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DOI: 10.1160/TH15-02-0108
All-cause mortality and use of antithrombotics within 90 days of discharge in acutely ill medical patients
Publication History
Received:
10 February 2015
Accepted after major revision:
19 May 2015
Publication Date:
29 November 2017 (online)
Summary
Conflicting evidence exists regarding predictors of and antithrombotic benefit on mortality in hospitalised acutely-ill medical patients. We compared mortality risk within 90 days post-discharge among medically ill patients who did and did not receive antithrombotics. This retrospective claims analysis included patients40 years with nonsurgical hospitalisation2 days between 2005 and 2009 using the HealthCore Integrated Research Database. Antithrombotic use (i.e. anticoagulants and antiplatelets) post-discharge was captured from pharmacy claims. All-cause mortality was determined from Social Security Death Index; cause of death was identified from National Death Index database. Kaplan-Meier survival curves were generated and hazard ratios (HR) for mortality risk were estimated using Cox proportional hazards models. Patients prescribed anticoagulants or antiplatelets post-discharge had lower risk of short-term mortality. For the anticoagulant model, the most significant predictors of mortality were malignant/benign neoplasms (hazard ratio [HR] 1.6, 95 % confidence interval [CI] 1.5–1.7), liver disease (HR 1.6, 95 % CI 1.5–1.7), anticoagulant omission (HR 1.6, 95 % CI 1.4–1.8), gastrointestinal or respiratory tract intubations (HR 1.5, 95 % CI 1.3–1.7), and blood dyscrasias (HR 1.4, 95 % CI 1.4–1.5). For the antiplatelet model, the most significant predictors of mortality were antiplatelet omission (HR 3.7, 95 % CI 3.3–4.1), liver disease (HR 1.6, 95 % CI 1.4–1.7), malignant/benign neoplasms (HR 1.6, 95 % CI 1.5–1.6), gastrointestinal or respiratory tract intubations (HR 1.5, 95 % CI 1.3–1.7), and blood dyscrasias (HR 1.4, 95 % CI 1.4–1.5). These mortality risk factors may guide future studies assessing potential benefits of antithrombotics in specific subsets of patients.
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