title: Predictors of poor outcome in chronic dialysis patients: The Netherlands Cooperative Study on the Adequacy of Dialysis. The NECOSAD Study Group.
abstract: In a prospective cohort study, we constructed a composite index of poor outcome that incorporates survival, morbidity, and quality of life (QL). We identified baseline patient and treatment characteristics that predicted poor outcome 1 year after the start of chronic dialysis. Outcome was classified as poor if a patient had died or if at least two of the following criteria were present: (1) 30 days or greater of hospitalization per year, (2) serum albumin level of 30 g/L or less or a malnutrition index score of 11 or greater, (3) a 36-item Medical Outcomes Study (MOS)-Short Form Health Survey Questionnaire (SF-36) physical summary QL score of 2 or more SDs less than the general population mean score, and (4) an SF-36 mental summary QL score of 2 or more SDs less than the general population mean score. Multivariate logistic regression analysis was used to identify independent predictors of poor outcome. Of 250 included patients, 189 were assessable with respect to poor outcome. Of these patients, 47 (25%) were classified as poor. A baseline presence of comorbidity, serum albumin level of 30 g/L or less, physical or mental QL score 2 or more SDs less than the general population mean score, and, to a lesser extent, residual glomerular filtration rate of 2.5 mL/min/1.73 m(2) or less were independently associated with a greater risk for poor outcome. A post hoc analysis indicated a mean arterial blood pressure greater than 107 mm Hg was predictive of poor outcome in patients undergoing peritoneal dialysis. In conclusion, our prognostic model provides a useful tool to identify chronic dialysis patients at risk for poor health status. Strategies aimed at preserving residual renal function, controlling blood pressure, monitoring QL, and consequently giving psychosocial support may reduce the risk for poor outcome.
authors.affiliation: Department of Clinical Epidemiology, Academic Medical Center, Amsterdam, The Netherlands. m.merkus@amc.uva.nl
authors.forename: M P
authors.initials: MP
authors.lastname: Merkus
authors.forename: K J
authors.initials: KJ
authors.lastname: Jager
authors.forename: F W
authors.initials: FW
authors.lastname: Dekker
authors.forename: R J
authors.initials: RJ
authors.lastname: de Haan
authors.forename: E W
authors.initials: EW
authors.lastname: Boeschoten
authors.forename: R T
authors.initials: RT
authors.lastname: Krediet
mesh_terms: D000328:Adult; D000368:Aged; D002423:Cause of Death; D015331:Cohort Studies; D015897:Comorbidity; D005260:Female; D006801:Humans; D006977:Hypertension, Renal / Q000401:mortality / Q000628:therapy; D007676:Kidney Failure, Chronic / Q000401:mortality / Q000628:therapy*; D007677:Kidney Function Tests; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009426:Netherlands; D010043:Outcome and Process Assessment, Health Care; D010359:Patient Readmission / Q000706:statistics & numerical data; D010530:Peritoneal Dialysis / Q000401:mortality; D011446:Prospective Studies; D011788:Quality of Life; D012372:ROC Curve; D006435:Renal Dialysis / Q000401:mortality; D018570:Risk Assessment; D015996:Survival Rate