External validation of the Intermountain Risk Scores for postdischarge thrombosis and bleeding in an independent population.

Authors

Mansour Gergi, Katherine S Wilkinson, Nicholas Roetker, Karlyn Martin, Allen B Repp, Neil A Zakai

Published in

Research and practice in thrombosis and haemostasis. Volume 10. Issue 6. Pages 106934. Epub Sep 17, 2026.

Abstract

Extended thromboprophylaxis after medical hospitalization has not consistently shown benefit, largely due to increased bleeding events. Accurate prediction of postdischarge (PD) venous thromboembolism (VTE) and bleeding risk is therefore essential. The Intermountain Risk Scores (IMRSs) were developed to predict 90-day risks of these outcomes following discharge.
To assess the predictive performance and external validity of the IMRSs in an independent cohort.
We retrospectively identified adults discharged alive from medical hospitalizations at an academic medical center between 2010 and 2019. PD VTE and bleeding events were identified using validated computable phenotypes. IMRSs were calculated using data at discharge, with missing data addressed via multiple imputation. We determined the observed risks of VTE and bleeding in our cohort for low- and high-risk patients and compared these with the corresponding risks reported in the original cohort and evaluated model discrimination by estimating the time-dependent area under the receiver operating characteristic curve.
Among 14,556 discharges, 108 PD VTE and 373 PD bleeding events occurred within 90 days. The observed risk for high-risk and low-risk categories was 0.9% and 0.5% for VTE (hazard ratio 1.51; 95% CI, 0.88-2.59) and 4.2% and 1.8% for bleeding (hazard ratio 2.51; 95% CI, 2.04-3.08), respectively. Discrimination was poor for both outcomes (area under the receiver operating characteristic curve 0.55 for VTE; 0.60 for bleeding).
The IMRSs demonstrated limited discrimination in this external cohort. These findings suggest that the IMRSs may not be generalizable to all medical populations and highlight the need for more robust risk-stratification tools.

PMID:
42787660
Bibliographic data and abstract were imported from PubMed on 25 Sep 2026.

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