To model the effects of active detection and isolation (ADI) regarding Clostridioides difficile infection (CDI) in the bone marrow transplant (BMT) unit of our hospital.

ADI was implemented in a 21-patient bone marrow unit.

Patients were bone marrow recipients on this unit.

We compared active ADI, in which patients who tested positive for colonization of C. difficile before their hospital stay were placed under extra contact precautions, with cases not under ADI.

Within the BMT unit, ADI reduced total cases of CDI by 24.5% per year and reduced hospital-acquired cases by ∼84%. The results from our simulations also suggest that ADI can save ∼$67,600 per year in healthcare costs.

Institutions with active BMT units should consider implementing ADI.

To improve dissemination and accessibility of guidelines to healthcare providers at our institution, guidance for infectious syndromes was incorporated into an electronic application (e-app). The objective of this study was to compare empiric antimicrobial prescribing before and after implementation of the e-app.

This study was a before-and-after trial.

A tertiary-care, public hospital in Halifax, Canada.

This study included pediatric patients admitted to hospital who were empirically prescribed an antibiotic for an infectious syndrome listed in the e-app.

Data were collected from medical records. Prescribing was independently assessed considering patient-specific characteristics using a standardized checklist by 2 members of the research team. Assessments of antimicrobial prescribing were compared, and discrepancies were resolved through discussion. Empiric antimicrobial prescribing before and after implementation of the e-app was compared using interrupted time-series analysis.

In total, 237 patients were included in the preimplementation arm and 243 patients were included in the postimplementation arm. Pneumonia (23.8%), appendicitis (19.2%), and sepsis (15.2%) were the most common indications for antimicrobial use. Empiric antimicrobial use was considered optimal in 195 (81.9%) of 238 patients before implementation compared to 226 (93.0%) 243 patients after implementation. An immediate 15.5% improvement (P = .019) in optimal antimicrobial prescribing was observed following the implementation of the e-app.

Empiric antimicrobial prescribing for pediatric patients with infectious syndromes improved after implementation of an e-app for dissemination of clinical practice guidelines. The use of e-apps may also be an effective strategy to improve antimicrobial use in other patient populations.

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.

Antibiotic exposure increases the risk of morbidity and mortality in premature infants. Many centers use at least 48 hours of antibiotics in the evaluation of early-onset sepsis (EOS, <72 hours after birth), yet most important pathogens grow within 24 hours. We investigated the safety and efficacy of reducing empiric antibiotic duration to 24 hours.

Quality improvement study.

A tertiary-care neonatal intensive care unit.

Inborn infants <35 weeks gestational age at birth (ie, preterm) admitted January 2019 through December 2020.

In December 2019, we changed the recommended duration of empiric antibiotics for negative EOS evaluations from 48 hours to 24 hours.

Patient characteristics before and after the intervention were similar. After the intervention, 71 preterm infants (57%) with negative EOS evaluations received ≤24 hours of antibiotics, an increase from 15 (10%) before the intervention. These 71 infants comprised 77% of infants with negative EOS blood cultures after excluding those treated as clinical sepsis (≥5 days of antibiotics). For all negative EOS blood cultures, the mean treatment duration decreased by 0.5 days from 3.9 days to 3.4 days. This finding equated to 2.4 fewer antibiotic days per 100 patient days for negative EOS blood cultures but similar antibiotic days per 30 patient days (7.2 days vs 7.5 days). This measure did not change over time. Subsequent sepsis evaluations <7 days after a negative EOS blood culture did not increase. Excluding contaminants, the median time to positivity was 13.2 hours (range, 8–23) in 8 positive blood cultures.

Implementation of a 24-hour antibiotic course for negative EOS evaluations safely reduced antibiotic exposure in 77% of infants <35 weeks gestational age at birth in whom EOS was ruled out. All clinically significant pathogens grew within 24 hours.

Resistant gram-negative bacteria (R-GNB) colonization in nursing home patients can cause clinical infection and intrafacility transmission. Limited data exist on the roles of age and function on R-GNB colonization.

A secondary data analysis was performed from a cohort study of 896 patients admitted to 6 Michigan nursing homes between November 2013 and May 2018. Swabs obtained upon enrollment, weekly for 1 month, then monthly until nursing home discharge from 5 anatomical sites were cultured for GNB. R-GNB were defined as resistant to ciprofloxacin, ceftazidime, or imipenem. Patients with growth of the same R-GNB as the initial positive visit, from any anatomical site at any subsequent visit, were considered persistently colonized. Demographic data, antibiotic use, device use, and physical self-maintenance scales (PSMSs) were obtained upon enrollment. Characteristics were compared between patients with R-GNB colonization versus those without, and those with persistent R-GNB colonization versus those with spontaneous decolonization.

Of 169 patients with a positive R-GNB culture and ≥2 subsequent study visits, 89 (53%) were transiently colonized and 80 (47%) were persistently colonized. Compared to uncolonized patients, persistent and transient R-GNB colonization were associated with higher PSMS score: 1.14 (95% confidence interval or CI, 1.05–1.23; P = .002) and 1.10 (95% CI, 1.01–1.19; P = .023), respectively. Persistent colonization was independently associated with longer duration of nursing home stay (1.02; 95% CI, 1.01–1.02; P < .001). Higher readmission rate among persistently colonized patients was observed on unadjusted analysis.

Persistent R-GNB colonization is associated with younger age, functional disability, and prolonged length of nursing home stay. In-depth longitudinal studies to understand new acquisition and transmission dynamics of R-GNB in nursing homes are needed.

The coronavirus disease 2019 pandemic caused substantial changes to healthcare delivery and antibiotic prescribing beginning in March 2020. To assess pandemic impact on Clostridioides difficile infection (CDI) rates, we described patients and trends in facility-level incidence, testing rates, and percent positivity during 2019–2020 in a large cohort of US hospitals.

We estimated and compared rates of community-onset CDI (CO-CDI) per 10,000 discharges, hospital-onset CDI (HO-CDI) per 10,000 patient days, and C. difficile testing rates per 10,000 discharges in 2019 and 2020. We calculated percent positivity as the number of inpatients diagnosed with CDI over the total number of discharges with a test for C. difficile. We used an interrupted time series (ITS) design with negative binomial and logistic regression models to describe level and trend changes in rates and percent positivity before and after March 2020.

In pairwise comparisons, overall CO-CDI rates decreased from 20.0 to 15.8 between 2019 and 2020 (P < .0001). HO-CDI rates did not change. Using ITS, we detected decreasing monthly trends in CO-CDI (−1% per month, P = .0036) and HO-CDI incidence (−1% per month, P < .0001) during the baseline period, prior to the COVID-19 pandemic declaration. We detected no change in monthly trends for CO-CDI or HO-CDI incidence or percent positivity after March 2020 compared with the baseline period.

While there was a slight downward trajectory in CDI trends prior to March 2020, no significant change in CDI trends occurred during the COVID-19 pandemic despite changes in infection control practices, antibiotic use, and healthcare delivery.

To update a 2005 review of nursing home–associated bloodstream infection (NHABSI) regarding sources, organisms, antibiotic resistance, and outcome.

A scoping review of studies of NHABSI identified by searching Google Scholar and Medline with OVID for the period January 1, 2004, to June 30, 2021, was conducted.

Overall, 6 studies of NHABSI were identified. Only 1 study was conducted with residents in North American facilities whereas in the 2005 review all studies were conducted in North America. Escherichia coli was the most common blood isolate, the urinary tract was the most common source of NHABSI; and the case-fatality rates ranged from 21% to 28%. These findings were comparable to those in the 2005 review. However, the proportion of NHABSI episodes due to antibiotic-resistant organisms increased substantially compared to the 2005 review. The most common antibiotic-resistant organisms were extended-spectrum β-lactamase–producing E. coli and Klebsiella spp. The 2 studies that evaluated the relationship between appropriate empiric antibiotic therapy and outcome came to different conclusions.

The only major difference between the 2 reviews in the epidemiology of NHABSI was the marked increase in antibiotic resistance among blood isolates. Despite the increased antibiotic resistance, the case fatality rates in the current review were comparable to those reported in the 2005 review. However, the impact of appropriate empiric antibiotic therapy on outcome of NHABSI remains unclear.

Healthcare personnel (HCP) may encounter unfamiliar personal protective equipment (PPE) during clinical duties, yet we know little about their doffing strategies in such situations.

To better understand how HCP navigate encounters with unfamiliar PPE and the factors that influence their doffing strategies.

The study was conducted at 2 Midwestern academic hospitals.

The study included 70 HCP: 24 physicians and resident physicians, 31 nurses, 5 medical or nursing students, and 10 other staff. Among them, 20 had special isolation unit training.

Participants completed 1 of 4 doffing simulation scenarios involving 3 mask designs, 2 gown designs, 2 glove designs, and a full PPE ensemble. Doffing simulations were video-recorded and reviewed with participants during think-aloud interviews. Interviews were audio-recorded and analyzed using thematic analysis.

Participants identified familiarity with PPE items and designs as an important factor in doffing. When encountering unfamiliar PPE, participants cited aspects of their routine practices such as designs typically used, donning and doffing frequency, and design cues, and their training as impacting their doffing strategies. Furthermore, they identified nonintuitive design and lack of training as barriers to doffing unfamiliar PPE appropriately.

PPE designs may not be interchangeable, and their use may not be intuitive. HCP drew on routine practices, experiences with familiar PPE, and training to adapt doffing strategies for unfamiliar PPE. In doing so, HCP sometimes deviated from best practices meant to prevent self-contamination. Hospital policies and procedures should include ongoing and/or just-in-time training to ensure HCP are equipped to doff different PPE designs encountered during clinical care.

To describe the natural course of procalcitonin (PCT) in patients with coronavirus disease 2019 (COVID-19) and the correlation between PCT and antimicrobial prescribing to provide insight into best practices for PCT data utilization in antimicrobial stewardship in this population.

Single-center, retrospective, observational study.

Michigan Medicine.

Inpatients aged ≥18 years hospitalized March 1, 2020, through October 31, 2021, who were positive for severe acute respiratory coronavirus virus 2 (SARS-CoV-2), with ≥1 PCT measurement. Exclusion criteria included antibiotics for nonpulmonary bacterial infection on admission, treatment with azithromycin only for chronic obstructive pulmonary disease (COPD) exacerbation, and pre-existing diagnosis of cystic fibrosis with positive respiratory cultures.

A structured query was used to extract data. For patients started on antibiotics, bacterial pneumonia (bPNA) was determined through chart review. Multivariable models were used to assess associations of PCT level and bPNA with antimicrobial use.

Of 793 patients, 224 (28.2%) were initiated on antibiotics: 33 (14.7%) had proven or probable bPNA, 125 (55.8%) had possible bPNA, and 66 (29.5%) had no bPNA. Patients had a mean of 4.1 (SD, ±5.2) PCT measurements if receiving antibiotics versus a mean of 2.0 (SD, ±2.6) if not. Initial PCT level was highest for those with proven/probable bPNA and was associated with antibiotic initiation (odds ratio 95% confidence interval [CI], 1.17–1.30). Initial PCT (rate ratio [RR] 95% CI, 1.01–1.08), change in PCT over time (RR 95% CI, 1.01–1.05), and bPNA group (RR 95% CI, 1.23–1.84) were associated with antibiotic duration.

PCT trends are associated with the decision to initiate antibiotics and duration of treatment, independent of bPNA status and comorbidities. Prospective studies are needed to determine whether PCT level can be used to safely make decisions regarding antibiotic treatment for COVID-19.

To examine associations between socioeconomic factors and (1) adherence to methicillin-resistant Staphylococcus aureus (MRSA) posttreatment follow-up swab sampling after 1 and 6 months and (2) successful decolonization treatment.

Cohort study with 2 years of follow-up. Data on patients diagnosed with MRSA were extracted from a regional MRSA database and national registries. We used a cluster-based logistic regression model to estimate the adjusted odds ratios (aOR) and 95% confidence interval (CI) for associations between socioeconomic factors and decolonization treatment.

Danish primary health care.

The rate of adherence to posttreatment follow-up swab sampling among 2,536 cases 1 month after decolonization treatment was 66% (95% CI, 64%–68%), and it decreased to 30% (95% CI, 28%–32%) after 6 months. Living in intermediate municipalities (76–159 inhabitants/km2) or having retired were associated with completed posttreatment follow-up swabs 1 month after decolonization treatment: aOR, 1.40 (95% CI, 1.2–1.74) and aOR, 2.67 (95% CI, 1.16–6.13), respectively. The rate of successful decolonization treatment 2 years after initiating treatment was 36% (95% CI, 34%–38%). Factors associated with successful decolonization treatment included individuals with higher education (aOR, 1.62; 95% CI, 1.22–2.15), early retirees (aOR, 1.63; 95% CI, 1.12–2.38), those living in intermediate municipalities (ie, 160–900+ inhabitants/km2; aOR, 1.35; 95% CI, 1.08–1.68), and those living in predominantly urban municipalities (ie, 160–900+ inhabitants/km2; aOR, 2.04; 95% CI, 1.5–2.76).

Disparities in the effect of decolonization treatment and adherence to MRSA follow-up sampling among MRSA-positive individuals appear to be largely explained by the level of education, area of residence, and employment status.

Carbapenem-resistant Enterobacterales (CRE) pose a serious public health threat and spread rapidly between healthcare facilities (HCFs) during interfacility patient movement. We examined patterns of transmission of CRE associated with network clustering and positions during patient interfacility transfer.

A retrospective cohort study was conducted in the Greater Houston region ofTexas, , and social network analysis was performed by constructing facility-to-facility patient transfer network using CRE surveillance data. The network method (community detection algorithm) was used to detect clustering patterns of CRE in the network. In addition, network measures of centrality and local connectivity (clustering coefficient) were computed for each healthcare facility. Zero-inflated negative binomial regression analysis was applied to test the association between network measures and facility-specific incidence rate of CRE.

A network of 268 healthcare facilities was identified, in which 10 acute-care hospitals (ACHs) alone accounted for 63% of identified CRE cases. Transmission of New Delhi metallo-β-lactamase–producing CRE occurred in 3 clusters, yet all cases were traced to patients who had had medical care abroad. The incidence rate of CRE attributed to ACHs was >4-fold (adjusted rate ratio, 4.5; 95% confidence interval [CI], 3.02–6.72) higher than that of long-term care facilities. Each additional patient shared with another HCF conferred a 3% (95% CI, 2%–4%) increase in the incidence rate of CRE at that HCF.

The incidence rates of CRE at a given HCF was predicted by the healthcare network metrics. Increased surveillance and selective targeting of high-risk facilities are warranted.

To explore an approach to identify the risk of local prevalence of extended-spectrum β-lactamase–producing Enterobacterales (ESBL-E) on ESBL-E colonization or infection and to reassess known risk factors.

Case–control study.

Johns Hopkins Health System emergency departments (EDs) in the Baltimore–Washington, DC, region.

Patients aged ≥18 years with a culture growing Enterobacterales between April 2019 and December 2021. Cases had a culture growing an ESBL-E.

Addresses were linked to Census Block Groups and placed into communities using a clustering algorithm. Prevalence in each community was estimated using the proportion of ESBL-E among Enterobacterales isolates. Logistic regression was used to determine risk factors for ESBL-E colonization or infection.

ESBL-E were detected in 1,167 of 11,224 patients (10.4%). Risk factors included a history of ESBL-E in the prior 6 months (aOR, 20.67; 95% CI, 13.71–31.18), exposure to a skilled nursing or long-term care facility (aOR, 1.64; 95% CI, 1.37–1.96), exposure to a third-generation cephalosporin (aOR, 1.79; 95% CI, 1.46–2.19), exposure to a carbapenem (aOR, 2.31; 95% CI, 1.68–3.18), or exposure to a trimethoprim-sulfamethoxazole (aOR, 1.54; 95% CI, 1.06–2.25) within the prior 6 months. Patients were at lower risk if their community had a prevalence <25th percentile in the prior 3 months (aOR, 0.83; 95% CI, 0.71–0.98), 6 months (aOR, 0.83; 95% CI, 0.71–0.98), or 12 months (aOR, 0.81; 95% CI, 0.68–0.95). There was no association between being in a community in the >75th percentile and the outcome.

This method of defining the local prevalence of ESBL-E may partially capture differences in the likelihood of a patient having an ESBL-E.

To describe IMP-type carbapenemase-producing Pseudomonas aeruginosa outbreaks at Galdakao University Hospital between March 2021 to December 2021.

Outbreak report.

Galdakao University Hospital is a tertiary-care hospital in the Basque Country (northern Spain).

All patients with a positive IMP-type carbapenemase producing Pseudomonas aeruginosa (IMP-PA) culture were included in this study, both colonization and infection cases.

An outbreak investigation was conducted, in which molecular epidemiology analysis [pulsed-field gel electrophoresis and whole-genome sequencing (WGS)] and environmental screenings were performed.

Between March and December 2021, 21 cases of IMP-PA were detected in Galdakao University Hospital: 18 infection cases and 3 colonization cases. In total, 4 different pulsotypes were detected belonging to 4 clones according to WGS: ST175 (n = 14), ST633 (n = 3), ST179 (n = 3), and ST348 (n = 1). IMP-13 was detected in most isolates belonging to the ST175 clone and in all ST179 and ST348 clones, whereas IMP-29 was detected in isolates belonging to the ST633 clone. Clinical isolates belonging to the ST175 clone were isolated mainly from patients admitted to the respiratory ward, and isolates belonging to the ST633 clone from patients admitted to the ICU. Two environmental isolates belonging to the ST175 clone were detected in the respiratory ward.

Molecular and genomic epidemiology revealed that there had been 2 independent IMP-PA outbreaks, one of long duration in the respiratory ward and the other more limited in the ICU.

In the coronavirus disease 2019 (COVID-19) pandemic, child and adolescent psychiatry wards face the risk of severe acute respiratory coronavirus 2 (SARS-CoV-2) introduction and spread within the facility. In this setting, mask and vaccine mandates are hard to enforce, especially for younger children. Surveillance testing may detect infection early and enable mitigation measures to prevent viral spread. We conducted a modeling study to determine the optimal method and frequency of surveillance testing and to analyze the effect of weekly team meetings on transmission dynamics.

Simulation with an agent-based model reflecting ward structure, work processes, and contact networks from a real-world child and adolescent psychiatry clinic with 4 wards, 40 patients, and 72 healthcare workers.

We simulated the spread of 2 SARS-CoV-2 variants over 60 days under surveillance testing with polymerase chain reaction (PCR) tests and rapid antigen tests in different scenarios. We measured the size, peak, and the duration of an outbreak. We compared medians and percentage of spillover events to other wards from 1,000 simulations for each setting.

The outbreak size, peak, and duration were dependent on test frequency, test type, SARS-CoV-2 variant, and ward connectivity. Under surveillance conditions, joint staff meetings and therapists shared between wards did not significantly change median outbreak size under surveillance conditions. With daily antigen testing, outbreaks were mostly confined to 1 ward and median outbreak sizes were lower than with twice-weekly PCR testing (1 vs 22; P < .001).

Modeling can help to understand transmission patterns and guide local infection control measures.