Excess stroke in Mexican Americans compared with non-Hispanic Whites: the Brain Attack Surveillance in Corpus Christi Project.

Mexican Americans are the largest subgroup of Hispanics, the largest minority population in the United States. Stroke is the leading cause of disability and third leading cause of death. The authors compared stroke incidence among Mexican Americans and non-Hispanic Whites in a population-based study. Stroke cases were ascertained in Nueces County, Texas, utilizing concomitant active and passive surveillance. Cases were validated on the basis of source documentation by board-certified neurologists masked to subjects' ethnicity. From January 2000 to December 2002, 2,350 cerebrovascular events occurred. Of the completed strokes, 53% were in Mexican Americans. The crude cumulative incidence was 168/10,000 in Mexican Americans and 136/10,000 in non-Hispanic Whites. Mexican Americans had a higher cumulative incidence for ischemic stroke (ages 45-59 years: risk ratio = 2.04, 95% confidence interval: 1.55, 2.69; ages 60-74 years: risk ratio = 1.58, 95% confidence interval: 1.31, 1.91; ages >or=75 years: risk ratio = 1.12, 95% confidence interval: 0.94, 1.32). Intracerebral hemorrhage was more common in Mexican Americans (age-adjusted risk ratio = 1.63, 95% confidence interval: 1.24, 2.16). The subarachnoid hemorrhage age-adjusted risk ratio was 1.57 (95% confidence interval: 0.86, 2.89). Mexican Americans experience a substantially greater ischemic stroke and intracerebral hemorrhage incidence compared with non-Hispanic Whites. As the Mexican-American population grows and ages, measures to target this population for stroke prevention are critical.

Comparison of Bayesian and frequentist approaches in clinical outcomes between hospitals

Many public health agencies and researchers are interested in comparing hospital outcomes, for example, morbidity, mortality, and hospitalization across areas and hospitals. However, since there is variation of rates in clinical trials among hospitals because of several biases, we are interested in controlling for the bias and assessing real differences in clinical practices. In this study, we compared the variations between hospitals in rates of severe Intraventricular Haemorrhage (IVH) infant using Frequentist statistical approach vs. Bayesian hierarchical model through simulation study. The template data set for simulation study was included the number of severe IVH infants of 24 intensive care units in Australian and New Zealand Neonatal Network from 1995 to 1997 in severe IVH rate in preterm babies. We evaluated the rates of severe IVH for 24 hospitals with two hierarchical models in Bayesian approach comparing their performances with the shrunken rates in Frequentist method. Gamma-Poisson (BGP) and Beta-Binomial (BBB) were introduced into Bayesian model and the shrunken estimator of Gamma-Poisson (FGP) hierarchical model using maximum likelihood method were calculated as Frequentist approach. To simulate data, the total number of infants in each hospital was kept and we analyzed the simulated data for both Bayesian and Frequentist models with two true parameters for severe IVH rate. One was the observed rate and the other was the expected severe IVH rate by adjusting for five predictors variables for the template data. The bias in the rate of severe IVH infant estimated by both models showed that Bayesian models gave less variable estimates than Frequentist model. We also discussed and compared the results from three models to examine the variation in rate of severe IVH by 20th centile rates and avoidable number of severe IVH cases. ^