26 research outputs found

    A self-report comorbidity questionnaire for haemodialysis patients

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    This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedBackground: 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 R2value 0.202), with a predictive power similar to that of the CCI (Nagelkerke R2value 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. Conclusion: 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.Peer reviewe

    Charlson index scores from administrative data and case-note review compared favourably in a renal disease cohort

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    Background: The Charlson index is a widely used measure of comorbidity. The objective was to compare Charlson index scores calculated using administrative data to those calculated using case-note review (CNR) in relation to all-cause mortality and initiation of renal replacement therapy (RRT) in the Grampian Laboratory Outcomes Mortality and Morbidity Study (GLOMMS-1) chronic kidney disease cohort. Methods: Modified Charlson index scores were calculated using both data sources in the GLOMMS-1 cohort. Agreement between scores was assessed using the weighted Kappa. The association with outcomes was assessed using Poisson regression, and the performance of each was compared using net reclassification improvement. Results: Of 3382 individuals, median age 78.5 years, 56% female, there was moderate agreement between scores derived from the two data sources (weighted kappa 0.41). Both scores were associated with mortality independent of a number of confounding factors. Administrative data Charlson scores were more strongly associated with death than CNR scores using net reclassification improvement. Neither score was associated with commencing RRT. Conclusion: Despite only moderate agreement, modified Charlson index scores from both data sources were associated with mortality. Neither was associated with commencing RRT. Administrative data compared favourably and may be superior to CNR when used in the Charlson index to predict mortality

    Glycemic Control and Cardiovascular Mortality in Hemodialysis Patients With Diabetes: A 6-Year Cohort Study

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    Previous observational studies using differing methodologies have yielded inconsistent results regarding the association between glycemic control and outcomes in diabetic patients receiving maintenance hemodialysis (MHD). We examined mortality predictability of A1C and random serum glucose over time in a contemporary cohort of 54,757 diabetic MHD patients (age 63 ± 13 years, 51% men, 30% African Americans, 19% Hispanics). Adjusted all-cause death hazard ratio (HR) for baseline A1C increments of 8.0–8.9, 9.0–9.9, and ≥10%, compared with 7.0–7.9% (reference), was 1.06 (95% CI 1.01–1.12), 1.05 (0.99–1.12), and 1.19 (1.12–1.28), respectively, and for time-averaged A1C was 1.11 (1.05–1.16), 1.36 (1.27–1.45), and 1.59 (1.46–1.72). A symmetric increase in mortality also occurred with time-averaged A1C levels in the low range (6.0–6.9%, HR 1.05 [95% CI 1.01–1.08]; 5.0–5.9%, 1.08 [1.04–1.11], and ≤5%, 1.35 [1.29–1.42]) compared with 7.0–7.9% in fully adjusted models. Adjusted all-cause death HR for time-averaged blood glucose 175–199, 200–249, 250–299, and ≥300 mg/dL, compared with 150–175 mg/dL (reference), was 1.03 (95% CI 0.99–1.07), 1.14 (1.10–1.19), 1.30 (1.23–1.37), and 1.66 (1.56–1.76), respectively. Hence, poor glycemic control (A1C ≥8% or serum glucose ≥200 mg/dL) appears to be associated with high all-cause and cardiovascular death in MHD patients. Very low glycemic levels are also associated with high mortality risk
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