TY - JOUR
T1 - Validation of Risk Assessment Models of Venous Thromboembolism in Hospitalized Medical Patients
AU - Greene, M. Todd
AU - Spyropoulos, Alex C.
AU - Chopra, Vineet
AU - Grant, Paul J.
AU - Kaatz, Scott
AU - Bernstein, Steven J.
AU - Flanders, Scott A.
N1 - Publisher Copyright:
© 2016
PY - 2016/9/1
Y1 - 2016/9/1
N2 - Background Patients hospitalized for acute medical illness are at increased risk for venous thromboembolism. Although risk assessment is recommended and several at-admission risk assessment models have been developed, these have not been adequately derived or externally validated. Therefore, an optimal approach to evaluate venous thromboembolism risk in medical patients is not known. Methods We conducted an external validation study of existing venous thromboembolism risk assessment models using data collected on 63,548 hospitalized medical patients as part of the Michigan Hospital Medicine Safety (HMS) Consortium. For each patient, cumulative venous thromboembolism risk scores and risk categories were calculated. Cox regression models were used to quantify the association between venous thromboembolism events and assigned risk categories. Model discrimination was assessed using Harrell's C-index. Results Venous thromboembolism incidence in hospitalized medical patients is low (1%). Although existing risk assessment models demonstrate good calibration (hazard ratios for “at-risk” range 2.97-3.59), model discrimination is generally poor for all risk assessment models (C-index range 0.58-0.64). Conclusions The performance of several existing risk assessment models for predicting venous thromboembolism among acutely ill, hospitalized medical patients at admission is limited. Given the low venous thromboembolism incidence in this nonsurgical patient population, careful consideration of how best to utilize existing venous thromboembolism risk assessment models is necessary, and further development and validation of novel venous thromboembolism risk assessment models for this patient population may be warranted.
AB - Background Patients hospitalized for acute medical illness are at increased risk for venous thromboembolism. Although risk assessment is recommended and several at-admission risk assessment models have been developed, these have not been adequately derived or externally validated. Therefore, an optimal approach to evaluate venous thromboembolism risk in medical patients is not known. Methods We conducted an external validation study of existing venous thromboembolism risk assessment models using data collected on 63,548 hospitalized medical patients as part of the Michigan Hospital Medicine Safety (HMS) Consortium. For each patient, cumulative venous thromboembolism risk scores and risk categories were calculated. Cox regression models were used to quantify the association between venous thromboembolism events and assigned risk categories. Model discrimination was assessed using Harrell's C-index. Results Venous thromboembolism incidence in hospitalized medical patients is low (1%). Although existing risk assessment models demonstrate good calibration (hazard ratios for “at-risk” range 2.97-3.59), model discrimination is generally poor for all risk assessment models (C-index range 0.58-0.64). Conclusions The performance of several existing risk assessment models for predicting venous thromboembolism among acutely ill, hospitalized medical patients at admission is limited. Given the low venous thromboembolism incidence in this nonsurgical patient population, careful consideration of how best to utilize existing venous thromboembolism risk assessment models is necessary, and further development and validation of novel venous thromboembolism risk assessment models for this patient population may be warranted.
KW - Venous thromboembolism
UR - http://www.scopus.com/inward/record.url?scp=84971658578&partnerID=8YFLogxK
U2 - 10.1016/j.amjmed.2016.03.031
DO - 10.1016/j.amjmed.2016.03.031
M3 - Article
C2 - 27107925
AN - SCOPUS:84971658578
SN - 0002-9343
VL - 129
SP - 1001.e9-1001.e18
JO - American Journal of Medicine
JF - American Journal of Medicine
IS - 9
ER -