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1.
Clin Infect Dis ; 78(1): 90-93, 2024 01 25.
Article in English | MEDLINE | ID: mdl-37585653

ABSTRACT

In a cross-sectional analysis of 354 Ugandan children (age 12-48 months) infected with Schistosoma mansoni, we assessed relationships between infection intensity and nutritional morbidities. Higher intensity was associated with an increased risk for anemia (RR = 1.05, 95% confidence interval [CI] 1.01-1.10) yet not associated with risk for underweight, stunting, or wasting.


Subject(s)
Anemia , Schistosomiasis mansoni , Child , Animals , Humans , Child, Preschool , Infant , Schistosomiasis mansoni/complications , Schistosomiasis mansoni/epidemiology , Uganda/epidemiology , Nutritional Status , Cross-Sectional Studies , Prevalence , Schistosoma mansoni , Anemia/epidemiology , Anemia/etiology
2.
PLOS Glob Public Health ; 3(12): e0002022, 2023.
Article in English | MEDLINE | ID: mdl-38064420

ABSTRACT

Kawempe National Referral Hospital (KNRH) is a tertiary facility with over 21,000 pregnant or postpartum women admitted annually. The hospital, located in Kampala, Uganda, uses an Electronic Medical Records (EMR) system to capture patient data. Used since 2017, this readily available electronic health record (EHR) has the benefit of informing real-time clinical care, especially during pandemics such as COVID-19. We investigated the use of EHR to assess risk factors for adverse pregnancy and infant outcomes that can be incorporated into a data visualization dashboard for real time decision making during pandemics. This study analysed data from the UgandaEMR collected at pre-, during- and post-lockdown timepoints of the COVID-19 pandemic to determine its use in monitoring risk factors for adverse pregnancy and neonatal outcomes. Logistic regression models were used to identify the risk factors for adverse pregnancy and maternal outcomes including prematurity, obstetric complications, still births and neonatal deaths. Pearson chi-square test was used for pair-wise comparison of the outcomes at the various stages of the pandemic. Data analysis was performed in R, within the International COVID-19 Data Alliance (ICODA) workbench. A visualisation dashboard was developed based on the risk factors, to support decision making and improved healthcare delivery. Comparison of pre-and post-lockdown variables showed an increased risk of pre-term birth (adjusted Odds Ratio (aOR = 1.67, 95% confidence interval (CI) 1.38-2.01)); obstetric complications (aOR = 2.77, 95% CI: 2.53-3.03); immediate neonatal death (aOR = 3.89, 95% CI 2.65-5.72) and Caesarean section (aOR = 1.22, 95% CI 1.11-1.34). The significant risk factors for adverse outcomes were younger maternal age and gestational age <32weeks at labour. This study demonstrates the feasibility of using EHR to identify and monitor at-risk subpopulation groups accessing health services in real time. This information is critical for the development of timely and appropriate interventions in outbreaks and pandemic situations.

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