Clostridioides difficile infection (CDI) is among the most common cause of healthcare-associated infections. Persons requiring maintenance hemodialysis (MHD) are at increased risk of CDI and associated mortality compared to persons not requiring MHD. Given the clinical impact of CDI among persons requiring MHD, we aimed to quantify the burden of CDI and trends over time in this patient population.

A systematic review and meta-analysis of studies reporting rates of CDI among persons requiring MHD in MEDLINE, Embase, Web of Science Core Collection, CINAHL, and Cochrane Central Register of Controlled Trials were performed. Searches were conducted on May 17, 2021, and March 4, 2022.

In total, 2,408 titles and abstracts were identified; 240 underwent full text review. Among them, 15 studies provided data on rates of CDI among persons requiring MHD, and 8 of these also provided rates among persons not requiring MHD. The pooled prevalence of CDI among persons requiring MHD was 19.14%, compared to 5.16% among persons not requiring MHD (odds ratio [OR], 4.35; 95% confidence interval [CI], 2.07–9.16; P = .47). The linear increase in CDI over time was significant, increasing an average of 31.97% annually between 1993 and 2017 (OR, 1.32; 95% CI, 1.1–1.58; P < .01). The linear annual increase was similar among persons requiring and not requiring MHD (OR, 1.28; 95% CI, 1.13–1.45; P = .11).

Persons requiring MHD have a 4-fold higher risk of CDI compared to persons not requiring MHD, and rates of CDI are increasing over time in both groups.

Few data are available to quantify the Clostridioides difficile infection (CDI) burden in US adults depending on Medicaid insurance status; thus, we sought to contribute to this body of information.

Retrospective cohort study to identify adults with codes for CDI from 2011 to 2017 in MarketScan commercial and Medicaid databases (for those aged 25–64 years) and the CMS Medicare database (for those aged ≥65 years). CDI was categorized as healthcare-facility–associated (HCA-CDI) and community-associated CDI (CA-CDI). CDI incidence rates were compared by year, insurer, and age group.

The overall CDI incidence in the elderly was 3.1-fold higher in persons insured by Medicare plus Medicaid than in those insured by Medicare only (1,935 vs 618 per 100,000 person years (PY)), and the CDI incidence was 2.7-fold higher in younger adults with Medicaid compared to commercial insurance (195 vs 73 per 100,000 PY). From 2011 to 2017, HCA-CDI rates declined in the younger Medicaid population (124.0 to 95.2 per 100,000 PY; P < .001) but were stable in those commercially insured (25.9 to 24.8 per 100,000 PY; P = .33). In the elderly HCA-CDI rates declined from 2011 to 2017 in the Medicare-only population (403 to 318 per 100,000 PY; P < .001) and the Medicare plus Medicaid population (1,770 to 1,163 per 100,000 PY; P < .002). Persons with chronic medical conditions and those with immunocompromising conditions insured by Medicaid had 2.8- and 2.7-fold higher CDI incidence compared to the commercially insured population, respectively. The incidence of CDI was lowest in Medicaid and commercially insured younger adults without chronic medical or immunosuppressive conditions (67.5 and 45.6 per 100,000 PY, respectively).

Although HCA-CDI incidence decreased from 2011 to 2017 in elderly and younger adults insured by Medicaid, the burden of CDI remains much higher in low-income adults insured by Medicaid.

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.

Observational survey.

Inpatients at 5 acute-care hospitals in Rochester, New York, and Atlanta, Georgia, during two 10-workday periods in 2020 and 2021.

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.

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).

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.

Candida auris is an emerging fungal pathogen causing outbreaks in healthcare facilities. Five distinctive genomic clades exhibit clade-unique characteristics, highlighting the importance of real-time genomic surveillance and incorporating genotypic information to inform infection prevention practices and treatment algorithms.

Both active and passive surveillance were used to screen hospitalized patients. C. auris polymerase chain reaction (PCR) assay on inguinal-axillary swabs was performed on high-risk patients upon admission. All clinical yeast isolates were identified to the species level. C. auris isolates were characterized by both phenotypic antifungal susceptibility tests and whole-genome sequencing.

From late 2019 to early 2022, we identified 45 patients with C. auris. Most had a tracheostomy or were from a facility with a known outbreak. Moreover, 7 patients (15%) were only identified through passive surveillance. Also, 8 (18%) of the patients had a history of severe COVID-19. The overall mortality was 18%. Invasive C. auris infections were identified in 13 patients (29%), 9 (69%) of whom had bloodstream infections. Patients with invasive infection were more likely to have a central line. All C. auris isolates were resistant to fluconazole but susceptible to echinocandins. Genomic analysis showed that 1 dominant clade-III lineage is circulating in Los Angeles, with very limited intrahost and interhost genetic diversity.

We have demonstrated that a robust C. auris surveillance program can be established using both active and passive surveillance, with multidisciplinary efforts involving the microbiology laboratory and the hospital epidemiology team. In Los Angeles County, C. auris strains are highly related and echinocandins should be used for empiric therapy.

To evaluate the need for mandatory infectious diseases consultation (IDC) for candidemia in the setting of antimicrobial stewardship guidance.

Retrospective cohort study from January 2016 to December 2019.

Academic quaternary-care referral center.

All episodes of candidemia in adults (n = 92), excluding concurrent bacterial infection or death or hospice care within 48 hours.

Primary outcome was all-cause 30-day mortality. Secondary outcomes included guideline-adherence and treatment choice. Guideline-adherence was assessed with the EQUAL Candida score.

Of 186 episodes of candidemia, 92 episodes in 88 patients were included. Central venous catheters (CVCs) were present in 66 episodes (71.7%) and were the most common infection source (N = 38, 41.3%). The most frequently isolated species was Candida glabrata (40 of 94, 42.6%). IDC was performed in 84 (91.3%) of 92 candidemia episodes. Mortality rates were 20.8% (16 of 77) in the IDC group versus 25% (2 of 8) in the no-IDC group (P = .67). Other comparisons were numerically different but not significant: repeat blood culture (98.8% vs 87.5%; P = .17), echocardiography (70.2% vs 50%; P = .26), CVC removal (91.7% vs 83.3%; P = .45), and initial echinocandin treatment (67.9% vs 50%; P = .44). IDC resulted in more ophthalmology examinations (67.9% vs 12.5%; P = .0035). All patients received antifungal therapy. Antimicrobial stewardship recommendations were performed in 19 episodes (20.7%). The median EQUAL Candida score with CVC was higher with IDC (16 vs 11; P = .001) but not in episodes without CVC (12 vs 11.5; P = .81).

In the setting of an active antimicrobial stewardship program and high consultation rates, mandatory IDC may not be warranted for candidemia.

To examine the impact of SARS-CoV-2 infection on CLABSI rate and characterize the patients who developed a CLABSI. We also examined the impact of a CLABSI-reduction quality-improvement project in patients with and without COVID-19.

Retrospective cohort analysis.

Academic 889-bed tertiary-care teaching hospital in urban Los Angeles.

Inpatients 18 years and older with CLABSI as defined by the National Healthcare Safety Network (NHSN).

CLABSI rate and patient characteristics were analyzed for 2 cohorts during the pandemic era (March 2020–August 2021): COVID-19 CLABSI patients and non–COVID-19 CLABSI patients, based on diagnosis of COVID-19 during admission. Secondary analyses were non–COVID-19 CLABSI rate versus a historical control period (2019), ICU CLABSI rate in COVID-19 versus non–COVID-19 patients, and CLABSI rates before and after a quality- improvement initiative.

The rate of COVID-19 CLABSI was significantly higher than non–COVID-19 CLABSI. We did not detect a difference between the non–COVID-19 CLABSI rate and the historical control. COVID-19 CLABSIs occurred predominantly in the ICU, and the ICU COVID-19 CLABSI rate was significantly higher than the ICU non–COVID-19 CLABSI rate. A hospital-wide quality-improvement initiative reduced the rate of non–COVID-19 CLABSI but not COVID-19 CLABSI.

Patients hospitalized for COVID-19 have a significantly higher CLABSI rate, particularly in the ICU setting. Reasons for this increase are likely multifactorial, including both patient-specific and process-related issues. Focused quality-improvement efforts were effective in reducing CLABSI rates in non–COVID-19 patients but were less effective in COVID-19 patients.

We aimed to demonstrate the role of real-time, on-site, whole-genome sequencing (WGS) of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in the management of hospital outbreaks of coronavirus disease 2019 (COVID-19).

This retrospective study was undertaken at our institutions in Sydney, New South Wales, Australia, between July 2021 and April 2022. We included SARS-CoV-2 outbreaks due to SARS-CoV-2 δ (delta) and ο (omicron) variants. All unexpected SARS-CoV-2–positive cases identified within the hospital were managed by the infection control team. An outbreak was defined as 2 or more cases acquired on a single ward. We included only outbreaks with 2 or more suspected transmission events in which WGS was utilized to assist with outbreak assessment and management.

We studied 8 outbreaks involving 266 patients and 486 staff, of whom 73 (27.4%) and 39 (8.0%), respectively, tested positive for SARS-CoV-2 during the outbreak management. WGS was used to evaluate the source of the outbreak, to establish transmission chains, to highlight deficiencies in infection control practices, and to delineate between community and healthcare acquired infection.

Real-time, on-site WGS combined with epidemiologic assessment is a useful tool to guide management of hospital SARS-CoV-2 outbreaks. WGS allowed us (1) to establish likely transmission events due to personal protective equipment (PPE) breaches; (2) to detect inadequacies in infection control infrastructure including ventilation; and (3) to confirm multiple viral introductions during periods of high community SARS-CoV-2 transmission. Insights gained from WGS-guides outbreak management directly influenced policy including modifying PPE requirements, instituting routine inpatient SARS-CoV-2 surveillance, and confirmatory SARS-CoV-2 testing prior to placing patients in a cohort setting.

In Québec, Canada, we evaluated the risk of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection associated with (1) the demographic and employment characteristics among healthcare workers (HCWs) and (2) the workplace and household exposures and the infection prevention and control (IPC) measures among patient-facing HCWs.

Test-negative case-control study.

Provincial health system.

HCWs with PCR-confirmed coronavirus disease 2019 (COVID-19) diagnosed between November 15, 2020, and May 29, 2021 (ie, cases), were compared to HCWs with compatible symptoms who tested negative during the same period (ie, controls).

Adjusted odds ratios (aORs) of infection were estimated using regression logistic models evaluating demographic and employment characteristics (all 4,919 cases and 4,803 controls) or household and workplace exposures and IPC measures (2,046 patient-facing cases and 1,362 controls).

COVID-19 risk was associated with working as housekeeping staff (aOR, 3.6), as a patient-support assistant (aOR, 1.9), and as nursing staff (aOR, 1.4), compared to administrative staff. Other risk factors included being unexperienced (aOR, 1.5) and working in private seniors’ homes (aOR, 2.1) or long-term care facilities (aOR, 1.5), compared to acute-care hospitals. Among patient-facing HCWs, exposure to a household contact was reported by 9% of cases and was associated with the highest risk of infection (aOR, 7.8). Most infections were likely attributable to more frequent exposure to infected patients (aOR, 2.7) and coworkers (aOR, 2.2). Wearing an N95 respirator during contacts with COVID-19 patients (aOR, 0.7) and vaccination (aOR, 0.2) were the measures associated with risk reduction.

In the context of the everchanging SARS-CoV-2 virus with increasing transmissibility, measures to ensure HCW protection, including vaccination and respiratory protection, and patient safety will require ongoing evaluation.

Which educational method is best for 3-month retention of proper skills in removing personal protective equipment (PPE) in the setting of highly infectious diseases is unclear. We evaluated the effectiveness of a Web-based learning system after 3 months of use.

One general hospital in Japan.

We conducted a randomized, nonblinded, parallel-group trial with 35 nurses using the substitution block method. At baseline, both groups received face-to-face training in putting on and removing PPE. The intervention group was given access to the Web-based learning system we developed using Modular Object-Oriented Dynamic Learning Environment (Moodle). After 3 months, we assessed both groups regarding knowledge and skills in removing PPE using a 34-point test, fluorescent markers, and video recordings.

Overall, 34 participants completed the trial: 16 in the intervention group and 18 in the control group. Postintervention knowledge test scores (1.3 vs −0.8; P = .013; effect size r = .42) and deviations from the required procedure (−5.4 vs 1.9; P = .001; effect size r = .55) were significantly better in the intervention group than in the control group. The number of contaminated sites (−0.5 vs 0.4; P = .128; effect size r = .26) and contaminated participants (−18.7% vs 11.1% decreased in the intervention group, and increased in the control group, although this was not significant (P = .242; effect size ϕ = .47).

This learning system was an effective educational method in maintaining and improving knowledge of proper PPE removal skills. The number of deviations from the required procedure decreased, and this reduction continued after 3 months.

Evaluation of the Web materials for learning PPE removal skills in the setting of highly infectious diseases. University Hospital Medical Information Network, UMIN000042725: https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000048767

Ventilator-associated pneumonia (VAP) remains a challenge. The importance of viruses in VAP is not established. We sought to determine the prevalence of viruses in VAP and the outcomes of viral VAP.

Retrospective study of VAP over 3 years. The frequency of a viral process represented the primary endpoint. Clinical outcomes served as secondary endpoints. We identified variables independently associated with a virus and conducted sensitivity analyses to assess the interaction between type of infection and patient characteristics.

Tertiary-care referral center.

The final cohort consisted of 710 patients and a virus was isolated in 5.1%.

None.

The most common viruses included: rhinovirus, influenza A, and cytomegalovirus. Baseline characteristics were similar between those with and without viral infections. In logistic regression, immunosuppression (adjusted odds ratio [aOR], 2.97; 95% confidence interval [CI], 1.44–6.14) and stem-cell transplantation (SCT, aOR, 3.58; 95% CI, 1.17–10.99) were independently associated with a virus. The presence of either variable performed poorly as a screening test for a virus. In-hospital (22.4% vs 21.6%; P = .869) and 30-day (32.8% vs 27.9%; P = .448) mortality rates were similar between the cohorts, respectively. Sensitivity analyses restricted to patients without a mixed viral and bacterial infection or those who were immunocompetent yielded similar results.

Although infrequent, a range of viruses may cause VAP. Viruses more often complicate SCT and immunosuppression, but one can isolate viruses in immunocompetent subjects. Viral VAP produces severe infection and results in high mortality rates. Clinical features do not differentiate viral from nonviral VAP.

To derive and validate a model for risk of resistance to first-line community-acquired pneumonia (CAP) therapy.

We developed a logistic regression prediction model from a large multihospital discharge database and validated it versus the Drug Resistance in Pneumonia (DRIP) score in a holdout sample and another hospital system outside that database. Resistance to first-line CAP therapy (quinolone or third generation cephalosporin plus macrolide) was based on blood or respiratory cultures.

This study was conducted using data from 177 Premier Healthcare database hospitals and 11 Cleveland Clinic hospitals.

Adults hospitalized for CAP.

Risk factors for resistant infection.

Among 138,762 eligible patients in the Premier database, 12,181 (8.8%) had positive cultures and 5,200 (3.8%) had organisms resistant to CAP therapy. Infection with a resistant organism in the previous year was the strongest predictor of resistance; markers of acute illness (eg, receipt of mechanical ventilation or vasopressors) and chronic illness (eg, pressure ulcer, paralysis) were also associated with resistant infections. Our model outperformed the DRIP score with a C-statistic of 0.71 versus 0.63 for the DRIP score (P < .001) in the Premier holdout sample, and 0.65 versus 0.58 (P < .001) in Cleveland Clinic hospitals. Clinicians at Premier facilities used broad-spectrum antibiotics for 20%–30% of patients. In discriminating between patients with and without resistant infections, physician judgment slightly outperformed the DRIP instrument but not our model.

Our model predicting infection with a resistant pathogen outperformed both the DRIP score and physician practice in an external validation set. Its integration into practice could reduce unnecessary use of broad-spectrum antibiotics.