Publications

OBJECTIVE

African Americans are disproportionately burdened by asthma. We assessed the individual and joint contribution of socioeconomic status (SES) on asthma morbidity among African American youth.

METHODS

We examined 686 African Americans (8-21 years) with asthma. To account for the joint effects of SES, a composite index was derived from maternal educational attainment, household income, and insurance status. Ordinal logistic regression was used to estimate the individual and joint effect of SES on asthma control. Models were adjusted for age, sex, controller medication use, in utero smoke exposure, family history of asthma, family history of rhinitis, breastfeeding, daycare attendance, and mold exposure.

RESULTS

Participants were classified as Poorly Controlled Asthma (40.8%), Partially Controlled Asthma (29.7%), or Controlled Asthma (30.2%). Of the individual SES indicators, low income was the strongest predictor of poor asthma control. Children with low income had worse asthma control than those with higher income (OR 1.39; 95% CI 0.92-2.12). The SES index ranged from 4-9. SES was associated with 17% increased odds of poor asthma control with each decrease in the index (95% CI 1.05-1.32). The SES index was associated with asthma-related symptoms, nocturnal awakenings, limited activity, and missed school days.

CONCLUSIONS

The negative effects of SES were observed along the entire socioeconomic gradient, and the adverse asthma outcomes observed in African American youth were not limited to the very poor. We also found that the SES index may be a more consistent and useful predictor of poor asthma outcomes than each indicator alone.

Nonsense mutations in FGF16 have recently been linked to X-linked recessive hand malformations with fusion between the fourth and the fifth metacarpals and hypoplasia of the fifth digit (MF4; MIM#309630). The purpose of this study was to perform careful clinical phenotyping and to define molecular mechanisms behind X-linked recessive MF4 in three unrelated families. We performed whole-exome sequencing, and identified three novel mutations in FGF16. The functional impact of FGF16 loss was further studied using morpholino-based suppression of fgf16 in zebrafish. In addition, clinical investigations revealed reduced penetrance and variable expressivity of the MF4 phenotype. Cardiac disorders, including myocardial infarction and atrial fibrillation followed the X-linked FGF16 mutated trait in one large family. Our findings establish that a mutation in exon 1, 2 or 3 of FGF16 results in X-linked recessive MF4 and expand the phenotypic spectrum of FGF16 mutations to include a possible correlation with heart disease.

BACKGROUND

Current 30-day readmission models used by the Center for Medicare and Medicaid Services for the purpose of hospital-level comparisons lack measures of socioeconomic status (SES). We examined whether the inclusion of an SES measure in 30-day congestive heart failure readmission models changed hospital risk-standardized readmission rates in New York City (NYC) hospitals.

METHODS AND RESULTS

Using a Centers for Medicare & Medicaid Services (CMS)-like model, we estimated 30-day hospital-level risk-standardized readmission rates by adjusting for age, sex, and comorbid conditions. Next, we examined how hospital risk-standardized readmission rates changed relative to the NYC mean with inclusion of the Agency for Healthcare Research and Quality (AHRQ)-validated SES index score. In a secondary analysis, we examined whether inclusion of the AHRQ SES index score in 30-day readmission models disproportionately impacted the risk-standardized readmission rates of minority-serving hospitals. Higher AHRQ SES scores, indicators of higher SES, were associated with lower odds (0.99) of 30-day readmission (P<0.019). The addition of the AHRQ SES index did not change the model's C statistic (0.63). After adjustment for the AHRQ SES index, 1 hospital changed status from worse than the NYC average to no different than the NYC average. After adjustment for the AHRQ SES index, 1 NYC minority-serving hospital was reclassified from worse to no different than average.

CONCLUSIONS

Although patients with higher SES were less likely to be admitted, the impact of SES on readmission was small. In NYC, inclusion of the AHRQ SES score in a CMS-based model did not impact hospital-level profiling based on 30-day readmission.

OBJECTIVES

To evaluate the risk and predictors of thiazide-induced adverse events (AEs) in multimorbid older adults in real-world clinical settings.

DESIGN

Observational cohort study.

SETTING

National Veterans Affairs data from 2007 to 2008.

PARTICIPANTS

Veterans aged 65 and older newly prescribed a thiazide (N = 1,060) compared with propensity-matched nonusers of antihypertensive medications (N = 1,060).

MEASUREMENTS

The primary outcome was a composite of metabolic AEs defined as sodium less than 135 mEq/L, potassium less than 3.5 mEq/L, or a decrease in the estimated glomerular filtration rate (eGFR) of more than 25% from the baseline rate. Secondary outcomes included sev-ere AEs (sodium <130 mEq/L, potassium <3.0 mEq/L, or a decrease in eGFR of more than 50%).

RESULTS

Over 9 months of follow-up, 14.3% of new thiazide users developed an AE, compared with 6.0% of nonusers (number needed to harm (NNH) 12, 95% confidence interval (CI) = 9-17, P < .001); 1.8% of new users developed a severe AE, compared with 0.6% of nonusers (NNH = 82, P = .008), and 3.8% of new users had an emergency department visit or hospitalization with an AE, compared with 2.0% of nonusers (NNH = 56, P = .02). Risk of AEs did not vary according to age, but having five or more comorbidities was associated with 3.0 times the odds (95% CI = 1.4-6.2) of developing an AE as having one comorbidity (hypertension). Low-normal and unmeasured baseline sodium and potassium values were among the strongest predictors of hyponatremia and hypokalemia, respectively. Only 42% of thiazide users had laboratory monitoring within 90 days after initiation.

CONCLUSION

Thiazide-induced AEs are common in older adults. Greater attention should be paid to potential complications in prescribing thiazides to older adults, including closer laboratory monitoring before and after initiation of thiazides.