To evaluate hospital-level variation in using first-line antibiotics for Clostridioides difficile infection (CDI) based on the burden of laboratory-identified (LabID) CDI.

Using data on hospital-level LabID CDI events and antimicrobial use (AU) for CDI (oral/rectal vancomycin or fidaxomicin) submitted to the National Healthcare Safety Network in 2019, we assessed the association between hospital-level CDI prevalence (per 100 patient admissions) and rate of CDI AU (days of therapy per 1,000 days present) to generate a predicted value of AU based on CDI prevalence and CDI test type using negative binomial regression. The ratio of the observed to predicted AU was then used to identify hospitals with extreme discordance between CDI prevalence and CDI AU, defined as hospitals with a ratio outside of the intervigintile range.

Among 963 acute-care hospitals, rate of CDI prevalence demonstrated a positive dose–response relationship with rate of CDI AU. Compared with hospitals without extreme discordance (n = 902), hospitals with lower-than-expected CDI AU (n = 31) had, on average, fewer beds (median, 106 vs 208), shorter length of stay (median, 3.8 vs 4.2 days), and higher proportion of undergraduate or nonteaching medical school affiliation (48% vs 39%). Hospitals with higher-than-expected CDI AU (n = 30) were similar overall to hospitals without extreme discordance.

The prevalence rate of LabID CDI had a significant dose–response association with first-line antibiotics for treating CDI. We identified hospitals with extreme discordance between CDI prevalence and CDI AU, highlighting potential opportunities for data validation and improvements in diagnostic and treatment practices for CDI.

To quantitatively evaluate relationships between infection preventionists (IPs) staffing levels, nursing hours, and rates of 10 types of healthcare-associated infections (HAIs).

An ambidirectional observation in a 528-bed teaching hospital.

All inpatients from July 1, 2012, to February 1, 2021.

Standardized US National Health Safety Network (NHSN) definitions were used for HAIs. Staffing levels were measured in full-time equivalents (FTE) for IPs and total monthly hours worked for nurses. A time-trend analysis using control charts, t tests, Poisson tests, and regression analysis was performed using Minitab and R computing programs on rates and standardized infection ratios (SIRs) of 10 types of HAIs. An additional analysis was performed on 3 stratifications: critically low (2–3 FTE), below recommended IP levels (4–6 FTE), and at recommended IP levels (7–8 FTE).

The observation covered 1.6 million patient days of surveillance. IP staffing levels fluctuated from ≤2 IP FTE (critically low) to 7–8 IP FTE (recommended levels). Periods of highest catheter-associated urinary tract infection SIRs, hospital-onset Clostridioides difficile and carbapenem-resistant Enterobacteriaceae infection rates, along with 4 of 5 types of surgical site SIRs coincided with the periods of lowest IP staffing levels and the absence of certified IPs and a healthcare epidemiologist. Central-line–associated bloodstream infections increased amid lower nursing levels despite the increased presence of an IP and a hospital epidemiologist.

Of 10 HAIs, 8 had highest incidences during periods of lowest IP staffing and experience. Some HAI rates varied inversely with levels of IP staffing and experience and others appeared to be more influenced by nursing levels or other confounders.

Limited data are available on the implementation of an area under the concentration-time curve (AUC)–based dosing protocol with multidisciplinary team (MT) support to improve adherence with vancomycin dosing protocol.

To evaluate the effectiveness of an AUC-based dosing protocol with MT support intervention with adherence to a hospital-wide vancomycin dosing protocol at Thammasat University Hospital.

We conducted a quasi-experimental study in patients who were prescribed intravenous vancomycin. The study was divided into 2 periods; (1) the preintervention period when the vancomycin dosing protocol was already applied in routine practice and (2) the post-intervention period when the implementation of an AUC-based dosing protocol with MT support was added to the existing vancomycin dosing protocol. The primary outcome was the rate of adherence, and the secondary outcomes included acute kidney injury events, vancomycin-related adverse events, and 30-day mortality rate.

In total, 240 patients were enrolled. The most common infections were skin and soft-tissue infections (24.6%) and bacteremia (24.6%). The most common pathogens were coagulase-negative staphylococci (19.6%) and Enterococcus spp (15.4%). Adherence with the vancomycin dosing protocol was significantly higher in the postintervention period (90.8% vs 55%; P ≤ .001). By multivariate analysis, an AUC-based dosing protocol with MT support was the sole predictor for adherence with the vancomycin dosing protocol (adjusted odds ratio, 10.31; 95% confidence interval, 4.54–23.45; P ≤ .001). The 30-day mortality rate was significantly lower during the postintervention period (8.3% vs 20%; P = .015).

AUC-based dosing protocol with MT support significantly improved adherence with vancomycin dosing protocol and was associated with a lower 30-day mortality rate.

We sought to determine the incidence of community-onset and hospital-acquired coinfection in patients hospitalized with coronavirus disease 2019 (COVID-19) and to evaluate associated predictors and outcomes.

In this multicenter retrospective cohort study of patients hospitalized for COVID-19 from March 2020 to August 2020 across 38 Michigan hospitals, we assessed prevalence, predictors, and outcomes of community-onset and hospital-acquired coinfections. In-hospital and 60-day mortality, readmission, discharge to long-term care facility (LTCF), and mechanical ventilation duration were assessed for patients with versus without coinfection.

Of 2,205 patients with COVID-19, 141 (6.4%) had a coinfection: 3.0% community onset and 3.4% hospital acquired. Of patients without coinfection, 64.9% received antibiotics. Community-onset coinfection predictors included admission from an LTCF (OR, 3.98; 95% CI, 2.34–6.76; P < .001) and admission to intensive care (OR, 4.34; 95% CI, 2.87–6.55; P < .001). Hospital-acquired coinfection predictors included fever (OR, 2.46; 95% CI, 1.15–5.27; P = .02) and advanced respiratory support (OR, 40.72; 95% CI, 13.49–122.93; P < .001). Patients with (vs without) community-onset coinfection had longer mechanical ventilation (OR, 3.31; 95% CI, 1.67–6.56; P = .001) and higher in-hospital mortality (OR, 1.90; 95% CI, 1.06–3.40; P = .03) and 60-day mortality (OR, 1.86; 95% CI, 1.05–3.29; P = .03). Patients with (vs without) hospital-acquired coinfection had higher discharge to LTCF (OR, 8.48; 95% CI, 3.30–21.76; P < .001), in-hospital mortality (OR, 4.17; 95% CI, 2.37–7.33; P ≤ .001), and 60-day mortality (OR, 3.66; 95% CI, 2.11–6.33; P ≤ .001).

Despite community-onset and hospital-acquired coinfection being uncommon, most patients hospitalized with COVID-19 received antibiotics. Admission from LTCF and to ICU were associated with increased risk of community-onset coinfection. Future studies should prospectively validate predictors of COVID-19 coinfection to facilitate the reduction of antibiotic use.

Research on complications with peripherally inserted central catheter (PICC) lines that are placed for the treatment of prosthetic joint infection (PJI) after total hip arthroplasty (THA) and total knee arthroplasty (TKA) is scarce. We investigated the timing, frequency, and risk factors for PICC complications during treatment of PJI after THA and TKA.

We retrospectively queried an institutional database for THA and TKA patients from January 2015 through December 2020 that developed a PJI and required PICC placement at an academic, tertiary-care referral center.

The study included 889 patients (48.3% female) with a mean age of 64.6 years (range, 18.7–95.2) who underwent 435 THAs and 454 TKAs that were revised for PJI. The cohort had 275 90-day ED visits (30.9%), and 51 (18.5%) were PICC related. The average time from discharge to PICC ED visit was 26.2 days (range, 0.3–89.4). The most common reasons for a 90-day ED visit were issues related to the joint replacement or wound site (musculoskeletal or MSK; n = 116, 42.2%) and PICC complaints (n = 51, 18.5%). A multivariable logistic regression demonstrated that non-White race (odds ratio [OR], 2.24; 95% confidence interval [CI], 1.24–4.04; P = .007) and younger age (OR, 0.98; 95% CI, 0.95–1.00; P = .035) were associated with PICC-related ED visits. Malposition/readjustment (41.2%) and occlusion (35.3%) were the most common PICC complications leading to ED presentation.

PICC complications are common after PJI treatment, accounting for nearly 20% of 90-day ED visits.

Coronavirus disease 2019 (COVID-19) vaccination effectiveness in healthcare personnel (HCP) has been established. However, questions remain regarding its performance in high-risk healthcare occupations and work locations. We describe the effect of a COVID-19 HCP vaccination campaign on SARS-CoV-2 infection by timing of vaccination, job type, and work location.

We conducted a retrospective review of COVID-19 vaccination acceptance, incidence of postvaccination COVID-19, hospitalization, and mortality among 16,156 faculty, students, and staff at a large academic medical center. Data were collected 8 weeks prior to the start of phase 1a vaccination of frontline employees and ended 11 weeks after campaign onset.

The COVID-19 incidence rate among HCP at our institution decreased from 3.2% during the 8 weeks prior to the start of vaccinations to 0.38% by 4 weeks after campaign initiation. COVID-19 risk was reduced among individuals who received a single vaccination (hazard ratio [HR], 0.52; 95% confidence interval [CI], 0.40–0.68; P < .0001) and was further reduced with 2 doses of vaccine (HR, 0.17; 95% CI, 0.09–0.32; P < .0001). By 2 weeks after the second dose, the observed case positivity rate was 0.04%. Among phase 1a HCP, we observed a lower risk of COVID-19 among physicians and a trend toward higher risk for respiratory therapists independent of vaccination status. Rates of infection were similar in a subgroup of nurses when examined by work location.

Our findings show the real-world effectiveness of COVID-19 vaccination in HCP. Despite these encouraging results, unvaccinated HCP remain at an elevated risk of infection, highlighting the need for targeted outreach to combat vaccine hesitancy.

To describe the cumulative seroprevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies during the coronavirus disease 2019 (COVID-19) pandemic among employees of a large pediatric healthcare system.

Prospective observational cohort study open to adult employees at the Children’s Hospital of Philadelphia, conducted April 20–December 17, 2020.

Employees were recruited starting with high-risk exposure groups, utilizing e-mails, flyers, and announcements at virtual town hall meetings. At baseline, 1 month, 2 months, and 6 months, participants reported occupational and community exposures and gave a blood sample for SARS-CoV-2 antibody measurement by enzyme-linked immunosorbent assays (ELISAs). A post hoc Cox proportional hazards regression model was performed to identify factors associated with increased risk for seropositivity.

In total, 1,740 employees were enrolled. At 6 months, the cumulative seroprevalence was 5.3%, which was below estimated community point seroprevalence. Seroprevalence was 5.8% among employees who provided direct care and was 3.4% among employees who did not perform direct patient care. Most participants who were seropositive at baseline remained positive at follow-up assessments. In a post hoc analysis, direct patient care (hazard ratio [HR], 1.95; 95% confidence interval [CI], 1.03–3.68), Black race (HR, 2.70; 95% CI, 1.24–5.87), and exposure to a confirmed case in a nonhealthcare setting (HR, 4.32; 95% CI, 2.71–6.88) were associated with statistically significant increased risk for seropositivity.

Employee SARS-CoV-2 seroprevalence rates remained below the point-prevalence rates of the surrounding community. Provision of direct patient care, Black race, and exposure to a confirmed case in a nonhealthcare setting conferred increased risk. These data can inform occupational protection measures to maximize protection of employees within the workplace during future COVID-19 waves or other epidemics.