Mind the Gap: Hospitalizations from Multiple Sources in a Longitudinal Study

Background Medicare claims and prospective studies with self-reported utilization are important sources of hospitalization data for epidemiologic and outcomes research. Objectives To assess the concordance of Medicare claims merged with interview-based surveillance data to determine factors associated with source completeness. Methods The Atherosclerosis Risk in Communities (ARIC) study recruited 15,792 cohort participants aged 45 to 64 years in the period 1987 to 1989 from four communities. Hospitalization records obtained through cohort report and hospital record abstraction were matched to Medicare inpatient records (MedPAR) from 2006 to 2011. Factors associated with concordance were assessed graphically and using multinomial logit regression. Results Among fee-for-service enrollees, MedPAR and ARIC hospitalizations matched approximately 67% of the time. For Medicare Advantage enrollees, completeness increased after initiation of hospital financial incentives in 2008 to submit shadow bills for Medicare Advantage enrollees. Concordance varied by geographic site, age, veteran status, proximity to death, study attrition, and whether hospitalizations were within ARIC catchment areas. Conclusions ARIC and MedPAR records had good concordance among fee-for-service enrollees, but many hospitalizations were available from only one source. MedPAR hospital records may be missing for veterans or observation stays. Maintaining study participation increases stay completeness, but new sources such as electronic health records may be more efficient than surveillance for mobile elderly populations

Contribution of medications and risk factors to QTc interval lengthening in the atherosclerosis risk in communities (ARIC) study

Rationale, aims, and objectives: Prolongation of the corrected QT (QTc) interval is associated with increased morbidity and mortality. The association between QTc interval–prolonging medications (QTPMs) and risk factors with magnitude of QTc interval lengthening is unknown. We examined the contribution of risk factors alone and in combination with QTPMs to QTc interval lengthening. Method: The Atherosclerosis Risk in Communities study assessed 15 792 participants with a resting, standard 12-lead electrocardiogram and ≥1 measure of QTc interval over 4 examinations at 3-year intervals (1987-1998). From 54 638 person-visits, we excluded participants with QRS ≥ 120 milliseconds (n = 2333 person-visits). We corrected the QT interval using the Bazett and Framingham formulas. We examined QTc lengthening using linear regression for 36 602 person-visit observations for 14 160 cohort members controlling for age ≥ 65 years, female sex, left ventricular hypertrophy, QTc > 500 milliseconds at the prior visit, and CredibleMeds categorized QTPMs (Known, Possible, or Conditional risk). We corrected standard errors for repeat observations per person. Results: Eighty percent of person-visits had at least one risk factor for QTc lengthening. Use of QTPMs increased over the 4 visits from 8% to 17%. Among persons not using QTPMs, history of prolonged QTc interval and female sex were associated with the greatest QTc lengthening, 39 and 12 milliseconds, respectively. In the absence of risk factors, Known QTPMs and ≥2 QTPMs were associated with modest but greater QTc lengthening than Possible or Conditional QTPMs. In the presence of risk factors, ≥2 QTPM further increased QTc lengthening. In combination with risk factors, the association of all QTPM categories with QTc lengthening was greater than QTPMs alone. Conclusion: Risk factors, particularly female sex and history of prolonged QTc interval, have stronger associations with QTc interval lengthening than any QTPM category alone. All QTPM categories augmented QTc interval lengthening associated with risk factors

The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109975/1/cpt6100087.pd

The causes and consequences of variation in offspring size: a case study using Daphnia.

Offspring size can have large and direct fitness implications, but we still do not have a complete understanding of what causes offspring size to vary. Daphnia (water fleas) generally produce fewer and larger offspring when food is limited. Here, we use a mathematical model to show that this could be explained by either: (1) an advantage of producing larger eggs when food is limited; or (2) a lower boundary on egg volume (below which eggs do not have sufficient resources to be viable), that is similar in volume to the evolutionarily stable egg volume predicted by standard clutch size models. We tested the first possibilities experimentally by placing offspring from mothers kept at two food treatments (high and low - leading to relatively small and large eggs respectively) into two food treatments (same as maternal treatments, in a fully factorial design) and measuring their fitness (reproduction, age at maturity, and size at maturity). We also tested survival under starvation conditions of offspring produced from mothers at low and high food treatments. We found that (larger) offspring produced by low-food mothers actually had lower fitness as they took longer to reproduce, regardless of their current food treatment. Additionally, we found no survival advantage to being born of a food-stressed mother. Consequently, our results do not support the hypothesis that there is an advantage to producing larger eggs when food is limited. In contrast, data from the literature support the importance of a lower boundary on egg size