Hemodialysis patient-assessed functional health status predicts continued survival, hospitalization, and dialysis-attendance compliance

Am J Kidney Dis. 1997 Aug;30(2):204-12. doi: 10.1016/s0272-6386(97)90053-6.


We asked patients to assess their functional health status by completing the SF-36. Over 2 years, we studied 1,000 patients (average age, 58 years; 50% male; 25% white; 36% diabetic) in three outpatient, staff-assisted hemodialysis units. We used both the eight-scale scores and two-component summary scores to study the relationship between baseline functional health status and clinical outcomes. The physical component summary (PCS) score was as significant a predictor of mortality as was the normalized protein catabolic rate or the delivered Kt/V. Patients with a PCS score below the median for our patients (< 34) were twice as likely to die and 1.5 times more likely to be hospitalized as patients with PCS scores at or above the median score. Either a low PCS score or a low mental component summary (MCS) score correlated with the number of days of hospitalization. While the average dialysis patient has a relatively normal (47 v 50) MCS score and a low (37 v 50) PCS score compared with the normal population, patients who skipped more than two treatments per month tended to have a relatively higher PCS score (judged themselves physically healthier) and a relatively lower MCS score (judged themselves less mentally healthy) than patients who did not skip two or more treatments per month. The prevalence of depression as defined by an MCS score of < or = 42 was approximately 25%. The SF-36 provided a good screening tool for patients at high risk for death, hospitalization, poor attendance, and depression.

MeSH terms

  • Activities of Daily Living
  • Adolescent
  • Adult
  • Aged
  • Attitude to Health*
  • Depression / diagnosis
  • Female
  • Health Status
  • Hospitalization*
  • Humans
  • Male
  • Middle Aged
  • Patient Compliance*
  • Proportional Hazards Models
  • Prospective Studies
  • Quality of Life
  • Regression Analysis
  • Renal Dialysis* / mortality
  • Renal Dialysis* / psychology
  • Surveys and Questionnaires
  • Survival Analysis