Pre-diagnosis and pre-treatment loss to follow-up and associated factors among presumptive tuberculosis patients in Uganda

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Wafula, Mary Nakafeero, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4641015/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Dec, 2024 Read the published version in BMC Health Services Research → Version 1 posted 13 You are reading this latest preprint version Abstract Background Loss to follow-up (LTFU) of presumptive tuberculosis (TB) patients before completing diagnosis (pre-diagnosis LTFU) and before initiating treatment for those diagnosed (pre-treatment LTFU) is a challenge in the realization of the End TB Strategy. We assessed the proportion of pre-diagnosis and pre-treatment LTFU and associated factors among presumptive and diagnosed TB patients in the selected health facilities. Methods This was a retrospective cohort study involving a review of routinely collected data from presumptive, laboratory and TB treatment registers from January 2019 to December 2022. The study was conducted in three general hospitals and one lower-level health center IV in Central Uganda. We defined pre-diagnosis LTFU as failure to complete TB diagnosis within 30 days of being presumed and pre-treatment LTFU as failure to initiate TB treatment within 14 days from being diagnosed. Modified Poisson regression was used to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) of factors associated with pre-diagnosis and pre-treatment LTFU. Results Of the 13,064 presumptive TB patients, 39.9% were aged 25 to 44 years, and 57.1% were females. Almost a third, 28.3% (3,699/13.064) experienced pre-diagnosis LTFU and 13.7% (163/1187) did not initiate treatment. Pre-diagnosis LTFU was more likely to occur among patients aged 0–14 years (adj PR 1.1, 95% CI: 1.06,1.24), females (adj.PR = 1.06, 95% CI: 1.01, 1.12) and those with no record of place of residence (adj. PR = 2.7, 95% CI: 2.54, 2.93). In addition, patients with no record of phone contact were more likely to be LTFU, (adj. PR = 1.1, 95% CI: 1.05, 1.17). Pre-treatment LTFU was also more likely among patients with no record of place of residence (adj PR 7.1, 95% CI: 5.13,9.85) and those with no record of phone contact (adj PR 2.2, 95% CI: 1.63,2.86). Patients presumed from the HIV clinics were 40% less likely to experience pre-treatment LTFU compared to those in the outpatient departments (adj PR 0.6, 95% CI: 0.41,0.88). Conclusion High proportions of pre-diagnosis and pre-treatment LTFU were observed in this study. This calls for urgent interventions at these time points in the TB care cascade to be able to realise the End TB Strategy. Tuberculosis loss to follow-up pre-diagnosis loss to follow-up pre-treatment loss to follow-up Uganda Figures Figure 1 Figure 2 Figure 3 Introduction Tuberculosis (TB) remains a global public health challenge and is the second leading cause of death from a single infectious agent after COVID-19 [ 1 ]. Although the global incidence has been reduced by approximately 2% for most of the decades, delays in TB diagnosis and treatment initiation remain globally, requiring more effort to find the missing patients and achieve the 2035 End TB strategy [ 2 , 3 ]. In 2022, there were an estimated 10.6 million new TB patients out of which 3.1 million, around 30%, were either not diagnosed or were not notified to national TB programs [ 1 ]. The largest gap in the TB care cascade in both high- and low-TB burden countries is the significant number of patients who are not diagnosed [ 4 ]. Pre-diagnosis loss to follow-up (LTFU) has been estimated to range between 8% and 55% in Asia and Africa [ 5 – 12 ]. Similarly, a comparison study between 30 high and 153 low-TB burden countries revealed that 35% of TB incident cases in high-TB burden countries were not diagnosed compared to 20% in low-TB burden countries [ 4 ]. Moreso, in a systematic review in low- and middle-income countries (LMICs), pre-treatment LTFU was estimated to be between 6% and 38% in Africa, excluding Uganda [ 13 ]. Pre-diagnosis or pre-treatment LTFU increases community transmission of TB, TB severity and poor patient outcomes [ 7 , 13 – 16 ]. Earlier studies revealed some of the associated factors for pre-diagnosis and pre-treatment LTFU as being HIV positive, residing far from the health facility, no record of tracking information such as phone contact and place of residence, poor communication between health workers and patients, long waiting time and need for repeat visits at health facilities [ 7 , 8 , 17 – 19 ]. In Uganda, a few studies have assessed this LTFU in the TB care cascade with Ekuka et al., reporting a pre-diagnosis LTFU of up to 40.7% and Zawedde et al., reporting a pre-treatment LTFU of 19.6% [ 12 , 16 ]. Both studies focused on one type of loss in the TB care cascade that is; pre-diagnosis LTFU only for Ekuka et al., [ 12 ] and pre-treatment LTFU only for Zawedde et al., [ 16 ] which limits understanding of the extent of these losses in Uganda. Therefore, the aim of this study was to assess the proportion of both pre-diagnosis and pre-treatment LTFU and associated factors among presumptive TB patients in Uganda over a four-year period. Methods Study setting The study was conducted in four selected health facilities in Mukono, Buikwe and Mityana districts, Central Uganda. The health facilities included three general hospitals (2 government-owned and 1 private-not-for profit) and one lower-level health center IV (government-owned). The selection of study facilities was based on high volume and to ensure representation of the different levels of the health care system and type of facility ownership, whether government or private-not-for profit owned. In the study facilities, patients presenting with symptoms suggestive of TB are screened and presumed to have TB from any entry point of the health facility, including the outpatient department (OPD), HIV clinic, Pediatric clinic and Antenatal clinic. The symptomatic screening is in accordance with the four cardinal symptoms of TB: persistent cough of two weeks or more, night sweets, fever of more than two weeks, weight loss and if a child, poor weight gain and previous contact with a TB patient [ 20 ]. After the patient has been presumed, they are referred for TB diagnosis (Fig. 1 ). TB diagnosis is performed using GeneXpert (Xpert MTB/RIF), which is the recommended first diagnostic test [ 21 ]. Depending on the availability of tests and how the patient presents, other diagnostic tests are available, including sputum microscopy, chest X-ray and urine TB LAM (for HIV-positive patients) [ 21 , 22 ]. A diagnosed TB patient is defined as one who is bacteriologically confirmed by either Xpert MTB/RIF, smear microscopy or TB Lam or those confirmed by chest X-ray. Patient socio-demographic information, contacts, address of residence, clinical details and dates of registration are recorded in the national standardized paper-based registers at each care entry point, as described in Fig. 1 . More details on the flow of the patients right from when they arrive at the health facility are provided in the flow chart in Fig. 1 . Study design and population This was a retrospective cohort study involving a review of routinely collected data of presumptive and diagnosed TB patients presenting to the study facilities. The study included presumptive TB patients of all ages who presented to the study facilities from January 2019 to December 2022. Presumptive TB patients were defined as those presenting with any of the four cardinal symptoms of TB. The four-year period was selected to allow comparison of the pre-diagnosis and pre-treatment LTFU; before and during the COVID-19 pandemic. We referred to 2019 as before the COVID-19 pandemic and 2020–2022 as during the pandemic based on WHO periods of declarations of COVID-19 as a public health emergency of international concern [ 23 , 24 ]. Data collection procedures : Data on presumptive TB patients who presented to the study health facilities were extracted from the presumptive TB registers at all screening points/units. These patients were then followed up in the laboratory and radiology registers for completion of TB diagnosis within 30 days. Presumptive TB patients who tested positive for TB were followed up in the facility treatment register for treatment initiation within 14 days. Data were cross-matched from all the registers (presumptive, laboratory, radiology and treatment), following up a patient once they were presumed to have TB up to when they completed diagnosis or initiated treatment if diagnosed or lost to follow-up. Four variables were used for cross-matching the data in the different registers: patient name, age, area of stay and date of presumption. Data were collected using an extraction tool adapted from a similar study conducted in Zimbabwe [ 8 ]. The data extraction tool was pre-tested, and the refined tool was uploaded to the KoboCollect mobile data collection app. The following variables were extracted: age, sex, place of residence and phone contact, TB disease type, HIV status and dates of presumption, diagnosis and initiation of treatment for the presumptive patients who tested positive. Research assistants with experience in research and extracting data from large databases were recruited and trained in a three-day workshop for data collection. Meetings were held at the end of each data collection day to check for adherence to the data collection procedures and operational definitions, consistency, and completeness of the data collected. The data submitted daily to the server were checked for accuracy and any errors which were communicated to the research assistants for correction during subsequent data extraction. Statistical methods Sampling We used total enumerative sampling, where all records meeting the inclusion criteria were extracted from the registers. A post hoc power estimation was performed to estimate whether we had the power to conduct the analysis. Variables and measurements: We defined pre-diagnosis LTFU as failure to complete TB diagnosis within 30 days of being presumed for TB. The 30-day follow-up period was selected based on previous studies for comparison [ 10 , 13 ]. This referred to either dropping out before having the requested investigations done or after by not having results. Having results documented in the register was used as a proxy for receipt of results by the patient. Pre-diagnosis LTFU was measured as the proportion of patients who were lost before completing TB out of the total number of all presumptive TB patients registered in the study period. Pre-treatment LTFU was defined as failure to initiate TB treatment within 14 days of being diagnosed based on previous studies [ 16 , 18 , 25 ]. This was measured as the proportion of diagnosed TB patients who were lost before initiating treatment out of the total number of diagnosed TB patients registered in the study period. Data management and analysis The final dataset was downloaded from the Kobocollect mobile app into an Excel spreadsheet and exported to Stata software version 14 for cleaning and analysis. Age, name, area of stay and registration date were key variables for identifying duplicates. Presumptive TB patients with missing age and dates were excluded because these were key variables for analysis and identifiers for duplicates. We also dropped anyone with a duplicate registration date within 3 days which signified double registration. Descriptive statistics such as frequency distributions, median and interquartile ranges (IQRs) were computed. The trends of pre-diagnosis LTFU over time were compared using a line graph. A modified Poisson regression analysis model via generalized linear models with family (Poisson) and link (log) was constructed to obtain the unadjusted estimates for factors associated with pre-diagnosis LTFU [ 26 ]. Modified Poisson regression was preferred over logistic regression because the proportions of pre-diagnosis and pre-treatment LTFU were greater than 10%; hence, odds ratios would provide biased estimates of prevalence ratios [ 27 , 28 ]. Independent variables that were statistically significant at the bivariate analysis at p < 0.2 and those known from the literature to be associated with pre-diagnosis LTFU were entered into a model to establish factors independently associated while controlling for potential confounders. The level of statistical significance was set at a p-value less than 0.05. An exploratory logical model-building method following the conceptualization of the study outcome and literature review was used to generate the final model. Variables in a model that were found to be consistently insignificant and did not add any value in terms of goodness of fit were eliminated. Selection of the final model was performed using likelihood ratio tests. Results A total of 13,496 presumptive patient records were abstracted from the facility records. Of these, 432 records were excluded from the analysis (Fig. 2 ). Socio-demographic and clinical characteristics of study participants Thirty-nine percent (5,213/13,064) of the patients were aged 25 to 44 years, with a median age of 35 years (IQR, 24–50). Over half of the patients 57.1% (7,462/13,064) were female. The percentage of presumptive TB patients was highest in the year 2022 at 34.2% (4,464/13,064) and lowest in 2020 at 14.9% (1956/13,064) see Table 1 . Forty-two percent of the patients were HIV positive, 42.9% (5,605/13,064) see Table 1 . Table 1 Socio-demographic and clinical characteristics of the participants Variable N = 13,064 (%) Age (median = 35, IQR; 24, 50) 0 to 14 1603 (12.3) 15 to 24 1907 (14.6) 25 to 44 5213 (39.9) 45+ 4341 (33.2) Sex Male 5,602 (42.9) Female 7,462 (57.1) Record of place of residence available Yes 11,002 (84.2) No 2,062 (15.8) Record of phone contact available Yes 8,679 (66.4) No 4,385 (33.6) Facility unit of screening for presumptive patients Outpatient department 4302 (32.9) TB Unit 2,995 (22.9) Maternity 398 (3.1) HIV clinic 3,506 (26.8) Pediatric clinic 1,284 (9.8) *Community outreach programs 579 (4.4) Year of presumption 2019 3,760 (28.8) 2020 1,956 (14.9) 2021 2,884 (22.1) 2022 4,464 (34.2) Facility ownership Public (Government funded) 10,220 (78.2) Private not for Profit (PNFP) 2,844 (21.8) Facility level Health center IV 1,668 (12.8) Hospital 11,396 (87.2) Accessibility to TB testing services at the health facility Multiple services (Gene Xpert, microscopy, TB Lam, Chest Xray) 11,396 (87.2) Only microscopy 1,668 (12.8) District of presumption Buikwe 4615 (35.3) Mityana 3937 (30.1) Mukono 4512 (34.6) HIV status (n = 13,064) Negative 5,936 (45.4) Positive 5,605 (42.9) Unknown 1,523 (11.7) * Presumptive TB patients from the community outreach programs were documented in the health center IV only in a presumptive TB register at the outpatient department Pre-diagnosis LTFU and factors associated among presumptive TB patients Overall, 28.3% (3699/13064) experienced pre-diagnosis LTFU (Fig. 2 ). Over half of those who conducted the TB investigations required, did not have their test results documented in the laboratory or chest x-ray register on the same day of being presumed, 52.8% (4983/9439). TB was diagnosed among 12.7% (1187/9365) patients (Fig. 2 ). Pre-diagnosis LTFU among the study participants was highest in 2019 at 48.7% (1,832/3760) and 42.9% (840/1956) in 2020. This was followed by a sharp decline in 2021 to 14.3% (413/2884) and 13.8% (614/4464) in 2022 (Fig. 3 ). Factors associated with pre-diagnosis LTFU among presumptive TB patients At multivariate analysis, females (adj PR 1.1, 95% CI: 1.01,1.12), those aged 0–14 years (adj PR 1.1, 95% CI: 1.06,1.24) and patients presumed from PNFPs (adj PR 1.2, 95% CI: 1.11,1.28) were more likely to experience pre-diagnosis LTFU. In addition, patients with no record of place of residence (adj PR 2.7, 95% CI: 2.54,2.93) and no record of phone contact (adj PR 1.1, 95% CI: 1.05,1.17) were also more likely to experience pre-diagnosis LTFU compared to those whose details were recorded in the registers. On the other hand, patients presumed from hospitals (adj PR 0.7, 95% CI: 0.69,0.81) and those presumed to have TB between 2020 and 2022 were less likely to be lost before completing TB diagnosis (Table 2 ). Table 2 Factors associated with pre-diagnosis LTFU from 2019 to 2022 in study health facilities in Uganda Characteristic Pre-diagnosis LTFU % (n/N) Crude PR (95% CI) Adjusted PR (95% CI) P-value Age 45+ 28.7 (1246/4341) 1 (Ref) 1 (Ref) 0 to 14 33.9 (543/1603) 1.2 (1.09–1.28) 1.1 (1.06–1.24) < 0.001* 15 to 24 27.8 (531/1907) 1.0 (0.89–1.06) 1.0 (0.89–1.05) 0.477 25 to 44 26.5 (1379/5213) 0.9 (0.86–0.98) 1.0 (0.90–1.01) 0.120 Sex Male 27.4 (1537/5602) 1 (Ref) 1 (Ref) Female 28.9 (2162/7462) 1.1 (0.99–1.11) 1.1 (1.01–1.12) 0.019* Record of place of residence available Yes 26.5 (2913/11002) 1 (Ref) 1 (Ref) No 38.1 (786/2062) 1.4 (1.35–1.53) 2.7 (2.54–2.93) < 0.001* Record of phone contact available Yes 27.1 (2354/8679) 1 (Ref) 1 (Ref) No 30.7 (1345/4385) 1.1 (1.07–1.19) 1.1 (1.05–1.17) < 0.001* Facility unit of screening for presumptive patients Outpatient department 33.7 (1449/4302) 1 (Ref) 1 (Ref) TB Unit 35.3 (1056/2995) 1.0 (0.98–1.12) 1.1 (1.03–1.17) 0.005* Maternity 35.7 (142/398) 1.1 (0.92–1.21) 1.1 (0.96–1.26) 0.183 HIV clinic 21.6 (756/3506) 0.6 (0.59–0.69) 0.8 (0.74–0.87) < 0.001* Pediatric clinic 21.1 (271/1284) 0.6 (0.56–0.70) 0.9 (0.79–0.99) 0.036* Community outreach programs 4.3 (25/579) 0.1 (0.09–0.19) 0.2 (0.14–0.31) < 0.001* HIV status Negative 28.0 (1664/5936) 1 (Ref) 1 (Ref) Positive 24.9 (1399/5605) 0.9 (0.84–0.95) 1.0 (0.94–1.08) 0.784 Unknown 41.8 (636/1523) 1.5 (1.39–1.60) 1.4 (1.30–1.51) < 0.001* Year of presumption 2019 48.7 (1832/3760) 1 (Ref) 1 (Ref) 2020 42.9 (840/1956) 0.9 (0.83–0.94) 0.9 (0.84–0.95) < 0.001* 2021 14.3 (413/2884) 0.3 (0.27–0.32) 0.2 (0.22–0.26) < 0.001* 2022 13.8 (614/4464) 0.3 (0.26–0.31) 0.2 (0.21–0.24) < 0.001* Facility level Health center IV 25.8 (430/1668) 1 (Ref) 1 (Ref) Hospital 28.7 (3269/11396) 1.1 (1.02–1.21) 0.7 (0.69–0.81) < 0.001* Facility ownership Public (Government funded) 29.8 (3042/10220) 1 (Ref) 1 (Ref) Private not for Profit (PNFP) 23.1 (657/2844) 0.8 (0.72–0.84) 1.2 (1.11–1.28) < 0.001* Accessibility to TB testing services at the health facility Only microscopy 25.8 (430/1668) 1 (Ref) Multiple services (Gene Xpert, microscopy, TB Lam, Chest Xray) 28.7 (3269/11396) 1.1 (1.02–1.21) District of presumption Buikwe 31.9 (1470/4615) 1 (Ref) Mityana 29.0 (1142/3937) 0.9 (0.85–0.97) Mukono 24.1 (1087/4512) 0.8 (0.71–0.81) * Statistically significant at < 0.05 Pre-treatment LTFU and factors associated among diagnosed TB patients Thirteen percent (163/1187) of the patients who were diagnosed with TB experienced pre-treatment LTFU (Fig. 2 ). Pre-treatment LTFU was highest in 2019 at 15.0% (36/240) which slightly decreased in 2020 to 13.7% (20/146) and 13.2% (50/378) in 2022. Patients who had no record of place of residence (adj PR 7.1, 95% CI: 5.16,9.88) and no record of phone contact (adj PR 2.2, 95% CI: 1.63,2.86) were more likely to experience pre-treatment LTFU compared to those whose details were recorded in the registers. Those with an unknown HIV status were 1.9 times more likely to experience pre-treatment LTFU compared to those who were HIV negative, (adj PR 1.9, 95% CI: 1.09,3.27). Patients presumed from the HIV clinics were 40% less likely to experience pre-treatment LTFU compared to those presumed from the outpatient departments (adj PR 0.6, 95% CI: 0.41,0.88). Patients presumed to have TB in 2022 were less likely to be lost before initiating treatment compared to those presumed to have TB in 2019 (adj PR 0.6, 95% CI: 0.42,0.96) see Table 3 . Table 3 Factors associated with pre-treatment LTFU from 2019 to 2022 in study health facilities in Uganda Characteristic Pre-treatment LTFU % (n/N) Crude PR (95% CI) Adjusted PR (95% CI) P-value Age 45+ 15.4 (57/371) 1 (Ref) 1 (Ref) 0 to 14 15.4 (18/117) 1.0 (0.61–1.63) 1.2 (0.77–1.93) 0.394 15 to 24 13.2 (22/167) 0.9 (0.54–1.35) 0.8 (0.54–1.29) 0.416 25 to 44 12.4 (66/532) 0.8 (0.58–1.12) 1.0 (0.73–1.35) 0.968 Sex Male 11.9 (87/730) 1 (Ref) 1 (Ref) Female 16.6 (76/457) 1.4 (1.05–1.86) 1.2 (0.93–1.61) 0.149 Record of place of residence available Yes 10.4 (117/1129) 1 (Ref) 1 (Ref) No 79.3 (46/58) 7.7 (6.17–9.50) 7.1 (5.16–9.88) < 0.001* Record of Phone contact available Yes 10.6 (101/953) 1 (Ref) 1 (Ref) No 26.5 (62/234) 2.5 (1.89–3.32) 2.2 (1.63–2.86) < 0.001* Facility unit of screening for presumptive patients Outpatient department 16.9 (64/378) 1 (Ref) 1 (Ref) TB Unit 12.9 (46/355) 0.8 (0.54–1.09) 0.8 (0.56–1.13) 0.209 Maternity 25.00 (4/16) 1.5 (0.61–3.55) 1.4 (0.62–3.03) 0.439 HIV clinic 11.1 (37/334) 0.7 (0.45–0.95) 0.6 (0.41–0.88) 0.010* Pediatric clinic 10.6 (10/94) 0.6 (0.34–1.18) 0.7 (0.36–1.43) 0.341 Community outreach programs 20.0 (2/10) 1.2 (0.34–4.16) 2.4 (0.64–9.26) 0.190 HIV status Negative 13.4 (74/553) 1 (Ref) 1 (Ref) Positive 12.5 (76/610) 0.9 (0.69–1.26) 1.1 (0.77–1.50) 0.667 Unknown 54.2 (13/24) 4.0 (2.65–6.19) 1.9 (1.09–3.27) 0.024* Year of presumption 2019 15.0 (36/240) 1 (Ref) 1 (Ref) 2020 13.7 (20/146) 0.9 (0.55–1.52) 1.0 (0.58–1.58) 0.871 2021 13.5 (57/423) 0.9 (0.61–1.32) 0.8 (0.55–1.20) 0.303 2022 13.2 (50/378) 0.9 (0.59–1.31) 0.6 (0.42–0.96) 0.032* Facility level Health center IV 10.2 (14/137) 1 (Ref) 1 (Ref) Hospital 14.2 (149/1050) 1.4 (0.83–2.33) 1.1 (0.63–1.90) 0.758 Facility ownership Public (Government funded) 13.9 (137/988) 1 (Ref) 1 (Ref) Private not for Profit (PNFP) 13.1 (26/199) 0.9 (0.64–1.39) 1.1 (0.71–1.59) 0.760 Accessibility to TB testing services at the health facility Only microscopy 10.2 (14/137) 1 (Ref) Multiple services (Gene Xpert, microscopy, TB Lam, Chest Xray) 14.2 (149/1050) 1.4 (0.83–2.33) District of presumption Buikwe 15.5 (50/323) 1 (Ref) Mityana 13.8 (73/528) 0.9 (0.64–1.25) Mukono 11.9 (40/336) 0.8 (0.52–1.13) * Statistically significant at < 0.05 Discussion This study assessed pre-diagnosis and pre-treatment LTFU and associated factors among presumptive and diagnosed TB patients from 2019 to 2022 in selected health facilities in central Uganda. Twenty-eight percent of the participants experienced pre-diagnosis LTFU and thirteen percent of those who tested positive for TB did not initiate treatment when they were diagnosed. Over half of those who conducted the TB investigations required, did not have their results on the same day of being presumed, 52.8% (4983/9439). Pre-diagnosis LTFU was highest in 2019 and 2020 which decreased sharply in 2021 and 2022. Patients with no record of place of residence and no record of phone contact were more likely to experience pre-diagnosis and pre-treatment LTFU. The high pre-diagnosis LTFU was attributed to no record of patient tracking information of place of residence and phone contact. Our study also revealed that half of the participants do not have results on the same day of being presumed for TB which requires repeat visits to the health facilities hence contributing to the LTFU. Similar pre-diagnosis LTFU proportions have been reported in studies in Zimbabwe (10%-25%), Tanzania (16%), India (30%) and in a study of 30 countries with a high-TB burden (35%) [ 4 , 5 , 8 , 10 , 29 , 30 ]. However, a previous study in Uganda reported a higher proportion of LTFU of 40.7% [ 12 ]. This could be because of the differences in the study setting, as the study by Ekuka et al. was conducted in a rural area where patients face more challenges in healthcare access. Indeed, studies have indicated that presumptive TB patients from rural health facilities tend to be LTFU (Murongazvombo et al., 2019, Padingani et al., 2018, Tedla et al., 2020). Pre-diagnosis LTFU threatens TB control by increasing the risk of community spread of the disease hence the need for health system strengthening solutions to ensure that every patient presumed to have TB is diagnosed. Similarly, the high pre-treatment LTFU reported in this study was due to the non-availability of patient tracking information of place of residence and phone contact coupled with the failure of health facilities to provide patients with same day results. Other studies have found the same reason of no patient tracking records, poor patient-provider communication, older age, history of TB disease, distance of residence from the health facility, complexity of navigating the system, and health care worker attitude as contributing factors to the pre-treatment LTFU [ 17 – 19 , 25 , 31 – 33 ]. This proportion of pre-treatment LTFU is comparable to that in other studies, which reported a range of 4–42% [ 13 , 16 , 18 , 25 , 31 ]. The lack of timely treatment initiation for TB patients increases the severity of the disease and the likelihood of poor treatment outcomes [ 14 , 16 , 34 , 35 ]. Patients aged 0–14 years were more likely to experience pre-diagnosis LTFU compared to those aged 45 years and above. This may be because of the existing diagnostic challenges of TB among children, such as difficulty obtaining sputum and a lack of functional radiological investigations (X-rays) at health facilities [ 36 – 38 ]. Moreso, patients aged 0–14 years do not independently make decisions to seek care and hence depend on the availability and decisions of the care takers to seek care. Although our study revealed no association for pre-treatment LTFU among this age group, a study in Uganda revealed that 18.7% of smear-positive children were not initiated on treatment [ 39 ]. Early detection of TB especially in children and adolescents is crucial for improving treatment outcomes and preventing post TB lung impairment. Pre-diagnosis and pre-treatment LTFU levels were highest in 2019 and 2020 and drastically decreased in 2021 and 2022 during the peak of the COVID-19 pandemic. The reduction in LTFU from 2020 to 2021 was attributed to the intensified efforts by the National TB and Leprosy Program (NTLP), which included the integration of TB and COVID-19 services; community campaigns such as TB Catch-up and Community Awareness, Screening, Testing, prevention and treatment to end TB Campaign (CAST TB), which involved community awareness of TB; and intensified screening and diagnosis of patients for TB [ 40 , 41 ]. These findings are similar to those of national and WHO reports showing that Uganda is one of the countries that quickly recovered from the effects of COVID-19 in terms of case notification of newly diagnosed TB patients [ 1 ]. The integration of health services, especially during outbreaks, is key to ensuring continuity of service delivery while harnessing the power of available human resource. A key strength to our study is the analysis of data giving a perspective of one year before the COVID-19 pandemic (2019) and three years into the pandemic (2020–2022). This provides information on the effect of disease outbreaks on the continuity of service provision and health seeking behaviors of the patients. This information may inform preparedness and response planning for future outbreaks and pandemics. We also had a large sample size of 13,064 which improved the precision of the estimates. We utilized secondary data which often present with missing data and quality issues. We mitigated the likelihood of this by cross-matching data from the presumptive, laboratory and TB unit treatment registers during data collection to limit the missingness of data on key variables such as age, sex, date of sample collection and results received. This information is often recorded in at least two of the registers. Moreso, availability of results in the register was used as a proxy for the completion of TB diagnosis, which may not translate to a patient receiving results for further management. A prospective study is recommended for future studies to establish the actual receipt of results by patients as an endpoint for the completion of TB diagnosis. Another limitation is that we could not verify whether the patients who were LTFU before completing TB diagnosis completed the diagnosis from another health facility elsewhere or did not complete at all. We recommend that future studies explore whether TB diagnosis is completed elsewhere through the use of patient pathway analysis and more robust triangulation methods across health facilities. Conclusion In this retrospective cohort analysis study in central Uganda, we found a high pre-diagnosis LTFU of 28% among the presumptive TB patients and pre-treatment LTFU of 13%. This calls for urgent interventions to reduce these losses in the care cascade to be able to realise the End TB Strategy. Over half of participants who conducted the TB investigations required did not have results on the same day of being presumed. There is need to strengthen the capacity of laboratories to provide same day results for patients so as to reduce chances of LTFU. No record of place of residence or phone contact in the patient registers was significantly associated with LTFU, which calls for improved documentation at health facilities to ease patient follow-up for TB service provision and contact tracing. Abbreviations Adj Adjusted ART Antiretroviral therapy CAST TB Community Awareness, Screening, Testing, prevention and treatment to end TB Campaign CI Confidence Interval COVID-19 Coronavirus disease HIV Human immunodeficiency virus IQR Interquartile ranges LMICs Low- and middle-income countries LTFU Loss to follow-up MOH Ministry of Health NTLP National TB and Leprosy Program PNFP Private-not-for-profit PR Prevalence ratio TB Tuberculosis UN United Nations WHO World Health Organization Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki [42]. Approval to conduct the study was obtained from the Research and Ethics Committee of Makerere University School of Public Health (#SPH-2023-427), and the study was registered with the Uganda National Council of Science and Technology (HS3000ES). The privacy and confidentiality of all the data obtained were ensured by limiting access of the data to only the study investigator and data manager. Since this was a review of records with no face-to-face interviews with patients, the need for informed consent was waived by the ethics committee. Consent for publication Not Applicable Availability of data and materials The data and materials supporting results of this manuscript are available through the Research and Ethics Committee of Makerere University School of Public Health. They can be contacted at [email protected] . Competing interests The authors declare no competing interests in the study. Funding This study is part of the EDCTP2 programme supported by the European Union (grant number: TMA2018SF-2472-MILEAGE4TB). Author contributions RN co-conceptualised the study with EB and coordinated the implementation including manuscript writing. STW, MN, AND LN participated in study implementation, data analysis and manuscript writing. NK, HL, ST, JNS and LA provided technical support during implementation of the study and guided the contextual interpretation of the results during analysis and manuscript writing. EB conceptualised the study and provided overall technical guidance during implementation and manuscript writing. All authors read and approved the final manuscript. Acknowledgements We extend our appreciation to Ms. Lillian Tabwenda, Mr. Emmanuel Biryabarema, Mr. Joshua Mwebaze and Mr. Ignatius Kiiza and the health workers in the study health facilities for the devoted efforts invested in the study’s data collection and management processes. References WHO. Global tuberculosis report 2023. Geneva: World Health Organization; 2023. UN. The Sustainable Development Goals eSocialSciences; 2015. Uplekar M, Weil D, Lonnroth K, Jaramillo E, Lienhardt C, Dias HM, et al. WHO's new end TB strategy. 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Pre-diagnostic drop out of presumptive TB patients and its associated factors at Bugembe Health Centre IV in Jinja, Uganda. Afr Health Sci. 2020;20(2):633–40. MacPherson P, Houben RM, Glynn JR, Corbett EL, Kranzer K. Pre-treatment loss to follow-up in tuberculosis patients in low- and lower-middle-income countries and high-burden countries: a systematic review and meta-analysis. Bull World Health Organ. 2014;92(2):126–38. Tiemersma EW, van der Werf MJ, Borgdorff MW, Williams BG, Nagelkerke NJ. Natural history of tuberculosis: duration and fatality of untreated pulmonary tuberculosis in HIV negative patients: a systematic review. PLoS ONE. 2011;6(4):e17601. Getnet F, Demissie M, Worku A, Gobena T, Tschopp R, Girmachew M, et al. Delay in diagnosis of pulmonary tuberculosis increases the risk of pulmonary cavitation in pastoralist setting of Ethiopia. BMC Pulm Med. 2019;19:1–10. Zawedde-Muyanja S, Musaazi J, Manabe YC, Katamba A, Nankabirwa JI, Castelnuovo B, et al. Estimating the effect of pretreatment loss to follow up on TB associated mortality at public health facilities in Uganda. PLoS ONE. 2020;15(11):e0241611. Mulaku MN, Nyagol B, Owino EJ, Ochodo E, Young T, Steingart KR. Factors contributing to pre-treatment loss to follow-up in adults with pulmonary tuberculosis: a qualitative evidence synthesis of patient and healthcare worker perspectives. Global Health Action. 2023;16(1):2148355. Mulaku M, Ochodo E, Young T, Steingart K. Pre-treatment loss to follow-up in adults with pulmonary TB in Kenya. Public health action. 2024;14(1):34–9. Zawedde-Muyanja S, Katamba A, Cattamanchi A, Castelnuovo B, Manabe YC. Patient and health system factors associated with pretreatment loss to follow up among patients diagnosed with tuberculosis using Xpert® MTB/RIF testing in Uganda. BMC Public Health. 2020;20(1):1855. WHO. WHO consolidated guidelines on tuberculosis. Module 2: screening – systematic screening for tuberculosis disease. Geneva: World Health Organization; 2021. MoH. In: Programme UNTLC, editor. Manual for management and control of Tuberculosis and Leprosy in Uganda. Kampala: Ministry of Health, Uganda; 2017. NTLP. National tuberculosis and leprosy program quarterly bulletin. National Tuberculosis and Leprosy Program, Ministry of Health Uganda; 2018. Statement on the fifteenth meeting of the IHR. (2005) Emergency Committee on the COVID-19 pandemic [press release]. Geneva: World Health Organization2023. COVID-19 Public Health Emergency of International Concern (PHEIC). Global research and innovation forum [press release]. Geneva2020. Thomas BE, Subbaraman R, Sellappan S, Suresh C, Lavanya J, Lincy S, et al. Pretreatment loss to follow-up of tuberculosis patients in Chennai, India: a cohort study with implications for health systems strengthening. BMC Infect Dis. 2018;18(1):142. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702–6. skove T, Deddens J, Petersen MR, Endahl L. Prevalence proportion ratios: estimation and hypothesis testing. Int J Epidemiol. 1998;27(1):91–5. Lee J, Tan CS, Chia KS. A practical guide for multivariate analysis of dichotomous outcomes. Ann Acad Med Singap. 2009;38(8):714–9. Mgina N, Elias G, Godfather K, Ramadhan S, Erica S, Sayoki M, et al. Magnitude and factors associated with pre-diagnosis loss to follow-up among tuberculosis presumptive patients in the Cycle of Health Care, Musoma, Tanzania: Cross-sectional study. Tanzan J health Res. 2022;23(1):1–9. Padingani M, Kumar A, Tripathy JP, Masuka N, Khumalo S. Does pre-diagnostic loss to follow-up among presumptive TB patients differ by type of health facility? An operational research from Hwange, Zimbabwe in 2017. Pan Afr Med J. 2018;31(1). Jiang Y, Chen J, Ying M, Liu L, Li M, Lu S et al. Factors associated with loss to follow-up before and after treatment initiation among patients with tuberculosis: A 5-year observation in China. Front Med. 2023;10. Tedla K, Medhin G, Berhe G, Mulugeta A, Berhe N. Factors associated with treatment initiation delay among new adult pulmonary tuberculosis patients in Tigray, Northern Ethiopia. PLoS ONE. 2020;15(8):e0235411. Beena ET, Chandra S, Lavanya J, Mika ML, Amith TG, Senthil S, et al. Understanding pretreatment loss to follow-up of tuberculosis patients: an explanatory qualitative study in Chennai, India. BMJ Global Health. 2020;5(2):e001974. Allwood BW, Byrne A, Meghji J, Rachow A, van der Zalm MM, Schoch OD. Post-Tuberculosis Lung Disease: Clinical Review of an Under-Recognised Global Challenge. Respiration. 2021;100(8):751–63. Tedla K, Medhin G, Berhe G, Mulugeta A, Berhe N. Delay in treatment initiation and its association with clinical severity and infectiousness among new adult pulmonary tuberculosis patients in Tigray, northern Ethiopia. BMC Infect Dis. 2020;20(1):456. Gunasekera KS, Vonasek B, Oliwa J, Triasih R, Lancioni C, Graham SM et al. Diagnostic Challenges in Childhood Pulmonary Tuberculosis-Optimizing the Clinical Approach. Pathogens (Basel Switzerland). 2022;11(4). An Y, Teo AKJ, Huot CY, Tieng S, Khun KE, Pheng SH, et al. Barriers to childhood tuberculosis case detection and management in Cambodia: the perspectives of healthcare providers and caregivers. BMC Infect Dis. 2023;23(1):80. Shitol SA, Saha A, Barua M, Towhid KMS, Islam A, Sarker M. A qualitative exploration of challenges in childhood TB patients identification and diagnosis in Bangladesh. Heliyon. 2023;9(10):e20569. Kizito S, Nakalega R, Nampijja D, Atuheire C, Amanya G, Kibuuka E, et al. High burden of pulmonary tuberculosis and missed opportunity to initiate treatment among children in Kampala. Uganda Afr health Sci. 2022;22(4):607–18. MOH, Uganda National TB. and Leprosy Program Annual Report 2020/2021. Kampala: Ministry of Health Uganda-National TB and Leprosy Program, Program UNTaL; 2021 November 2021. NTLP. National Tuberculosis and Leprosy Program report for the financial year 2022/23 Kampala. Uganda: Ministry of Health, National Tuberculosis and Leprosy Program; 2023. WMA. World Medical Association Declaration of Helsinki. Ethical Principles for Medical Research Involving Human Subjects. JAMA. 2013;310(20):2191–4. Additional Declarations No competing interests reported. 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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-4641015","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":329550438,"identity":"2e3ed898-874c-4f56-a573-dc8e59eff40c","order_by":0,"name":"Rebecca Nuwematsiko","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3PsUrEQBCA4VkW1kax3RAhr7CHkHAcJq+SZcFrYu2BoAHhbHLYnuhDHAgD1wkDZ+MDBLQQfIGzuyCCu1jK4qUT2b8YpvkYBiAU+tNxAbB2i9wSSEfYvB8BAXx3G5LdNql8r/Lz5Erot6OKiiyu2XoDlNcecvDylEY3aKQiQYcnSHp598CjBsj4iJRV+ryHXCq+M40tKVVbQgyWeH9w5BMvZHJpyRCpsIR//EoYkgQSq9gubNGWwl3J/eT4tJvhY7QgYQYzHOvlXE+HjRqXfmLuVYdn+8n1avDa4ajIpKF2MxkVPvIzBax2U9c9yHc9roRCodA/7wuLF1G2xyauIwAAAABJRU5ErkJggg==","orcid":"","institution":"Makerere University","correspondingAuthor":true,"prefix":"","firstName":"Rebecca","middleName":"","lastName":"Nuwematsiko","suffix":""},{"id":329550441,"identity":"c790eab8-69f9-48e2-a8f0-9d3d1b85ffc8","order_by":1,"name":"Noah Kiwanuka","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Noah","middleName":"","lastName":"Kiwanuka","suffix":""},{"id":329550444,"identity":"c6e2ecfc-a3c8-4bae-be45-739b51031183","order_by":2,"name":"Solomon T. 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Although the global incidence has been reduced by approximately 2% for most of the decades, delays in TB diagnosis and treatment initiation remain globally, requiring more effort to find the missing patients and achieve the 2035 End TB strategy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In 2022, there were an estimated 10.6\u0026nbsp;million new TB patients out of which 3.1\u0026nbsp;million, around 30%, were either not diagnosed or were not notified to national TB programs [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The largest gap in the TB care cascade in both high- and low-TB burden countries is the significant number of patients who are not diagnosed [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePre-diagnosis loss to follow-up (LTFU) has been estimated to range between 8% and 55% in Asia and Africa [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Similarly, a comparison study between 30 high and 153 low-TB burden countries revealed that 35% of TB incident cases in high-TB burden countries were not diagnosed compared to 20% in low-TB burden countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreso, in a systematic review in low- and middle-income countries (LMICs), pre-treatment LTFU was estimated to be between 6% and 38% in Africa, excluding Uganda [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePre-diagnosis or pre-treatment LTFU increases community transmission of TB, TB severity and poor patient outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Earlier studies revealed some of the associated factors for pre-diagnosis and pre-treatment LTFU as being HIV positive, residing far from the health facility, no record of tracking information such as phone contact and place of residence, poor communication between health workers and patients, long waiting time and need for repeat visits at health facilities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Uganda, a few studies have assessed this LTFU in the TB care cascade with Ekuka et al., reporting a pre-diagnosis LTFU of up to 40.7% and Zawedde et al., reporting a pre-treatment LTFU of 19.6% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Both studies focused on one type of loss in the TB care cascade that is; pre-diagnosis LTFU only for Ekuka et al., [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and pre-treatment LTFU only for Zawedde et al., [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] which limits understanding of the extent of these losses in Uganda. Therefore, the aim of this study was to assess the proportion of both pre-diagnosis and pre-treatment LTFU and associated factors among presumptive TB patients in Uganda over a four-year period.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting\u003c/h2\u003e \u003cp\u003eThe study was conducted in four selected health facilities in Mukono, Buikwe and Mityana districts, Central Uganda. The health facilities included three general hospitals (2 government-owned and 1 private-not-for profit) and one lower-level health center IV (government-owned). The selection of study facilities was based on high volume and to ensure representation of the different levels of the health care system and type of facility ownership, whether government or private-not-for profit owned. In the study facilities, patients presenting with symptoms suggestive of TB are screened and presumed to have TB from any entry point of the health facility, including the outpatient department (OPD), HIV clinic, Pediatric clinic and Antenatal clinic. The symptomatic screening is in accordance with the four cardinal symptoms of TB: persistent cough of two weeks or more, night sweets, fever of more than two weeks, weight loss and if a child, poor weight gain and previous contact with a TB patient [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. After the patient has been presumed, they are referred for TB diagnosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTB diagnosis is performed using GeneXpert (Xpert MTB/RIF), which is the recommended first diagnostic test [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Depending on the availability of tests and how the patient presents, other diagnostic tests are available, including sputum microscopy, chest X-ray and urine TB LAM (for HIV-positive patients) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A diagnosed TB patient is defined as one who is bacteriologically confirmed by either Xpert MTB/RIF, smear microscopy or TB Lam or those confirmed by chest X-ray. Patient socio-demographic information, contacts, address of residence, clinical details and dates of registration are recorded in the national standardized paper-based registers at each care entry point, as described in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. More details on the flow of the patients right from when they arrive at the health facility are provided in the flow chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003e This was a retrospective cohort study involving a review of routinely collected data of presumptive and diagnosed TB patients presenting to the study facilities. The study included presumptive TB patients of all ages who presented to the study facilities from January 2019 to December 2022. Presumptive TB patients were defined as those presenting with any of the four cardinal symptoms of TB. The four-year period was selected to allow comparison of the pre-diagnosis and pre-treatment LTFU; before and during the COVID-19 pandemic. We referred to 2019 as before the COVID-19 pandemic and 2020\u0026ndash;2022 as during the pandemic based on WHO periods of declarations of COVID-19 as a public health emergency of international concern [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eData collection procedures\u003c/b\u003e: Data on presumptive TB patients who presented to the study health facilities were extracted from the presumptive TB registers at all screening points/units. These patients were then followed up in the laboratory and radiology registers for completion of TB diagnosis within 30 days. Presumptive TB patients who tested positive for TB were followed up in the facility treatment register for treatment initiation within 14 days. Data were cross-matched from all the registers (presumptive, laboratory, radiology and treatment), following up a patient once they were presumed to have TB up to when they completed diagnosis or initiated treatment if diagnosed or lost to follow-up. Four variables were used for cross-matching the data in the different registers: patient name, age, area of stay and date of presumption.\u003c/p\u003e \u003cp\u003eData were collected using an extraction tool adapted from a similar study conducted in Zimbabwe [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The data extraction tool was pre-tested, and the refined tool was uploaded to the \u003cem\u003eKoboCollect\u003c/em\u003e mobile data collection app. The following variables were extracted: age, sex, place of residence and phone contact, TB disease type, HIV status and dates of presumption, diagnosis and initiation of treatment for the presumptive patients who tested positive.\u003c/p\u003e \u003cp\u003eResearch assistants with experience in research and extracting data from large databases were recruited and trained in a three-day workshop for data collection. Meetings were held at the end of each data collection day to check for adherence to the data collection procedures and operational definitions, consistency, and completeness of the data collected. The data submitted daily to the server were checked for accuracy and any errors which were communicated to the research assistants for correction during subsequent data extraction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eSampling\u003c/strong\u003e \u003cp\u003eWe used total enumerative sampling, where all records meeting the inclusion criteria were extracted from the registers. A post hoc power estimation was performed to estimate whether we had the power to conduct the analysis.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eVariables and measurements:\u003c/h2\u003e \u003cp\u003eWe defined pre-diagnosis LTFU as failure to complete TB diagnosis within 30 days of being presumed for TB. The 30-day follow-up period was selected based on previous studies for comparison [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This referred to either dropping out before having the requested investigations done or after by not having results. Having results documented in the register was used as a proxy for receipt of results by the patient. Pre-diagnosis LTFU was measured as the proportion of patients who were lost before completing TB out of the total number of all presumptive TB patients registered in the study period.\u003c/p\u003e \u003cp\u003ePre-treatment LTFU was defined as failure to initiate TB treatment within 14 days of being diagnosed based on previous studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This was measured as the proportion of diagnosed TB patients who were lost before initiating treatment out of the total number of diagnosed TB patients registered in the study period.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData management and analysis\u003c/strong\u003e \u003cp\u003eThe final dataset was downloaded from the \u003cem\u003eKobocollect\u003c/em\u003e mobile app into an Excel spreadsheet and exported to Stata software version 14 for cleaning and analysis. Age, name, area of stay and registration date were key variables for identifying duplicates. Presumptive TB patients with missing age and dates were excluded because these were key variables for analysis and identifiers for duplicates. We also dropped anyone with a duplicate registration date within 3 days which signified double registration.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eDescriptive statistics such as frequency distributions, median and interquartile ranges (IQRs) were computed. The trends of pre-diagnosis LTFU over time were compared using a line graph. A modified Poisson regression analysis model via generalized linear models with family (Poisson) and link (log) was constructed to obtain the unadjusted estimates for factors associated with pre-diagnosis LTFU [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Modified Poisson regression was preferred over logistic regression because the proportions of pre-diagnosis and pre-treatment LTFU were greater than 10%; hence, odds ratios would provide biased estimates of prevalence ratios [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Independent variables that were statistically significant at the bivariate analysis at p\u0026thinsp;\u0026lt;\u0026thinsp;0.2 and those known from the literature to be associated with pre-diagnosis LTFU were entered into a model to establish factors independently associated while controlling for potential confounders. The level of statistical significance was set at a p-value less than 0.05. An exploratory logical model-building method following the conceptualization of the study outcome and literature review was used to generate the final model. Variables in a model that were found to be consistently insignificant and did not add any value in terms of goodness of fit were eliminated. Selection of the final model was performed using likelihood ratio tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 13,496 presumptive patient records were abstracted from the facility records. Of these, 432 records were excluded from the analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic and clinical characteristics of study participants\u003c/h2\u003e \u003cp\u003eThirty-nine percent (5,213/13,064) of the patients were aged 25 to 44 years, with a median age of 35 years (IQR, 24\u0026ndash;50). Over half of the patients 57.1% (7,462/13,064) were female. The percentage of presumptive TB patients was highest in the year 2022 at 34.2% (4,464/13,064) and lowest in 2020 at 14.9% (1956/13,064) see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Forty-two percent of the patients were HIV positive, 42.9% (5,605/13,064) see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\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\u003eSocio-demographic and clinical characteristics of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \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\u003eN\u0026thinsp;=\u0026thinsp;13,064 (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (median\u0026thinsp;=\u0026thinsp;35, IQR; 24, 50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 to 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1603 (12.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 to 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1907 (14.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25 to 44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5213 (39.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4341 (33.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,602 (42.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,462 (57.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of place of residence available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,002 (84.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,062 (15.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of phone contact available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,679 (66.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,385 (33.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility unit of screening for presumptive patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4302 (32.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB Unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,995 (22.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e398 (3.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,506 (26.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePediatric clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,284 (9.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e*Community outreach programs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e579 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,760 (28.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,956 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,884 (22.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,464 (34.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic (Government funded)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10,220 (78.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate not for Profit (PNFP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,844 (21.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,668 (12.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,396 (87.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessibility to TB testing services at the health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple services (Gene Xpert, microscopy, TB Lam, Chest Xray)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,396 (87.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly microscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,668 (12.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistrict of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuikwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4615 (35.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMityana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3937 (30.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMukono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4512 (34.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV status (n\u0026thinsp;=\u0026thinsp;13,064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,936 (45.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,605 (42.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,523 (11.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003e* Presumptive TB patients from the community outreach programs were documented in the health center IV only in a presumptive TB register at the outpatient department\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePre-diagnosis LTFU and factors associated among presumptive TB patients\u003c/h2\u003e \u003cp\u003eOverall, 28.3% (3699/13064) experienced pre-diagnosis LTFU (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Over half of those who conducted the TB investigations required, did not have their test results documented in the laboratory or chest x-ray register on the same day of being presumed, 52.8% (4983/9439). TB was diagnosed among 12.7% (1187/9365) patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Pre-diagnosis LTFU among the study participants was highest in 2019 at 48.7% (1,832/3760) and 42.9% (840/1956) in 2020. This was followed by a sharp decline in 2021 to 14.3% (413/2884) and 13.8% (614/4464) in 2022 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with pre-diagnosis LTFU among presumptive TB patients\u003c/h2\u003e \u003cp\u003eAt multivariate analysis, females (adj PR 1.1, 95% CI: 1.01,1.12), those aged 0\u0026ndash;14 years (adj PR 1.1, 95% CI: 1.06,1.24) and patients presumed from PNFPs (adj PR 1.2, 95% CI: 1.11,1.28) were more likely to experience pre-diagnosis LTFU. In addition, patients with no record of place of residence (adj PR 2.7, 95% CI: 2.54,2.93) and no record of phone contact (adj PR 1.1, 95% CI: 1.05,1.17) were also more likely to experience pre-diagnosis LTFU compared to those whose details were recorded in the registers. On the other hand, patients presumed from hospitals (adj PR 0.7, 95% CI: 0.69,0.81) and those presumed to have TB between 2020 and 2022 were less likely to be lost before completing TB diagnosis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eFactors associated with pre-diagnosis LTFU from 2019 to 2022 in study health facilities in Uganda\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-diagnosis LTFU % (n/N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude PR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted PR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.7 (1246/4341)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 to 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33.9 (543/1603)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2 (1.09\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.1 (1.06\u0026ndash;1.24)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 to 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.8 (531/1907)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0 (0.89\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.89\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25 to 44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.5 (1379/5213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.86\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.90\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.4 (1537/5602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.9 (2162/7462)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.99\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.1 (1.01\u0026ndash;1.12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.019*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of place of residence available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.5 (2913/11002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.1 (786/2062)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (1.35\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.7 (2.54\u0026ndash;2.93)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of phone contact available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.1 (2354/8679)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.7 (1345/4385)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (1.07\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.1 (1.05\u0026ndash;1.17)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility unit of screening for presumptive patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33.7 (1449/4302)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB Unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.3 (1056/2995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0 (0.98\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.1 (1.03\u0026ndash;1.17)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.7 (142/398)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (0.92\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.96\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.6 (756/3506)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.59\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.8 (0.74\u0026ndash;0.87)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePediatric clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.1 (271/1284)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.56\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.9 (0.79\u0026ndash;0.99)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.036*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity outreach programs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.3 (25/579)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1 (0.09\u0026ndash;0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.2 (0.14\u0026ndash;0.31)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.0 (1664/5936)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.9 (1399/5605)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.84\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.94\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.8 (636/1523)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (1.39\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.4 (1.30\u0026ndash;1.51)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.7 (1832/3760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.9 (840/1956)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.83\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.9 (0.84\u0026ndash;0.95)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.3 (413/2884)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 (0.27\u0026ndash;0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.2 (0.22\u0026ndash;0.26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.8 (614/4464)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 (0.26\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.2 (0.21\u0026ndash;0.24)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.8 (430/1668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.7 (3269/11396)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (1.02\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.7 (0.69\u0026ndash;0.81)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic (Government funded)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.8 (3042/10220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate not for Profit (PNFP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1 (657/2844)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.72\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.2 (1.11\u0026ndash;1.28)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessibility to TB testing services at the health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly microscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.8 (430/1668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple services (Gene Xpert, microscopy, TB Lam, Chest Xray)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.7 (3269/11396)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 (1.02\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistrict of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuikwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.9 (1470/4615)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMityana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.0 (1142/3937)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.85\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMukono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.1 (1087/4512)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.71\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e* Statistically significant at \u0026lt;\u0026thinsp;0.05\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003ePre-treatment LTFU and factors associated among diagnosed TB patients\u003c/h2\u003e \u003cp\u003eThirteen percent (163/1187) of the patients who were diagnosed with TB experienced pre-treatment LTFU (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Pre-treatment LTFU was highest in 2019 at 15.0% (36/240) which slightly decreased in 2020 to 13.7% (20/146) and 13.2% (50/378) in 2022.\u003c/p\u003e \u003cp\u003ePatients who had no record of place of residence (adj PR 7.1, 95% CI: 5.16,9.88) and no record of phone contact (adj PR 2.2, 95% CI: 1.63,2.86) were more likely to experience pre-treatment LTFU compared to those whose details were recorded in the registers. Those with an unknown HIV status were 1.9 times more likely to experience pre-treatment LTFU compared to those who were HIV negative, (adj PR 1.9, 95% CI: 1.09,3.27). Patients presumed from the HIV clinics were 40% less likely to experience pre-treatment LTFU compared to those presumed from the outpatient departments (adj PR 0.6, 95% CI: 0.41,0.88). Patients presumed to have TB in 2022 were less likely to be lost before initiating treatment compared to those presumed to have TB in 2019 (adj PR 0.6, 95% CI: 0.42,0.96) see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eFactors associated with pre-treatment LTFU from 2019 to 2022 in study health facilities in Uganda\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-treatment LTFU % (n/N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude PR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted PR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\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\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.4 (57/371)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 to 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.4 (18/117)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0 (0.61\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2 (0.77\u0026ndash;1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 to 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.2 (22/167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.54\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (0.54\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25 to 44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.4 (66/532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.58\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.73\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.9 (87/730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.6 (76/457)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (1.05\u0026ndash;1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2 (0.93\u0026ndash;1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of place of residence available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.4 (117/1129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79.3 (46/58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7 (6.17\u0026ndash;9.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7.1 (5.16\u0026ndash;9.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecord of Phone contact available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.6 (101/953)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.5 (62/234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5 (1.89\u0026ndash;3.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.2 (1.63\u0026ndash;2.86)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility unit of screening for presumptive patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutpatient department\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.9 (64/378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB Unit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.9 (46/355)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.54\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (0.56\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00 (4/16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (0.61\u0026ndash;3.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4 (0.62\u0026ndash;3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.1 (37/334)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7 (0.45\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.6 (0.41\u0026ndash;0.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.010*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePediatric clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.6 (10/94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.34\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7 (0.36\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity outreach programs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.0 (2/10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2 (0.34\u0026ndash;4.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (0.64\u0026ndash;9.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.4 (74/553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.5 (76/610)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.69\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.77\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.2 (13/24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 (2.65\u0026ndash;6.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.9 (1.09\u0026ndash;3.27)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.024*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.0 (36/240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.7 (20/146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.55\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.58\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.5 (57/423)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.61\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8 (0.55\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.2 (50/378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.59\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.6 (0.42\u0026ndash;0.96)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.032*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.2 (14/137)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.2 (149/1050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (0.83\u0026ndash;2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.63\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFacility ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic (Government funded)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.9 (137/988)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate not for Profit (PNFP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.1 (26/199)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.64\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1 (0.71\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessibility to TB testing services at the health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly microscopy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.2 (14/137)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple services (Gene Xpert, microscopy, TB Lam, Chest Xray)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.2 (149/1050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 (0.83\u0026ndash;2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistrict of presumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuikwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.5 (50/323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMityana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.8 (73/528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.64\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMukono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.9 (40/336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.52\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e* Statistically significant at \u0026lt;\u0026thinsp;0.05\u003c/h2\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed pre-diagnosis and pre-treatment LTFU and associated factors among presumptive and diagnosed TB patients from 2019 to 2022 in selected health facilities in central Uganda. Twenty-eight percent of the participants experienced pre-diagnosis LTFU and thirteen percent of those who tested positive for TB did not initiate treatment when they were diagnosed. Over half of those who conducted the TB investigations required, did not have their results on the same day of being presumed, 52.8% (4983/9439). Pre-diagnosis LTFU was highest in 2019 and 2020 which decreased sharply in 2021 and 2022. Patients with no record of place of residence and no record of phone contact were more likely to experience pre-diagnosis and pre-treatment LTFU.\u003c/p\u003e \u003cp\u003eThe high pre-diagnosis LTFU was attributed to no record of patient tracking information of place of residence and phone contact. Our study also revealed that half of the participants do not have results on the same day of being presumed for TB which requires repeat visits to the health facilities hence contributing to the LTFU. Similar pre-diagnosis LTFU proportions have been reported in studies in Zimbabwe (10%-25%), Tanzania (16%), India (30%) and in a study of 30 countries with a high-TB burden (35%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, a previous study in Uganda reported a higher proportion of LTFU of 40.7% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This could be because of the differences in the study setting, as the study by Ekuka et al. was conducted in a rural area where patients face more challenges in healthcare access. Indeed, studies have indicated that presumptive TB patients from rural health facilities tend to be LTFU (Murongazvombo et al., 2019, Padingani et al., 2018, Tedla et al., 2020). Pre-diagnosis LTFU threatens TB control by increasing the risk of community spread of the disease hence the need for health system strengthening solutions to ensure that every patient presumed to have TB is diagnosed.\u003c/p\u003e \u003cp\u003eSimilarly, the high pre-treatment LTFU reported in this study was due to the non-availability of patient tracking information of place of residence and phone contact coupled with the failure of health facilities to provide patients with same day results. Other studies have found the same reason of no patient tracking records, poor patient-provider communication, older age, history of TB disease, distance of residence from the health facility, complexity of navigating the system, and health care worker attitude as contributing factors to the pre-treatment LTFU [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This proportion of pre-treatment LTFU is comparable to that in other studies, which reported a range of 4\u0026ndash;42% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The lack of timely treatment initiation for TB patients increases the severity of the disease and the likelihood of poor treatment outcomes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients aged 0\u0026ndash;14 years were more likely to experience pre-diagnosis LTFU compared to those aged 45 years and above. This may be because of the existing diagnostic challenges of TB among children, such as difficulty obtaining sputum and a lack of functional radiological investigations (X-rays) at health facilities [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moreso, patients aged 0\u0026ndash;14 years do not independently make decisions to seek care and hence depend on the availability and decisions of the care takers to seek care. Although our study revealed no association for pre-treatment LTFU among this age group, a study in Uganda revealed that 18.7% of smear-positive children were not initiated on treatment [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Early detection of TB especially in children and adolescents is crucial for improving treatment outcomes and preventing post TB lung impairment.\u003c/p\u003e \u003cp\u003ePre-diagnosis and pre-treatment LTFU levels were highest in 2019 and 2020 and drastically decreased in 2021 and 2022 during the peak of the COVID-19 pandemic. The reduction in LTFU from 2020 to 2021 was attributed to the intensified efforts by the National TB and Leprosy Program (NTLP), which included the integration of TB and COVID-19 services; community campaigns such as TB Catch-up and Community Awareness, Screening, Testing, prevention and treatment to end TB Campaign (CAST TB), which involved community awareness of TB; and intensified screening and diagnosis of patients for TB [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These findings are similar to those of national and WHO reports showing that Uganda is one of the countries that quickly recovered from the effects of COVID-19 in terms of case notification of newly diagnosed TB patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The integration of health services, especially during outbreaks, is key to ensuring continuity of service delivery while harnessing the power of available human resource.\u003c/p\u003e \u003cp\u003eA key strength to our study is the analysis of data giving a perspective of one year before the COVID-19 pandemic (2019) and three years into the pandemic (2020\u0026ndash;2022). This provides information on the effect of disease outbreaks on the continuity of service provision and health seeking behaviors of the patients. This information may inform preparedness and response planning for future outbreaks and pandemics. We also had a large sample size of 13,064 which improved the precision of the estimates.\u003c/p\u003e \u003cp\u003eWe utilized secondary data which often present with missing data and quality issues. We mitigated the likelihood of this by cross-matching data from the presumptive, laboratory and TB unit treatment registers during data collection to limit the missingness of data on key variables such as age, sex, date of sample collection and results received. This information is often recorded in at least two of the registers. Moreso, availability of results in the register was used as a proxy for the completion of TB diagnosis, which may not translate to a patient receiving results for further management. A prospective study is recommended for future studies to establish the actual receipt of results by patients as an endpoint for the completion of TB diagnosis. Another limitation is that we could not verify whether the patients who were LTFU before completing TB diagnosis completed the diagnosis from another health facility elsewhere or did not complete at all. We recommend that future studies explore whether TB diagnosis is completed elsewhere through the use of patient pathway analysis and more robust triangulation methods across health facilities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this retrospective cohort analysis study in central Uganda, we found a high pre-diagnosis LTFU of 28% among the presumptive TB patients and pre-treatment LTFU of 13%. This calls for urgent interventions to reduce these losses in the care cascade to be able to realise the End TB Strategy. Over half of participants who conducted the TB investigations required did not have results on the same day of being presumed. There is need to strengthen the capacity of laboratories to provide same day results for patients so as to reduce chances of LTFU. No record of place of residence or phone contact in the patient registers was significantly associated with LTFU, which calls for improved documentation at health facilities to ease patient follow-up for TB service provision and contact tracing.\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdj\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eART\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAntiretroviral therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAST TB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunity Awareness, Screening, Testing, prevention and treatment to end TB Campaign\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoronavirus disease\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman immunodeficiency virus\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInterquartile ranges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMICs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow- and middle-income countries\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLTFU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoss to follow-up\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinistry of Health\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTLP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational TB and Leprosy Program\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate-not-for-profit\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrevalence ratio\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Nations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWorld Health Organization\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":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in\u0026nbsp;accordance with the Declaration of Helsinki\u0026nbsp;[42]. Approval to conduct the study was obtained from the Research and Ethics Committee of Makerere University School of Public Health (#SPH-2023-427), and the study was registered with the Uganda National Council of Science and Technology (HS3000ES). The privacy and confidentiality of all the data obtained were ensured by limiting access of the data to only the study investigator and data manager. Since this was a review of records with no face-to-face interviews with patients, the need for informed consent was waived by the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data and materials supporting results of this manuscript are available through the Research and Ethics Committee of Makerere University School of Public Health. They can be contacted at [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is part of the EDCTP2 programme supported by the European Union \u003cem\u003e(grant number: TMA2018SF-2472-MILEAGE4TB).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRN co-conceptualised the study with EB and coordinated the implementation including manuscript writing. STW, MN, AND LN participated in study implementation, data analysis and manuscript writing. NK, HL, ST, JNS and LA provided technical support during implementation of the study and guided the contextual interpretation of the results during analysis and manuscript writing. EB conceptualised the study and provided overall technical guidance during implementation and manuscript writing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our appreciation to Ms. Lillian Tabwenda, Mr. Emmanuel Biryabarema, Mr. Joshua Mwebaze and Mr. Ignatius Kiiza and the health workers in the study health facilities for the devoted efforts invested in the study\u0026rsquo;s data collection and management processes.\u003cstrong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. Global tuberculosis report 2023. Geneva: World Health Organization; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUN. The Sustainable Development Goals eSocialSciences; 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUplekar M, Weil D, Lonnroth K, Jaramillo E, Lienhardt C, Dias HM, et al. 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Pathogens (Basel Switzerland). 2022;11(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAn Y, Teo AKJ, Huot CY, Tieng S, Khun KE, Pheng SH, et al. Barriers to childhood tuberculosis case detection and management in Cambodia: the perspectives of healthcare providers and caregivers. BMC Infect Dis. 2023;23(1):80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShitol SA, Saha A, Barua M, Towhid KMS, Islam A, Sarker M. A qualitative exploration of challenges in childhood TB patients identification and diagnosis in Bangladesh. Heliyon. 2023;9(10):e20569.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKizito S, Nakalega R, Nampijja D, Atuheire C, Amanya G, Kibuuka E, et al. High burden of pulmonary tuberculosis and missed opportunity to initiate treatment among children in Kampala. Uganda Afr health Sci. 2022;22(4):607\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMOH, Uganda National TB. and Leprosy Program Annual Report 2020/2021. Kampala: Ministry of Health Uganda-National TB and Leprosy Program, Program UNTaL; 2021 November 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNTLP. National Tuberculosis and Leprosy Program report for the financial year 2022/23 Kampala. Uganda: Ministry of Health, National Tuberculosis and Leprosy Program; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWMA. World Medical Association Declaration of Helsinki. Ethical Principles for Medical Research Involving Human Subjects. JAMA. 2013;310(20):2191\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, loss to follow-up, pre-diagnosis loss to follow-up, pre-treatment loss to follow-up, Uganda","lastPublishedDoi":"10.21203/rs.3.rs-4641015/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4641015/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLoss to follow-up (LTFU) of presumptive tuberculosis (TB) patients before completing diagnosis (pre-diagnosis LTFU) and before initiating treatment for those diagnosed (pre-treatment LTFU) is a challenge in the realization of the End TB Strategy. We assessed the proportion of pre-diagnosis and pre-treatment LTFU and associated factors among presumptive and diagnosed TB patients in the selected health facilities.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e This was a retrospective cohort study involving a review of routinely collected data from presumptive, laboratory and TB treatment registers from January 2019 to December 2022. The study was conducted in three general hospitals and one lower-level health center IV in Central Uganda. We defined pre-diagnosis LTFU as failure to complete TB diagnosis within 30 days of being presumed and pre-treatment LTFU as failure to initiate TB treatment within 14 days from being diagnosed. Modified Poisson regression was used to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) of factors associated with pre-diagnosis and pre-treatment LTFU.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 13,064 presumptive TB patients, 39.9% were aged 25 to 44 years, and 57.1% were females. Almost a third, 28.3% (3,699/13.064) experienced pre-diagnosis LTFU and 13.7% (163/1187) did not initiate treatment. Pre-diagnosis LTFU was more likely to occur among patients aged 0\u0026ndash;14 years (adj PR 1.1, 95% CI: 1.06,1.24), females (adj.PR\u0026thinsp;=\u0026thinsp;1.06, 95% CI: 1.01, 1.12) and those with no record of place of residence (adj. PR\u0026thinsp;=\u0026thinsp;2.7, 95% CI: 2.54, 2.93). In addition, patients with no record of phone contact were more likely to be LTFU, (adj. PR\u0026thinsp;=\u0026thinsp;1.1, 95% CI: 1.05, 1.17). Pre-treatment LTFU was also more likely among patients with no record of place of residence (adj PR 7.1, 95% CI: 5.13,9.85) and those with no record of phone contact (adj PR 2.2, 95% CI: 1.63,2.86). Patients presumed from the HIV clinics were 40% less likely to experience pre-treatment LTFU compared to those in the outpatient departments (adj PR 0.6, 95% CI: 0.41,0.88).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHigh proportions of pre-diagnosis and pre-treatment LTFU were observed in this study. This calls for urgent interventions at these time points in the TB care cascade to be able to realise the End TB Strategy.\u003c/p\u003e","manuscriptTitle":"Pre-diagnosis and pre-treatment loss to follow-up and associated factors among presumptive tuberculosis patients in Uganda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 10:59:18","doi":"10.21203/rs.3.rs-4641015/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-13T07:09:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-08T15:05:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257685812724157932979304905374589382797","date":"2024-11-08T14:29:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283747750043878717045367954394507945783","date":"2024-10-16T07:34:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"320373999415144857833492164536136769641","date":"2024-09-18T09:18:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235880837474480491492957854711893997649","date":"2024-07-18T09:55:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-17T12:02:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134875621058653242567953618669791825543","date":"2024-07-16T12:56:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-15T15:54:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-01T11:57:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-29T03:27:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-29T03:27:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2024-06-26T08:09:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05dea38a-a3c8-4b5e-9f25-c3493727e836","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-30T15:58:09+00:00","versionOfRecord":{"articleIdentity":"rs-4641015","link":"https://doi.org/10.1186/s12913-024-12115-4","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2024-12-23 15:56:52","publishedOnDateReadable":"December 23rd, 2024"},"versionCreatedAt":"2024-07-22 10:59:18","video":"","vorDoi":"10.1186/s12913-024-12115-4","vorDoiUrl":"https://doi.org/10.1186/s12913-024-12115-4","workflowStages":[]},"version":"v1","identity":"rs-4641015","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4641015","identity":"rs-4641015","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}