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Thromb Haemost 2022; 122(07): 1231-1238
DOI: 10.1055/a-1698-6506
Stroke, Systemic or Venous Thromboembolism

Derivation and Validation of a Risk Factor Model to Identify Medical Inpatients at Risk for Venous Thromboembolism

Michael B. Rothberg
1   Center for Value-Based Care Research, Cleveland Clinic, Cleveland, Ohio, United States
2   Department of Internal Medicine, Cleveland Clinic, Cleveland, Ohio, United States
,
Aaron C. Hamilton
3   Department of Hospital Medicine, Cleveland Clinic, Cleveland, Ohio, United States
,
M. Todd Greene
4   The Michigan Hospital Medicine Safety Consortium Data Coordinating Center, Ann Arbor, Michigan, United States
5   Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States
6   Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States
,
Jacqueline Fox
1   Center for Value-Based Care Research, Cleveland Clinic, Cleveland, Ohio, United States
,
Oleg Lisheba
7   Enterprise Analytics eResearch Department, Cleveland Clinic, Cleveland, Ohio, United States
,
Alex Milinovich
8   Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, United States
,
Thomas N. Gautier IV
9   Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, United States
,
Priscilla Kim
9   Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, United States
,
Scott Kaatz
4   The Michigan Hospital Medicine Safety Consortium Data Coordinating Center, Ann Arbor, Michigan, United States
10   Division of Hospital Medicine, Henry Ford Hospital, Detroit, Michigan, United States
,
Bo Hu
8   Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, United States
› Author Affiliations Funding This study was sponsored by U.S. Department of Health and Human Services, Agency for Healthcare Research and Quality (R01HS022883). The sponsor had no role in the design, conduct, interpretation, writing, or publication of the study.
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Abstract

Background Venous thromboembolism (VTE) prophylaxis is recommended for hospitalized medical patients at high risk for VTE. Multiple risk assessment models exist, but few have been compared in large datasets.

Methods We constructed a derivation cohort using 6 years of data from 12 hospitals to identify risk factors associated with developing VTE within 14 days of admission. VTE was identified using a complex algorithm combining administrative codes and clinical data. We developed a multivariable prediction model and applied it to three validation cohorts: a temporal cohort, including two additional years, a cross-validation, in which we refit the model excluding one hospital each time, applying the refitted model to the holdout hospital, and an external cohort. Performance was evaluated using the C-statistic.

Results The derivation cohort included 155,026 patients with a 14-day VTE rate of 0.68%. The final multivariable model contained 13 patient risk factors. The model had an optimism corrected C-statistic of 0.79 and good calibration. The temporal validation cohort included 53,210 patients, with a VTE rate of 0.64%; the external cohort had 23,413 patients and a rate of 0.49%. Based on the C-statistic, the Cleveland Clinic Model (CCM) outperformed both the Padua (0.76 vs. 0.72, p = 0.002) and IMPROVE (0.68, p < 0.001) models in the temporal cohort. C-statistics for the CCM at individual hospitals ranged from 0.68 to 0.78. In the external cohort, the CCM C-statistic was similar to Padua (0.70 vs. 0.66, p = 0.17) and outperformed IMPROVE (0.59, p < 0.001).

Conclusion A new VTE risk assessment model outperformed recommended models.

Keywords

VTE - risk models - validation

Note

This study was presented at the Society of General Internal Medicine Annual Meeting in Denver, Colorado, United States, April 13, 2018.


Supplementary Material



Publication History

Received: 11 May 2021

Accepted: 13 November 2021

Accepted Manuscript online:
16 November 2021

Article published online:
29 December 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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