External validation of inpatient neonatal mortality prediction models in high-mortality settings.

ABSTRACT:

Background

Two neonatal mortality prediction models, the Neonatal Essential Treatment Score (NETS) which uses treatments prescribed at admission and the Score for Essential Neonatal Symptoms and Signs (SENSS) which uses basic clinical signs, were derived in high-mortality, low-resource settings to utilise data more likely to be available in these settings. In this study, we evaluate the predictive accuracy of two neonatal prediction models for all-cause in-hospital mortality.

Methods

We used retrospectively collected routine clinical data recorded by duty clinicians at admission from 16 Kenyan hospitals used to externally validate and update the SENSS and NETS models that were initially developed from the data from the largest Kenyan maternity hospital to predict in-hospital

SUBMITTER: Tuti T 

PROVIDER: S-EPMC9347100 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature