Circadian variation of death in hemodialysis patients.

BACKGROUND: There is a circadian variation of death in nondialysis populations, with more cardiovascular events occurring in the morning. Whether this holds true in hemodialysis patients was never investigated. STUDY DESIGN: Case series. SETTING & PARTICIPANTS: All prevalent (>3 months on hemodialysis therapy) and incident (<or=3 months on hemodialysis therapy) patients of a dialysis network followed up prospectively for 18 months. PREDICTORS: Patient characteristics and circumstances of death. OUTCOMES & MEASUREMENTS: Time of death. Data for time of death were collected within 72 hours of the event. The frequency of deaths occurring in the morning hours (4:01 am to 12:00 noon) was compared with that expected by chance alone. RESULTS: Time of death could be defined in 873 of 927 deaths (94.2%). In 459 prevalent hemodialysis patients, morning deaths occurred 24.8% more frequently than expected (P < 0.001). No similar excess was observed in the 414 incident hemodialysis patients (P = 0.9). In logistic regression, significant predictors of death occurring from 4:01 am to 12:00 noon in all subjects were being an outpatient (odds ratio [OR], 1.89; 95% confidence interval [CI], 1.24 to 2.88) and time since the end of the last dialysis treatment (postdialysis 49- to 72-hour period: OR, 1.73 [95% CI, 1.13 to 2.64] compared with 1 to 24 hours postdialysis). Considering prevalent hemodialysis patients only, being an outpatient (OR, 1.93; 95% CI, 1.17 to 3.18), postdialysis 25- to 48- and 49- to 72-hour periods (OR, 1.68; 95% CI, 1.05 to 2.68 and OR, 1.80; 95% CI, 1.03 to 3.12), diabetes (OR, 1.73; 95% CI, 1.14 to 2.63]), and beta-blocker use (OR, 1.62; 95% CI, 1.08 to 2.43) were directly related and the presence of medical symptoms during the last dialysis treatment (OR, 0.53; 95% CI, 0.34 to 0.83) was inversely related to the risk of morning death. LIMITATIONS: No information for causes of deaths was gathered. CONCLUSIONS: Prevalent hemodialysis patients have an excess of morning deaths, and its predictors suggest potential avenues for intervention studies.