# Validation of intensive care unit predictive scoring systems in West Africans

**Authors:** Charles Frederick Hayfron-Benjamin, Theresa Ruby Quartey-Papafio, Akua Kissi-Prah, Delphine Delali Grant, Tracy Amo-Nyarko, Anastasia Naa Koshie Bruce, Divine Agbenyegah Kwami, Andrew Kwabena-Adade

PMC · DOI: 10.1016/j.mex.2026.103817 · 2026-02-09

## TL;DR

This study validates ICU scoring systems in West African populations to improve mortality and length-of-stay predictions.

## Contribution

The study is the first to validate ICU predictive scoring systems in a West African population.

## Key findings

- Existing ICU scoring systems will be tested for accuracy in predicting mortality and length of stay in Ghanaians.
- Supervised machine learning will be used to identify predictors of ICU mortality.

## Abstract

Intensive care unit(ICU) predictive scoring systems (PSS) are valuable in predicting outcomes in the ICU. However, they have not been validated in many populations, including West Africans, limiting their utility in these populations. The study population comprises Ghanaians managed in the ICUs of two major tertiary/quaternary hospitals in Ghana from 2017 to 2026. The Acute Physiologic and Chronic Health Evaluation-IV(APACHE-IV), Simplified Acute Physiologic Score-III (SAPS-III), Mortality Prediction Model-III(MPM0-III), Sequential (Sepsis-related) Organ Failure Assessment(SOFA)/quick SOFA(qSOFA), and National Early Warning Score-2(NEWS-2) scores will be calculated. For APACHE-IV, SAPS-III, and MPM0-III, the primary outcome measures are mortality and/or length of stay(LOS). The APACHE IV, SAPS-III, and MPM0-III scores and their corresponding predicted mortality ratios will be calculated. The overall observed and predicted ICU mortality rates will be assessed. Validation will be tested by assessing calibration and discrimination. For SOFA/qSOFA and NEWS-2, the associations of the mean score, highest score, and change in score with mortality will be assessed. Conventional statistical tools and supervised machine learning algorithms will be used to identify predictors of ICU mortality.•This study aims to validate the performance of existing ICU PSS in predicting ICU mortality and LOS among West Africans, and to identify their predictors.

This study aims to validate the performance of existing ICU PSS in predicting ICU mortality and LOS among West Africans, and to identify their predictors.

Image, graphical abstract

## Linked entities

- **Species:** Homo sapiens (taxon 9606)

## Full-text entities

- **Genes:** SKAP2 (src kinase associated phosphoprotein 2) [NCBI Gene 8935] {aka PRAP, RA70, SAPS, SCAP2, SKAP-HOM, SKAP55R}, PSS (Potocki-Shaffer syndrome) [NCBI Gene 780904], CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}
- **Diseases:** drug overdose (MESH:D062787), Sepsis (MESH:D018805), illness (MESH:D002908), post-COVID-19 (MESH:D000094024), abdominal obesity (MESH:D056128), Chronic Health (MESH:D000071069), neuromuscular disease (MESH:D009468), restrictive diseases (MESH:D002313), perforation (MESH:D057112), diabetic ketoacidosis (MESH:D016883), hepatic failure (MESH:D017093), hyperosmolar diabetic coma (MESH:D003926), embolism (MESH:D004617), aspiration pneumonia (MESH:D011015), acid-base disorders (MESH:D000137), infection (MESH:D007239), parasitic/fungal pneumonia (MESH:D008172), coagulopathy (MESH:D001778), thrombocytopenia (MESH:D013921), COVID-19 (MESH:D000086382), MPM0-III (MESH:C537189), ICU mortality (MESH:D003643), neutropenia (MESH:D009503), intracerebral hemorrhage (MESH:D002543), subarachnoid hemorrhage (MESH:D013345), albuminuria (MESH:D000419), burns (MESH:D002056), airway obstruction (MESH:D000402), seizure (MESH:D012640), APS (MESH:D000208), COPD (MESH:D029424), bacterial pneumonia (MESH:D018410), stroke (MESH:D020521), respiratory arrest (MESH:D012131), AIDS (MESH:D000163), pleural effusion (MESH:D010996), Organ Failure (MESH:D009102), bleeding (MESH:D006470), vascular insufficiency (MESH:D065666), edema (MESH:D004487), asthma (MESH:D001249), pancreatitis (MESH:D010195), electrolyte disorders (MESH:D014883), -failure (MESH:D051437), aneurysm (MESH:D000783), Physiology (MESH:D012735), pancytopenia (MESH:D010198), cancer (MESH:D009369), pain (MESH:D010146), intra/retroperitoneal bleeding (MESH:D012186), trauma (MESH:D014947), inflammatory (MESH:D007249), hematoma (MESH:D006406), variceal bleeding (MESH:D014648), Critically ill (MESH:D016638)
- **Chemicals:** creatinine (MESH:D003404), urea (MESH:D014508), agents (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12925423/full.md

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Source: https://tomesphere.com/paper/PMC12925423