Predicting ICU transfer for high-risk patients upon medical admission via the medical intensive care prediction score (MICAPS)

Predicting ICU transfer for high-risk patients upon medical admission via the medical intensive care prediction score (MICAPS)

Emergency departments, Intensive care, Critical care, Admission prediction.

Background Early identification of patients at risk for admission to the medical intensive care unit (MICU) at the time
of medical admission is crucial for optimizing resource utilization and improving patient outcomes. No standardized,
unified scoring system exists to predict MICU requirements for early medical admissions (EMA). This study aimed to
develop and validate a predictive scoring system, the Medical Intensive Care Admission Prediction Score (MICAPS), to
identify patients at high risk of transfer to the MICU based on demographic data, triage hemodynamics, and limited
presentation-day laboratory data.
Methods This retrospective cross-sectional study included 11,847 adult patients admitted to medical floors via the
emergency department (ED) at Hamad General Hospital, Qatar, between January 2019 and December 2019. Cerner®
was used to extract relevant data. Multivariate logistic regression identified significant predictors of MICU admission,
and regression coefficients were used to develop the MICAPS model. ROC curve analysis and bootstrapping methods
were employed to validate the model’s performance and accuracy.
Results Of 11,847 patients admitted to medical services, 909 (7.7%) were transferred to MICU. Significant predictors
included male gender (OR: 1.41, 95% CI: 1.17-1.70), age≤60 years (OR: 2.15, 95% CI: 1.72–2.68), abnormal respiratory
rate (OR: 2.35, 95% CI: 1.48–3.72), oxygen saturation<88% (OR: 1.95, 95% CI: 1.30–2.92), Glasgow Coma Scale<9 (OR:
6.54, 95% CI: 4.91–8.71), RRT activation (OR: 3.82, 95% CI: 3.19–4.56), and abnormal laboratory values such as WBC≥10
(OR: 1.29, 95% CI: 1.08–1.54) and lactate>1.7 mmol/L (OR: 1.96, 95% CI: 1.64–2.34). MICAPS demonstrated good
predictive power, with an area under the ROC curve of 0.809 (95% CI: 0.79–0.82), a sensitivity of 67.4%, a specificity of
81.3%, and a positive likelihood ratio of 3.60 at a score of ≥40.
Conclusion MICAPS is a simple-to-apply scoring system that enables the identification of patients early in their
hospitalization who may require ICU care later during the hospital stay. It can support early clinical decision-making
and optimize resource allocation in emergency departments, medical floors, and critical care settings. Further
multicenter prospective validation is needed to assess its generalizability in the real world.
Clinical trial number Not applicable.

Muhammad Zahid1,2,3*, Fateen Ata4

, Adeel Ahmad Khan5

, Prem Chandra6

, Rajvir Singh7
,

Abdelnaser Y. Awad Elzouki1,2,3, Dabia Hamad S. H. Al. Mohanadi1,2,3 and Ahmed Ali A. A. Al-Mohammed1,2,3

https://doi.org/10.1186/s12873-025-01448-w

2026

PERI IRAWAN

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