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To evaluate the efficacy of a new continuously active disinfectant (CAD) to decrease bioburden on high-touch environmental surfaces compared to a standard disinfectant in the intensive care unit.
A single-blind randomized controlled trial with 1:1 allocation.
Medical intensive care unit (MICU) at an urban tertiary-care hospital.
Adult patients admitted to the MICU and on contact precautions.
A new CAD wipe used for daily cleaning.
Samples were collected from 5 high-touch environmental surfaces before cleaning and at 1, 4, and 24 hours after cleaning. The primary outcome was the mean bioburden 24 hours after cleaning. The secondary outcome was the detection of any epidemiologically important pathogen (EIP) 24 hours after cleaning.
In total, 843 environmental samples were collected from 43 unique patient rooms. At 24 hours, the mean bioburden recovered from the patient rooms cleaned with the new CAD wipe (intervention) was 52 CFU/mL, and the mean bioburden was 92 CFU/mL in the rooms cleaned the standard disinfectant (control). After log transformation for multivariable analysis, the mean difference in bioburden between the intervention and control arm was −0.59 (95% CI, −1.45 to 0.27). The odds of EIP detection were 14% lower in the rooms cleaned with the CAD wipe (OR, 0.86; 95% CI, 0.31–2.32).
The bacterial bioburden and odds of detection of EIPs were not statistically different in rooms cleaned with the CAD compared to the standard disinfectant after 24 hours. Although CAD technology appears promising in vitro, larger studies may be warranted to evaluate efficacy in clinical settings.
Hospital readmission is unsettling to patients and caregivers, costly to the healthcare system, and may leave patients at additional risk for hospital-acquired infections and other complications. We evaluated the association between comorbidities present during index coronavirus disease 2019 (COVID-19) hospitalization and the risk of 30-day readmission.
Design, setting, and participants:
We used the Premier Healthcare database to perform a retrospective cohort study of COVID-19 hospitalized patients discharged between April 2020 and March 2021 who were followed for 30 days after discharge to capture readmission to the same hospital.
Among the 331,136 unique patients in the index cohort, 36,827 (11.1%) had at least 1 all-cause readmission within 30 days. Of the readmitted patients, 11,382 (3.4%) were readmitted with COVID-19 as the primary diagnosis. In the multivariable model adjusted for demographics, hospital characteristics, coexisting comorbidities, and COVID-19 severity, each additional comorbidity category was associated with an 18% increase in the odds of all-cause readmission (adjusted odds ratio [aOR], 1.18; 95% confidence interval [CI], 1.17–1.19) and a 10% increase in the odds of readmission with COVID-19 as the primary readmission diagnosis (aOR, 1.10; 95% CI, 1.09–1.11). Lymphoma (aOR, 1.86; 95% CI, 1.58–2.19), renal failure (aOR, 1.32; 95% CI, 1.25–1.40), and chronic lung disease (aOR, 1.29; 95% CI, 1.24–1.34) were most associated with readmission for COVID-19.
Readmission within 30 days was common among COVID-19 survivors. A better understanding of comorbidities associated with readmission will aid hospital care teams in improving postdischarge care. Additionally, it will assist hospital epidemiologists and quality administrators in planning resources, allocating staff, and managing bed-flow issues to improve patient care and safety.
To assess preventability of hospital-onset bacteremia and fungemia (HOB), we developed and evaluated a structured rating guide accounting for intrinsic patient and extrinsic healthcare-related risks.
HOB preventability rating guide was compared against a reference standard expert panel.
A 10-member panel of clinical experts was assembled as the standard of preventability assessment, and 2 physician reviewers applied the rating guide for comparison.
The expert panel independently rated 82 hypothetical HOB scenarios using a 6-point Likert scale collapsed into 3 categories: preventable, uncertain, or not preventable. Consensus was defined as concurrence on the same category among ≥70% experts. Scenarios without consensus were deliberated and followed by a second round of rating.
Two reviewers independently applied the rating guide to adjudicate the same 82 scenarios in 2 rounds, with interim revisions. Interrater reliability was evaluated using the κ (kappa) statistic.
Expert panel consensus criteria were met for 52 scenarios (63%) after 2 rounds.
After 2 rounds, guide-based rating matched expert panel consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewers 1 and 2, respectively. Agreement rates between the 2 reviewers were 84% overall (κ, 0.76; 95% confidence interval [CI], 0.64–0.88]) and 87% (κ, 0.79; 95% CI, 0.65–0.94) for the 52 scenarios with expert consensus.
Preventability ratings of HOB scenarios by 2 reviewers using a rating guide matched expert consensus in most cases with moderately high interreviewer reliability. Although diversity of expert opinions and uncertainty of preventability merit further exploration, this is a step toward standardized assessment of HOB preventability.
To determine whether electronically available comorbidities and laboratory values on admission are risk factors for hospital-onset Clostridioides difficile infection (HO-CDI) across multiple institutions and whether they could be used to improve risk adjustment.
All patients at least 18 years of age admitted to 3 hospitals in Maryland between January 1, 2016, and January 1, 2018.
Comorbid conditions were assigned using the Elixhauser comorbidity index. Multivariable log-binomial regression was conducted for each hospital using significant covariates (P < .10) in a bivariate analysis. Standardized infection ratios (SIRs) were computed using current Centers for Disease Control and Prevention (CDC) risk adjustment methodology and with the addition of Elixhauser score and individual comorbidities.
At hospital 1, 314 of 48,057 patient admissions (0.65%) had a HO-CDI; 41 of 8,791 patient admissions (0.47%) at community hospital 2 had a HO-CDI; and 75 of 29,211 patient admissions (0.26%) at community hospital 3 had a HO-CDI. In multivariable regression, Elixhauser score was a significant risk factor for HO-CDI at all hospitals when controlling for age, antibiotic use, and antacid use. Abnormal leukocyte level at hospital admission was a significant risk factor at hospital 1 and hospital 2. When Elixhauser score was included in the risk adjustment model, it was statistically significant (P < .01). Compared with the current CDC SIR methodology, the SIR of hospital 1 decreased by 2%, whereas the SIRs of hospitals 2 and 3 increased by 2% and 6%, respectively, but the rankings did not change.
Electronically available patient comorbidities are important risk factors for HO-CDI and may improve risk-adjustment methodology.
Background: Hospital-onset bacteremia and fungemia (HOB) may be a preventable hospital-acquired condition and a potential healthcare quality measure. We developed and evaluated a tool to assess the preventability of HOB and compared it to a more traditional consensus panel approach. Methods: A 10-member healthcare epidemiology expert panel independently rated the preventability of 82 hypothetical HOB case scenarios using a 6-point Likert scale (range, 1= “Definitively or Almost Certainly Preventable” to 6= “Definitely or Almost Certainly Not Preventable”). Ratings on the 6-point scale were collapsed into 3 categories: Preventable (1–2), Uncertain (3–4), or Not preventable (5–6). Consensus was defined as concurrence on the same category among ≥70% expert raters. Cases without consensus were deliberated via teleconference, web-based discussion, and a second round of rating. The proportion meeting consensus, overall and by predefined HOB source attribution, was calculated. A structured HOB preventability rating tool was developed to explicitly account for patient intrinsic and extrinsic healthcare-related risks (Fig. 1). Two additional physician reviewers independently applied this tool to adjudicate the same 82 case scenarios. The tool was iteratively revised based on reviewer feedback followed by repeat independent tool-based adjudication. Interrater reliability was evaluated using the Kappa statistic. Proportion of cases where tool-based preventability category matched expert consensus was calculated. Results: After expert panel round 1, consensus criteria were met for 29 cases (35%), which increased to 52 (63%) after round 2. Expert consensus was achieved more frequently for respiratory or surgical site infections than urinary tract and central-line–associated bloodstream infections (Fig. 2a). Most likely to be rated preventable were vascular catheter infections (64%) and contaminants (100%). For tool-based adjudication, following 2 rounds of rating with interim tool revisions, agreement between the 2 reviewers was 84% for cases overall (κ, 0.76; 95% CI, 0.64–0.88]), and 87% for the 52 cases with expert consensus (κ, 0.79; 95% CI, 0.65–0.94). Among cases with expert consensus, tool-based rating matched expert consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewer 1 and reviewer 2, respectively. The proportion of cases rated “uncertain“ was lower among tool-based adjudicated cases with reviewer agreement (15 of 69) than among cases with expert consensus (23 of 52) (Fig. 2b). Conclusions: Healthcare epidemiology experts hold varying perspectives on HOB preventability. Structured tool-based preventability rating had high interreviewer reliability, matched expert consensus in most cases, and rated fewer cases with uncertain preventability compared to expert consensus. This tool is a step toward standardized assessment of preventability in future HOB evaluations.
Background: Estimates of contamination of healthcare personnel (HCP) gloves and gowns with methicillin-resistant Staphylococcus aureus (MRSA) following interactions with colonized or infected patients range from 17% to 20%. Most studies were conducted in the intensive care unit (ICU) setting where patients had a recent positive clinical culture. The aim of this study was to determine the rate of MRSA transmission to HCP gloves and gown in non-ICU acute-care hospital units and to identify associated risk factors. Methods: Patients on contact precautions with history of MRSA colonization or infection admitted to non-ICU settings were randomly selected from electronic health records. We observed patient care activities and cultured the gloves and gowns of 10 HCP interactions per patient prior to doffing. Cultures from patients’ anterior nares, chest, antecubital fossa and perianal area were collected to quantify bacterial bioburden. Bacterial counts were log transformed. Results: We observed 55 patients (Fig. 1), and 517 HCP–patient interactions. Of the HCP–patient interactions, 16 (3.1%) led to MRSA contamination of HCP gloves, 18 (3.5%) led to contamination of HCP gown, and 28 (5.4%) led to contamination of either gloves or gown. In addition, 5 (12.8%) patients had a positive clinical or surveillance culture for MRSA in the prior 7 days. Nurses, physicians and technicians were grouped in “direct patient care”, and rest of the HCPs were included in “no direct care group.” Of 404 interactions, 26 (6.4%) of providers in the “direct patient care” group showed transmission of MRSA to gloves or gown in comparison to 2 of 113 (1.8%) interactions involving providers in the “no direct patient care” group (P = .05) (Fig. 2). The median MRSA bioburden was 0 log 10CFU/mL in the nares (range, 0–3.6), perianal region (range, 0–3.5), the arm skin (range, 0-0.3), and the chest skin (range, 0–6.2). Detectable bioburden on patients was negatively correlated with the time since placed on contact precautions (rs= −0.06; P < .001). Of 97 observations with detectable bacterial bioburden at any site, 9 (9.3%) resulted in transmission of MRSA to HCP in comparison to 11 (3.6%) of 310 observations with no detectable bioburden at all sites (P = .03). Conclusions: Transmission of MRSA to gloves or gowns of HCP caring for patients on contact precautions for MRSA in non-ICU settings was lower than in the ICU setting. More evidence is needed to help guide the optimal use of contact precautions for the right patient, in the right setting, for the right type of encounter.
The transmission rate of methicillin-resistant Staphylococcus aureus (MRSA) to gloves or gowns of healthcare personnel (HCP) caring for MRSA patients in a non–intensive care unit setting was 5.4%. Contamination rates were higher among HCP performing direct patient care and when patients had detectable MRSA on their body. These findings may inform risk-based contact precautions.
We studied the association between chlorhexidine gluconate (CHG) concentration on skin and resistant bacterial bioburden. CHG was almost always detected on the skin, and detection of methicillin-resistant Staphylococcus aureus, carbapenem-resistant Enterobacteriaceae, and vancomycin-resistant Enterococcus on skin sites was infrequent. However, we found no correlation between CHG concentration and bacterial bioburden.
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