Despite the high prevalence of chronic kidney disease among the elderly, few studies have described their loss of kidney function. We sought to determine the progression of kidney dysfunction among a community-based cohort of elderly subjects. The cohort included 10 184 subjects 66 years of age or older, who had one or more outpatient serum creatinine measurements during each of two time periods: 1 July to 31 December 2001 and 1 July to 31 December 2003. A mixed effects model, including covariates for age, gender, diabetes mellitus, and comorbidity, was used to determine the rate of decline in estimated glomerular filtration rate (eGFR, in ml/min/1.73 m2) per year over a median follow-up of 2.0 years. Subjects with diabetes mellitus had the greatest decline in eGFR of 2.1 (95% CI 1.8-2.5) and 2.7 (95% CI 2.3-3.1) ml/min/1.73 m2 per year in women and men, respectively. The rate of decline for women and men without diabetes mellitus was 0.8 (95% CI 0.6-1.0) and 1.4 (95% CI 1.2-1.6) ml/min/1.73 m2 per year. Subjects with a study mean eGFR<30 ml/min/1.73 m2, both those with and without diabetes mellitus, experienced the greatest decline in eGFR. In conclusion, we found that the majority of elderly subjects have no or minimal progression of kidney disease over 2 years. Strategies aimed at slowing progression of kidney disease should consider underlying risk factors for progression and the negligible loss of kidney function that occurs in the majority of older adults.
Background: Low income appears to be associated with a higher prevalence of diabetes and diabetes related complications, however, little is known about how income influences access to diabetes care. The objective of the present study was to determine whether income is associated with referral to a diabetes centre within a universal health care system.
BackgroundWe have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance.MethodsA multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year.ResultsThe prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit.ConclusionThe ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.
In patients with ACS but no AF, the CHADS2 and CHA2DS2-VASc scores predict ischaemic stroke/TIA events with similar accuracy to that observed in historical populations with non-valvular AF, but with lower absolute event rates. Further study of the utility of the CHADS2 and CHA2DS2-VASc scores for the assessment of thromboembolic risk and selection of antithrombotic therapy in patients without AF is warranted.
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