Elias Kumbakumba

Background: Prior cesarean delivery (CD) is a leading indication for repeat CD and a key driver of rising cesarean rates in Sub‐Saharan Africa. Evidence on associations between prior CD and adverse outcomes in low‐resource settings remains limited. Objective: We examined the association between one prior CD and adverse maternal and perinatal outcomes and examined current delivery mode as a mediator of this association among women delivering at Mbarara Regional Referral Hospital (MRRH), Uganda. Methods: We conducted a secondary analysis of four prospective studies at MRRH (2014–2024). The exposure was having one prior CD, and outcomes included composite adverse maternal outcomes (postpartum hemorrhage, infection, blood transfusion, prolonged hospital stay, and others) and composite adverse perinatal outcomes (stillbirth, neonatal death, preterm birth, low birthweight, low Apgar score, and neonatal intensive care unit admission). We compared the odds of adverse outcomes for women with one prior CD to those with none using multivariable logistic regression. Causal mediation analysis was used to assess whether current CD mediated the effect of prior CD on adverse maternal outcomes. Results: Of 2222 women with at least one prior delivery, 611 (27.5%) had one prior CD. Women with one prior CD more often delivered by cesarean (73.7% vs. 26.4%) and experienced more adverse maternal outcomes (24.5% vs. 15.4%, P < 0.001), including prolonged hospital stay (21.6% vs. 12.7%, P < 0.001). Prior CD was associated with increased odds of adverse maternal outcomes (adjusted odds ratio [aOR]: 1.99, 95% confidence interval [CI]: 1.54–2.57), with 88.9% of this effect mediated through current delivery mode (indirect odds ratio [OR]: 1.78, 95% CI: 1.41–2.25; direct OR: 1.09, 95% CI: 0.79–1.51, P = 0.586). Adverse perinatal outcomes (19.1%) did not differ by prior CD status ( P = 0.28). HIV‐positive serostatus (aOR: 1.29), referral (aOR: 1.69), and low antenatal care (ANC) attendance (aOR: 1.66) independently predicted perinatal outcomes. Conclusion: While prior CD was associated with higher odds of poor maternal outcomes due to repeat cesarean, HIV‐positive serostatus, facility referral, and low ANC attendance (but not prior CD) independently predicted adverse perinatal outcomes. Individualized delivery planning and improving surgical safety for women with prior CD and strengthened antenatal surveillance are critical to reducing maternal and perinatal morbidity at referral facilities in low‐resource settings.

PurposeVerbal autopsy (VA) is widely used to infer causes of death (COD) in settings where medical certification and autopsy are unavailable. Physician-certified COD determination after review of verbal autopsy is commonly used, but it is time- and effort-intensive, and often cloaked in diagnostic uncertainty. We introduce a framework for soft-label (probabilistic) supervised VA modelling that accommodates physician diagnostic uncertainty in settings where gold-standard labels are unavailable, and compare this to a traditional hard-label (deterministic) approach.MethodsUsing pediatric post-discharge mortality VA data (N = 356) from a multisite cohort study in Uganda, we constructed soft labels (probability vectors) from primary and alternative physician-assigned causes, along with associated confidence levels. XGBoost was used to create and compare models.ResultsThe soft-label model had population-level performance, as assessed by the cause-specific mortality fraction (CSMF) accuracy, of 0.88 ± 0.04, compared with 0.78 ± 0.03 for hard labels. Individual-level performance was slightly lower with a chance-corrected concordance of 0.38 ± 0.05 vs 0.40 ± 0.06.ConclusionsBy explicitly modelling physician uncertainty, soft-label learning substantially improves population-level cause-specific mortality estimation derived from VA data. The proposed framework is well-suited for mortality surveillance and policy-relevant applications in low-resource settings.

Background: Many children under five die post hospital discharge in low-and middle-income countries (LMICs), particularly after treatment for severe infections. While some models exist, evidence on risk prediction for post-discharge mortality remains limited, with most relying solely on admission characteristics, overlooking in-hospital disease progression and discharge features. Methods: We used secondary data from prospective cohort studies in six Ugandan hospitals (2012-2021) to update models at discharge. Of 8,810 children included, 3,665 were aged P ), achieving an AUROC of 0.81 and a Brier score of 0.06. In the 6–60m cohort, the model AUROC increased by 4.4% (95% CI 2.0 – 6.9, P ), with an AUROC of 0.79 and a Brier score of 0.04. The NRI was 10.41% for children <6 months and 14.51% for those 6-60m and was achieved primarily through a reduction of false positive rates. Conclusion: Adding only three discharge characteristics to the post-discharge mortality model based on admission characteristics enhanced prediction accuracy, including model calibration, discrimination and risk stratification compared to admission-only models. Key Messages: Post-discharge mortality risk prediction models that incorporated discharge characteristics performed better than admission-only models for children under five in Uganda. The augmented model achieved stronger discrimination, improved calibration and substantial reclassification gains, primarily by reducing false positive rates. Most of the benefits of these improved models stem from accurately identifying low-risk survivors, which reduces unwarranted follow-up and enables the more effective utilization of the health system’s limited resources.

Introduction: Post-discharge mortality among children following an acute illness in low-resource settings is high and demands urgent attention. We aimed to assess the impact of Smart Discharges, a mortality prevention risk-differentiated approach to peri-discharge care among children under five years admitted with suspected sepsis. Methods: We conducted a before-after two-phase study with staggered implementation at six hospitals in Uganda. During a baseline period (Phase-1), clinical prediction algorithms for post-discharge mortality were developed based on clinical and socio-demographic data collected at hospital admission. Outcomes, primarily mortality within six months of discharge, were compared against an interventional period (Phase-2). In the Smart Discharges intervention each family was given soap, a mosquito net, their risk category (low/medium/high/very high), counselling, and educational materials regardless of risk stratification, after which the intensity of recommended follow-up care was determined by age (0-6, 6-60 months) and predicted post-discharge mortality risk. Results: Overall, 13,051 children were enrolled: Phase-1, n=6,955; Phase-2, n=6,096. Characteristics were similar between groups, including mean predicted post-discharge mortality risk (6.3% Phase-1 vs. 5.9% Phase-2). With Smart Discharges, 2,331/3,891 (59.9%) medium/high/very high-risk families attending all their scheduled visits. The observed post-discharge mortality rate was 439 (6.3%) in Phase-1 vs. 296 (4.9%) in Phase-2; adjusted hazard ratio 0.77 (95%CI 0.67 to 0.90) favouring the intervention. In Phase-1, 1,313 (18.9%) children were re-admitted to hospital vs. 1,024 (16.8%) in Phase-2. Conclusion: A simple approach of risk assessment paired with education and engagement through scheduled follow-up after discharge is an appropriate strategy to improve child survival in low-resource settings.

Background: A timely differential diagnostic is essential to identify the etiology of central nervous system (CNS) infections in children, in order to facilitate targeted treatment, manage patients, and improve clinical outcome. Objective: The Pediatric Infection-Point-of-Care (PI-POC) trial is investigating novel methods to improve and strengthen the differential diagnostics of suspected childhood CNS infections in low-income health systems such as those in Southwestern Uganda. This will be achieved by evaluating (1) a novel DNA-based diagnostic assay for CNS infections, (2) a commercially available multiplex PCR-based meningitis/encephalitis (ME) panel for clinical use in a facility-limited laboratory setting, (3) proteomics profiling of blood from children with severe CNS infection as compared to outpatient controls with fever yet not severely ill, and (4) Myxovirus resistance protein A (MxA) as a biomarker in blood for viral CNS infection. Further changes in the etiology of childhood CNS infections after the introduction of the pneumococcal conjugate vaccine against Streptococcus pneumoniae will be investigated. In addition, the carriage and invasive rate of Neisseria meningitidis will be recorded and serotyped, and the expression of its major virulence factor (polysaccharide capsule) will be investigated. Methods: The PI-POC trial is a prospective observational study of children including newborns up to 12 years of age with clinical features of CNS infection, and age-/sex-matched outpatient controls with fever yet not severely ill. Participants are recruited at 2 Pediatric clinics in Mbarara, Uganda. Cerebrospinal fluid (for cases only), blood, and nasopharyngeal (NP) swabs (for both cases and controls) sampled at both clinics are analyzed at the Epicentre Research Laboratory through gold-standard methods for CNS infection diagnosis (microscopy, biochemistry, and culture) and a commercially available ME panel for multiplex PCR analyses of the cerebrospinal fluid. An additional blood sample from cases is collected on day 3 after admission. After initial clinical analyses in Mbarara, samples will be transported to Stockholm, Sweden for (1) validation analyses of a novel nucleic acid–based POC test, (2) biomarker research, and (3) serotyping and molecular characterization of S. pneumoniae and N. meningitidis. Results: A pilot study was performed from January to April 2019. The PI-POC trial enrollment of patients begun in April 2019 and will continue until September 2020, to include up to 300 cases and controls. Preliminary results from the PI-POC study are expected by the end of 2020. Conclusions: The findings from the PI-POC study can potentially facilitate rapid etiological diagnosis of CNS infections in low-resource settings and allow for novel methods for determination of the severity of CNS infection in such environment. Trial Registration: ClinicalTrials.gov NCT03900091; https://clinicaltrials.gov/ct2/show/NCT03900091 International Registered Report Identifier (IRRID): DERR1-10.2196/21430

BACKGROUND A timely differential diagnostic is essential to identify the etiology of central nervous system (CNS) infections in children, in order to facilitate targeted treatment, manage patients, and improve clinical outcome. OBJECTIVE The Pediatric Infection-Point-of-Care (PI-POC) trial is investigating novel methods to improve and strengthen the differential diagnostics of suspected childhood CNS infections in low-income health systems such as those in Southwestern Uganda. This will be achieved by evaluating (1) a novel DNA-based diagnostic assay for CNS infections, (2) a commercially available multiplex PCR-based meningitis/encephalitis (ME) panel for clinical use in a facility-limited laboratory setting, (3) proteomics profiling of blood from children with severe CNS infection as compared to outpatient controls with fever yet not severely ill, and (4) Myxovirus resistance protein A (MxA) as a biomarker in blood for viral CNS infection. Further changes in the etiology of childhood CNS infections after the introduction of the pneumococcal conjugate vaccine against Streptococcus pneumoniae will be investigated. In addition, the carriage and invasive rate of Neisseria meningitidis will be recorded and serotyped, and the expression of its major virulence factor (polysaccharide capsule) will be investigated. METHODS The PI-POC trial is a prospective observational study of children including newborns up to 12 years of age with clinical features of CNS infection, and age-/sex-matched outpatient controls with fever yet not severely ill. Participants are recruited at 2 Pediatric clinics in Mbarara, Uganda. Cerebrospinal fluid (for cases only), blood, and nasopharyngeal (NP) swabs (for both cases and controls) sampled at both clinics are analyzed at the Epicentre Research Laboratory through gold-standard methods for CNS infection diagnosis (microscopy, biochemistry, and culture) and a commercially available ME panel for multiplex PCR analyses of the cerebrospinal fluid. An additional blood sample from cases is collected on day 3 after admission. After initial clinical analyses in Mbarara, samples will be transported to Stockholm, Sweden for (1) validation analyses of a novel nucleic acid–based POC test, (2) biomarker research, and (3) serotyping and molecular characterization of S. pneumoniae and N. meningitidis. RESULTS A pilot study was performed from January to April 2019. The PI-POC trial enrollment of patients begun in April 2019 and will continue until September 2020, to include up to 300 cases and controls. Preliminary results from the PI-POC study are expected by the end of 2020. CONCLUSIONS The findings from the PI-POC study can potentially facilitate rapid etiological diagnosis of CNS infections in low-resource settings and allow for novel methods for determination of the severity of CNS infection in such environment. CLINICALTRIAL ClinicalTrials.gov NCT03900091; https://clinicaltrials.gov/ct2/show/NCT03900091 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/21430

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