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Published on: September 22, 2020
A prognostic risk index for long-term mortality in patients with peripheral arterial disease
Harm H H Feringa1, Jeroen J Bax, Sanne Hoeks
1Erasmus Medical Center, Department of Anesthesiology, Dr Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
Background:
Prognostic information in peripheral arterial disease (PAD) may provide the basis for optimal management strategies at an early stage. This study aimed to develop a prognostic risk index for long-term mortality in patients with PAD.
Methods:
In a single-center observational cohort study, 2642 patients with an ankle-brachial index of 0.90 or lower were randomly divided into derivation (n = 1332) and validation (n = 1310) cohorts. Cox regression analysis with stepwise backward elimination identified predictors of 1-year, 5-year, and 10-year mortality in the derivation cohort. Weighted points were assigned to each predictor. Index discrimination was determined in both the derivation and validation cohorts.
Results:
During 10 years of follow-up, 42.2% and 40.4% of patients died in the derivation and validation cohorts, respectively. The risk index for 10-year mortality (+ points) included renal dysfunction (+12), heart failure (+7), ST-segment changes (+5), age greater than 65 years (+5), hypercholesterolemia (+5), ankle-brachial index lower than 0.60 (+4), Q-waves (+4), diabetes (+3), cerebrovascular disease (+3), and pulmonary disease (+3). Statins (-6), aspirin (-4), and beta-blockers (-4) were associated with reduced 10-year mortality. Patients were stratified into low (<0 points), low-intermediate (0-5 points), high-intermediate (6-9 points), and high (>9 points) risk categories, according to risk score. Ten-year mortality rates were 22.1%, 32.2%, 45.8%, and 70.4%, respectively (P < .001) and comparable to mortality in the validation cohort. C statistics demonstrated good discrimination in both the derivation (0.72) and validation cohorts (0.73).
Conclusions:
A prognostic risk index for long-term mortality stratified patients with PAD into different risk categories. This may be useful for risk stratification, patient counseling, and medical decision making.
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