759 research outputs found

    Determinants of the creatinine clearance to glomerular filtration rate ratio in patients with chronic kidney disease: a cross-sectional study

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    BACKGROUND: Creatinine secretion, as quantified by the ratio of creatinine clearance (CrCl) to glomerular filtration rate (GFR), may introduce another source of error when using serum creatinine concentration to estimate GFR. Few studies have examined determinants of the CrCl/GFR ratio. We sought to study whether higher levels of albuminuria would be associated with higher, and being non-Hispanic black with lower, CrCl/GFR ratio. METHODS: We did a cross-sectional analysis of 1342 patients with chronic kidney disease from the Chronic Renal Insufficiency Cohort (CRIC) who had baseline measure of iothalamate GFR (iGFR) and 24-hour urine collections. Our predictors included urine albumin as determined from 24-hour urine collections (categorized as: <30, 30-299, 300-2999 and ≥3000 mg), and race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic). Our outcome was CrCl/iGFR ratio, a measure of creatinine secretion. RESULTS: Mean iGFR was 48.0 ± 19.9 mL/min/1.73 m(2), median albuminuria was 84 mg per day, and 36.8% of the study participants were non-Hispanic black. Mean CrCl/iGFR ratio was 1.19 ± 0.48. There was no association between the CrCl/iGFR ratio and urine albumin (coefficient 0.11 [95% CI−0.01-0.22] for higest verus lowest levels of albuminuria, p = 0.07). Also, there was no association between race/ethnicity and CrCl/iGFR ratio (coefficient for non-Hispanic blacks was−0.03 [95% CI−0.09-0.03] compared with whites, p = 0.38). CONCLUSIONS: Contrary to what had been suggested by prior smaller studies, CrCl/GFR ratio does not vary with degree of proteinuria or race/ethnicity. The ratio is also closer to 1.0 than reported by several frequently cited reports in the literature

    Population Impact & Efficiency of Benefit‐Targeted Versus Risk‐Targeted Statin Prescribing for Primary Prevention of Cardiovascular Disease

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    BACKGROUND: Benefit-targeted statin prescribing may be superior to risk-targeted statin prescribing (the current standard), but the impact and efficiency of this approach are unclear. METHODS AND RESULTS: We analyzed the National Health and Nutrition Examination Survey (NHANES) using an open-source model (the Prevention Impact and Efficiency Model) to compare targeting of statin therapy according to expected benefit (benefit-targeted) versus baseline risk (risk-targeted) in terms of projected population-level impact and efficiency. Impact was defined as relative % reduction in atherosclerotic cardiovascular disease in the US population for the given strategy compared to current statin treatment patterns; and efficiency as the number needed to treat over 10 years (NNT10, average and maximum) to prevent each atherosclerotic cardiovascular disease event. Benefit-targeted moderate-intensity statin therapy at a treatment threshold of 2.3% expected 10-year absolute risk reduction could produce a 5.7% impact (95% confidence interval, 4.8-6.7). This is approximately equivalent to the potential impact of risk-targeted therapy at a treatment threshold of 5% 10-year atherosclerotic cardiovascular disease risk (5.6% impact [4.7-6.6]). Whereas the estimated maximum NNT10 is much improved for benefit-targeted versus risk-targeted therapy at these equivalent-impact thresholds (43.5 vs 180), the average NNT10 is nearly equivalent (24.2 vs 24.6). Reaching 10% impact (half the Healthy People 2020 impact objective, loosely defined) is theoretically possible with benefit-targeted moderate-intensity statins of persons with expected absolute risk reduction >2.3% if we expand age eligibility and account for treatment of all persons with diabetes mellitus or with low-density lipoprotein >190 mg/dL (impact=12.4%; average NNT10=23.0). CONCLUSIONS: Benefit-based targeting of statin therapy provides modest gains in efficiency over risk-based prescribing and could theoretically help attain approximately half of the Healthy People 2020 impact goal with reasonable efficiency

    Change in physical activity after smoking cessation: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

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    AIMS: To estimate physical activity trajectories for people who quit smoking, and compare them to what would have been expected had smoking continued. DESIGN, SETTING AND PARTICIPANTS: A total of 5115 participants in the Coronary Artery Risk Development in Young Adults Study (CARDIA) study, a population-based study of African American and European American people recruited at age 18-30 years in 1985/6 and followed over 25 years. MEASUREMENTS: Physical activity was self-reported during clinical examinations at baseline (1985/6) and at years 2, 5, 7, 10, 15, 20 and 25 (2010/11); smoking status was reported each year (at examinations or by telephone, and imputed where missing). We used mixed linear models to estimate trajectories of physical activity under varying smoking conditions, with adjustment for participant characteristics and secular trends. FINDINGS: We found significant interactions by race/sex (P = 0.02 for the interaction with cumulative years of smoking), hence we investigated the subgroups separately. Increasing years of smoking were associated with a decline in physical activity in black and white women and black men [e.g. coefficient for 10 years of smoking: -0.14; 95% confidence interval (CI) = -0.20 to -0.07, P &lt; 0.001 for white women]. An increase in physical activity was associated with years since smoking cessation in white men (coefficient 0.06; 95% CI = 0 to 0.13, P = 0.05). The physical activity trajectory for people who quit diverged progressively towards higher physical activity from the expected trajectory had smoking continued. For example, physical activity was 34% higher (95% CI = 18 to 52%; P &lt; 0.001) for white women 10 years after stopping compared with continuing smoking for those 10 years (P = 0.21 for race/sex differences). CONCLUSIONS: Smokers who quit have progressively higher levels of physical activity in the years after quitting compared with continuing smokers
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