Rates of respiratory syncytial virus (RSV)-associated hospitalization among adults with congestive heart failure—United States, 2015–2017

Background

Respiratory syncytial virus (RSV) can cause severe disease in adults with cardiopulmonary conditions, such as congestive heart failure (CHF). We quantified the rate of RSV-associated hospitalization in adults by CHF status using population-based surveillance in the United States.

Methods

Population-based surveillance for RSV (RSV-NET) was performed in 35 counties in seven sites during two respiratory seasons (2015–2017) from October 1–April 30. Adults (≥18 years) admitted to a hospital within the surveillance catchment area with laboratory-confirmed RSV identified by clinician-directed testing were included. Presence of underlying CHF was determined by medical chart abstraction. We calculated overall and age-stratified (<65 years and ≥65 years) RSV-associated hospitalization rates by CHF status. Estimates were adjusted for age and the under-detection of RSV. We also report rate differences (RD) and rate ratios (RR) by comparing the rates for those with and without CHF.

Results

2042 hospitalized RSV cases with CHF status recorded were identified. Most (60.2%, n = 1230) were ≥65 years, and 28.3% (n = 577) had CHF. The adjusted RSV hospitalization rate was 26.7 (95% CI: 22.2, 31.8) per 10,000 population in adults with CHF versus 3.3 (95% CI: 3.3, 3.3) per 10,000 in adults without CHF (RR: 8.1, 95% CI: 6.8, 9.7; RD: 23.4, 95% CI: 18.9, 28.5). Adults with CHF had higher rates of RSV-associated hospitalization in both age groups (<65 years and ≥65 years). Adults ≥65 years with CHF had the highest rate (40.5 per 10,000 population, 95% CI: 35.1, 46.6).

Conclusions

Adults with CHF had 8 times the rate of RSV-associated hospitalization compared with adults without CHF. Identifying high-risk populations for RSV infection can inform future RSV vaccination policies and recommendations.

Risk Factors for Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization: COVID-19-Associated Hospitalization Surveillance Network and Behavioral Risk Factor Surveillance System

Background

Data on risk factors for COVID-19-associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors independently associated with COVID-19-associated hospitalizations

Methods

U.S. community-dwelling adults (≥18 years) hospitalized with laboratory-confirmed COVID-19 during March 1–June 23, 2020 were identified from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a multi-state surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m ²], severe obesity [BMI≥40 kg/m ²], chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRR) for hospitalization

Results

Among 5,416 adults, hospitalization rates were higher among those with ≥3 underlying conditions (versus without)(aRR: 5.0; 95%CI: 3.9, 6.3), severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65, 45-64 (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites)

Conclusion

Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions

Antimicrobial Use in a Cohort of US Nursing Homes, 2017

IMPORTANCE

Controlling antimicrobial resistance in health care is a public health priority, although data describing antimicrobial use in US nursing homes are limited.

OBJECTIVE

To measure the prevalence of antimicrobial use and describe antimicrobial classes and common indications among nursing home residents.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional, 1-day point-prevalence surveys of antimicrobial use performed between April 2017 and October 2017, last survey date October 31, 2017, and including 15 276 residents present on the survey date in 161 randomly selected nursing homes from selected counties of 10 Emerging Infections Program (EIP) states. EIP staff reviewed nursing home records to collect data on characteristics of residents and antimicrobials administered at the time of the survey. Nursing home characteristics were obtained from nursing home staff and the Nursing Home Compare website.

EXPOSURES

Residence in one of the participating nursing homes at the time of the survey.

MAIN OUTCOMES AND MEASURES

Prevalence of antimicrobial use per 100 residents, defined as the number of residents receiving antimicrobial drugs at the time of the survey divided by the total number of surveyed residents. Multivariable logistic regression modeling of antimicrobial use and percentages of drugs within various classifications.

RESULTS

Among 15 276 nursing home residents included in the study (mean [SD] age, 77.6 [13.7] years; 9475 [62%] women), complete prevalence data were available for 96.8%. The overall antimicrobial use prevalence was 8.2 per 100 residents (95% CI, 7.8-8.8). Antimicrobial use was more prevalent in residents admitted to the nursing home within 30 days before the survey date (18.8 per 100 residents; 95% CI, 17.4-20.3), with central venous catheters (62.8 per 100 residents; 95% CI, 56.9-68.3) or with indwelling urinary catheters (19.1 per 100 residents; 95% CI, 16.4-22.0). Antimicrobials were most often used to treat active infections (77% [95% CI, 74.8%-79.2%]) and primarily for urinary tract infections (28.1% [95% CI, 15.5%-30.7%]). While 18.2% (95% CI, 16.1%-20.1%) were for medical prophylaxis, most often use was for the urinary tract (40.8% [95% CI, 34.8%-47.1%]). Fluoroquinolones were the most common antimicrobial class (12.9% [95% CI, 11.3%-14.8%]), and 33.1% (95% CI, 30.7%-35.6%) of antimicrobials used were broad-spectrum antibiotics.

CONCLUSIONS AND RELEVANCE

In this cross-sectional survey of a cohort of US nursing homes in 2017, prevalence of antimicrobial use was 8.2 per 100 residents. This study provides information on the patterns of antimicrobial use among these nursing home residents.

Reducing Fluoroquinolone Use and Clostridioides difficile Infections in Community Nursing Homes Through Hospital-Nursing Home Collaboration

OBJECTIVE

Nursing homes (NHs) are an important target for antibiotic stewardship (AS). We describe a collaborative model to reduce Clostridioides difficile infections (CDIs) in NHs through optimization of antibiotic use including a reduction in high-risk antibiotics such as fluoroquinolones.

DESIGN

Quasi-experimental, pre- and post-intervention study.

SETTING AND PARTICIPANTS

Six NHs in Monroe County, NY.

METHODS

A hospital-based AS expert team assisted NHs in identifying targets for improving antibiotic use. Interventions included (1) collaboration with a medical director advisory group to develop NH consensus guidelines for testing and treatment of 2 syndromes (urinary tract infections and pneumonia) for which fluoroquinolone use is common, (2) provision of multifaceted NH staff education on these guidelines and education of residents and family members on the judicious use of antibiotics, and (3) sharing facility-specific and comparative antibiotic and CDI data. We used Poisson regression to estimate antibiotic use per 1000 resident days (RD) and CDIs per 10,000 RD, pre- and post-intervention. Segmented regression analysis was used to estimate changes in fluoroquinolone and total antibiotic rates over time.

RESULTS

Postintervention, the monthly rate of fluoroquinolone days of therapy (DOT) per 1000 RD significantly decreased by 39% [rate ratio (RR) 0.61, 95% confidence interval (CI) 0.59-0.62, P < .001] across all NHs and the total antibiotic DOT decreased by 9% (RR 0.91, 95% CI 0.90-0.92, P < .001). Interrupted time series analysis of fluoroquinolone and total DOT rates confirmed these changes. The quarterly CDI rate decreased by 18% (RR 0.82, 95% CI 0.68-0.99, P = .042).

CONCLUSIONS AND IMPLICATIONS

A hospital-NH partnership with a medical director advisory group achieved a significant reduction in total antibiotic and fluoroquinolone use and contributed to a reduction in CDI incidence. This approach offers one way for NHs to gain access to AS expertise and resources and to standardize practices within the local community.

Relationship between neighborhood census-tract level socioeconomic status and respiratory syncytial virus-associated hospitalizations in U.S. adults, 2015-2017

Background

Respiratory syncytial virus (RSV) infection causes substantial morbidity and mortality in children and adults. Socioeconomic status (SES) is known to influence many health outcomes, but there have been few studies of the relationship between RSV-associated illness and SES, particularly in adults. Understanding this association is important in order to identify and address disparities and to prioritize resources for prevention.

Methods

Adults hospitalized with a laboratory-confirmed RSV infection were identified through population-based surveillance at multiple sites in the U.S. The incidence of RSV-associated hospitalizations was calculated by census-tract (CT) poverty and crowding, adjusted for age. Log binomial regression was used to evaluate the association between Intensive Care Unit (ICU) admission or death and CT poverty and crowding.

Results

Among the 1713 cases, RSV-associated hospitalization correlated with increased CT level poverty and crowding. The incidence rate of RSV-associated hospitalization was 2.58 (CI 2.23, 2.98) times higher in CTs with the highest as compared to the lowest percentages of individuals living below the poverty level (≥ 20 and < 5%, respectively). The incidence rate of RSV-associated hospitalization was 1.52 (CI 1.33, 1.73) times higher in CTs with the highest as compared to the lowest levels of crowding (≥5 and < 1% of households with > 1 occupant/room, respectively). Neither CT level poverty nor crowding had a correlation with ICU admission or death.

Conclusions

Poverty and crowding at CT level were associated with increased incidence of RSV-associated hospitalization, but not with more severe RSV disease. Efforts to reduce the incidence of RSV disease should consider SES.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05989-w.