Understanding the role of antibiotic-associated adverse events in influencing antibiotic decision-making.

Objective: To (1) understand the role of antibiotic-associated adverse events (ABX-AEs) on antibiotic decision-making, (2) understand clinician preferences for ABX-AE feedback, and (3) identify ABX-AEs of greatest clinical concern. Design: Focus groups. Setting: Academic medical center. Participants: Medical and surgical house staff, attending physicians, and advanced practice practitioners. Methods: Focus groups were conducted from May 2022 to December 2022. Participants discussed the role of ABX-AEs in antibiotic decision-making and feedback preferences and evaluated the prespecified categorization of ABX-AEs based on degree of clinical concern. Thematic analysis was conducted using inductive coding. Results: Four focus groups were conducted (n = 15). Six themes were identified. (1) ABX-AE risks during initial prescribing influence the antibiotic prescribed rather than the decision of whether to prescribe. (2) The occurrence of an ABX-AE leads to reassessment of the clinical indication for antibiotic therapy. (3) The impact of an ABX-AE on other management decisions is as important as the direct harm of the ABX-AE. (4) ABX-AEs may be overlooked because of limited feedback regarding the occurrence of ABX-AEs. (5) Clinicians are receptive to feedback regarding ABX-AEs but are concerned about it being punitive. (6) Feedback must be curated to prevent clinicians from being overwhelmed with data. Clinicians generally agreed with the prespecified categorizations of ABX-AEs by degree of clinical concern. Conclusions: The themes identified and assessment of ABX-AEs of greatest clinical concern may inform antibiotic stewardship initiatives that incorporate reporting of ABX-AEs as a strategy to reduce unnecessary antibiotic use.

Association of Long-Term, New-Onset, and Postsurgical Diabetes With Survival in Patients With Resectable Pancreatic Cancer: A Retrospective Cohort Study.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis. Identifying modifiable risk factors, such as diabetes, is crucial. In the context of PDAC diagnosis, diabetes manifests as long-term (LTD), new-onset (NOD), or postsurgical (PSD) phenotypes. The link between these diabetes phenotypes and PDAC survival is debated. MATERIALS AND METHODS: We performed a retrospective study on patients with resectable PDAC who underwent pancreatectomy at Johns Hopkins Hospital from 2003 to 2017. We utilized the National Death Index and electronic medical records to determine vital status. We categorized diabetes as LTD, NOD, or PSD based on the timing of diagnosis relative to pancreatic resection. Using multivariable Cox models, we assessed hazard ratios (HRs) for survival times associated with each phenotype, considering known PDAC prognostic factors. RESULTS: Of 1556 patients, the 5-year survival was 19% (95% CI, 17-21). No significant survival differences were observed between diabetes phenotypes and non-diabetic patients. NOD and PSD presented nonsignificant increased risks of death (aHR: 1.14 [95% CI, 0.8-1.19] and 1.05 [95% CI, 0.89-1.25], respectively). LTD showed no survival difference (aHR, 0.98; 95% CI, 0.99-1.31). CONCLUSIONS: No link was found between diabetes phenotypes and survival in resectable PDAC patients. Comprehensive prospective studies are required to validate these results.

An Electronic Algorithm to Identify Vancomycin-Associated Acute Kidney Injury.

Background: The burden of vancomycin-associated acute kidney injury (V-AKI) is unclear because it is not systematically monitored. The objective of this study was to develop and validate an electronic algorithm to identify cases of V-AKI and to determine its incidence. Methods: Adults and children admitted to 1 of 5 health system hospitals from January 2018 to December 2019 who received at least 1 dose of intravenous (IV) vancomycin were included. A subset of charts was reviewed using a V-AKI assessment framework to classify cases as unlikely, possible, or probable events. Based on review, an electronic algorithm was developed and then validated using another subset of charts. Percentage agreement and kappa coefficients were calculated. Sensitivity and specificity were determined at various cutoffs, using chart review as the reference standard. For courses ≥48 hours, the incidence of possible or probable V-AKI events was assessed. Results: The algorithm was developed using 494 cases and validated using 200 cases. The percentage agreement between the electronic algorithm and chart review was 92.5% and the weighted kappa was 0.95. The electronic algorithm was 89.7% sensitive and 98.2% specific in detecting possible or probable V-AKI events. For the 11 073 courses of ≥48 hours of vancomycin among 8963 patients, the incidence of possible or probable V-AKI events was 14.0%; the V-AKI incidence rate was 22.8 per 1000 days of IV vancomycin therapy. Conclusions: An electronic algorithm demonstrated substantial agreement with chart review and had excellent sensitivity and specificity in detecting possible or probable V-AKI events. The electronic algorithm may be useful for informing future interventions to reduce V-AKI.

Healthcare personnel interactive pathogen exposure response system.

Exposure investigations are labor intensive and vulnerable to recall bias. We developed an algorithm to identify healthcare personnel (HCP) interactions from the electronic health record (EHR), and we evaluated its accuracy against conventional exposure investigations. The EHR algorithm identified every known transmission and used ranking to produce a manageable contact list.

The utility of home sleep apnea tests in patients with low versus high pre-test probability for moderate to severe OSA.

PURPOSE: Home sleep apnea tests (HSATs) are an alternative to attended polysomnograms (PSGs) when the pre-test probability for moderate to severe OSA is high. However, insurers often mandate use anytime OSA is suspected regardless of the pre-test probability. Our objective was to determine the ability of HSATs to rule in OSA when the pre-test probability of an apnea hypopnea index (AHI) in the moderate to severe range is low. METHODS: Patients who underwent HSATs were characterized as low or high pre-test probability based on the presence of two symptoms of the STOP instrument plus either BMI > 35 or male gender. The odds of HSAT diagnostic for OSA dependent on pre-test probability was calculated. Stepwise selection determined predictors of non-diagnostic HSAT. As PSG is performed after HSATs that do not confirm OSA, false negative results were assessed. RESULTS: Among 196 individuals, pre-test probability was low in 74 (38%) and high in 122 (62%). A lower percentage of individuals with a low versus high pre-test probability for moderate to severe OSA had HSAT results that confirmed OSA (61 versus 84%, p = 0.0002) resulting in an odds ratio (OR) of 0.29 for confirmatory HSAT in the low pre-test probability group (95% CI [0.146, 0.563]). Multivariate logistic regression demonstrated that age ≤ 50 (OR 3.10 [1.24-7.73]), female gender (OR 3.58[1.50-8.66]), non-enlarged neck circumference (OR 11.50 [2.50-52.93]), and the absence of loud snoring (OR 3.47 [1.30-9.25]) best predicted non-diagnostic HSAT. OSA was diagnosed by PSG in 54% of individuals with negative HSAT which was similar in both pre-test probability groups. CONCLUSION: HSATs should be reserved for individuals with high pre-test probability for moderate to severe disease as opposed to any individual with suspected OSA.