Outpatient antibiotic prescription trends in the United States: A national cohort study

OBJECTIVETo characterize trends in outpatient antibiotic prescriptions in the United StatesDESIGNRetrospective ecological and temporal trend study evaluating outpatient antibiotic prescriptions from 2013 to 2015SETTINGNational administrative claims data from a pharmacy benefits manager PARTICIPANTS. Prescription pharmacy beneficiaries from Express Scripts Holding CompanyMEASUREMENTSAnnual and seasonal percent change in antibiotic prescriptionsRESULTSApproximately 98 million outpatient antibiotic prescriptions were filled by 39 million insurance beneficiaries during the 3-year study period. The most commonly prescribed antibiotics were azithromycin, amoxicillin, amoxicillin/clavulanate, ciprofloxacin, and cephalexin. No significant changes in individual or overall annual antibiotic prescribing rates were found during the study period. Significant seasonal variation was observed, with antibiotics being 42% more likely to be prescribed during February than September (peak-to-trough ratio [PTTR], 1.42; 95% confidence interval [CI], 1.39–1.61). Similar seasonal trends were found for azithromycin (PTTR, 2.46; 95% CI, 2.44–3.47), amoxicillin (PTTR, 1.52; 95% CI, 1.42–1.89), and amoxicillin/clavulanate (PTTR, 1.78; 95% CI, 1.68–2.29).CONCLUSIONSThis study demonstrates that annual national outpatient antibiotic prescribing practices remained unchanged during our study period. Furthermore, seasonal peaks in antibiotics generally used to treat viral upper respiratory tract infections remained unchanged during cold and influenza season. These results suggest that inappropriate prescribing of antibiotics remains widespread, despite the concurrent release of several guideline-based best practices intended to reduce inappropriate antibiotic consumption; however, further research linking national outpatient antibiotic prescriptions to associated medical conditions is needed to confirm these findings.Infect Control Hosp Epidemiol 2018;39:584–589</jats:sec

Abstract Sociodemographic, Comorbid And Geographic Determinants Of Covid-19 Outcomes In New England Veterans

Objective:The aim of this study is to investigate sociodemographic characteristics and comorbidities associated with hospitalization and clinical outcomes among veterans diagnosed with COVID-19 infection. Methods: A chart review of veterans diagnosed with COVID-19 in six states of New England region (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont) was performed using the veterans Affairs healthcare system electronic medical record. Relevant sociodemographic information and comorbidities were extracted. Data on the clinical course including treatment and outcomes among hospitalized patients were collected. Univariate and multivariate analyses were conducted to determine risk factors associated with hospitalization, ICU admission and length of stay. In the outpatient setting, analyses were performed on outcomes including recovery from illness and time to recovery. Addresses were geocoded using the Census Bureau Lookup Tool. For Veterans residing in Connecticut, geographic characteristics such as neighborhood socioeconomic status, and their association with relevant outcomes were analyzed. Statistical analyses were performed using STATA. Results: A total of 214 veterans with confirmed COVID-19 infection were identified: 62 were hospitalized and 152 remained in the outpatient setting. In univariate analyses, age, BMI over 30, chronic heart disease, type II diabetes mellitus and COPD were predictors of hospitalization. After adjusting for covariates, increased age (OR:1.1 95% C.I (1.06 - 1.14) and COPD (OR: 2.8 95% C.I (0.97 – 8.1) were associated with an increased odd of hospitalization with COVID-19 infection. Patients with Type II diabetes mellitus were less likely to be hospitalized (OR:0,14 95% C.I: 0.04-0.46). ICU admission was associated with male gender, immunosuppression, and chronic liver disease. Chronic liver disease was the only significant predictor of length of stay. Overall, 6% of patients died during the study period. Among hospitalized patients, the mortality rate was 17%. In the outpatient setting, older age and chronic heart disease were significantly associated with prolonged time to recovery. Neighborhood socioeconomic scores were higher among hospitalized patients, but was not significantly associated with hospitalization after adjusting for age. Discussion/Conclusion:This study identified several risk factors associated with poor clinical outcomes among veterans diagnosed with COVID-19. We found that old age, COPD and diabetic status were significant predictors of hospitalization from SARS-CoV-2 among veterans, in univariate and multivariate analyses. All factors considered, age was the leading predictor of clinical outcomes, the risk of hospitalization increasing by 10% with each one-yea increase in age and time to recovery increased by 0.1 days for every one-year increase in age in the outpatient setting. Adverse outcomes, such as ICU admission, were associated with male gender, immunosuppression and chronic liver disease. While hospitalizations were higher among patients from socioeconomically advantaged backgrounds in univariate analysis, this association was no longer present when adjusted for age. When NSES was classified in terciles, patients living in highest NSES neighborhoods were most likely to be hospitalized after adjusting for age

COVID-19 Outcomes and Genomic Characterization of SARS-CoV-2 Isolated From Veterans in New England States: Retrospective Analysis

BackgroundClinical and virologic characteristics of COVID-19 infections in veterans in New England have not been described. The average US veteran is a male older than the general US population. SARS-CoV-2 infection is known to cause poorer outcomes among men and older adults, making the veteran population an especially vulnerable group for COVID-19. ObjectiveThis study aims to evaluate clinical and virologic factors impacting COVID-19 outcomes. MethodsThis retrospective chart review included 476 veterans in six New England states with confirmed SARS-CoV-2 infection between April and September 2020. Whole genome sequencing was performed on SARS-CoV-2 RNA isolated from these veterans, and the correlation of genomic data to clinical outcomes was evaluated. Clinical and demographic variables were collected by manual chart review and were correlated to the end points of peak disease severity (based on oxygenation requirements), hospitalization, and mortality using multivariate regression analyses. ResultsOf 476 veterans, 274 had complete and accessible charts. Of the 274 veterans, 92.7% (n=254) were men and 83.2% (n=228) were White, and the mean age was 63 years. In the multivariate regression, significant predictors of hospitalization (C statistic 0.75) were age (odds ratio [OR] 1.05, 95% CI 1.03-1.08) and non-White race (OR 2.39, 95% CI 1.13-5.01). Peak severity (C statistic 0.70) also varied by age (OR 1.07, 95% CI 1.03-1.11) and O2 requirement on admission (OR 45.7, 95% CI 18.79-111). Mortality (C statistic 0.87) was predicted by age (OR 1.06, 95% CI 1.01-1.11), dementia (OR 3.44, 95% CI 1.07-11.1), and O2 requirement on admission (OR 6.74, 95% CI 1.74-26.1). Most (291/299, 97.3%) of our samples were dominated by the spike protein D614G substitution and were from SARS-CoV-2 B.1 lineage or one of 37 different B.1 sublineages, with none representing more than 8.7% (26/299) of the cases. ConclusionsIn a cohort of veterans from the six New England states with a mean age of 63 years and a high comorbidity burden, age was the largest predictor of hospitalization, peak disease severity, and mortality. Non-White veterans were more likely to be hospitalized, and patients who required oxygen on admission were more likely to have severe disease and higher rates of mortality. Multiple SARS-CoV-2 lineages were distributed in patients in New England early in the COVID-19 era, mostly related to viruses from New York State with D614G mutation