"Weekend effect" on stroke mortality revisited

Cheng Yang Hsieh, Huey Juan Lin, Chih Hung Chen, Chung Yi Li, Meng Jun Chiu, Sheng Feng Sung

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15 Citations (Scopus)


Previous studies have yielded inconsistent results on whether weekend admission is associated with increased mortality after stroke, partly because of differences in case mix. Claims-based studies generally lack sufficient information on disease severity and, thus, suffer from inadequate case-mix adjustment. In this study, we examined the effect of weekend admission on 30-day mortality in patients with ischemic stroke by using a claims-based stroke severity index. This was an observational study using a representative sample of the National Health Insurance claims data linked to the National Death Registry. We identified patients hospitalized for ischemic stroke, and examined the effect of weekend admission on 30-day mortality with vs without adjustment for stroke severity by using multilevel logistic regression analysis adjusting for patient-, physician-, and hospital-related factors. We analyzed 46,007 ischemic stroke admissions, in which weekend admissions accounted for 23.0%. Patients admitted on weekends had significantly higher 30-day mortality (4.9% vs 4.0%, P<0.001) and stroke severity index (7.8 vs 7.4, P<0.001) than those admitted on weekdays. In multivariate analysis without adjustment for stroke severity, weekend admission was associated with increased 30-day mortality (odds ratio (OR), 1.20; 95% confidence interval [CI], 1.08-1.34). This association became null after adjustment for stroke severity (OR, 1.07; 95% CI, 0.95-1.20). The "weekend effect" on stroke mortality might be attributed to higher stroke severity in weekend patients. While claims data are useful for examining stroke outcomes, adequate adjustment for stroke severity is warranted.

Original languageEnglish
Article numbere4046
JournalMedicine (United States)
Issue number25
Publication statusPublished - 2016 Jun 1

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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