American journal of infection control最新文献

Background: A clean patient care environment is critical for safety, yet medical technology, unclear cleaning ownership, and diverse teams complicate expectations. Reliable cleaning practices are essential.

Methods & results: A partnership between Infection Prevention, Nursing, and Environmental Services led to sustained improvements in room cleanliness and staff understanding of cleaning roles. A toolkit was created including monitoring tools, education, and staff talking points.

Summary: This toolkit provides a framework and tools to support improvement for environmental cleanliness in inpatient settings.

Background: Health care-associated infections (HAIs) pose a serious challenge to health care systems. Early identification of high-risk patients is crucial for optimizing resource allocation and preventive screening. This study develops and evaluates machine learning (ML) models to predict mortality in HAI patients across different hospital wards.

Methods: This cross-sectional study analyzed a dataset of 4,346 HAI-diagnosed patients from a 700-bed hospital in Tehran, Iran, spanning March 2018 to January 2023. The dataset included demographics, clinical factors, and laboratory results. We applied 4 ML algorithms: multilayer perceptron (MLP), extreme gradient boosting, gradient boosting machines, and decision trees. Model performance was assessed using accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve.

Results: MLP achieved the highest accuracy (91%) and area under the receiver operating characteristic curve (0.95), outperforming extreme gradient boosting, gradient boosting machines, and decision trees. Learning curves and cross-validation confirmed its robustness and generalizability.

Conclusions: ML techniques, particularly MLP, effectively predict mortality in HAI patients across hospital departments. By enabling targeted interventions and optimized resource allocation, MLP models can significantly improve HAI management and patient outcomes. Integrating these models into clinical decision support systems may enhance patient care and reduce the burden of HAIs.

Background: Methicillin-resistant Staphylocccus aureus (MRSA) bacteremia causes significant morbidity and mortality. At our center, a semiautomated algorithm is used to identify patients with hospital-attributable (HA) MRSA bacteremia. A postinfection review (PIR) is conducted to determine contributing factors for HA-MRSA bacteremia.

Methods: Incident cases of MRSA bacteremia between April 1, 2017 and December 31, 2023 were reviewed. Demographic and clinical characteristics of patients with HA-MRSA versus non-HA-MRSA bacteremia were analyzed using univariable and multivariable logistic regression analysis.

Results: Among 341 patients with MRSA bacteremia during the study period, 122 (35.8%) had HA-MRSA bacteremia requiring PIR. Factors significantly associated with HA-MRSA bacteremia included invasive image-guided procedures within the preceding 2 weeks (aOR 8.21, 95% CI: 2.63-25.61; P < .001), new MRSA acquisition (aOR 6.01, 95% CI: 2.77-13.03; P < .001), and use of intravenous cannulas (aOR 1.99, 95% CI: 1.12-3.54; P = .019). The most common issue identified in PIRs was suboptimal adherence or erroneous administration of MRSA decolonization therapy (18.9%), which was improved through staff training and patient education.

Conclusions: HA-MRSA bacteremia was associated with preceding invasive image-guided procedures, new MRSA acquisition, and the use of intravenous cannulas. PIRs complemented data analyses by identifying practices contributing to HA-MRSA bacteremia and guiding infection prevention measures.

Background: Textiles in healthcare settings can act as reservoirs for microbial contamination. However, their role in transmitting healthcare-associated infections (HAIs) remains underexplored.

Methods: This scoping review mapped existing evidence on the composition and management of hospital textiles for HAI prevention. A systematic search was conducted across PubMed, CINAHL, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus.

Results: Twenty studies were included, investigating antimicrobial textile compositions and management interventions, such as decontamination methods and replacement schedules. Decontamination of privacy curtains with hydrogen peroxide (spray, wipe, or dry aerosol), quaternary ammonium compounds (daily or biweekly), and sodium hypochlorite (Endurocide brand and BioSmart) showed reductions in bacterial load. BioSmart without hypochlorite showed no significant difference from standard curtains. Endurocide reduced total aerobic count, while Ecomed curtains with silver did not. Effects on multidrug-resistant organisms were inconsistent. Bedding textiles treated with copper oxide, zinc oxide, or Bio-kil nanotechnology yielded mixed results, with some studies reporting HAIs reductions, including catheter-related urinary tract and bloodstream infections, Clostridium-difficile, and multidrug-resistant organisms, while others found no significant effects.

Conclusions: Textile management strategies, including antimicrobial treatments and cleaning protocols, potentially reduce microbial contamination and HAIs. Future research should address gaps in textile handling (laundering, storage, replacement) for comprehensive infection prevention.

Background: Hand hygiene (HH) is essential for infection prevention in health care, but the quality of its performance, meaning how well it is done, receives much less attention than compliance. This review examines how HH technique is assessed and can be improved among health care providers.

Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, 6 databases were searched through May 15, 2025. Studies assessing HH performance quality in health care were included. Quality indicators included technique completeness, product volume, and duration. Study selection, data extraction, and risk-of-bias assessments were performed independently by 2 reviewers.

Results: Forty studies met inclusion criteria. Despite compliance rates, ranging from 23.5% to 93.2%, proper technique was often lacking. Few HH events followed all recommended steps, and frequently missed areas included fingertips, thumbs, and wrists. Alcohol-based hand rubs (ABHRs) outperformed soap and water in quality and coverage. Interventions such as real-time feedback, ultraviolet markers, and augmented reality tools improved technique temporarily, though sustained improvement was rare. Educational interventions showed mixed long-term results.

Conclusions: HH performance quality remains suboptimal even with high compliance. Future efforts should prioritize technique-focused training, innovative feedback, and simplified protocols to enhance HH quality in clinical practice.

Background: Needlestick injuries (NSIs) are major occupational hazard for health care workers, particularly clinical nurses. Regional disparities in NSI incidence and related knowledge, attitude, and practice (KAP) remain underexplored in China.

Methods: A cross-sectional online survey collected 16,070 valid responses from 34 provincial-level regions in China between November 2022 and February 2023. Propensity score matching (PSM) was applied to control for demographic differences, followed by univariate and multivariate analyses to compare KAP levels and influencing factors of NSIs.

Results: After PSM, nurses in Chongqing demonstrated higher frequencies of NSI prevention training, broader adoption of needleless connectors, and more comprehensive institutional management measures (all P < .001) compared with national counterparts. KAP scores in Chongqing were significantly superior across all domains (P < .001), and the self-reported NSI incidence was lower (P = .005). Multivariable analyses identified frequent training (≥3 times/year), awareness of needleless systems, and integration of NSI prevention into hospital quality control systems as independent predictors of higher KAP scores and lower NSI risk.

Conclusions: Clinical nurses in Chongqing exhibited superior KAP profiles and reduced NSI incidence compared with national averages. Systematic training and institutional integration of NSI prevention emerged as critical strategies to enhance occupational safety.

Background: Coronary artery bypass graft (CABG) is a common procedure that can result in surgical complications.

Methods: Cross-sectional study of 757 acute care hospitals performing CABG surgery. Data on 24,066 Medicare beneficiaries were merged with data from the American Hospital Association Annual Survey and ZIP code-based community characteristics from the Social Vulnerability Index (SVI). Multivariate logistic regression models were fit to estimate the association between social vulnerability and CABG surgical site infection (SSI).

Results: Minority Status and Language were associated with an increase in the likelihood of CABG SSI. In a fully adjusted model, patients from the highest Minority Status and Language SVI quartile had a 60% increase in the likelihood of CABG SSI compared to the lowest SVI quartile.

Discussion: These findings suggest that racial and language differences that exist within communities' impact Medicare beneficiaries who undergo CABG surgery. These differences result in a higher risk for SSI.

Conclusions: It is imperative that health care organizations and clinicians recognize that community factors can place surgical patients at increased risk for infection and may require community-based interventions.

Background: This study compared risk-adjusted postoperative infection outcomes estimated by statistical models applied to electronic health record (EHR) data ("automated") to gold-standard manual chart review outcomes estimated by the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP).

Methods: 307,335 adult patients who underwent 441,047 operations in nine surgical specialties at five large hospitals between 2013-2019 were included. Records from 30,603 patients were linked to the local ACS-NSQIP database (97% linkage). Previously published models for estimating preoperative risk and occurrence of postoperative infections were used to estimate observed-to-expected event ratios (O/E) for surgical site infections, urinary tract infections, sepsis/septic shock, and pneumonia.

Results: O/E ratios were similar when comparing automated methods to ACS-NSQIP across 5 hospitals and 4 infection types. The Pearson correlation coefficient of the hospital O/E ratios was 0.77, mean absolute difference was 0.13%, and 100% of the confidence intervals were overlapping. The correlations and mean absolute differences for individual infection types improved as incidence rates increased.

Discussion: Parsimonious statistical models applied to EHR data can be used to accurately estimate hospital risk-adjusted postoperative infection outcomes.

Conclusions: These models could be used to augment postoperative infection surveillance for hospital quality monitoring.