary healthcare: A systematic review. BMC Nephrol. 2020;21(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgiraneza G, Dusabejambo V, Finklestein FO, Rastegar A. Challenges in the Recognition and Management of Acute Kidney Injury by Hospitals in Resource-Limited Settings. Kidney Int Rep. 2020;5(7):991.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCormick MC. Martinez RMarie. Addressing sickle cell disease: a strategic plan and blueprint for action. Volume 496. National Academies; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGargano LP, Fachi MM, Oliveira LA, Lobo C, Melnikoff KNT, Soriano S et al. Updating the Brazilian clinical practice guidelines for sickle cell disease: Recommendations and development process. Hematol Transfus Cell Ther. 2025;47(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiem RI, Lanzkron S, Coates TD, DeCastro L, Desai AA, Ataga KI, et al. American Society of Hematology 2019 guidelines for sickle cell disease: cardiopulmonary and kidney disease. Blood Adv. 2019;3(23):3867\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBabu BV, Sridevi P, Surti Sb, Ranjit M, Bhat D, Sarmah J, et al. Improving the Capacity of Health System and Community for Sickle Cell Disease Screening and Management Among Tribal Population in India: Protocol of an Intervention Study. Curr Health Sci J. 2020;46(3):270.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnto EO, Obirikorang C, Acheampong E, Adua E, Donkor S, Afranie BO, et al. Renal abnormalities among children with sickle cell conditions in highly resource-limited setting in Ghana. PLoS ONE. 2019;14(11):e0225310.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeruva SLH, Paul Y, Oneal P, Nouraie M. Renal Failure in Sickle Cell Disease: Prevalence, Predictors of Disease, Mortality and Effect on Length of Hospital Stay. Hemoglobin. 2016;40(5):295.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeart N, Institute B. Evidence-Based Management of Sickle Cell Disease: Expert Panel, 2014. 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStevens PE, Ahmed SB, Carrero JJ, Foster B, Francis A, Hall RK, et al. KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int. 2024;105(4):S117\u0026ndash;314.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRutebarika DA, Namuganga AR, Otike C, Aturinde J, Mpiima S, Nanyinji E et al. Bridging gaps in sickle cell disease care: Screening uptake and policy challenges [Conference Abstract]. Journal of Interventional Epidemiology and Public Health. 2025;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCulloch MI, Argent AC, Morrow B, Nourse P, Coetzee A, Du Buisson C, et al. Lessons learned from regional training of paediatric nephrology fellows in Africa. Pediatr Nephrol. 2023;38(11):3757.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmekal MD, Bello AK, Donald M, Zaidi D, McBrien K, Nicholson K, et al. Enhancing primary care capacity in chronic kidney disease management: a quality improvement educational initiative. BMJ Open. 2021;11(11):e046068.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmeltzer MP, Howell KE, Treadwell M, Preiss L, King AA, Glassberg JA, et al. Identifying barriers to evidence-based care for sickle cell disease: results from the Sickle Cell Disease Implementation Consortium cross-sectional survey of healthcare providers in the USA. BMJ Open. 2021;11(11):e050880.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasese RV, Bulgin D, Douglas C, Shah N, Tanabe P. Barriers and facilitators to care for individuals with sickle cell disease in central North Carolina: The emergency department providers\u0026rsquo; perspective. PLoS ONE. 2019;14(5):e0216414.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInusa BPD, Mariachiara L, Giovanni P, Ataga I, Inusa K, Mariachiara BPD. L, et al. Sickle Cell Nephropathy: Current Understanding of the Presentation, Diagnostic and Therapeutic Challenges. Hematology - Latest Research and Clinical Advances; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamkelawan V, Mbeje PN, Mtshali NG. Recommendation to improve chronic kidney disease management guideline in primary healthcare. 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Understanding the barriers for prevention and detection of chronic kidney disease among healthcare professionals in Syria: a qualitative study. BMJ Open. 2025;15(12):e103959.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArcher NM, Inusa B, Makani J, Nkya S, Tshilolo L, Tubman VN, et al. Enablers and barriers to newborn screening for sickle cell disease in Africa: results from a qualitative study involving programmes in six countries. BMJ Open. 2022;12(3):e057623.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKilonzi M, Mlyuka HJ, Felician FF, Mwakawanga DL, Chirande L, Myemba DT, et al. Barriers and Facilitators of Use of Hydroxyurea among Children with Sickle Cell Disease: Experiences of Stakeholders in Tanzania. Hemato. 2021;2(4):713\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObeagu EI. Public\u0026ndash;private partnerships in tackling sickle cell disease in Uganda: a narrative review. Annals Med Surg. 2025;87(6):3339\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGyamfi J, Ojo T, Iwelunmor J, Ogedegbe G, Ryan N, Diawara A, et al. Implementation science research for the scale-up of evidence-based interventions for sickle cell disease in africa: a commentary. Global Health. 2021;17(1):20.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Sickle cell nephropathy, Early renal screening, Healthcare provider readiness, Diagnostic availability, North-Kivu, Democratic Republic of the Congo","lastPublishedDoi":"10.21203/rs.3.rs-8630909/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8630909/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSickle cell nephropathy is a common and progressive complication of sickle cell disease in children and a major contributor to early morbidity and long-term chronic kidney disease. Although early renal screening is essential to prevent irreversible damage, its implementation remains limited in resource-constrained settings. This study assessed healthcare provider readiness for the early detection and management of sickle cell nephropathy in North Kivu Province, Democratic Republic of the Congo.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003e We conducted an exploratory cross-sectional study among medical and paramedical healthcare providers involved in the care of children with sickle cell disease. Data were collected using a structured electronic questionnaire evaluating knowledge, attitudes, practices, and diagnostic availability related to renal screening. Composite scores were constructed for these domains, and factors associated with adequate renal care readiness were examined using multivariable logistic regression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTwo hundred providers were included. Adequate knowledge was observed in 50.5% of participants, while only 21.0% demonstrated favorable attitudes. Reported practices were poor, with good practice identified in only 4.1% of respondents. Diagnostic availability was limited (mean score 39.8\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5), particularly in primary and secondary facilities. Overall renal care readiness was suboptimal, and adequate diagnostic availability emerged as the main independent determinant. Key barriers included recurrent shortages of diagnostic supplies, financial constraints, and high workload, whereas standardized protocols and institutional support were reported as facilitators.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDespite moderate knowledge levels, early renal screening for children with sickle cell disease is insufficiently implemented in North Kivu. Health system capacity, especially access to essential diagnostic tools, is central to effective renal care readiness. Strengthening diagnostic availability, standardizing care pathways, and reinforcing targeted training may substantially improve early detection and prevention of kidney disease in resource-limited settings.\u003c/p\u003e","manuscriptTitle":"Renal care readiness and gaps in early detection of sickle cell nephropathy in children in North Kivu Province, Democratic Republic of the Congo: an exploratory cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 06:56:52","doi":"10.21203/rs.3.rs-8630909/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-28T14:18:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-23T22:35:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-21T13:13:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-20T03:57:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115318964679803030335338153855087763830","date":"2026-02-15T04:36:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38285669218483829189486820988201887864","date":"2026-02-14T20:04:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318240597069383606056531067195217478683","date":"2026-02-13T18:45:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295964173735860764830213266386043832148","date":"2026-02-13T02:15:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"309594538394556203288916675033154368028","date":"2026-02-12T20:06:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-12T19:56:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-20T13:01:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-20T12:11:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-20T12:06:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2026-01-18T11:12:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f1bcda7-4569-4a85-bb06-437c7920d6e7","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T10:14:13+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 06:56:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8630909","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8630909","identity":"rs-8630909","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}