Search

[This corrects the article DOI: 10.1371/journal.pone.0221750.].

BackgroundSeveral clinical trials reported that clopidogrel was superior to aspirin in secondary stroke prevention by reducing the risk of major adverse cardiovascular events (MACE). We aimed to compare the efficacy of clopidogrel with aspirin in reducing one-year risk of MACE based on real-world evidence from Taiwan Health Insurance Database.MethodsWe identified ischemic stroke patients between 2000 and 2012 who took aspirin or clopidogrel within 7 days of stroke onset for 1-year follow-up. The primary outcome was one-year MACE including recurrent stroke, acute myocardial infarction, and death. Propensity score matching and conditional Cox proportional hazards regression were conducted to control the confounding factors.ResultsFrom 9,089 ischemic stroke patients, we found 654 patients on aspirin and 465 patients on clopidogrel who met the selective inclusion criteria. After propensity score matching, 379 patients were selected from each group. The clopidogrel group had a 1.78-fold MACE risk compared with the aspirin group at one-year follow-up (95% CI = 1.41-2.26, pConclusionsAmong first-ever ischemic stroke patients, secondary stroke prevention using clopidogrel was associated with higher rates of MACE than aspirin. Aspirin might have better efficacy in secondary stroke prevention and was associated with lower risk of MACE. The real-world evidence raises the need to re-assess the current therapeutic options in secondary stroke prevention applying aspirin vs. clopidogrel.

To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in clinical practice. We apply a modern machine learning method, the support vector machine to establish a predicting model for the severity of OSA. The support vector machine was applied to build up a prediction model based on three anthropometric features (neck circumference, waist circumference, and body mass index) and age on the first database. The established model was then valided independently on the second database. The anthropometric features and age were combined to generate powerful predictors for OSA. Following the common practice, we predict if a subject has the apnea-hypopnea index greater then 15 or not as well as 30 or not. Dividing by genders and age, for the AHI threhosld 15 (respectively 30), the cross validation and testing accuracy for the prediction were 85.3% and 76.7% (respectively 83.7% and 75.5%) in young female, while the negative likelihood ratio for the AHI threhosld 15 (respectively 30) for the cross validation and testing were 0.2 and 0.32 (respectively 0.06 and 0.1) in young female. The more accurate results with lower negative likelihood ratio in the younger patients, especially the female subgroup, reflect the potential of the proposed model for the screening purpose and the importance of approaching by different genders and the effects of aging.