%0 Journal Article
%T An Immediate Mortality Prediction Score That is Robust to Missing Data
%A Tara M. Westover
%A Marta B. Fernandes
%A M. Brandon Westover
%A Sahar F. Zafar
%J Open Journal of Statistics
%P 73-80
%@ 2161-7198
%D 2025
%I Scientific Research Publishing
%R 10.4236/ojs.2025.151005
%X <b>Objective: </b>To develop an illness severity score that predicts short-term mortality, based on a small number of readily available measurements, and overcomes limitations of the SOFA score, for use in research involving large-scale electronic health records. <b>Design:</b> Retrospective analysis of electronic records for 37,739 adult inpatients. <b>Setting: </b>A single tertiary care hospital system from 2016-2022. <b>Patients:</b> 37,739 adult ICU patients. <b>Interventions:</b> IMPS was developed using logistic regression with the 6 SOFA components, age, sex and missingness indicators as predictors, and 10-day mortality as the outcome. This was compared with SOFA with median imputation. <b>Measurements and Main Results:</b> Discrimination was evaluated by AUROC, calibration by comparing predicted and observed mortality. IMPS showed excellent discrimination (AUROC 0.80) and calibration. It outperformed SOFA alone (AUROC 0.70) and with age/sex (0.74). <b>Conclusions:</b> By retaining continuous data, adding age, allowing for missingness, and optimizing weights based on empirical mortality association, IMPS achieved substantially better mortality prediction than the original SOFA.
%K Critical Care
%K Missing Data
%K Electronic Health Records
%K Illness Severity
%K Mortality
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=140770