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

Abstract Background In many low-income countries, more than five percent of hospitalized children die following hospital discharge. The identification of those at risk has limited progress to improve outcomes. We aimed to develop algorithms to predict post-discharge mortality among children admitted with suspected sepsis. Methods Four prospective cohort studies were conducted at six hospitals in Uganda between 2012 and 2021. Death occurring within six months of discharge was the primary outcome. Separate models were developed for children 0-6 months of age and for those 6-60 months of age, based on candidate predictors collected at admission. Within each age group, three models were derived, each with a maximum of eight variables based on variable importance. Deriving parsimonious models with different sets of predictors was prioritized to improve usability and support implementation in settings where some data elements are unavailable. All models were internally validated using 10-fold cross validation. Findings 8,810 children were prospectively enrolled, of whom 470 died in hospital and 161 (1·9%) were lost to follow-up; 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 were good with Brier scores of 0·07 and 0·04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included duration of illness, 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. Interpretation 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 integrated into existing processes to improve peri-discharge care as children transition from the hospital to the community. Funding Grand Challenges Canada (#TTS-1809-1939), Thrasher Research Fund (#13878), BC Children’s Hospital Foundation, and Mining4Life.