ABSTRACT
BACKGROUND: Antibiotics are a strong risk factor for Clostridioides difficile infection (CDI), and CDI incidence is often measured as an important outcome metric for antimicrobial stewardship interventions aiming to reduce antibiotic use. However, risk of CDI from antibiotics varies by agent and dependent on the intensity (i.e., spectrum and duration) of antibiotic therapy. Thus, the impact of stewardship interventions on CDI incidence is variable, and understanding this risk requires a more granular measure of intensity of therapy than traditionally used measures like days of therapy (DOT). METHODS: We performed a retrospective cohort study to measure the independent association between intensity of antibiotic therapy, as measured by the antibiotic spectrum index (ASI), and hospital-associated CDI (HA-CDI) at a large academic medical center between January 2018 and March 2020. We constructed a marginal Poisson regression model to generate adjusted relative risks for a unit increase in ASI per antibiotic day. RESULTS: We included 35,457 inpatient encounters in our cohort. Sixty-eight percent of patients received at least one antibiotic. We identified 128 HA-CDI cases, which corresponds to an incidence rate of 4.1 cases per 10,000 patient-days. After adjusting for known confounders, each additional unit increase in ASI per antibiotic day is associated with 1.09 times the risk of HA-CDI (Relative Risk = 1.09, 95% Confidence Interval: 1.06 to 1.13). CONCLUSIONS: ASI was strongly associated with HA-CDI and could be a useful tool in evaluating the impact of antibiotic stewardship on HA-CDI rates, providing more granular information than the more commonly used days of therapy.
ABSTRACT
Data evaluating dalbavancin use for vertebral osteomyelitis remain limited. In our retrospective cohort, 29 of 34 (85.3%) patients completed their dalbavancin course. Adverse reactions occurred for 6 (17.6%) and infection recurrence in 3 (8.8%) within 90 days. Dalbavancin appears to be safe and well-tolerated for vertebral osteomyelitis.
ABSTRACT
Background: Clinical research focused on the burden and impact of Clostridioides difficile infection (CDI) often relies upon accurate identification of cases using existing health record data. Use of diagnosis codes alone can lead to misclassification of cases. Our goal was to develop and validate a multi-component algorithm to identify hospital-associated CDI (HA-CDI) cases using electronic health record (EHR) data. Methods: We performed a validation study using a random sample of adult inpatients at a large academic hospital setting in Portland, Oregon from January 2018 to March 2020. We excluded patients with CDI on admission and those with short lengths of stay (< 4 days). We tested a multi-component algorithm to identify HA-CDI; case patients were required to have received an inpatient course of metronidazole, oral vancomycin, or fidaxomicin and have at least one of the following: a positive C. difficile laboratory test or the International Classification of Diseases, Tenth Revision (ICD-10) code for non-recurrent CDI. For a random sample of 80 algorithm-identified HA-CDI cases and 80 non-cases, we performed manual EHR review to identify gold standard of HA-CDI diagnosis. We then calculated overall percent accuracy, sensitivity, specificity, and positive and negative predictive value for the algorithm overall and for the individual components. Results: Our case definition algorithm identified HA-CDI cases with 94% accuracy (95% Confidence Interval (CI): 88% to 97%). We achieved 100% sensitivity (94% to 100%), 89% specificity (81% to 95%), 88% positive predictive value (78% to 94%), and 100% negative predictive value (95% to 100%). Requiring a positive C. difficile test as our gold standard further improved diagnostic performance (97% accuracy [93% to 99%], 93% PPV [85% to 98%]). Conclusions: Our algorithm accurately detected true HA-CDI cases from EHR data in our patient population. A multi-component algorithm performs better than any isolated component. Requiring a positive laboratory test for C. difficile strengthens diagnostic performance even further. Accurate detection could have important implications for CDI tracking and research.
ABSTRACT
BACKGROUND & AIMS: Given the myriad causes of altered mental status (AMS), patients with cirrhosis and hepatic encephalopathy often present a diagnostic dilemma. In light of the perceived bleeding tendency of patients with cirrhosis, intracranial hemorrhage (ICH) is often feared, so these patients frequently undergo non-contrast computed tomography (CT) of the head. However, little is known about the diagnostic yield of CT for patients with cirrhosis presenting with AMS. METHODS: We analyzed all unique admissions of patients with cirrhosis who underwent head CT from 2003 through 2013 (N = 462) at the Beth Israel Deaconess Medical Center in Boston. By using blinded reviewers, we coded the indications and results of the CT scans separately and evaluated patient characteristics associated with acute findings. RESULTS: A higher proportion of patients who presented with falls or trauma, focal neurologic signs, or history of ICH were found to have ICH (13 of 146, 8.9%) than of patients who presented with AMS, headache, or fever (1 of 316, 0.3%; P < .0001). The odds ratio of ICH in patients with low-risk indications was 0.02 (95% confidence interval, 0.001-0.14). The number needed to scan (NNS) for each positive result from CT varied by indication: focal neurologic deficits (NNS = 9), fall/trauma (NNS = 20), and AMS (NNS = 293). There was no association between presence of new, acute ICH and platelet count, international normalized ratio, level of creatinine, or Model for End-Stage Liver Disease score. CONCLUSIONS: Despite abnormal hemostatic indices, patients with cirrhosis presenting with AMS in the absence of focal neurologic deficits or trauma have a low likelihood of ICH.
