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Updated: Oct 21, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Development and internal validation of the HIV In-hospital Mortality Prediction (HIV-IMP) risk score
Abdullah E Laher1, Fathima Paruk2, Willem D F Venter3
1Department of Emergency Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
Background:
Despite advances in availability and access to antiretroviral therapy (ART), HIV still ranks as a major cause of global mortality. Hence, the aim of this study was to develop and internally validate a risk score capable of accurately predicting in-hospital mortality in HIV-positive patients requiring hospital admission.
Methods:
Consecutive HIV-positive patients presenting to the Charlotte Maxeke Johannesburg Academic Hospital adult emergency department between 7 July 2017 and 18 October 2018 were prospectively enrolled. Multivariate logistic regression was used to determine parameters for inclusion in the final risk score. Discrimination and calibration were assessed by means of the area under the receiver operating curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test, respectively. Internal validation was conducted using the regular bootstrap technique.
Results:
The overall in-hospital mortality rate was 13.6% (n = 166). Eight predictors were included in the final risk score: ART non-adherence or not yet on ART, Glasgow Coma Scale < 15, respiratory rate > 20 breaths/min, oxygen saturation < 90%, white cell count < 4 × 109 /L, creatinine > 120 μmol/L, lactate > 2 mmol/L and albumin < 35 g/L. After internal validation, the risk score maintained good discrimination [AUROC 0.83, 95% confidence interval (CI): 0.78-0.88] and calibration (Hosmer-Lemeshow χ2 = 2.26, p = 0.895).
Conclusion:
The HIV In-hospital Mortality Prediction (HIV-IMP) risk score has overall good discrimination and calibration and is relatively easy to use. Further studies should be aimed at externally validating the score in varying clinical settings.
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