Methicillin-resistant Staphylococcus aureus (MRSA) is an important pathogen in neonatal intensive care units (NICU) that confers significant morbidity and mortality.

Improving our understanding of MRSA transmission dynamics, especially among high-risk patients, is an infection prevention priority.

We investigated a cluster of clinical MRSA cases in the NICU using a combination of epidemiologic review and whole-genome sequencing (WGS) of isolates from clinical and surveillance cultures obtained from patients and healthcare personnel (HCP).

Phylogenetic analysis identified 2 genetically distinct phylogenetic clades and revealed multiple silent-transmission events between HCP and infants. The predominant outbreak strain harbored multiple virulence factors. Epidemiologic investigation and genomic analysis identified a HCP colonized with the dominant MRSA outbreak strain who cared for most NICU patients who were infected or colonized with the same strain, including 1 NICU patient with severe infection 7 months before the described outbreak. These results guided implementation of infection prevention interventions that prevented further transmission events.

Silent transmission of MRSA between HCP and NICU patients likely contributed to a NICU outbreak involving a virulent MRSA strain. WGS enabled data-driven decision making to inform implementation of infection control policies that mitigated the outbreak. Prospective WGS coupled with epidemiologic analysis can be used to detect transmission events and prompt early implementation of control strategies.

We compared the rates of hospital-onset secondary bacterial infections in patients with coronavirus disease 2019 (COVID-19) with rates in patients with influenza and controls, and we investigated reports of increased incidence of Enterococcus infections in patients with COVID-19.

Retrospective cohort study.

An academic quaternary-care hospital in San Francisco, California.

Patients admitted between October 1, 2019, and October 1, 2020, with a positive SARS-CoV-2 PCR (N = 314) or influenza PCR (N = 82) within 2 weeks of admission were compared with inpatients without positive SARS-CoV-2 or influenza tests during the study period (N = 14,332).

National Healthcare Safety Network definitions were used to identify infection-related ventilator-associated complications (IVACs), probable ventilator-associated pneumonia (PVAP), bloodstream infections (BSIs), and catheter-associated urinary tract infections (CAUTIs). A multiple logistic regression model was used to control for likely confounders.

COVID-19 patients had significantly higher rates of IVAC and PVAP compared to controls, with adjusted odds ratios of 4.7 (95% confidence interval [CI], 1.7–13.9) and 10.4 (95 % CI, 2.1–52.1), respectively. COVID-19 patients had higher incidence of BSI due to Enterococcus but not BSI generally, and whole-genome sequencing of Enterococcus isolates demonstrated that nosocomial transmission did not explain the increased rate. Subanalyses of patients admitted to the intensive care unit and patients who required mechanical ventilation revealed similar findings.

COVID-19 is associated with an increased risk of IVAC, PVAP, and Enterococcus BSI compared with hospitalized controls, which is not fully explained by factors such as immunosuppressive treatments and duration of mechanical ventilation. The mechanism underlying increased rates of Enterococcus BSI in COVID-19 patients requires further investigation.

To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.

Multicenter retrospective cohort study.

The study included 43 hospitals using a common infection prevention surveillance system.

A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods.

We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work.

Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.

To evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.

Retrospective cohort study.

Eight tertiary-care referral general hospitals in California.

We used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.

For these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15–1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, −25%; IQR, −20% to −29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%–105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, −15%; IQR, −14% to −21%) and decreased the SIR at all hospitals (median, −8%; IQR, −4% to −11%).

For tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR.

To determine whether oral vancomycin prophylaxis accompanying systemic antibiotics reduces the risk of relapse in patients with history of Clostridioides difficile infection (CDI).

Retrospective cohort study.

Adult inpatients with a history of CDI who received systemic antibiotics in either of 2 hospitals between January 2009 and June 2015.

We compared relapse rates in patients who started oral vancomycin concurrently with systemic antibiotics (exposed group) versus those who did not. We assessed for CDI relapse by toxin or nucleic acid testing at 90 days. We used inverse probability weighting and machine learning to adjust for confounders, to estimate propensity for treatment, and to calculate odds ratios for CDI relapse. We performed secondary analyses limited to toxin-positive relapses, patients with 1 versus >1 prior CDI episodes, and patients who received oral vancomycin on each antibiotic day.

CDI relapse occurred within 90 days in 19 of 193 exposed patients (9.8%) versus 53 of 567 unexposed patients (9.4%; unadjusted odds ratio [OR], 1.06; 95% confidence interval [CI], 0.60–1.81; adjusted OR, 0.63; 95% CI, 0.35–1.14). CDI relapses at 90 days were less frequent in exposed patients with only 1 prior episode of CDI (OR, 0.42; 95% CI, 0.19–0.93) but not in those with >1 prior episode (OR, 1.19; 95% CI, 0.42–3.33). Our findings were consistent with a lack of benefit of oral vancomycin when restricting results to toxin-positive relapses and to patients who received vancomycin each antibiotic day.

Prophylactic oral vancomycin was not consistently associated with reduced risk of CDI relapse among hospitalized patients receiving systemic antibiotics. However, patients with only 1 prior CDI episode may benefit.

Bathing intensive care unit (ICU) patients with 2% chlorhexidine gluconate (CHG)–impregnated cloths decreases the risk of healthcare-associated bacteremia and multidrug-resistant organism transmission. Hospitals employ different methods of CHG bathing, and few studies have evaluated whether those methods yield comparable results.

To determine whether 3 different CHG skin cleansing methods yield similar residual CHG concentrations and bacterial densities on skin.

Prospective, randomized 2-center study with blinded assessment.

Healthcare personnel in surgical ICUs at 2 tertiary-care teaching hospitals in Chicago, Illinois, and Boston, Massachusetts, from July 2015 to January 2016.

Cleansing skin of one forearm with no-rinse 2% CHG-impregnated polyester cloth (method A) versus 4% CHG liquid cleansing with rinsing on the contralateral arm, applied with either non–antiseptic-impregnated cellulose/polyester cloth (method B) or cotton washcloth dampened with sterile water (method C).

In total, 63 participants (126 forearms) received method A on 1 forearm (n=63). On the contralateral forearm, 33 participants received method B and 30 participants received method C. Immediately and 6 hours after cleansing, method A yielded the highest residual CHG concentrations (2500 µg/mL and 1250 µg/mL, respectively) and lowest bacterial densities compared to methods B or C (P<.001).

In healthy volunteers, cleansing with 2% CHG-impregnated cloths yielded higher residual CHG concentrations and lower bacterial densities than cleansing with 4% CHG liquid applied with either of 2 different cloth types and followed by rinsing. The relevance of these differences to clinical outcomes remains to be determined.

Infect Control Hosp Epidemiol 2018;39:405–411

To determine which comorbid conditions are considered causally related to central-line associated bloodstream infection (CLABSI) and surgical-site infection (SSI) based on expert consensus.

Using the Delphi method, we administered an iterative, 2-round survey to 9 infectious disease and infection control experts from the United States.

Based on our selection of components from the Charlson and Elixhauser comorbidity indices, 35 different comorbid conditions were rated from 1 (not at all related) to 5 (strongly related) by each expert separately for CLABSI and SSI, based on perceived relatedness to the outcome. To assign expert consensus on causal relatedness for each comorbid condition, all 3 of the following criteria had to be met at the end of the second round: (1) a majority (>50%) of experts rating the condition at 3 (somewhat related) or higher, (2) interquartile range (IQR)≤1, and (3) standard deviation (SD)≤1.

From round 1 to round 2, the IQR and SD, respectively, decreased for ratings of 21 of 35 (60%) and 33 of 35 (94%) comorbid conditions for CLABSI, and for 17 of 35 (49%) and 32 of 35 (91%) comorbid conditions for SSI, suggesting improvement in consensus among this group of experts. At the end of round 2, 13 of 35 (37%) and 17 of 35 (49%) comorbid conditions were perceived as causally related to CLABSI and SSI, respectively.

Our results have produced a list of comorbid conditions that should be analyzed as risk factors for and further explored for risk adjustment of CLABSI and SSI.

Infect Control Hosp Epidemiol 2017;38:449–454

To create a national policy model to evaluate the projected cost-effectiveness of multiple hospital-based strategies to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission and infection.

Cost-effectiveness analysis using a Markov microsimulation model that simulates the natural history of MRSA acquisition and infection.

Hypothetical cohort of 10,000 adult patients admitted to a US intensive care unit.

We compared 7 strategies to standard precautions using a hospital perspective: (1) active surveillance cultures; (2) active surveillance cultures plus selective decolonization; (3) universal contact precautions (UCP); (4) universal chlorhexidine gluconate baths; (5) universal decolonization; (6) UCP + chlorhexidine gluconate baths; and (7) UCP+decolonization. For each strategy, both efficacy and compliance were considered. Outcomes of interest were: (1) MRSA colonization averted; (2) MRSA infection averted; (3) incremental cost per colonization averted; (4) incremental cost per infection averted.

A total of 1989 cases of colonization and 544 MRSA invasive infections occurred under standard precautions per 10,000 patients. Universal decolonization was the least expensive strategy and was more effective compared with all strategies except UCP+decolonization and UCP+chlorhexidine gluconate. UCP+decolonization was more effective than universal decolonization but would cost $2469 per colonization averted and $9007 per infection averted. If MRSA colonization prevalence decreases from 12% to 5%, active surveillance cultures plus selective decolonization becomes the least expensive strategy.

Universal decolonization is cost-saving, preventing 44% of cases of MRSA colonization and 45% of cases of MRSA infection. Our model provides useful guidance for decision makers choosing between multiple available hospital-based strategies to prevent MRSA transmission.

Infect Control Hosp Epidemiol 2015;36(1): 17–27