No abstract

Pertussis is endemic in the United States, with periodic epidemics that continue to highlight its importance as a public health issue. The clinical presentation of pertussis can vary by age and vaccination status. However, little is known about the factors that affect time to antibiotic treatment of pertussis cases. We analyzed 5 years of data from the Georgia Department of Public Health to understand how factors such as age, symptoms, and vaccination status can alter the clinical picture of pertussis and affect time to treatment. We used multivariable linear regression to assess the impact of each variable on time to antibiotic treatment. There was little consistency across age groups for symptom and demographic predictors of time to antibiotic treatment. Overall, the multivariate linear regression showed that among patients <18 years old, none of the variables had an impact on time to antibiotic treatment greater than ؊0.25 to 1.47 days. Among patients >18 years old, most variables had little impact on time to treatment, though two (paroxysmal cough in >18-to 40-year-olds and hospitalization in individuals over 40) were associated with an additional 5 days in time to treatment from cough onset. This study highlights how the difficulties in pertussis diagnosis, particularly among adults, can affect time to antibiotic treatment; adults may not begin antibiotic treatment until there is an accumulation of symptoms. Health care providers need to recognize the variety of symptoms that pertussis can present with and consider confirmatory testing early.

In total, 13 facilities changed C. difficile testing to reflexive testing by enzyme immunoassay (EIA) only after a positive nucleic acid-amplification test (NAAT); the standardized infection ratio (SIR) decreased by 46% (range, −12% to −71% per hospital). Changing testing practice greatly influenced a performance metric without changing C. difficile infection prevention practice.

Objective: We evaluated the impact of test-order frequency per diarrheal episodes on Clostridioides difficile infection (CDI) incidence estimates in a sample of hospitals at 2 CDC Emerging Infections Program (EIP) sites. Design: Observational survey. Setting: Inpatients at 5 acute-care hospitals in Rochester, New York, and Atlanta, Georgia, during two 10-workday periods in 2020 and 2021. Outcomes: We calculated diarrhea incidence, testing frequency, and CDI positivity (defined as any positive NAAT test) across strata. Predictors of CDI testing and positivity were assessed using modified Poisson regression. Population estimates of incidence using modified Emerging Infections Program methodology were compared between sites using the Mantel-Hanzel summary rate ratio. Results: Surveillance of 38,365 patient days identified 860 diarrhea cases from 107 patient-care units mapped to 26 unique NHSN defined location types. Incidence of diarrhea was 22.4 of 1,000 patient days (medians, 25.8 for Rochester and 16.2 for Atlanta; P < .01). Similar proportions of diarrhea cases were hospital onset (66%) at both sites. Overall, 35% of patients with diarrhea were tested for CDI, but this differed by site: 21% in Rochester and 49% in Atlanta (P < .01). Regression models identified location type (ie, oncology or critical care) and laxative use predictive of CDI test ordering. Adjusting for these factors, CDI testing was 49% less likely in Rochester than Atlanta (adjusted rate ratio, 0.51; 95% confidence interval [CI], 0.40–0.63). Population estimates in Rochester had a 38% lower incidence of CDI than Atlanta (summary rate ratio, 0.62; 95% CI, 0.54–0.71). Conclusion: Accounting for patient-specific factors that influence CDI test ordering, differences in testing practices between sites remain and likely contribute to regional differences in surveillance estimates.