Incidence and Factors Associated with Immediate Adverse Neonatal Outcomes Among Emergency Obstetric Referrals in Labor at a Tertiary Hospital in Uganda: A Prospective Cohort Study 

Incidence and Factors Associated with Immediate Adverse Neonatal Outcomes Among Emergency Obstetric Referrals in Labor at a Tertiary Hospital in Uganda: A Prospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incidence and Factors Associated with Immediate Adverse Neonatal Outcomes Among Emergency Obstetric Referrals in Labor at a Tertiary Hospital in Uganda: A Prospective Cohort Study Geoffrey Okot, Samuel Omara, Musa Kasujja, Francis Pebalo, Petrus Baruti, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4268699/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 11 You are reading this latest preprint version Abstract Background High incidences of adverse neonatal outcomes especially in resource-limited settings are multifactorial and vary from country to country and even within the same country, there are regional and institutional variations. In sub-Saharan Africa, the majority of adverse neonatal outcomes are intrapartum related, and studies in Uganda have shown that referral in labor is a major determinant of adverse neonatal outcomes. This study aimed to assess the incidence and factors associated with immediate adverse neonatal outcomes among emergency obstetric referrals in labor at a tertiary hospital in Eastern Uganda. Materials and Methods This was a prospective cohort study involving 265 women referred with obstetric emergencies in labor at Jinja Regional Referral Hospital over 3 months. Consecutive sampling was employed, and interviewer-administered questionnaires were used for data collection. Sociodemographic, referral, and obstetrical factors were recorded, and log-binominal regression analysis was used to establish risk ratios and associations with adverse neonatal outcomes. Results Of the 265 emergency obstetric referrals, 40% had adverse neonatal outcomes. Neonatal intensive care admission (27.6%), low Apgar score (23.8%), fresh stillbirth (11.3%), early-onset neonatal infection (6.8%), and early neonatal death (2.3%) were the common neonatal adverse outcomes. Factors significantly associated with adverse neonatal outcomes were; maternal age ≥ 35 years aRR = 1.72, ( p = 0.004 ) , APH aRR = 2.48, ( p < 0.001 ) and nonreassuring fetal status aRR = 1.90, ( p < 0.001). Conclusions The study revealed a notable incidence of adverse neonatal outcomes, with the most common being admissions to neonatal intensive care units and low Apgar scores. Strong and statistically significant associations with adverse neonatal outcomes were observed for maternal age of 35 years or older, antepartum hemorrhage, and nonreassuring fetal status. Improving obstetric referral protocols is essential to ease the burden on tertiary care centers, enhance the birthing journey, and minimize risks for newborns. Obstetrical Emergency Referrals Adverse Neonatal Outcomes Figures Figure 1 Figure 2 Figure 3 Background Globally, 2.5 million neonates die annually, 80% in sub-Saharan Africa and Asia with 1.2 million in the intrapartum period, two-thirds in the first day of life, and three-quarters in the first week [ 1 ]. Notably, 80% of the leading causes of these deaths are preventable through cost-effective interventions such as an organized primary health care system, and timely, appropriate, and accessible referral services, [ 1 , 2 ]. In sub-Saharan Africa, improvement in newborn survival has been slow, with neonatal mortality reduction lagging, hence contributing to approximately 45%-50% of total underfive mortality, however, a scale-up intervention such as early referrals with faster and responsive care could avert approximately 71% of these deaths [ 3 ]. Reports indicate that over 6700 newborn deaths occur per day with 1 million within the first 24hrs, accounting for 50% of under-five mortality [ 4 ] At this rate, it is unlikely to meet the Sustainable Development Goals (SDGs) of reducing under-5 mortality by 50% in the African Region [ 5 ] Emergency obstetric referrals account for more than 30% of all referrals and contribute greatly to adverse neonatal outcomes, mostly in low-resource settings [ 6 ], especially those referred in labor [ 6 , 7 ]. Obstetric referrals in low-income countries are compounded by a majority third delay (delay in getting the right care) and a second delay (delay in reaching the referral site)[ 8 , 9 ]. This has been seen in Rwanda with 37% experiencing a third delay [ 10 ] and in Ethiopia in which 52.3% and 74.7% experienced a second and third delays [ 11 ]. The incidence of adverse neonatal outcomes such as neonatal deaths, low APGAR score, fresh stillbirths, early neonatal infections, and admission to NICU among obstetric referrals varies between countries and settings from 10 to 45% [ 10 , 12 ]. For instance, the Netherlands, Malawi, and Kenya demonstrated this [ 8 , 13 , 14 , 15 ], Nepal indicated a range of 18 to 42%, India 7.3–47%, Nigeria 16.4–47%, Ethiopia 16 to 37.4%, and Rwanda 10 to 37.1% [ 12 , 16 , 17 , 18 , 19 , 11 , 20 , 10 ]. Reported incidences in Uganda vary from region to region, 0.6 to 19.2% (Western Uganda) and 8.1 to 33.3% (North and Eastern Uganda) for low APGAR score, FSB, Early neonatal deaths and NICU admissions [ 21 , 22 , 23 ]. Obstetric factors, sociodemographic factors, and obstetric delays are the key attributes of adverse neonatal outcomes and their variation in incidences regionally and per country[ 18 , 19 , 11 , 12 ]. Low socioeconomic status, low levels of education, rural residency, large family status, delays in reaching & receiving care at referral site, and obstetric factors such as prolonged labor, antepartum hemorrhage (APH), obstructed labor, fetal distress, hypertensive disorders are the great influencers adverse neonatal outcomes in low-income settings like Uganda [ 6 , 7 , 14 , 15 , 13 , 8 ]. For example, a study indicated 7.7 times the risks of adverse neonatal among women with APH [ 9 , 10 ], and in western Uganda, attributes were made to malpresentation and previous cesarean section [ 24 ] East and Northern Uganda have the highest incidences compared to other regions, and attributes to this have been made to, lower socioeconomic status, lower education level, maternal age ≥ 35years or age ≤ 20 years, referral delays (especially third and second delays), under-resourced facilities, understaffing of critical cadres [ 25 , 26 , 24 , 23 , 21 , 27 ]. Given the significance of maternal and newborn health and the burden at hand, this study aimed to ascertain the incidence, common types, and associated factors of adverse neonatal outcomes among emergency obstetric referrals at Jinja Regional Referral Hospital. Materials and Methods Study Design A prospective cohort study. Study Site The study was conducted at Jinja Regional Referral Hospital (JRRH), a government-funded facility with a bed capacity of 500, situated in Jinja City within the district of Jinja, Eastern Uganda. The hospital's maternity ward, where the study took place, handles approximately 5,124 deliveries each year, including 1,104 (21.5%) emergency obstetric referrals. Among these referrals, 30–40% of newborns typically require additional care and support. Adjacent to the maternity ward is the Neonatal Intensive Care Unit (NICU), which admits around 450 neonates annually, primarily those born to mothers referred with obstetrical complications. Sample size calculation To identify the common adverse neonatal outcomes among emergency obstetric referrals, Daniels WW,1999 was used. N = \(\frac{{{(\text{z}}_{{\alpha }})}^{2}\text{p} (1-\text{p})}{{\text{e}}^{2}}\) where N = the desired sample size for a population greater than 10,000. Z = 1.96. Standard normal deviation. Z is the level of significance in the Z scores (assuming a 95% confidence interval). p = Incidence of adverse neonatal outcomes (19.2%) in a study in western Uganda among emergency obstetric referrals q = 1-p; therefore, q = 1-0.192 e = 0.05 is the absolute precision (taking a 95% confidence interval) The minimum sample size required was 239, however, to cater for non-response and reliability, a 10% addition was made. Therefore, the sample size considered was 265 Inclusion and exclusion criteria All women in labor who were referred for emergency obstetric care at Jinja Regional Referral Hospital were included. Women in labor referred for emergency obstetric care with multifetal gestation and preterm labor, and who were unconscious or hemodynamically unstable were excluded. Study procedure All women referred for emergency obstetric care were educated about the research, its study objectives, and the inclusion and exclusion criteria, including the benefits of the study to the institution, the community, and all referred women in labor with obstetrical emergencies. A consecutive sampling technique was employed, and all women who met the eligibility criteria were approached to participate in the study. Those who agreed to participate provided consent and were given the appropriate privacy and confidentiality. The researcher and two research assistants administered a structured questionnaire privately and confidentially to each participant in the language they understood (English or Lusoga). All neonates were followed for 72 hours, and adverse outcomes were recorded for each neonate. Blood samples for complete blood count (CBC) from neonates who showed clinical signs and symptoms of early-onset neonatal infection were obtained aseptically by a laboratory technologist after all the reasons for the procedures and techniques were explained to and understood by the mothers. Every 10th sample was taken to the Lancet laboratory for independent analysis to ensure quality. Study Variables The study investigated the influence of independent variables encompassing sociodemographic factors (maternal age, marital status, place of residence, education level, occupation, family size, and decision maker), referral factors such as facility distance from home, time taken to reach the referral site and obstetrical factors, including gravidity, obstructed labor, prolonged labor, APH, previous cesarean, nonreassuring fetal status, and hypertensive disorders), on the dependent variable, immediate adverse neonatal outcomes, which included low Apgar of less than 7 at 5 minutes, any newborn of women referred with obstetrical emergency admitted in NICU, Fresh stillbirth, early-onset neonatal infections occurring within the first 72 hours of life and Any death of a neonate occurring within 72 hours after delivery (early neonatal deaths). The above data were collected using structured interviewer-administered questionnaires. Data quality control To ensure that the data collection tools were appropriate, simple English was used as opposed to technical terms. The questionnaires were created based on available literature and factors within the study settings, translated into the local language (Lusoga), and back-translated into English for accuracy. A pretest of the data collection tool was performed to ascertain the reliability of the tool. All data collection processes were monitored by the researcher, and immediate cross-checking of the completed questionnaires was carried out to ensure the accuracy and completeness of the information. A content validity index was used on data obtained from five participants who were not part of the study, and interparticipant agreement was measured, with an agreement of 83%. Data Management and Analysis The collected data from completed questionnaires underwent thorough checks for consistency, accuracy, and completeness. Subsequently, it was entered into Epi info software version 7.2. Following this, a data extract was created in Microsoft Excel (2019) format and imported into the STATA version 14 statistical package. Within STATA, the data was further cleaned, coded, and analyzed. The incidence of adverse neonatal outcomes was determined by dividing the total number of participants who experienced adverse outcomes (numerator) by the overall study participants (denominator), then expressed in percentage. This calculation helped identify common adverse outcomes, where each specific adverse outcome’s total occurrence ( numerators) was divided by the total number of participants with adverse outcomes ( denominator) also expressed as a percentage. For factors associated with adverse neonatal outcomes, log-binominal regression analysis was used for risk ratios and associations. Statistical significance was set at a p-value of less than 0.05. The results were presented in pie charts, tables, and bar graphs and discussed for effective understanding and interpretation. Results The study was conducted in the maternity ward and neonatal intensive care units of Jinja Regional Referral Hospital over three months from July to September 2023. A total of 265 women were educated on the study objectives, inclusion and exclusion criteria, and benefits. Women who met the exclusion criteria or did not provide consent were excluded from participation. The study flow chart is shown in Fig. 1 below. Figure 1 Study flowchart Descriptive statistics for participants' characteristics Table 1 Present the sociodemographic, referral, and obstetric characteristics of the participants (n = 265) Variables Category Frequency (n) Percentage (%) Sociodemographic Maternal age < 20 years 20–34 years 35 years above 59 181 25 22.6 68.3 9.4 Marital status Single Married Cohabiting 39 72 154 14.7 27.2 58.1 Place of residence Urban Rural 57 208 21.5 78.5 Education level Primary Secondary Tertiary 91 108 66 34.3 40.8 24.9 Occupation Peasant Formal employment Business 105 50 110 39.6 18.9 41.5 Family size ≤ 5 People > 5 People 201 64 75.9 24.1 Decision maker Husband Wife Both 50 42 173 18.9 15.9 65.2 Referral factors Distance to referring facility 10 kilometers 185 74 6 69.8 27.9 2.3 Time to the referral site 2 hours 234 31 88.3 11.7 Obstetrics factors Gravidity Primigravida Multigravida 108 157 40.8 59.2 Obstetric emergencies Obstructed labor Prolonged labor Antepartum hemorrhage Previous Cesarean Section Non-Reassuring fetal status Hypertensive disorder 62 113 17 18 34 21 23.4 42.6 6.4 6.8 12.8 7.9 From the above Table 1 , out of the 265 participants enrolled in the study, the majority were aged 20–34 years 81(63.3%), were cohabiting 154 (58.1%), and lived in rural settings 208 (78.5%). Most had attained secondary education 108 (40.8%) and were businesswomen 110(41.5%) with a family size of less than five 201(75.9%). Most decision-making was shared by the spouses 173 (65.2%), and the majority lived less than 5 km from the nearest health facility 185(69.8%), taking less than 2 hours to reach the referral site 234 (88.3%). The most common emergency was multigravidity 157(59.2%), and the most common obstetrical emergency was prolonged labor 113(42.6%). Incidence of immediate adverse neonatal outcomes Figure 2 below illustrates the incidence of immediate adverse neonatal outcomes among obstetrical emergency referrals. Of the 265 respondents, 106 (40%) had immediate adverse neonatal outcomes, as shown in Fig. 2 below. Figure 2 . Pie charts showing the incidence of immediate adverse neonatal outcomes (n = 265). Common adverse neonatal outcomes Figure 3 below shows the distribution of common adverse neonatal outcomes among women referred for obstetrical emergencies. The majority of the 106 respondents who experienced adverse neonatal outcomes were admitted to the NICU 73 (27.6%), followed by a low Apgar score 63(23.8%), a fresh stillbirth rate 30(11.3%) and early-onset neonatal infections 18(6.8%). The lowest number of adverse neonatal outcomes was early neonatal deaths 6, (2.3%). Figure 3 . The common adverse neonatal outcomes (n = 106). Factors associated with immediate adverse neonatal outcomes Table 2 below presents the results of a multivariate analysis examining the relationships between the various participant characteristics and immediate adverse neonatal outcomes. The information included both unadjusted (crude) and adjusted risk ratios (RRs) along with 95% confidence intervals (CIs) for each characteristic. Table 2 Multivariable analysis of factors associated with adverse neonatal outcomes Variable Category cRR(95%CI) p-value aRR(95%CI) p-value Sociodemographic Maternal age 20–34 years 35 years above Ref 1.96(1.461–2.639) - 5 People Ref 1.36(1.001–1.842) - 0.049 - 1.07(0.745–1.574) - 0.723 Referral factors Distance to referring facility 10 kilometers 1.27(0.892–1.794) Ref 0.187 - 1.23(0.878–1.710) - 0.233 - Obstetric factors Obstetric emergencies Prolonged labor Antepartum hemorrhage Previous Cesarean Section Nonreassuring fetal status Ref 2.22(1.689–2.918) 0.54(0.22–1.293) 1.99(1.506–2.626) - < 0.001 0.166 < 0.001 - 2.48(1.859–3.311) 0.60(0.258–1.404) 1.90(1.394–2.584) - < 0.001* 0.240 < 0.001* Ref Reference category * p value < 0.05, cRR, crude risk ratio; aRR, adjusted risk ratio; CI, confidence interval. Multivariable analysis revealed that maternal age 35 years and above (aRR = 1.72, CI: 1.194–2.477, p value = 0.004), antepartum hemorrhage (aRR = 2.48, CI: 1.859–3.311, p-value < 0.001) and nonreassuring fetal status (aRR = 1.90, CI: 1.394–2.584, p-value < 0.001) were significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor at Jinja Regional Referral Hospital. Women aged 35 years and above had a 1.72-fold greater risk of having adverse neonatal outcomes than their counterparts aged less than 35 years (p-value < 0.05). Additionally, women referred to antepartum hemorrhage at 2.48 times the risk of having adverse neonatal outcomes (p-value < 0.05) and nonreassuring fetal status at 1.90 times the risk of having adverse neonatal outcomes (p value < 0.05) compared to mothers referred without APH or nonreassuring status, respectively. Discussion Incidence of adverse neonatal outcomes This study found the incidence of adverse neonatal outcomes to be high at 40% and similar to findings in Nepal [ 12 ], Ethiopia [ 11 ], and Rwanda [ 10 ] whose incidences were, 42%, 37.4%, and 37.1%, respectively. This similarity could stem from the fact that they were all hospital-based studies with similar study settings and characteristics. For example, in all these studies, the majority of the participants were from rural areas and experienced some form of referral delays. For instance, 52.4% and 74.7% experienced a second and third delay in Ethiopia [ 11 ], 37% experienced third delays in Rwanda [ 10 ] hence possible reasons for the similarities. However, other studies had lower incidences than this study. For example, India [ 17 ], Nigeria[ 18 ], Ethiopia [ 19 ], and Uganda [ 21 ] reported that the incidences of adverse neonatal outcomes among this group were 7.3%, 16.4%, 26.7%, and 13.9%, respectively. Although all these were institutional-based studies, discrepancies could be due to differences in the study designs and methodologies employed. For instance, the study in Uganda [ 21 ] was a retrospective cohort study that used data drawn from the integrated maternity register in one year; hence, there was a possibility of errors and missing data since this was based on records. Additionally, the study had a larger sample size of 780 participants compared to this study with only 265, therefore the bigger denominator could have contributed to the lower incidence. Moreover, the studies in Nigeria [ 18 ], and Ethiopia [ 20 ] had prospective cohort studies with shorter follow-up periods of 24 hours; hence, other adverse outcomes could have been missed. The study in India [ 17 ] was a population-based multicenter prospective study that had a longer duration of four years and a larger sample size of 34,319 participants; therefore, the denominator was larger. Common adverse neonatal outcomes among emergency obstetrics referrals This study revealed that of the 106 neonates who experienced adverse outcomes, 73 (27.6%) had NICU admissions, 63 (23.8%) had low Apgar scores, 30 (11.3%) had fresh stillborn infants, 18 (6.8%) had early-onset neonatal infections, and 6 (2.3%) had early neonatal deaths. This finding was similar to those of other researchers in, Ethiopia [ 20 ] and Western Uganda [ 22 ] who found common adverse outcomes to be low Apgar scores (23.1% and 19.2%, respectively). Also, other studies in Ethiopia [ 14 ] and [ 20 ] indicated NICU admissions of 23.5% and 34.8%, respectively. Additionally, similar findings regarding FSB were found in studies done in, India[ 16 ], Ghana [ 6 ], and Uganda [ 22 ], with incidences of FSB standing at, 17.4%, 16.4%, and 8.1% respectively. Other studies in Nepal [ 12 ] and Uganda [ 21 ] reported early neonatal deaths of 4.3% and 1.8%, respectively. The similarities between these studies can be explained by the fact that all the studies were conducted in tertiary hospitals with similar study settings, were in low-resourced settings as this study, and some almost had similar sample sizes. For example, the studies in Ethiopia [ 20 ], Uganda [ 22 ], and Nepal [ 12 ] had sample sizes of, 270, 177, and 212 which are similar to this study with a sample size of 265, therefore similar denominators. However, as much as similarities exist, other studies have demonstrated low incidences of different common adverse outcomes and others indicated higher incidences. For example, studies in Uganda [ 22 ], and Ethiopia [ 13 ], reported lower incidences of NICU admissions of 14%, and 12. 5%, respectively. Moreover, in India [ 17 ] and in Uganda [ 22 ] lower incidences of fresh stillbirths (6.8% and 7.3%, respectively) were reported. Additionally in western Uganda [ 24 ] lower incidences of early neonatal deaths (0.6%) was also reported. Meanwhile, a study in the Netherlands [ 15 ] also found low Apgar scores (2.7%). The low incidence discrepancies can be explained by the following: The Ugandan study [ 22 ], was a quasi-experimental study involving referral phone calls. This could have improved some of the adverse neonatal outcomes by facilitating timely referral among this group. The findings in India [ 17 ] was a population-based study that had a longer duration (4 years) and larger sample size (34,319 participants) hence a bigger denominator. In the Netherlands [ 15 ], the study was retrospective not in African or low-income countries like Uganda where this study was carried out. Therefore, better and quality service provision among referrals could have improved the outcomes. Higher incidences of FSB of 23.4%, was registered in Rwanda [ 10 ] and in Eastern Uganda [ 23 ] at 43.8%. Moreover, a 37.0% increase in the incidence of low Apgar was noted in Kenya [ 15 ]. Additionally, in Nepal [ 12 ] a high incidence of NICU admission of 40% was reported, while in Rwanda [ 10 ] and Eastern Uganda [ 23 ] a higher incidence of early neonatal death of 2.3%, and 37.2% respectively, were recorded. The higher incidences compared to this study can be explained by the following. The study in Uganda [ 23 ] was a prospective cohort study similar to this study design, however, it focused only on obstructed labor among referrals. Therefore, all adverse outcomes were attributed to one variable; hence the possible confounding can explain this. The Rwanda study [ 18 ] had a different study design (perinatal audits based on hospital records), hence the possibility of errors. Factors associated with immediate adverse neonatal outcomes. This study established that maternal age of 35 years and above (aRR = 1.72, 95% CI: 1.194–2.477, p-value = 0.004) was significantly and independently associated with adverse neonatal outcomes among emergency obstetric referrals. The risks of adverse neonatal outcomes were increased in women aged 35 years or older. Specifically, women who were 35 years and above were 1.72 times more at risk of having adverse neonatal outcomes than their counterparts were. This finding is similar to that of a cohort study in northern Uganda [ 25 ] in which age 35 years and above was significantly associated with adverse neonatal outcomes. The study revealed that women ≥ 35 years were 2.5 times more likely to be at risk of adverse neonatal outcomes than those aged less than 35 years. This similarity could be because, both studies were conducted under similar study settings ( Regional Referral Hospital), and had similar study designs ( cohort study). However, in contrast to this study, a study in Uganda [ 27 ] reported that women younger than 19 years were 1.9 times more at risk of adverse neonatal outcomes than older mothers. The study focused only on obstructed labor among referrals and highlighted that obstructed labor was more common in this group. Hence, this explains the attributes of most of the adverse neonatal outcomes to this younger age and the possibility for the discrepancy. The study also revealed that antepartum hemorrhage (aRR = 2.48, 95% CI: 1.859–3.311, p-value < 0.001) was significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor at Jinja Regional Referral Hospital. Compared with those who did not have APH, women who had APH had a 2.48-fold greater risk of having adverse neonatal outcomes. This finding is consistent with findings from other researchers who noted that antepartum hemorrhage is significantly associated with adverse neonatal outcomes. For example, in Ethiopia [ 14 ] it noted a 3.96-fold greater risk of having adverse neonatal outcomes than did their counterparts. A study in India [ 2 ] also reported that APH contributed to 7.3% of adverse neonatal outcomes. The similarities in findings to the study in India [ 2 ] and Ethiopia [ 14 ] could be because, both studies were carried out in a similar setting to this study (low-resourced settings, tertiary hospital-based. The study in India had a similar sample size of 320 participants and a similar study design (cohort) to this study. However, in Afghanistan [ 9 ] a significant association between APH and adverse neonatal outcomes among this group was also reported, although the risk of adverse outcomes was 7.7 times greater. This is probably because of the smaller sample size of only 92. Similarly, this study also established that nonreassuring fetal status was significantly associated with adverse neonatal outcomes (nonreassuring fetal status: aRR = 1.90, 95% CI: 1.394–2.584, p-value < 0.001). Women with a nonreassuring fetal status had a 1.90-fold greater risk of adverse outcomes than their counterparts without a nonreassuring fetal status. These findings are similar to those found in Ethiopia [ 14 ] and [ 20 ] which reported a 3.07-fold increase in the risk of adverse neonatal outcomes and a greater risk for adverse neonatal outcomes among women with nonreassuring fetal status respectively. This similarity is possibly stemming from similar study settings and sample sizes. Conclusions The incidence of adverse neonatal outcomes was found to be high at 40% among emergency obstetric referrals in labor. The most common neonatal adverse outcomes were NICU admission and low Apgar scores among this group. Maternal age 35 years and above, APH status, and nonreassuring fetal status were significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor. Study limitations This study's findings should be considered in light of several limitations. Firstly, the small sample size prevented separate examination of each specific adverse obstetric outcome in relation to parity. Additionally, there may have been a recall bias regarding participants' characteristics. Lastly, the follow-up period (72 hours) was brief, limiting the assessment of additional potential adverse outcomes in the neonates that occurred after the follow-up period. Areas for further research A comparative study between women who are referred and those who are not, to better understand the extent of adverse neonatal outcomes among obstetric referrals. Recommendations Obstetric referral protocols should be enhanced to alleviate the strains on tertiary care facilities, improve birth experiences, and mitigate adverse neonatal outcomes. We recommend a community-based intervention for community-based policies targeted at mitigating factors contributing to adverse neonatal outcomes during obstetric emergencies. . Abbreviations ANC Antenatal Care APH Antepartum Hemorrhage CBC Complete Blood Count EMCS Emergency Cesarean Section EmONC Emergency Obstetric & Newborn Care FSB Fresh Stillbirth HMIS Health Management Information System IMNCI Integrated management of Neonatal and Childhood Illnesses LB Live Birth MDG Millennium Development Goal MOH Ministry of Health NICU Neonatal Intensive Care Unit PROM Premature Rupture of Membranes SDG Sustainable Development Goal WHO World Health Organization Declarations Ethical approval and consent to participate All research methodologies adhered to ethical principles and received approval from the Research Ethics Committee (REC) of Bishop Stuart University, under REC number BSU-REC-2023-113. Additionally, permission was granted by the Administration of Jinja Regional Referral Hospital. Prior to participation, all individuals were fully informed about the study's objectives, and their informed consent was obtained. Consent for Publications: Not applicable to this study Availability of data and material: The datasets utilized in this study can be obtained from the corresponding author upon request. Please contact Geoffrey Okot via email at [email protected] . Competing of interest: There are no conflicts of interest related to this study . Funding: No grants were received for this study . Author contributions: GO served as the principal investigator, responsible for designing the study, collecting and analyzing the data, and drafting the manuscript . MK, FP, and SO contributed to discussions and drawing conclusions based on the study results. PB and UAN served as supervisors for the study. Acknowledgments We extend our gratitude to all participants who willingly took part in this study. Guarantor: Geoffrey Okot Author Information 1 Kampala International University Western Campus, Kampala, Uganda. 2 Gulu University Faculty of Medicine, Gulu, Uganda. 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BMC Pregnancy Childbirth [Internet]. 2022;22(1):1–8. Available from: https://doi.org/10.1186/s12884-022-04999-z Ghosh R, Santos N, Butrick E, Wanyoro A, Waiswa P, Kim E, et al. Stillbirth, neonatal and maternal mortality among cesarean births in Kenya and Uganda: a register-based prospective cohort study. BMJ Open. 2022;12(4):1–9. Bindal J. JMSCR Vol || 05 || Issue || 05 || Page 22485-22491 || May. 2017;(June). Patel AB, Prakash AA, Raynes-Greenow C, Pusdekar Y V, Hibberd PL. Description of inter-institutional referrals after admission for labor and delivery: A prospective population-based cohort study in rural Maharashtra, India. BMC Health Serv Res. 2017;17(1). Akaba GO, Ekele BA. Maternal and fetal outcomes of emergency obstetric referrals to a Nigerian teaching hospital. Trop Doct [Internet]. 2018 Apr 1 [cited 2022 Feb 24];48(2):132–5. Available from: https://journals.sagepub.com/doi/10.1177/0049475517735474 Aftab F, Ahmed I, Ahmed S, Ali SM, Amenga-Etego S, Ariff S, et al. Direct maternal morbidity and the risk of pregnancy-related deaths, stillbirths, and neonatal deaths in South Asia and sub-Saharan Africa: A population-based prospective cohort study in 8 countries. PLoS Med [Internet]. 2021;18(6):1–19. Available from: http://dx.doi.org/10.1371/journal.pmed.1003644 Elias S, Wolde Z, Tantu T, Gunta M, Zewudu D. Determinants of early neonatal outcomes after emergency cesarean delivery at Hawassa University Comprehensive Specialized Hospital, Hawassa, Ethiopia. PLoS One [Internet]. 2022;17(3 March):1–15. Available from: http://dx.doi.org/10.1371/journal.pone.0263837 Elizabeth N, Otim C. Outcome of Obstetric Referrals to a Tertiary Referral Hospital in Northern Uganda. Int J Sci Basic Appl Resreach. 2020;4531(24):224–33. Kanyesigye H, Kabakyenga J, Mulogo E, Fajardo Y, Atwine D, MacDonald NE, et al. Improved maternal-fetal outcomes among emergency obstetric referrals following phone call communication at a teaching hospital in southwestern Uganda: a quasi-experimental study. BMC Pregnancy Childbirth [Internet]. 2022 Dec 1 [cited 2022 Nov 23];22(1):1–10. Available from: https://doi.org/10.1186/s12884-022-05007-0 Musaba MW, Ndeezi G, Barageine JK, Weeks AD, Wandabwa JN, Mukunya D, et al. Incidence and determinants of perinatal mortality among women with obstructed labor in eastern Uganda : a prospective cohort study. 2021;7:1–9. Kanyesigye H, Ngonzi J, Mulogo E, Fajardo Y, Kabakyenga J. Health Care Workers’ Experiences, Challenges of Obstetric Referral Processes and Self-Reported Solutions in South Western Uganda: Mixed Methods Study. Risk Manag Health Policy. 2022;15(September):1869–86. Arach AAO, Tumwine JK, Nakasujja N, Ndeezi G, Kiguli J, Mukunya D, et al. Perinatal death in Northern Uganda: incidence and risk factors in a community-based prospective cohort study. Glob Health Action [Internet]. 2021 [cited 2022 Mar 20];14(1). Available from: https://pubmed.ncbi.nlm.nih.gov/33446087/ Hughes NJ, Namagembe I, Nakimuli A, Sekikubo M, Moffett A, Patient CJ, et al. Decision-to-delivery interval of emergency cesarean section in Uganda: A retrospective cohort study. BMC Pregnancy Childbirth [Internet]. 2020 May 27 [cited 2023 Feb 1];20(1):1–10. Available from: https://link.springer.com/articles/10.1186/s12884-020-03010-x Ayebare E, Hanson C, Nankunda J, Hjelmstedt A, Nantanda R, Jonas W, et al. Factors associated with birth asphyxia among term singleton births at two referral hospitals in Northern Uganda: a cross-sectional study. BMC Pregnancy Childbirth [Internet]. 2022;22(1):767. Available from: https://doi.org/10.1186/s12884-022-05095-y Perdok H, Jans S, Verhoeven C, van Dillen J, Mol BW, de Jonge A. Intrapartum Referral from Primary to Secondary Care in The Netherlands: A Retrospective Cohort Study on Management of Labor and Outcomes. Birth [Internet]. 2015 Jun 1 [cited 2022 Nov 22];42(2):156–64. Available from: https://onlinelibrary.wiley.com/doi/full/10.1111/birt.12160 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 12 Jun, 2024 Reviews received at journal 04 Jun, 2024 Reviews received at journal 31 May, 2024 Reviewers agreed at journal 27 May, 2024 Reviewers agreed at journal 26 May, 2024 Reviewers agreed at journal 25 May, 2024 Reviewers invited by journal 24 May, 2024 Editor invited by journal 07 May, 2024 Editor assigned by journal 25 Apr, 2024 Submission checks completed at journal 25 Apr, 2024 First submitted to journal 15 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4268699","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":295296224,"identity":"9b3d1fc5-fcfd-4136-b751-d6c27aec3891","order_by":0,"name":"Geoffrey Okot","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYDACHoYEhgobGx429uYDQK6EDHFazqSlyfHzHEsAaeEhRgsDUMthY8kZOQYwPn7Az3Pg4YMDCcyJG86c+fzqRo0FDwP74aMb8GmR7G1INjiQwJa44XjvNuucY0CH8aSl3cCnxeA8Q5r0xx88QFvObjPOYQNqkeAxI6Ql/ceBBInEDTdynhnn/CNGy9mGNIYDCQYg7zM/zm0jQotkz4FkiQMJCaBANmPO7ZPgYSPkF36enMQPBxL+g6Ly8eecb3Vy/OyHj+HVAoyIBBiLTQJM4lcOAuwHYCzmD4RVj4JRMApGwUgEALB/TjPWZlNKAAAAAElFTkSuQmCC","orcid":"","institution":"Kampala International University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Geoffrey","middleName":"","lastName":"Okot","suffix":""},{"id":295296225,"identity":"3301b143-5f1a-4d5b-b8fb-f605b6dea361","order_by":1,"name":"Samuel Omara","email":"","orcid":"","institution":"Kampala International University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Omara","suffix":""},{"id":295296226,"identity":"12fc4951-98a6-48ba-b0bc-5f0bb041a48e","order_by":2,"name":"Musa Kasujja","email":"","orcid":"","institution":"Kampala International University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Musa","middleName":"","lastName":"Kasujja","suffix":""},{"id":295296227,"identity":"80ce50f6-263e-436f-83c1-41b82d256e01","order_by":3,"name":"Francis Pebalo","email":"","orcid":"","institution":"Gulu University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Francis","middleName":"","lastName":"Pebalo","suffix":""},{"id":295296228,"identity":"bd61bc63-376f-4348-bd03-ccb8ff1fdeeb","order_by":4,"name":"Petrus Baruti","email":"","orcid":"","institution":"Kampala International University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Petrus","middleName":"","lastName":"Baruti","suffix":""},{"id":295296229,"identity":"a9d3b934-69a2-40b2-b8f5-3aaa3235def9","order_by":5,"name":"Naranjo Almenares Ubarnel","email":"","orcid":"","institution":"Kampala International University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Naranjo","middleName":"Almenares","lastName":"Ubarnel","suffix":""}],"badges":[],"createdAt":"2024-04-15 09:29:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4268699/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4268699/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-024-06900-6","type":"published","date":"2024-10-30T16:20:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55760680,"identity":"7f581fd7-cf59-4d51-84a7-4049dfde6957","added_by":"auto","created_at":"2024-05-02 18:56:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77345,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4268699/v1/d1f9cd90ac6cd56ec082d1c9.png"},{"id":55760678,"identity":"97b3caa9-af7b-47b5-8b2f-d276259da63f","added_by":"auto","created_at":"2024-05-02 18:56:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17462,"visible":true,"origin":"","legend":"\u003cp\u003ePie charts showing the incidence of immediate adverse neonatal outcomes (n=265).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4268699/v1/c86146bba99bf0657b73abd7.png"},{"id":55760679,"identity":"aa46077e-5cf3-45fb-82ed-2317840dd6b3","added_by":"auto","created_at":"2024-05-02 18:56:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23590,"visible":true,"origin":"","legend":"\u003cp\u003eshows the common adverse neonatal outcomes (n=106).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4268699/v1/186ce83f26ecd1d9a6a207d7.png"},{"id":68207325,"identity":"9a3a19c8-23a8-4e93-bc45-dc0063a9e1c8","added_by":"auto","created_at":"2024-11-04 16:36:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":864203,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4268699/v1/14d4855b-8f04-4f18-a15d-1378957d4884.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incidence and Factors Associated with Immediate Adverse Neonatal Outcomes Among Emergency Obstetric Referrals in Labor at a Tertiary Hospital in Uganda: A Prospective Cohort Study ","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, 2.5\u0026nbsp;million neonates die annually, 80% in sub-Saharan Africa and Asia with 1.2\u0026nbsp;million in the intrapartum period, two-thirds in the first day of life, and three-quarters in the first week [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Notably, 80% of the leading causes of these deaths are preventable through cost-effective interventions such as an organized primary health care system, and timely, appropriate, and accessible referral services, [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn sub-Saharan Africa, improvement in newborn survival has been slow, with neonatal mortality reduction lagging, hence contributing to approximately 45%-50% of total underfive mortality, however, a scale-up intervention such as early referrals with faster and responsive care could avert approximately 71% of these deaths [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Reports indicate that over 6700 newborn deaths occur per day with 1\u0026nbsp;million within the first 24hrs, accounting for 50% of under-five mortality [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] At this rate, it is unlikely to meet the Sustainable Development Goals (SDGs) of reducing under-5 mortality by 50% in the African Region [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eEmergency obstetric referrals account for more than 30% of all referrals and contribute greatly to adverse neonatal outcomes, mostly in low-resource settings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], especially those referred in labor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Obstetric referrals in low-income countries are compounded by a majority third delay (delay in getting the right care) and a second delay (delay in reaching the referral site)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This has been seen in Rwanda with 37% experiencing a third delay [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and in Ethiopia in which 52.3% and 74.7% experienced a second and third delays [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe incidence of adverse neonatal outcomes such as neonatal deaths, low APGAR score, fresh stillbirths, early neonatal infections, and admission to NICU among obstetric referrals varies between countries and settings from 10 to 45% [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For instance, the Netherlands, Malawi, and Kenya demonstrated this [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], Nepal indicated a range of 18 to 42%, India 7.3\u0026ndash;47%, Nigeria 16.4\u0026ndash;47%, Ethiopia 16 to 37.4%, and Rwanda 10 to 37.1% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Reported incidences in Uganda vary from region to region, 0.6 to 19.2% (Western Uganda) and 8.1 to 33.3% (North and Eastern Uganda) for low APGAR score, FSB, Early neonatal deaths and NICU admissions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eObstetric factors, sociodemographic factors, and obstetric delays are the key attributes of adverse neonatal outcomes and their variation in incidences regionally and per country[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Low socioeconomic status, low levels of education, rural residency, large family status, delays in reaching \u0026amp; receiving care at referral site, and obstetric factors such as prolonged labor, antepartum hemorrhage (APH), obstructed labor, fetal distress, hypertensive disorders are the great influencers adverse neonatal outcomes in low-income settings like Uganda [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For example, a study indicated 7.7 times the risks of adverse neonatal among women with APH [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and in western Uganda, attributes were made to malpresentation and previous cesarean section [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eEast and Northern Uganda have the highest incidences compared to other regions, and attributes to this have been made to, lower socioeconomic status, lower education level, maternal age\u0026thinsp;\u0026ge;\u0026thinsp;35years or age\u0026thinsp;\u0026le;\u0026thinsp;20 years, referral delays (especially third and second delays), under-resourced facilities, understaffing of critical cadres [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the significance of maternal and newborn health and the burden at hand, this study aimed to ascertain the incidence, common types, and associated factors of adverse neonatal outcomes among emergency obstetric referrals at Jinja Regional Referral Hospital.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cb\u003eStudy Design\u003c/b\u003e A prospective cohort study.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStudy Site\u003c/strong\u003e \u003cp\u003eThe study was conducted at Jinja Regional Referral Hospital (JRRH), a government-funded facility with a bed capacity of 500, situated in Jinja City within the district of Jinja, Eastern Uganda. The hospital's maternity ward, where the study took place, handles approximately 5,124 deliveries each year, including 1,104 (21.5%) emergency obstetric referrals. Among these referrals, 30\u0026ndash;40% of newborns typically require additional care and support. Adjacent to the maternity ward is the Neonatal Intensive Care Unit (NICU), which admits around 450 neonates annually, primarily those born to mothers referred with obstetrical complications.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample size calculation\u003c/h2\u003e \u003cp\u003eTo identify the common adverse neonatal outcomes among emergency obstetric referrals, Daniels WW,1999 was used. N =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{{{(\\text{z}}_{{\\alpha }})}^{2}\\text{p} (1-\\text{p})}{{\\text{e}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere N\u0026thinsp;=\u0026thinsp;the desired sample size for a population greater than 10,000.\u003c/p\u003e \u003cp\u003e \u003cb\u003eZ\u003c/b\u003e\u0026thinsp;=\u0026thinsp;1.96. Standard normal deviation. Z is the level of significance in the Z scores (assuming a 95% confidence interval).\u003c/p\u003e \u003cp\u003e \u003cb\u003ep\u003c/b\u003e\u0026thinsp;=\u0026thinsp;Incidence of adverse neonatal outcomes (19.2%) in a study in western Uganda among emergency obstetric referrals\u003c/p\u003e \u003cp\u003e \u003cb\u003eq\u003c/b\u003e\u0026thinsp;=\u0026thinsp;1-p; therefore, q\u0026thinsp;=\u0026thinsp;1-0.192\u003c/p\u003e \u003cp\u003e \u003cb\u003ee\u003c/b\u003e\u0026thinsp;=\u0026thinsp;0.05 is the absolute precision (taking a 95% confidence interval)\u003c/p\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eThe minimum sample size required was 239, however, to cater for non-response and reliability, a 10% addition was made. Therefore, the sample size considered was \u003cb\u003e265\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eAll women in labor who were referred for emergency obstetric care at Jinja Regional Referral Hospital were included.\u003c/p\u003e \u003cp\u003eWomen in labor referred for emergency obstetric care with multifetal gestation and preterm labor, and who were unconscious or hemodynamically unstable were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy procedure\u003c/h2\u003e \u003cp\u003eAll women referred for emergency obstetric care were educated about the research, its study objectives, and the inclusion and exclusion criteria, including the benefits of the study to the institution, the community, and all referred women in labor with obstetrical emergencies. A consecutive sampling technique was employed, and all women who met the eligibility criteria were approached to participate in the study. Those who agreed to participate provided consent and were given the appropriate privacy and confidentiality. The researcher and two research assistants administered a structured questionnaire privately and confidentially to each participant in the language they understood (English or Lusoga). All neonates were followed for 72 hours, and adverse outcomes were recorded for each neonate. Blood samples for complete blood count (CBC) from neonates who showed clinical signs and symptoms of early-onset neonatal infection were obtained aseptically by a laboratory technologist after all the reasons for the procedures and techniques were explained to and understood by the mothers. Every 10th sample was taken to the Lancet laboratory for independent analysis to ensure quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy Variables\u003c/h2\u003e \u003cp\u003eThe study investigated the influence of independent variables encompassing sociodemographic factors (maternal age, marital status, place of residence, education level, occupation, family size, and decision maker), referral factors such as facility distance from home, time taken to reach the referral site and obstetrical factors, including gravidity, obstructed labor, prolonged labor, APH, previous cesarean, nonreassuring fetal status, and hypertensive disorders), on the dependent variable, immediate adverse neonatal outcomes, which included low Apgar of less than 7 at 5 minutes, any newborn of women referred with obstetrical emergency admitted in NICU, Fresh stillbirth, early-onset neonatal infections occurring within the first 72 hours of life and Any death of a neonate occurring within 72 hours after delivery (early neonatal deaths). The above data were collected using structured interviewer-administered questionnaires.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eData quality control\u003c/h2\u003e \u003cp\u003eTo ensure that the data collection tools were appropriate, simple English was used as opposed to technical terms. The questionnaires were created based on available literature and factors within the study settings, translated into the local language (Lusoga), and back-translated into English for accuracy. A pretest of the data collection tool was performed to ascertain the reliability of the tool. All data collection processes were monitored by the researcher, and immediate cross-checking of the completed questionnaires was carried out to ensure the accuracy and completeness of the information. A content validity index was used on data obtained from five participants who were not part of the study, and interparticipant agreement was measured, with an agreement of 83%.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Management and Analysis\u003c/h2\u003e \u003cp\u003eThe collected data from completed questionnaires underwent thorough checks for consistency, accuracy, and completeness. Subsequently, it was entered into Epi info software version 7.2. Following this, a data extract was created in Microsoft Excel (2019) format and imported into the STATA version 14 statistical package. Within STATA, the data was further cleaned, coded, and analyzed.\u003c/p\u003e \u003cp\u003eThe incidence of adverse neonatal outcomes was determined by dividing the total number of participants who experienced adverse outcomes (numerator) by the overall study participants (denominator), then expressed in percentage. This calculation helped identify common adverse outcomes, where each specific adverse outcome\u0026rsquo;s total occurrence ( numerators) was divided by the total number of participants with adverse outcomes ( denominator) also expressed as a percentage. For factors associated with adverse neonatal outcomes, log-binominal regression analysis was used for risk ratios and associations. Statistical significance was set at a p-value of less than 0.05. The results were presented in pie charts, tables, and bar graphs and discussed for effective understanding and interpretation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study was conducted in the maternity ward and neonatal intensive care units of Jinja Regional Referral Hospital over three months from July to September 2023. A total of 265 women were educated on the study objectives, inclusion and exclusion criteria, and benefits. Women who met the exclusion criteria or did not provide consent were excluded from participation. The study flow chart is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Study flowchart\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive statistics for participants' characteristics\u003c/h2\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\u003ePresent the sociodemographic, referral, and obstetric characteristics of the participants (n\u0026thinsp;=\u0026thinsp;265)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 years\u003c/p\u003e \u003cp\u003e20\u0026ndash;34 years\u003c/p\u003e \u003cp\u003e35 years above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003cp\u003e181\u003c/p\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003cp\u003e68.3\u003c/p\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eCohabiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003cp\u003e72\u003c/p\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003cp\u003e27.2\u003c/p\u003e \u003cp\u003e58.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003cp\u003e78.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e108\u003c/p\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.3\u003c/p\u003e \u003cp\u003e40.8\u003c/p\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeasant\u003c/p\u003e \u003cp\u003eFormal employment\u003c/p\u003e \u003cp\u003eBusiness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.6\u003c/p\u003e \u003cp\u003e18.9\u003c/p\u003e \u003cp\u003e41.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 People\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 People\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e201\u003c/p\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.9\u003c/p\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecision maker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHusband\u003c/p\u003e \u003cp\u003eWife\u003c/p\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e42\u003c/p\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003cp\u003e15.9\u003c/p\u003e \u003cp\u003e65.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferral factors\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistance to referring facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 kilometers\u003c/p\u003e \u003cp\u003e5\u0026ndash;10 kilometers\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 kilometers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e185\u003c/p\u003e \u003cp\u003e74\u003c/p\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.8\u003c/p\u003e \u003cp\u003e27.9\u003c/p\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to the referral site\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 hours\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e234\u003c/p\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.3\u003c/p\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetrics factors\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimigravida\u003c/p\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.8\u003c/p\u003e \u003cp\u003e59.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetric emergencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObstructed labor\u003c/p\u003e \u003cp\u003eProlonged labor\u003c/p\u003e \u003cp\u003eAntepartum hemorrhage\u003c/p\u003e \u003cp\u003ePrevious Cesarean Section\u003c/p\u003e \u003cp\u003eNon-Reassuring fetal status\u003c/p\u003e \u003cp\u003eHypertensive disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003cp\u003e113\u003c/p\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e18\u003c/p\u003e \u003cp\u003e34\u003c/p\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003cp\u003e42.6\u003c/p\u003e \u003cp\u003e6.4\u003c/p\u003e \u003cp\u003e6.8\u003c/p\u003e \u003cp\u003e12.8\u003c/p\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFrom the above Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, out of the 265 participants enrolled in the study, the majority were aged 20\u0026ndash;34 years 81(63.3%), were cohabiting 154 (58.1%), and lived in rural settings 208 (78.5%). Most had attained secondary education 108 (40.8%) and were businesswomen 110(41.5%) with a family size of less than five 201(75.9%). Most decision-making was shared by the spouses 173 (65.2%), and the majority lived less than 5 km from the nearest health facility 185(69.8%), taking less than 2 hours to reach the referral site 234 (88.3%). The most common emergency was multigravidity 157(59.2%), and the most common obstetrical emergency was prolonged labor 113(42.6%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIncidence of immediate adverse neonatal outcomes\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below illustrates the incidence of immediate adverse neonatal outcomes among obstetrical emergency referrals. Of the 265 respondents, 106 (40%) had immediate adverse neonatal outcomes, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Pie charts showing the incidence of immediate adverse neonatal outcomes (n\u0026thinsp;=\u0026thinsp;265).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCommon adverse neonatal outcomes\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below shows the distribution of common adverse neonatal outcomes among women referred for obstetrical emergencies. The majority of the 106 respondents who experienced adverse neonatal outcomes were admitted to the NICU 73 (27.6%), followed by a low Apgar score 63(23.8%), a fresh stillbirth rate 30(11.3%) and early-onset neonatal infections 18(6.8%). The lowest number of adverse neonatal outcomes was early neonatal deaths 6, (2.3%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The common adverse neonatal outcomes (n\u0026thinsp;=\u0026thinsp;106).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with immediate adverse neonatal outcomes\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below presents the results of a multivariate analysis examining the relationships between the various participant characteristics and immediate adverse neonatal outcomes. The information included both unadjusted (crude) and adjusted risk ratios (RRs) along with 95% confidence intervals (CIs) for each characteristic.\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\u003eMultivariable analysis of factors associated with adverse neonatal outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecRR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eaRR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSociodemographic\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;34 years\u003c/p\u003e \u003cp\u003e35 years above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003cp\u003e1.96(1.461\u0026ndash;2.639)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.72(1.194\u0026ndash;2.477)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0.004*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31(0.973\u0026ndash;1.750)\u003c/p\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17(0.868\u0026ndash;1.523)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.304\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5 People\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 People\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003cp\u003e1.36(1.001\u0026ndash;1.842)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e1.07(0.745\u0026ndash;1.574)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferral factors\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistance to referring facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 kilometers\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 kilometers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.27(0.892\u0026ndash;1.794)\u003c/p\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23(0.878\u0026ndash;1.710)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetric factors\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObstetric emergencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProlonged labor\u003c/p\u003e \u003cp\u003eAntepartum hemorrhage\u003c/p\u003e \u003cp\u003ePrevious Cesarean Section\u003c/p\u003e \u003cp\u003eNonreassuring fetal status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003cp\u003e2.22(1.689\u0026ndash;2.918)\u003c/p\u003e \u003cp\u003e0.54(0.22\u0026ndash;1.293)\u003c/p\u003e \u003cp\u003e1.99(1.506\u0026ndash;2.626)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e0.166\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e2.48(1.859\u0026ndash;3.311)\u003c/p\u003e \u003cp\u003e0.60(0.258\u0026ndash;1.404)\u003c/p\u003e \u003cp\u003e1.90(1.394\u0026ndash;2.584)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003cp\u003e0.240\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eRef\u003c/em\u003e Reference category *\u003cem\u003ep value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, cRR, crude risk ratio; aRR, adjusted risk ratio; CI, confidence interval.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eMultivariable analysis revealed that maternal age 35 years and above (aRR\u0026thinsp;=\u0026thinsp;1.72, CI: 1.194\u0026ndash;2.477, p value\u0026thinsp;=\u0026thinsp;0.004), antepartum hemorrhage (aRR\u0026thinsp;=\u0026thinsp;2.48, CI: 1.859\u0026ndash;3.311, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and nonreassuring fetal status (aRR\u0026thinsp;=\u0026thinsp;1.90, CI: 1.394\u0026ndash;2.584, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor at Jinja Regional Referral Hospital. Women aged 35 years and above had a 1.72-fold greater risk of having adverse neonatal outcomes than their counterparts aged less than 35 years (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, women referred to antepartum hemorrhage at 2.48 times the risk of having adverse neonatal outcomes (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and nonreassuring fetal status at 1.90 times the risk of having adverse neonatal outcomes (p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to mothers referred without APH or nonreassuring status, respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eIncidence of adverse neonatal outcomes\u003c/h2\u003e \u003cp\u003eThis study found the incidence of adverse neonatal outcomes to be high at 40% and similar to findings in Nepal [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Ethiopia [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and Rwanda [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] whose incidences were, 42%, 37.4%, and 37.1%, respectively. This similarity could stem from the fact that they were all hospital-based studies with similar study settings and characteristics. For example, in all these studies, the majority of the participants were from rural areas and experienced some form of referral delays. For instance, 52.4% and 74.7% experienced a second and third delay in Ethiopia [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], 37% experienced third delays in Rwanda [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] hence possible reasons for the similarities.\u003c/p\u003e \u003cp\u003eHowever, other studies had lower incidences than this study. For example, India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Nigeria[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Ethiopia [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and Uganda [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported that the incidences of adverse neonatal outcomes among this group were 7.3%, 16.4%, 26.7%, and 13.9%, respectively. Although all these were institutional-based studies, discrepancies could be due to differences in the study designs and methodologies employed. For instance, the study in Uganda [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] was a retrospective cohort study that used data drawn from the integrated maternity register in one year; hence, there was a possibility of errors and missing data since this was based on records. Additionally, the study had a larger sample size of 780 participants compared to this study with only 265, therefore the bigger denominator could have contributed to the lower incidence. Moreover, the studies in Nigeria [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and Ethiopia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] had prospective cohort studies with shorter follow-up periods of 24 hours; hence, other adverse outcomes could have been missed. The study in India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] was a population-based multicenter prospective study that had a longer duration of four years and a larger sample size of 34,319 participants; therefore, the denominator was larger.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCommon adverse neonatal outcomes among emergency obstetrics referrals\u003c/h2\u003e \u003cp\u003eThis study revealed that of the 106 neonates who experienced adverse outcomes, 73 (27.6%) had NICU admissions, 63 (23.8%) had low Apgar scores, 30 (11.3%) had fresh stillborn infants, 18 (6.8%) had early-onset neonatal infections, and 6 (2.3%) had early neonatal deaths. This finding was similar to those of other researchers in, Ethiopia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and Western Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] who found common adverse outcomes to be low Apgar scores (23.1% and 19.2%, respectively). Also, other studies in Ethiopia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] indicated NICU admissions of 23.5% and 34.8%, respectively. Additionally, similar findings regarding FSB were found in studies done in, India[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], Ghana [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], with incidences of FSB standing at, 17.4%, 16.4%, and 8.1% respectively. Other studies in Nepal [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and Uganda [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported early neonatal deaths of 4.3% and 1.8%, respectively.\u003c/p\u003e \u003cp\u003eThe similarities between these studies can be explained by the fact that all the studies were conducted in tertiary hospitals with similar study settings, were in low-resourced settings as this study, and some almost had similar sample sizes. For example, the studies in Ethiopia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and Nepal [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] had sample sizes of, 270, 177, and 212 which are similar to this study with a sample size of 265, therefore similar denominators.\u003c/p\u003e \u003cp\u003eHowever, as much as similarities exist, other studies have demonstrated low incidences of different common adverse outcomes and others indicated higher incidences. For example, studies in Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and Ethiopia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], reported lower incidences of NICU admissions of 14%, and 12. 5%, respectively. Moreover, in India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and in Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] lower incidences of fresh stillbirths (6.8% and 7.3%, respectively) were reported. Additionally in western Uganda [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] lower incidences of early neonatal deaths (0.6%) was also reported. Meanwhile, a study in the Netherlands [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] also found low Apgar scores (2.7%).\u003c/p\u003e \u003cp\u003eThe low incidence discrepancies can be explained by the following: The Ugandan study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], was a quasi-experimental study involving referral phone calls. This could have improved some of the adverse neonatal outcomes by facilitating timely referral among this group. The findings in India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] was a population-based study that had a longer duration (4 years) and larger sample size (34,319 participants) hence a bigger denominator. In the Netherlands [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the study was retrospective not in African or low-income countries like Uganda where this study was carried out. Therefore, better and quality service provision among referrals could have improved the outcomes.\u003c/p\u003e \u003cp\u003eHigher incidences of FSB of 23.4%, was registered in Rwanda [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and in Eastern Uganda [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] at 43.8%. Moreover, a 37.0% increase in the incidence of low Apgar was noted in Kenya [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, in Nepal [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] a high incidence of NICU admission of 40% was reported, while in Rwanda [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and Eastern Uganda [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] a higher incidence of early neonatal death of 2.3%, and 37.2% respectively, were recorded.\u003c/p\u003e \u003cp\u003eThe higher incidences compared to this study can be explained by the following. The study in Uganda [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] was a prospective cohort study similar to this study design, however, it focused only on obstructed labor among referrals. Therefore, all adverse outcomes were attributed to one variable; hence the possible confounding can explain this. The Rwanda study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] had a different study design (perinatal audits based on hospital records), hence the possibility of errors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors associated with immediate adverse neonatal outcomes.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study established that maternal age of 35 years and above (aRR\u0026thinsp;=\u0026thinsp;1.72, 95% CI: 1.194\u0026ndash;2.477, p-value\u0026thinsp;=\u0026thinsp;0.004) was significantly and independently associated with adverse neonatal outcomes among emergency obstetric referrals. The risks of adverse neonatal outcomes were increased in women aged 35 years or older. Specifically, women who were 35 years and above were 1.72 times more at risk of having adverse neonatal outcomes than their counterparts were. This finding is similar to that of a cohort study in northern Uganda [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] in which age 35 years and above was significantly associated with adverse neonatal outcomes. The study revealed that women\u0026thinsp;\u0026ge;\u0026thinsp;35 years were 2.5 times more likely to be at risk of adverse neonatal outcomes than those aged less than 35 years. This similarity could be because, both studies were conducted under similar study settings ( Regional Referral Hospital), and had similar study designs ( cohort study). However, in contrast to this study, a study in Uganda [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] reported that women younger than 19 years were 1.9 times more at risk of adverse neonatal outcomes than older mothers. The study focused only on obstructed labor among referrals and highlighted that obstructed labor was more common in this group. Hence, this explains the attributes of most of the adverse neonatal outcomes to this younger age and the possibility for the discrepancy.\u003c/p\u003e \u003cp\u003eThe study also revealed that antepartum hemorrhage (aRR\u0026thinsp;=\u0026thinsp;2.48, 95% CI: 1.859\u0026ndash;3.311, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor at Jinja Regional Referral Hospital. Compared with those who did not have APH, women who had APH had a 2.48-fold greater risk of having adverse neonatal outcomes. This finding is consistent with findings from other researchers who noted that antepartum hemorrhage is significantly associated with adverse neonatal outcomes. For example, in Ethiopia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] it noted a 3.96-fold greater risk of having adverse neonatal outcomes than did their counterparts. A study in India [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] also reported that APH contributed to 7.3% of adverse neonatal outcomes. The similarities in findings to the study in India [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and Ethiopia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] could be because, both studies were carried out in a similar setting to this study (low-resourced settings, tertiary hospital-based. The study in India had a similar sample size of 320 participants and a similar study design (cohort) to this study. However, in Afghanistan [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] a significant association between APH and adverse neonatal outcomes among this group was also reported, although the risk of adverse outcomes was 7.7 times greater. This is probably because of the smaller sample size of only 92.\u003c/p\u003e \u003cp\u003eSimilarly, this study also established that nonreassuring fetal status was significantly associated with adverse neonatal outcomes (nonreassuring fetal status: aRR\u0026thinsp;=\u0026thinsp;1.90, 95% CI: 1.394\u0026ndash;2.584, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Women with a nonreassuring fetal status had a 1.90-fold greater risk of adverse outcomes than their counterparts without a nonreassuring fetal status. These findings are similar to those found in Ethiopia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] which reported a 3.07-fold increase in the risk of adverse neonatal outcomes and a greater risk for adverse neonatal outcomes among women with nonreassuring fetal status respectively. This similarity is possibly stemming from similar study settings and sample sizes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe incidence of adverse neonatal outcomes was found to be high at 40% among emergency obstetric referrals in labor. The most common neonatal adverse outcomes were NICU admission and low Apgar scores among this group. Maternal age 35 years and above, APH status, and nonreassuring fetal status were significantly associated with adverse neonatal outcomes among emergency obstetric referrals in labor.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStudy limitations\u003c/h2\u003e \u003cp\u003eThis study's findings should be considered in light of several limitations. Firstly, the small sample size prevented separate examination of each specific adverse obstetric outcome in relation to parity. Additionally, there may have been a recall bias regarding participants' characteristics. Lastly, the follow-up period (72 hours) was brief, limiting the assessment of additional potential adverse outcomes in the neonates that occurred after the follow-up period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAreas for further research\u003c/h2\u003e \u003cp\u003eA comparative study between women who are referred and those who are not, to better understand the extent of adverse neonatal outcomes among obstetric referrals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations\u003c/h2\u003e \u003cp\u003eObstetric referral protocols should be enhanced to alleviate the strains on tertiary care facilities, improve birth experiences, and mitigate adverse neonatal outcomes.\u003c/p\u003e \u003cp\u003eWe recommend a community-based intervention for community-based policies targeted at mitigating factors contributing to adverse neonatal outcomes during obstetric emergencies.\u003c/p\u003e \u003cp\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eAntenatal Care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eAPH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eAntepartum Hemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eCBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eComplete Blood Count\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eEMCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eEmergency Cesarean Section\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eEmONC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eEmergency Obstetric \u0026amp; Newborn Care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eFSB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eFresh Stillbirth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eHMIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eHealth Management Information System\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eIMNCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eIntegrated management of Neonatal and Childhood Illnesses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eLB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eLive Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eMDG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eMillennium Development Goal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eMOH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eMinistry of Health\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003ePROM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003ePremature Rupture of Membranes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eSDG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eSustainable Development Goal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.98169717138103%\" valign=\"top\"\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"89.01830282861897%\" valign=\"top\"\u003e\n \u003cp\u003eWorld Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll research methodologies adhered to ethical principles and received approval from the Research Ethics Committee (REC) of Bishop Stuart University, under REC number BSU-REC-2023-113. Additionally, permission was granted by the Administration of Jinja Regional Referral Hospital. Prior to participation, all individuals were fully informed about the study\u0026apos;s objectives, and their informed consent was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publications:\u0026nbsp;\u003c/strong\u003eNot applicable to this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets utilized in this study can be obtained from the corresponding author upon request. Please contact \u003cstrong\u003eGeoffrey Okot\u003c/strong\u003e via email at \u003cu\[email protected].\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of interest:\u0026nbsp;\u003c/strong\u003eThere are no conflicts of interest related to this study\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo grants were received for this study\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions: GO\u0026nbsp;\u003c/strong\u003eserved as the principal investigator, responsible for designing the study, collecting and analyzing the data, and drafting the manuscript\u003cstrong\u003e. MK, FP,\u003c/strong\u003e and \u003cstrong\u003eSO\u003c/strong\u003e contributed to discussions and drawing conclusions based on the study results. \u003cstrong\u003ePB\u003c/strong\u003e and \u003cstrong\u003eUAN\u003c/strong\u003e served as supervisors for the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to all participants who willingly took part in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuarantor:\u0026nbsp;\u003c/strong\u003eGeoffrey Okot\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eKampala International University Western Campus, Kampala, Uganda.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003e2\u003c/sup\u003eGulu University Faculty of Medicine, Gulu, Uganda.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRosa-Mangeret F, Benski AC, Golaz A, Zala PZ, Kyokan M, Wagner N, et al. 2.5 Million Annual Deaths\u0026mdash;Are Neonates in Low-and Middle-Income Countries Too Small to Be Seen? A Bottom-Up Overview on Neonatal Morbi-Mortality. Trop Med Infect Dis. 2022;7(5):1\u0026ndash;21. \u003c/li\u003e\n\u003cli\u003eChowdhury S, Chakraborty P pratim. Universal health coverage ‑ There is more to it than meets the eye. J Fam Med Prim Care [Internet]. 2017;6(2):169\u0026ndash;70. Available from: http://www.jfmpc.com/article.asp?issn=2249-4863;year=2017;volume=6;issue=1;spage=169;epage=170;aulast=Faizi\u003c/li\u003e\n\u003cli\u003eWastnedge E, Waters D, Murray SR, McGowan B, Chipeta E, Nyondo-Mipando AL, et al. Interventions to reduce preterm birth and stillbirth, and improve outcomes for babies born preterm in low and middle-income countries: A systematic review. J Glob Health. 2021;11. \u003c/li\u003e\n\u003cli\u003eThomas G, Demena M, Hawulte B, Eyeberu A, Heluf H, Tamiru D. Neonatal Mortality and Associated Factors Among Neonates Admitted to the Neonatal Intensive Care Unit of Dil Chora Referral Hospital, Dire Dawa City, Ethiopia, 2021: A Facility-Based Study. Front Pediatr. 2022 Feb 11;9(February):1\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eGetachew B, Etefa T, Asefa A, Terefe B, Dereje D. Determinants of Low Fifth Minute Apgar Score among Newborn Delivered in Jimma University Medical Center, Southwest Ethiopia. Int J Pediatr (United Kingdom) [Internet]. 2020 [cited 2022 Dec 1];2020. Available from: https://www.hindawi.com/journals/ijpedi/2020/9896127/\u003c/li\u003e\n\u003cli\u003eOduro-Mensah E, Agyepong IA, Frimpong E, Zweekhorst M, Vanotoo LA. Implementation of a referral and expert advice call Center for Maternal and Newborn Care in the resource-constrained health system context of the Greater Accra region of Ghana. BMC Pregnancy Childbirth. 2021;21(1):1\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eForbes F, Wynter K, Zeleke BM, Fisher J. Male partner involvement in birth preparedness, complication readiness and obstetric emergencies in Sub-Saharan Africa: a scoping review. BMC Pregnancy Childbirth. 2021;21(1):1\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eAyeni OM, Aboyeji AP, Ijaiya MA, Adesina KT, Fawole AA, Adeniran AS. Determinants of the decision-to-delivery interval and the effect on perinatal outcome after emergency cesarean delivery: A cross-sectional study. Malawi Med J. 2021;33(1):28\u0026ndash;36. \u003c/li\u003e\n\u003cli\u003eHirose A, Borchert M, Cox J, Alkozai AS, Filippi V. Determinants of delays in traveling to an emergency obstetric care facility in Herat, Afghanistan: An analysis of cross-sectional survey data and spatial modeling. BMC Pregnancy Childbirth. 2015;15(1). \u003c/li\u003e\n\u003cli\u003eMusafili A, Persson L\u0026Aring;, Baribwira C, P\u0026aring;fs J, Mulindwa PA, Ess\u0026eacute;n B. Case review of perinatal deaths at hospitals in Kigali, Rwanda: Perinatal audit with application of a three-delays analysis. BMC Pregnancy Childbirth. 2017;17(1):1\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eAssefa EM, Berhane Y. Delays in emergency obstetric referrals in Addis Ababa hospitals in Ethiopia: a facility-based, cross-sectional study. BMJ Open. 2020;10(6):e033771. \u003c/li\u003e\n\u003cli\u003eMaskey S. Obstetric Referrals to a Tertiary Teaching Hospital of Nepal. Nepal J Obstet Gynaecol [Internet]. 2015 [cited 2022 Nov 22];10(1):52\u0026ndash;6. Available from: https://www.nepjol.info/index.php/NJOG/article/view/13197/10623\u003c/li\u003e\n\u003cli\u003eDesta M, Mekonen Z, Alemu AA, Demelash M, Getaneh T, Bazezew Y, et al. Determinants of obstructed labor and its adverse outcomes among women who gave birth in Hawassa University referral Hospital: A case-control study. PLoS One [Internet]. 2022;17(6 June):1\u0026ndash;14. Available from: http://dx.doi.org/10.1371/journal.pone.0268938\u003c/li\u003e\n\u003cli\u003eAjibo BD, Wolka E, Aseffa A, Nugusu MA, Adem AO, Mamo M, et al. Determinants of low fifth minute Apgar score among newborns delivered by cesarean section at Wolaita Sodo University Comprehensive Specialized Hospital, Southern Ethiopia: an unmatched case-control study. BMC Pregnancy Childbirth [Internet]. 2022;22(1):1\u0026ndash;8. Available from: https://doi.org/10.1186/s12884-022-04999-z\u003c/li\u003e\n\u003cli\u003eGhosh R, Santos N, Butrick E, Wanyoro A, Waiswa P, Kim E, et al. Stillbirth, neonatal and maternal mortality among cesarean births in Kenya and Uganda: a register-based prospective cohort study. BMJ Open. 2022;12(4):1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eBindal J. JMSCR Vol || 05 || Issue || 05 || Page 22485-22491 || May. 2017;(June). \u003c/li\u003e\n\u003cli\u003ePatel AB, Prakash AA, Raynes-Greenow C, Pusdekar Y V, Hibberd PL. Description of inter-institutional referrals after admission for labor and delivery: A prospective population-based cohort study in rural Maharashtra, India. BMC Health Serv Res. 2017;17(1). \u003c/li\u003e\n\u003cli\u003eAkaba GO, Ekele BA. Maternal and fetal outcomes of emergency obstetric referrals to a Nigerian teaching hospital. Trop Doct [Internet]. 2018 Apr 1 [cited 2022 Feb 24];48(2):132\u0026ndash;5. Available from: https://journals.sagepub.com/doi/10.1177/0049475517735474\u003c/li\u003e\n\u003cli\u003eAftab F, Ahmed I, Ahmed S, Ali SM, Amenga-Etego S, Ariff S, et al. Direct maternal morbidity and the risk of pregnancy-related deaths, stillbirths, and neonatal deaths in South Asia and sub-Saharan Africa: A population-based prospective cohort study in 8 countries. PLoS Med [Internet]. 2021;18(6):1\u0026ndash;19. Available from: http://dx.doi.org/10.1371/journal.pmed.1003644\u003c/li\u003e\n\u003cli\u003eElias S, Wolde Z, Tantu T, Gunta M, Zewudu D. Determinants of early neonatal outcomes after emergency cesarean delivery at Hawassa University Comprehensive Specialized Hospital, Hawassa, Ethiopia. PLoS One [Internet]. 2022;17(3 March):1\u0026ndash;15. Available from: http://dx.doi.org/10.1371/journal.pone.0263837\u003c/li\u003e\n\u003cli\u003eElizabeth N, Otim C. Outcome of Obstetric Referrals to a Tertiary Referral Hospital in Northern Uganda. Int J Sci Basic Appl Resreach. 2020;4531(24):224\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eKanyesigye H, Kabakyenga J, Mulogo E, Fajardo Y, Atwine D, MacDonald NE, et al. Improved maternal-fetal outcomes among emergency obstetric referrals following phone call communication at a teaching hospital in southwestern Uganda: a quasi-experimental study. BMC Pregnancy Childbirth [Internet]. 2022 Dec 1 [cited 2022 Nov 23];22(1):1\u0026ndash;10. Available from: https://doi.org/10.1186/s12884-022-05007-0\u003c/li\u003e\n\u003cli\u003eMusaba MW, Ndeezi G, Barageine JK, Weeks AD, Wandabwa JN, Mukunya D, et al. Incidence and determinants of perinatal mortality among women with obstructed labor in eastern Uganda : a prospective cohort study. 2021;7:1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eKanyesigye H, Ngonzi J, Mulogo E, Fajardo Y, Kabakyenga J. Health Care Workers\u0026rsquo; Experiences, Challenges of Obstetric Referral Processes and Self-Reported Solutions in South Western Uganda: Mixed Methods Study. Risk Manag Health Policy. 2022;15(September):1869\u0026ndash;86. \u003c/li\u003e\n\u003cli\u003eArach AAO, Tumwine JK, Nakasujja N, Ndeezi G, Kiguli J, Mukunya D, et al. Perinatal death in Northern Uganda: incidence and risk factors in a community-based prospective cohort study. Glob Health Action [Internet]. 2021 [cited 2022 Mar 20];14(1). Available from: https://pubmed.ncbi.nlm.nih.gov/33446087/\u003c/li\u003e\n\u003cli\u003eHughes NJ, Namagembe I, Nakimuli A, Sekikubo M, Moffett A, Patient CJ, et al. Decision-to-delivery interval of emergency cesarean section in Uganda: A retrospective cohort study. BMC Pregnancy Childbirth [Internet]. 2020 May 27 [cited 2023 Feb 1];20(1):1\u0026ndash;10. Available from: https://link.springer.com/articles/10.1186/s12884-020-03010-x\u003c/li\u003e\n\u003cli\u003eAyebare E, Hanson C, Nankunda J, Hjelmstedt A, Nantanda R, Jonas W, et al. Factors associated with birth asphyxia among term singleton births at two referral hospitals in Northern Uganda: a cross-sectional study. BMC Pregnancy Childbirth [Internet]. 2022;22(1):767. Available from: https://doi.org/10.1186/s12884-022-05095-y\u003c/li\u003e\n\u003cli\u003ePerdok H, Jans S, Verhoeven C, van Dillen J, Mol BW, de Jonge A. Intrapartum Referral from Primary to Secondary Care in The Netherlands: A Retrospective Cohort Study on Management of Labor and Outcomes. Birth [Internet]. 2015 Jun 1 [cited 2022 Nov 22];42(2):156\u0026ndash;64. Available from: https://onlinelibrary.wiley.com/doi/full/10.1111/birt.12160\u003c/li\u003e\n\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-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Obstetrical Emergency, Referrals, Adverse Neonatal Outcomes","lastPublishedDoi":"10.21203/rs.3.rs-4268699/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4268699/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHigh incidences of adverse neonatal outcomes especially in resource-limited settings are multifactorial and vary from country to country and even within the same country, there are regional and institutional variations. In sub-Saharan Africa, the majority of adverse neonatal outcomes are intrapartum related, and studies in Uganda have shown that referral in labor is a major determinant of adverse neonatal outcomes. This study aimed to assess the incidence and factors associated with immediate adverse neonatal outcomes among emergency obstetric referrals in labor at a tertiary hospital in Eastern Uganda.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eThis was a prospective cohort study involving 265 women referred with obstetric emergencies in labor at Jinja Regional Referral Hospital over 3 months. Consecutive sampling was employed, and interviewer-administered questionnaires were used for data collection. Sociodemographic, referral, and obstetrical factors were recorded, and log-binominal regression analysis was used to establish risk ratios and associations with adverse neonatal outcomes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 265 emergency obstetric referrals, 40% had adverse neonatal outcomes. Neonatal intensive care admission (27.6%), low Apgar score (23.8%), fresh stillbirth (11.3%), early-onset neonatal infection (6.8%), and early neonatal death (2.3%) were the common neonatal adverse outcomes. Factors significantly associated with adverse neonatal outcomes were; maternal age\u0026thinsp;\u0026ge;\u0026thinsp;35 years aRR\u0026thinsp;=\u0026thinsp;1.72, (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.004\u003cb\u003e)\u003c/b\u003e, APH aRR\u0026thinsp;=\u0026thinsp;2.48, (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e) and nonreassuring fetal status aRR\u0026thinsp;=\u0026thinsp;1.90, ( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e The study revealed a notable incidence of adverse neonatal outcomes, with the most common being admissions to neonatal intensive care units and low Apgar scores. Strong and statistically significant associations with adverse neonatal outcomes were observed for maternal age of 35 years or older, antepartum hemorrhage, and nonreassuring fetal status. Improving obstetric referral protocols is essential to ease the burden on tertiary care centers, enhance the birthing journey, and minimize risks for newborns.\u003c/p\u003e","manuscriptTitle":"Incidence and Factors Associated with Immediate Adverse Neonatal Outcomes Among Emergency Obstetric Referrals in Labor at a Tertiary Hospital in Uganda: A Prospective Cohort Study ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 18:56:34","doi":"10.21203/rs.3.rs-4268699/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-12T09:58:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-04T12:02:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-31T21:25:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184944858985760136807929923818381973391","date":"2024-05-27T18:55:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141883875444944162665955029681973060282","date":"2024-05-26T20:53:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262497823895849040842619536664928209936","date":"2024-05-25T05:52:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-24T15:45:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-07T04:17:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-25T07:40:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-25T07:40:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-04-15T09:28:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4baf18f-3f14-4426-9533-0f5138208b26","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:29:26+00:00","versionOfRecord":{"articleIdentity":"rs-4268699","link":"https://doi.org/10.1186/s12884-024-06900-6","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2024-10-30 16:20:36","publishedOnDateReadable":"October 30th, 2024"},"versionCreatedAt":"2024-05-02 18:56:34","video":"","vorDoi":"10.1186/s12884-024-06900-6","vorDoiUrl":"https://doi.org/10.1186/s12884-024-06900-6","workflowStages":[]},"version":"v1","identity":"rs-4268699","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4268699","identity":"rs-4268699","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}