title: A self-report comorbidity questionnaire for haemodialysis patients.
abstract: BACKGROUND
  Patients with end-stage renal disease (ESRD) have multiple comorbid conditions. Obtaining comorbidity data from medical records is cumbersome. A self-report comorbidity questionnaire is a useful alternative. Our aim in this study was to examine the predictive value of a self-report comorbidity questionnaire in terms of survival in ESRD patients.
  
  
  METHODS
  We studied a prospective cross-sectional cohort of 282 haemodialysis (HD) patients in a single centre. Participants were administered the self-report questionnaire during an HD session. Information on their comorbidities was subsequently obtained from an examination of the patient's medical records. Levels of agreement between parameters derived from the questionnaire, and from the medical records, were examined. Participants were followed-up for 18 months to collect survival data. The influence on survival of comorbidity scores derived from the self-report data (the Composite Self-report Comorbidity Score [CSCS]) and from medical records data--the Charlson Comorbidity Index [CCI] were compared.
  
  
  RESULTS
  The level of agreement between the self-report items and those obtained from medical records was almost perfect with respect the presence of diabetes (Kappa score κ 0.97), substantial for heart disease and cancer (κ 0.62 and κ 0.72 respectively), moderate for liver disease (κ 0.51), only fair for lung disease, arthritis, cerebrovascular disease, and depression (κ 0.34, 0.35, 0.34 and 0.29 respectively). The CSCS was strongly predictive of survival in regression models (Nagelkerke R(2) value 0.202), with a predictive power similar to that of the CCI (Nagelkerke R(2) value 0.211). The influences of these two parameters were additive in the models--suggesting that these parameters make different contributions to the assessment of comorbidity.
  
  
  CONCLUSIONS
  This self-report comorbidity questionnaire is a viable tool to collect comorbidity data and may have a role in the prediction of short-term survival in patients with end-stage renal disease on haemodialysis. Further work is required in this setting to refine the tool and define its role.
authors.affiliation: Renal Unit Lister Hospital, Stevenage SG1 4AB, UK. sridharansivakumar@gmail.com.
authors.forename: Sivakumar
authors.initials: S
authors.lastname: Sridharan
authors.forename: Jocelyn
authors.initials: J
authors.lastname: Berdeprado
authors.forename: Enric
authors.initials: E
authors.lastname: Vilar
authors.forename: Justin
authors.initials: J
authors.lastname: Roberts
authors.forename: Ken
authors.initials: K
authors.lastname: Farrington
mesh_terms: D000368:Aged; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology / Q000401:mortality; D015331:Cohort Studies; D015897:Comorbidity; D003430:Cross-Sectional Studies; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000453:epidemiology / Q000401:mortality*; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000175:diagnosis / Q000453:epidemiology / Q000401:mortality; D011446:Prospective Studies; D006435:Renal Dialysis / Q000401:mortality* / Q000639:trends; D057566:Self Report / Q000592:standards*; D011795:Surveys and Questionnaires / Q000592:standards*; D015996:Survival Rate / Q000639:trends