Zhang C
Wiens MO
Dunsmuir D
Pillay Y
Huxford C
Kimutai D
Tenywa E
Ouma M
Kigo J
Kamau S
Chege M
Kenya-Mugisha N
Mwaka S
Dumont GA
Kissoon N
Akech S
Ansermino JM
Pediatric Sepsis CoLab
PLOS Digit Health. 2024;3e0000311
Infectious diseases in neonates account for half of the under-five mortality in low- and middle-income countries. Data-driven algorithms such as clinical prediction models can be used to efficiently detect critically ill children in order to optimize care and reduce mortality. Thus far, only a handful of prediction models have been externally validated and are limited to neonatal in-hospital mortality. The aim of this study is to externally validate a previously derived clinical prediction model (Smart Triage) using a combined prospective baseline cohort from Uganda and Kenya with a composite endpoint of hospital admission, mortality, and readmission. We evaluated model discrimination using area under the receiver-operator curve (AUROC) and visualized calibration plots with age subsets (< 30 days,
