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

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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by Grand Challenges Canada (#TTS-1809-1939), Thrasher Research Fund (#13878), BC Childrens Hospital Foundation, and Mining4Life. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the institutional review boards of the Mbarara University of Science and Technology in Mbarara, Uganda (No. 15/10-16) and the University of British Columbia in Vancouver, Canada (H16-02679). This study was also approved by the Uganda National Council for Science and Technology (HS 2207). This manuscript adheres to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Study materials (including de-identified data, protocol, data collection tools and analysis code) are available upon reasonable request to the corresponding author or through the Pediatric Sepsis CoLab. The University of British Columbia Dataverse Collection: Pediatric Sepsis CoLab. Smart Discharges Dataverse. Borealis. 2022. https://borealisdata.ca/dataverse/smart_discharge