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Eric Weinhandl

Publications and source records attributed to Eric Weinhandl.

5 recordsLinked to original sources
PubMed2005

Angiotensin-converting enzyme inhibitor as a risk factor for the development of anemia, and the impact of incident anemia on mortality in patients with left ventricular dysfunction.

OBJECTIVES: We aimed to investigate the impact of angiotensin-converting enzyme inhibitors (ACEIs) on hematocrit values in those with heart failure, and the relationship between incident anemia and mortality. BACKGROUND: Prevalent anemia is an independent risk factor for morbidity and mortality in those with heart failure. Studies in patients with polycythemia have demonstrated that ACEIs are effective in lowering hematocrit values. METHODS: We used the Studies Of Left Ventricular Dysfunction (SOLVD) database to compare the odds of developing new anemia at one year in patients who were not anemic at entry and who were randomized to enalapril or placebo. Cox proportional hazards models were utilized to determine the impact of incident and prevalent anemia on subsequent mortality. RESULTS: Enalapril increased the odds of incident anemia (hematocrit < or =39% in men or < or =36% in women) at one year by 48% (odds ratio [OR] 1.48, 95% confidence interval [CI] 1.20 to 1.82) in unadjusted and 56% (OR 1.56, 95% CI 1.26 to 1.93) in adjusted models. With multivariate analysis, prevalent anemia at randomization was associated with a 44% (hazard ratio [HR] 1.44, 95% CI 1.31 to 1.66) increase in all-cause mortality, whereas incident anemia after randomization was associated with a 108% increase (HR 2.08, 95% CI 1.82 to 2.38). After adjusting for incident and prevalent anemia, use of enalapril was associated with a survival benefit. CONCLUSIONS: Enalapril was associated with increased odds of developing anemia at one year. Those with periods of time with incident anemia had the poorest survival, followed by those with prevalent anemia, then those without anemia. Enalapril was protective of overall mortality after adjusting for incident anemia and in those with prevalent anemia.

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PubMed2002

Risk set sampling for case-crossover designs.

In the case-crossover design, only cases are sampled, and effect estimates are based on within-subject comparisons of exposures at failure times with exposures at control times. Sampling control times appropriately can provide some control for unmeasured confounding, but may introduce bias owing to time trends in the exposure of interest. The theory of risk set sampling (Borgan Ø, Goldstein L, Langholz B. Ann Stat 1995;23:1749-1778) can be used to develop effect estimates in these situations that are free from bias caused by time trends. Through simulation, we compared four sampling schemes: the full-stratum bidirectional design, a matched pair design, the symmetric bidirectional design of Bateson and Schwartz (Bateson T, Schwartz J. Epidemiology 1999;10:539-544), and the semi-symmetric bidirectional design. We also studied a quasi-likelihood extension of Poisson regression with overdispersion. We used daily mean particulate matter less than 10 microm in aerodynamic diameter levels in Denver as the exposure of interest, simulated confounding with linear and seasonal trends, and simulated mortality counts using a log relative risk of 1.1. Neither the matched pair, the full-stratum design, or Poisson regression with overdispersion provided control for seasonal confounding. The symmetric bidirectional design controlled for seasonal confounding but exhibited bias from time trends in exposure. The semi-symmetric bidirectional design provided control of seasonal confounding equal to that of the symmetric bidirectional design, without any time-trend bias.

Air Pollution↗
PubMedDate not supplied

Comparison and survival of hemodialysis and peritoneal dialysis in the elderly.

Comparisons of clinical outcomes in hemodialysis (HD) and peritoneal dialysis (PD) patients have been marked by inconsistent results depending on the population studied and the methods used. In order to address this limitation of previous U.S. studies and to more specifically evaluate the higher-risk elderly population, we undertook a study of Medicare patients > or =67 years of age and assessed the comorbidity before they entered end-stage renal disease (ESRD) treatment. We then evaluated their survival outcomes at 6 month intervals in the follow-up period. In order to adequately assess the comorbidity we employed the Charlson comorbidity index and applied it to the comorbidity of the ESRD population up to 2 years before ESRD to characterize conditions from the start of ESRD treatment. We also counted inpatient hospital days in the 2 years prior to initiation of ESRD therapy as a marker of severity of disease. These two determinants of comorbidity were used to adjust the analysis along with other demographic and laboratory data. In the diabetic population, HD patients are shown to have a decreased risk of death, with the decrease ranging from 8% [relative risk (RR) (HD:PD) 0.82, 95% confidence interval (CI) 0.75-0.90] at month 6 to 54% [RR (HD:PD) 0.46, 95% CI 0.30-0.70] at month 48. In the nondiabetic population, HD patients are shown to have a 17% [RR (HD:PD) 1.17, 95% CI 1.07-1.28] increased risk of death in the first 6 months, and a decreased risk of death from months 6 to 48, a decrease ranging from 17% to 34%. Relative risks were significantly different from 1.0 at all intervals. These overall findings suggest that in the elderly population in the United States treated with PD had outcomes that were significantly worse than their HD patient counterparts, even after adjusting basic patient demographics, the comorbidity index, severity of disease with hospital days, demographics, and glomerular filtration rate (GFR) at the time of start of dialysis.

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