Infection Control and Hospital Epidemiology最新文献

Objective: To quantify the impact of patient- and unit-level risk adjustment on infant hospital-onset bacteremia (HOB) standardized infection ratio (SIR) ranking.

Design: A retrospective, multicenter cohort study.

Setting and participants: Infants admitted to 284 neonatal intensive care units (NICUs) in the United States between 2016 and 2021.

Methods: Expected HOB rates and SIRs were calculated using four adjustment strategies: birthweight (model 1), birthweight and postnatal age (model 2), birthweight and NICU complexity (model 3), and birthweight, postnatal age, and NICU complexity (model 4). Sites were ranked according to the unadjusted HOB rate, and these rankings were compared to rankings based on the four adjusted SIR models.

Results: Compared to unadjusted HOB rate ranking (smallest to largest), the number and proportion of NICUs that left the fourth quartile (worst-performing) following adjustments were as follows: adjusted for birthweight (16, 22.5%), birthweight and postnatal age (19, 26.8%), birthweight and NICU complexity (22, 31.0%), birthweight, postnatal age and NICU complexity (23, 32.4%). Comparing NICUs that moved into the better-performing quartiles after birthweight adjustment to those that remained in the better-performing quartiles regardless of adjustment, the median percentage of low birthweight infants was 17.1% (Interquartile Range (IQR): 15.8, 19.2) vs 8.7% (IQR: 4.8, 12.6); and the median percentage of infants who died was 2.2% (IQR: 1.8, 3.1) vs 0.5% (IQR: 0.01, 12.0), respectively.

Conclusion: Adjusting for patient and unit-level complexity moved one-third of NICUs in the worst-performing quartile into a better-performing quartile. Risk adjustment may allow for a more accurate comparison across units with varying levels of patient acuity and complexity.

Objective: Antimicrobial resistance is increased by antibiotic overuse, so it's crucial for stewardship programs to monitor and control their use. Pneumonia, particularly prevalent among older adults in Japan, is requiring higher rates of medical treatment. This study aimed to develop an improved method for benchmarking broad-spectrum antibiotic use in the empiric treatment of pneumonia in older adult inpatients by applying the "smoothed" observed-to-expected (O/E) ratio which adjusts for hospital-level variations and minimizes the effect of extreme values.

Methods: Using nationwide data from the Diagnosis Procedure Combination research group, pneumonia patients between April 1^st 2018 and March 31^st 2020 were analyzed. The primary outcome was the smoothed O/E ratio of the broad-spectrum antibiotic use for hospitals. It was calculated from the predicted values of broad-spectrum antibiotic use that were obtained through multilevel logistic regression using patient characteristics as predictors from data clustered by hospitals. The analysis investigated the risk-adjusted use of broad-spectrum antibiotics among hospitals.

Results: A total of 244,747 patients from 958 hospitals were included, with a mean age of 81 (±8.30) years. The proportion of broad-spectrum antibiotic use was 35.3% (n = 86,316). The prediction model showed a C-statistic of 0.722. There was a noticeable variation in the O/E ratio among hospitals with values ranging from 0.13 (95% CI: 0.09-0.20) to 2.81 (95% CI: 2.64-2.97).

Conclusions: Using a risk-adjusted smoothed O/E ratio, we assessed the use of broad-spectrum antibiotics across hospitals, identifying those with high O/E ratios that may indicate a need for improvement.

Introduction: Cases of hospital-onset bacteremia and fungemia (HOBF) are on the rise in Japanese hospitals, but little is known about their incidence in hospitals and how it relates to the availability of services provided by infectious diseases departments.

Methods: We herein investigated the monthly incidence density of HOBF per 1,000 patient days from 2013 through 2023 at a tertiary care hospital in Japan. The incidence of overall HOBF and pathogen-specific HOBF, including those caused by Enterobacterales, Staphylococcus aureus, coagulase-negative staphylococci (CNS), and Candida species, was tracked. Changes in the HOBF trend before and after the establishment of an infectious diseases department at the hospital were evaluated.

Results: In total, 4,315 HOBF-related events were identified. The overall incidence density of HOBF increased by 2.4-fold from 0.58 per 1,000 PD in 2013 to 1.42 per 1,000 PD in 2023. Both the level and trend changes in the incidence density of overall HOBF (+0.3142 for change in level [P < .001]; +0.0085 for change in trend [P < .001]), HOBF caused by S. aureus (+0.0983 for change in level [P < .001]; +0.0016 for change in trend [P = 0.016]), and Candida spp. (+0.0466 for change in level [P = 0.030]; +0.0019 for change in trend [P = 0.002]) significantly increased after the establishment of the infectious diseases department.

Conclusion: The incidence density of overall HOBF and clinically important pathogen-specific HOBF increased over the last decade. The availability of services through the infectious diseases department was significantly associated with an increase in the HOBF incidence, likely suggesting improvement in the diagnosis of HOBF.

Objectives: To identify risk factors for methicillin-susceptible (MSSA) and methicillin-resistant S. aureus (MRSA) nasal carriage and surgical site infection (SSI) among patients undergoing fracture fixation procedures who were included in a quality improvement protocol involving screening patients for S. aureus nasal carriage and treating carriers with intranasal mupirocin and chlorhexidine bathing.

Design: Retrospective cohort study.

Setting: Level 1 trauma center.

Participants: 1,254 adults who underwent operative fixation of 1,298 extremity or pelvis fractures between 8/1/2014 - 7/31/2017.

Methods: We calculated rates of S. aureus nasal carriage and SSI. We used multivariable stepwise logistic regression and selected the final models based on Akaike information criterion.

Results: Of the 1,040 screened first procedures, 262 (25.19%) were performed on S. aureus nasal carriers: 211 (20.29%) on MSSA carriers and 51 (4.90%) on MRSA carriers. Long-term care facility residence (odds ratio [OR] 3.38; 95% confidence interval [CI] 1.17-9.76) was associated with MRSA nasal carriage. After adjusting for statistically and clinically significant variables, MRSA carriage was significantly associated with any SSI (OR 4.58; 95% CI 1.63-12.88), S. aureus SSI (OR 10.11; 95% CI 3.25-31.42), and MRSA SSI (OR 27.25; 95% CI 5.33-139.24), whereas MSSA carriage was not. Among S. aureus carriers, any chlorhexidine use was documented for 232 (88.55%), and any intranasal mupirocin was documented for 85 (40.28%) MSSA carriers and 33 (64.71%) MRSA carriers.

Conclusions: MRSA carriage was associated with a significant risk of SSI after operative fracture fixation. Many carriers did not undergo decolonization, suggesting that a simplified decolonization protocol is needed.

Rodriguez-Nava et al. present a proof-of-concept study evaluating the use of a secure large language model (LLM) approved for healthcare data for retrospective identification of a specific healthcare-associated infection (HAI)-central line-associated bloodstream infections-from real patient data for the purposes of surveillance.¹ This study illustrates a promising direction for how LLMs can, at a minimum, semi-automate or streamline HAI surveillance activities.

Objective: Validate a public health model identifying patients at high risk for carbapenem-resistant Enterobacterales (CRE) on admission and evaluate performance across a healthcare network.

Design: Retrospective case-control studies.

Participants: Adults hospitalized with a clinical CRE culture within 3 days of admission (cases) and those hospitalized without a CRE culture (controls).

Methods: Using public health data from Atlanta, GA (1/1/2016-9/1/2019), we validated a CRE prediction model created in Chicago. We then closely replicated this model using clinical data from a healthcare network in Atlanta (1/1/2015-12/31/2021) ("Public Health Model") and optimized performance by adding variables from the healthcare system ("Healthcare System Model"). We frequency-matched cases and controls based on year and facility. We evaluated model performance in validation datasets using area under the curve (AUC).

Results: Using public health data, we matched 181 cases to 764,408 controls, and the Chicago model performed well (AUC 0.85). Using clinical data, we matched 91 cases to 384,013 controls. The Public Health Model included age, prior infection diagnosis, number of and mean length of stays in acute care hospitalizations (ACH) in the prior year. The final Healthcare System Model added Elixhauser score, antibiotic days of therapy in prior year, diabetes, admission to the intensive care unit in prior year and removed prior number of ACH. The AUC increased from 0.68 to 0.73.

Conclusions: A CRE risk prediction model using prior healthcare exposures performed well in a geographically distinct area and in an academic healthcare network. Adding variables from healthcare networks improved model performance.

Background: Bloodstream infections (BSI) are associated with high mortality rates, particularly when caused by resistant pathogens. Reducing the delay in diagnosis and initiation of appropriate treatment is crucial for improving clinical outcomes. The implementation of polymerase chain reaction (PCR) tests in the diagnostic process offers a promising approach to achieving quicker identification of pathogens, thereby potentially reducing mortality associated with BSI.

Methods: A difference-in-differences analysis was performed within a New York City hospital system, comparing mortality risk between patients with enterococcal BSI before and after the adoption of BCID2 PCR testing, using as control those with methicillin-sensitive S. aureus BSI, for which diagnostic protocol has been unchanged.

Results: The study included 548 inpatients; 164 diagnosed with vancomycin-resistant enterococci (VRE) BSI and 384 with MSSA BSI. The mean 30-day mortality risk difference in the period post-intervention estimated in our difference-in-differences model was -6.03 per 100 (95% CI: -10.35 to -1.7), with event study plots suggesting minimal deviation from parallel trends in the pre-treatment period.

Conclusions: Findings suggest that introduction of BCID2 PCR testing for enterococcal bloodstream infections (BSI) may be associated with a reduction in mortality, however, interpretation of the effects must be approached with caution given the relative imprecision of estimates. Further research with larger samples is essential to establish a definitive conclusion on the impact of rapid PCR testing on mortality in BSI. This is an innovative approach using causal methods to evaluate interventions aimed at the improvement of infection control and antimicrobial treatment strategies.

Objective: Resilience of the healthcare system has been described as the ability to absorb, adapt, and respond to stress while maintaining the provision of safe patient care. We quantified the impact that stressors associated with the COVID-19 pandemic had on patient safety, as measured by central line-associated bloodstream infections (CLABSIs) reported to the Centers for Disease Control and Prevention's National Healthcare Safety Network.

Design: Acute care hospitals were mandated to report markers of resource availability (staffing and hospital occupancy with COVID-19 inpatients) to the federal government between July 2020 and June 2021. These data were used with community levels of COVID-19 to develop a statistical model to assess factors influencing rates of CLABSIs among inpatients during the pandemic.

Results: After risk adjustment for hospital characteristics, measured stressors were associated with increased CLABSIs. Staff shortages for more than 10% of days per month were associated with a statistically significant increase of 2 CLABSIs per 10,000 central line days versus hospitals reporting staff shortages of less than 10% of days per month. CLABSIs increased with a higher inpatient COVID-19 occupancy rate; when COVID-19 occupancy was 20% or more, there were 5 more CLABSIs per 10,000 central line days versus the referent (less than 5%).

Conclusions: Reporting of data pertaining to hospital operations during the COVID-19 pandemic afforded an opportunity to evaluate resilience of US hospitals. We demonstrate how the stressors of staffing shortages and high numbers of patients with COVID-19 negatively impacted patient safety, demonstrating poor resilience. Understanding stress in hospitals may allow for the development of policies that support resilience and drive safe care.

Objective: We introduced a urinary tract infection (UTI) panel requiring symptom documentation and identification of special populations linked to reflex urine culturing and evaluated its impact on catheter-associated UTI (CAUTI) including during the COVID-19 pandemic.

Design: Quasi-experimental encompassing 3 periods: pre-panel (January 2014-March 2015), post-panel (April 2015-March 2020), and post-panel COVID (April 2020-June 2022).

Setting/participants: Tertiary care center inpatients.

Methods: Poisson regression and interrupted time series (ITS) analysis evaluated changes in catheter days (CD), urine cultures (UC), and CAUTI measured by 1,000 CD and patient days (PD). National Health Safety Network standardized infection ratio (SIR) and standardized utilization ratio (SUR) data were analyzed.

Results: UC per 1,000 PD decreased after implementation (pre-panel 36.9 vs 16.6 post-panel vs 14.4 post-panel COVID, all P < .001). CD declined pre-panel versus post-panel (RR 0.37, P < .001) but not from post-panel to post-panel COVID (RR 0.94, P = .88). UTI panel implementation was associated with a 40% decrease in CAUTI rates per 1,000 CD (P < .001). During the COVID-19 pandemic (post-panel COVID), a nonsignificant increase of 13% (P = .61) in CAUTI was noted but remained 32% lower than pre-panel (P = .02). The slope of change using ITS changed from negative to positive but was nonsignificant (P = .26). CAUTI rates per 1,000 PD demonstrated greater reductions (pre- vs post-panel (RR 0.37; 95% CI, 0.29-0.47) and pre- vs post-panel COVID (RR 0.35; 95% CI, 0.26-0.46)). SIRs were unavailable before 2016, but median SIRs post-panel compared to post-panel COVID were similar (1.05 vs 1.56, respectively, P = .067).

Conclusions: Implementation of the UTI panel was associated with a reduction in both UC and CAUTI with the impact maintained despite the COVID-19 pandemic.