title: Sleep quality predicts quality of life and mortality risk in haemodialysis patients: results from the Dialysis Outcomes and Practice Patterns Study (DOPPS).
abstract: BACKGROUND
  Poor sleep quality (SQ) affects many haemodialysis (HD) patients and could potentially predict their morbidity, mortality, quality of life (QOL) and patterns of medication use.
  
  
  METHODS
  Data on SQ were collected from 11,351 patients in 308 dialysis units in seven countries in the Dialysis Outcomes and Practice Patterns Study (DOPPS) between 1996 and 2001 through a patient self-reported SQ scale, ranging from 0 (worst) to 10 (best). A score of <6 reflected poor SQ. Sleep disturbance was also assessed by self-reported daytime sleepiness, feeling drained and nocturnal awakening. Logistic and multiple linear regression were used to assess predictors of SQ and associations with QOL. Cox regression examined associations with mortality. Analyses accounted for case-mix, facility clustering and country.
  
  
  RESULTS
  Nearly half (49%) of patients experienced poor SQ. Mean SQ scores varied by country, ranging from 4.9 in Germany to 6.5 in Japan. Patients with poor SQ were more likely to be prescribed antihistamines, antidepressants, anti-inflammatories, narcotics, gastrointestinal (GI) medications, anti-asthmatics or hypnotics. Physical exercise at least once a week (vs < once a week) was associated with lower odds of poor SQ (AOR = 0.55-0.85, P < 0.05). Poorer SQ was associated with significantly lower mental and physical component summary (MCS/PCS) scores (MCS scores 1.9-13.2 points lower and PCS scores 1.5-7.7 points lower when SQ scores were <10 vs 10). The RR of mortality was 16% higher for HD patients with poor SQ.
  
  
  CONCLUSIONS
  Poor SQ is common among HD patients in DOPPS countries and is independently associated with several QOL indices, medication use patterns and mortality. Assessment and management of SQ should be an important component of care.
authors.affiliation: Arbor Research Collaborative for Health, Ann Arbor, MI, USA.
authors.forename: Stacey J
authors.initials: SJ
authors.lastname: Elder
authors.forename: Ronald L
authors.initials: RL
authors.lastname: Pisoni
authors.forename: Tadao
authors.initials: T
authors.lastname: Akizawa
authors.forename: Rachel
authors.initials: R
authors.lastname: Fissell
authors.forename: Vittorio E
authors.initials: VE
authors.lastname: Andreucci
authors.forename: Shunichi
authors.initials: S
authors.lastname: Fukuhara
authors.forename: Kiyoshi
authors.initials: K
authors.lastname: Kurokawa
authors.forename: Hugh C
authors.initials: HC
authors.lastname: Rayner
authors.forename: Anna L
authors.initials: AL
authors.lastname: Furniss
authors.forename: Friedrich K
authors.initials: FK
authors.lastname: Port
authors.forename: Rajiv
authors.initials: R
authors.lastname: Saran
mesh_terms: D000368:Aged; D005060:Europe / Q000453:epidemiology; D005260:Female; D006306:Health Surveys; D006801:Humans; D007564:Japan / Q000453:epidemiology; D007674:Kidney Diseases / Q000503:physiopathology / Q000628:therapy; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D010818:Practice Patterns, Physicians'; D011237:Predictive Value of Tests; D011379:Prognosis; D011788:Quality of Life; D006435:Renal Dialysis / Q000401:mortality*; D012307:Risk Factors; D012893:Sleep Wake Disorders / Q000150:complications / Q000175:diagnosis / Q000503:physiopathology*; D014481:United States / Q000453:epidemiology