Vancomycin resistant enterococcus risk factors for hospital colonization in hematological patients: a matched case-control study

BackgroundVancomycin-resistant enterococcus (VRE) was the fastest growing pathogen in Europe in 2022 (+ 21%) but its clinical relevance is still unclear. We aim to identify risk factors for acquired VRE rectal colonization in hematological patients and evaluate the clinical impact of VRE colonization on subsequent infection, and 30- and 90-day overall mortality rates, compared to a matched control group.MethodsA retrospective, single center, case-control matched study (ratio 1:1) was conducted in a hematological department from January 2017 to December 2020. Case patients with nosocomial isolation of VRE from rectal swab screening (>= 48 h) were matched to controls by age, sex, ethnicity, and hematologic disease. Univariate and multivariate logistic regression compared risk factors for colonization.ResultsA total of 83 cases were matched with 83 controls. Risk factors for VRE colonization were febrile neutropenia, bone marrow transplant, central venous catheter, bedsores, reduced mobility, altered bowel habits, cachexia, previous hospitalization and antibiotic treatments before and during hospitalization. VRE bacteraemia and Clostridioides difficile infection (CDI) occurred more frequently among cases without any impact on 30 and 90-days overall mortality. Vancomycin administration and altered bowel habits were the only independent risk factors for VRE colonization at multivariate analysis (OR: 3.53 and 3.1; respectively).ConclusionsAntimicrobial stewardship strategies to reduce inappropriate Gram-positive coverage in hematological patients is urgently required, as independent risk factors for VRE nosocomial colonization identified in this study include any use of vancomycin and altered bowel habits. VRE colonization and infection did not influence 30- and 90-day mortality. There was a strong correlation between CDI and VRE, which deserves further investigation to target new therapeutic approaches

Do all critically ill patients with COVID-19 disease benefit from adding tocilizumab to glucocorticoids? A retrospective cohort study.

Background: Treatment guidelines recommend the tocilizumab use in patients with a CRP of >7.5 mg/dL. We aimed to estimate the causal effect of glucocorticoids + tocilizumab on mortality overall and after stratification for PaO2/FiO2 ratio and CRP levels. Methods: This was an observational cohort study of patients with severe COVID-19 pneumonia. The primary endpoint was day 28 mortality. Survival analysis was conducted to estimate the conditional and average causal effect of glucocorticoids + tocilizumab vs. glucocorticoids alone using Kaplan–Meier curves and Cox regression models with a time-varying variable for the intervention. The hypothesis of the existence of effect measure modification by CRP and PaO2/FiO2 ratio was tested by including an interaction term in the model. Results: In total, 992 patients, median age 69 years, 72.9% males, 597 (60.2%) treated with monotherapy, and 395 (31.8%), adding tocilizumab upon respiratory deterioration, were included. At BL, the two groups differed for median values of CRP (6 vs. 7 mg/dL; p 7.5 mg/dL prior to treatment initiation and the largest effect for a CRP > 15 mg/dL. Large randomized studies are needed to establish an exact cut-off for clinical use

Quality of life and intrinsic capacity in patients with post-acute COVID-19 syndrome is in relation to frailty and resilience phenotypes.

Background- The objective of this study was to characterize frailty and resilience in people evaluated for Post-Acute COVID-19 Syndrome (PACS), in relation to quality of life (QoL) and Intrinsic Capacity (IC). Methods- This cross-sectional, observational, study included consecutive people previously hospitalized for severe COVID-19 pneumonia attending Modena (Italy) PACS Clinic from July 2020 to April 2021. Four frailty-resilience phenotypes were built: “fit/resilient”, “fit/non-resilient”, “frail/resilient” and “frail/non-resilient”. Frailty and resilience were defined according to frailty phenotype and Connor Davidson resilience scale (CD-RISC-25) respectively. Study outcomes were: QoL assessed by means of Symptoms Short form health survey (SF-36) and health-related quality of life (EQ-5D-5L) and IC by means of a dedicated questionnaire. Their predictors including frailty-resilience phenotypes were explored in logistic regressions. Results- 232 patients were evaluated, median age was 58.0 years. PACS was diagnosed in 173 (74.6%) patients. Scarce resilience was documented in 114 (49.1%) and frailty in 72 (31.0%) individuals. Predictors for SF-36 score <61.60 were the phenotypes “frail/non-resilient” (OR=4.69, CI:2.08-10.55), “fit/non-resilient” (OR=2.79, CI:1.00-7.73). Predictors for EQ-5D-5L <89.7% were the phenotypes “frail/non-resilient” (OR=5.93, CI: 2.64-13.33) and “frail/resilient” (OR=5.66, CI:1.93-16.54). Predictors of impaired IC (below the mean score value) were “frail/non-resilient” (OR=7.39, CI:3.20-17.07), and “fit/non-resilient” (OR=4.34, CI:2.16-8.71) phenotypes. Conclusions- Resilience is complementary to frailty in the identification of clinical phenotypes with different impact on wellness and QoL. Frailty and resilience should be evaluated in hospitalized COVID-19 patients to identify vulnerable individuals to prioritize urgent health interventions in people with PACS