Mortality after hospital discharge among children younger than 5 years admitted with suspected sepsis in Uganda: a prospective, multisite, observational cohort study

Wiens, Matthew O.; Bone, Jeffrey N; Kumbakumba, Elias; Businge, Stephen; Tagoola, Abner; Sherine, Sheila Oyella; Byaruhanga, Emmanuel; Ssemwanga, Edward; Barigye, Celestine; Nsungwa, Jesca; Olaro, Charles; Ansermino, J. Mark; Kissoon, Niranjan; Singer, Joel; Larson, Charles P.; Lavoie, Pascal M.; Dunsmuir, Dustin; Moschovis, Peter P.; Novakowski, Stefanie K.; Komugisha, Clare; Tayebwa, Mellon; Mwesigwa, Douglas; Zhang, Cherri; Knappett, Martina; West, Nicholas; Nguyen, Vuong; Kenya-Mugisha, Nathan; Kabakyenga, Jerome

doi:10.1016/s2352-4642(23)00052-4

Cited by 19 publications

(23 citation statements)

References 30 publications

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“…These cohorts’ clinical and demographic details have been previously described ( Table 1 ) [ 6 , 13 ]. The mean ±standard deviation [SD] age was 2.1 ±1.8 months with 1,884 (56.3%) male in the 0-6-month group, and 21.7 ±13.7 months with 2,670 (55.3%) male in the 6-60-month group.…”

Section: Resultsmentioning

confidence: 99%

“…The first cohort (enrolment 13-Mar-2012 to 13-Jan-2014) was used previously to report a predictive model for post-discharge mortality in 6-60-month-olds [ 13 ]. The second and third cohorts were the primary enrolment for the present analysis, and were defined by age range: 0-6-month-olds (enrolment 11-Jan-2018 to 30-Mar-2020) and 6-60-month-olds (enrolment 13-Jul-2017 to 02-Jul-2019); these data have been previously reported [ 6 ]. The fourth cohort enrolled only 0-6-month-olds (enrolment 31-Mar-2020 to 05-Aug-2021) in order to understand how the early COVID-19 period impacted post-discharge outcomes.…”

Section: Methodsmentioning

confidence: 99%

“…Data collection tools are available through the Smart Discharges Dataverse [ 17 ]. Data collection procedures were previously described (also S1 Text ) [ 6 , 13 ]. Briefly, trained study nurses collected clinical, social, and demographic data from consented participants at hospital admission; largely overlapping between the two age groups, some variables were specific to 0-6-month-olds.…”

Section: Methodsmentioning

confidence: 99%

“…The primary study sample size was determined to accomplish three aims: to explore the epidemiology of post-discharge mortality, as previously reported [ 6 ]; to develop prediction models; and as a control period for a later interventional phase. The estimated sample size was determined as 2,117 and 1,551 for the 0-6-month and 6-60-month cohorts, respectively ( S2 Text ).…”

Section: Methodsmentioning

confidence: 99%

“…Robust epidemiological data for pediatric post-discharge mortality in the context of sepsis and severe infection have been limited [ 4 ]. Growing evidence points to a significant burden of post-discharge mortality, which accounts for as many deaths as the acute hospital phase of illness [ 5 , 6 ]. While comorbid conditions such as malnutrition and anemia have been linked to risk, other factors such as illness severity (at admission and discharge), prior hospitalizations, and underlying social vulnerability, are also independently associated with poor post-discharge outcomes [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

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Prediction models for post-discharge mortality among under-five children with suspected sepsis in Uganda: A multicohort analysis

Wiens,

Nguyen,

Bone

et al. 2024

PLOS Glob Public Health

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In many low-income countries, over five percent of hospitalized children die following hospital discharge. The lack of available tools to identify those at risk of post-discharge mortality has limited the ability to make progress towards improving outcomes. We aimed to develop algorithms designed to predict post-discharge mortality among children admitted with suspected sepsis. Four prospective cohort studies of children in two age groups (0–6 and 6–60 months) were conducted between 2012–2021 in six Ugandan hospitals. Prediction models were derived for six-months post-discharge mortality, based on candidate predictors collected at admission, each with a maximum of eight variables, and internally validated using 10-fold cross-validation. 8,810 children were enrolled: 470 (5.3%) died in hospital; 257 (7.7%) and 233 (4.8%) post-discharge deaths occurred in the 0-6-month and 6-60-month age groups, respectively. The primary models had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95%CI 0.74–0.80) for 0-6-month-olds and 0.75 (95%CI 0.72–0.79) for 6-60-month-olds; mean AUROCs among the 10 cross-validation folds were 0.75 and 0.73, respectively. Calibration across risk strata was good: Brier scores were 0.07 and 0.04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included: illness duration, jaundice-age interaction, and a bulging fontanelle among 0-6-month-olds; and prior admissions, coma score, temperature, age-respiratory rate interaction, and HIV status among 6-60-month-olds. Simple prediction models at admission with suspected sepsis can identify children at risk of post-discharge mortality. Further external validation is recommended for different contexts. Models can be digitally integrated into existing processes to improve peri-discharge care as children transition from the hospital to the community.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%