Impact of time to appropriate therapy on mortality in patients with vancomycin-intermediate Staphylococcus aureus infection

Despite the increasing incidence of vancomycin-intermediate Staphylococcus aureus (VISA) infections, few studies have examined the impact of delay in receipt of appropriate antimicrobial therapy on outcomes in VISA patients. We examined the effects of timing of appropriate antimicrobial therapy in a cohort of patients with sterile-site methicillin-resistant S. aureus (MRSA) and VISA infections. In this single-center, retrospective cohort study, we identified all patients with MRSA or VISA sterile-site infections from June 2009 to February 2015. Clinical outcomes were compared according to MRSA/VISA classification, demographics, comorbidities, and antimicrobial treatment. Thirty-day all-cause mortality was modeled with Kaplan-Meier curves. Multivariate logistic regression analysis (MVLRA) was used to determine odds ratios for mortality. We identified 354 patients with MRSA (n = 267) or VISA (n = 87) sterile-site infection. Fifty-five patients (15.5%) were nonsurvivors. Factors associated with mortality in MVLRA included pneumonia, unknown source of infection, acute physiology and chronic health evaluation (APACHE) II score, solid-organ malignancy, and admission from skilled care facilities. Time to appropriate antimicrobial therapy was not significantly associated with outcome. Presence of a VISA infection compared to that of a non-VISA S. aureus infection did not result in excess mortality. Linezolid use was a risk for mortality in patients with APACHE II scores of ≥14. Our results suggest that empirical vancomycin use in patients with VISA infections does not result in excess mortality. Future studies should (i) include larger numbers of patients with VISA infections to confirm the findings presented here and (ii) determine the optimal antibiotic therapy for critically ill patients with MRSA and VISA infections

Augmented renal clearance is not a risk factor for mortality in Enterobacteriaceae bloodstream infections treated with appropriate empiric antimicrobials

The main objective of the study was to assess whether augmented renal clearance was a risk factor for mortality in a cohort of patients with Enterobacteriaceae sepsis, severe sepsis, or septic shock that all received appropriate antimicrobial therapy within 12 hours. Using a retrospective cohort from Barnes-Jewish Hospital, a 1,250-bed teaching hospital, we collected data on individuals with Enterobacteriaceae sepsis, severe sepsis, and septic shock who received appropriate initial antimicrobial therapy between June 2009 and December 2013. Clinical outcomes were compared according to renal clearance, as assessed by Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas, sepsis classification, demographics, severity of illness, and comorbidities. We identified 510 patients with Enterobacteriaceae bacteremia and sepsis, severe sepsis, or septic shock. Sixty-seven patients (13.1%) were nonsurvivors. Augmented renal clearance was uncommon (5.1% of patients by MDRD and 3.0% by CKD-EPI) and was not associated with increased mortality. Our results are limited by the absence of prospective determination of augmented renal clearance. However, in this small cohort, augmented renal clearance as assessed by MDRD and CKD-EPI does not seem to be a risk factor for mortality in patients with Enterobacteriaceae sepsis. Future studies should assess this finding prospectively

Telemedicine infectious diseases consultations and clinical outcomes: A systematic review

Background: Telemedicine use is increasing in many specialties, but its impact on clinical outcomes in infectious diseases has not been systematically reviewed. We reviewed the current evidence for clinical effectiveness of telemedicine infectious diseases consultations, including outcomes of mortality, hospital readmission, antimicrobial use, cost, length of stay, adherence, and patient satisfaction. Methods: We queried Ovid MEDLINE 1946-, Embase.com 1947-, Scopus 1823-, Cochrane Database of Systematic Reviews (CDSR), Cochrane Central Register of Controlled Trials (CENTRAL), and ClinicalTrials.gov 1997- through August 5, 2019, for studies looking at clinical outcomes of infectious diseases in the setting of telemedicine use. We did not restrict by language or year of publication. Clinical outcomes searched included 30-day all-cause mortality, 30-day readmissions, patient compliance/adherence, patient satisfaction, cost or cost-effectiveness, length of hospital stay, antimicrobial use, and antimicrobial stewardship. Bias was assessed using standard methodologies. PROSPERO CRD42018105225. Results: From a search pool of 1154 studies, only 18 involved telemedicine infectious diseases consultation and our selected clinical outcomes. The outcomes tracked were heterogeneous, precluding meta-analysis, and the majority of studies were of poor quality. Overall, clinical outcomes with telemedicine infectious diseases consultation seem comparable to in-person infectious diseases consultation. Conclusions: Although in widespread use, the clinical effectiveness of telemedicine infectious diseases consultations has yet to be sufficiently studied. Further studies, or publication of previously collected and available data, are warranted to verify the cost-effectiveness of this widespread practice. Systematic review registration: PROSPERO CRD42018105225

Comparing compact binary parameter distributions I: Methods

Being able to measure each merger's sky location, distance, component masses, and conceivably spins, ground-based gravitational-wave detectors will provide a extensive and detailed sample of coalescing compact binaries (CCBs) in the local and, with third-generation detectors, distant universe. These measurements will distinguish between competing progenitor formation models. In this paper we develop practical tools to characterize the amount of experimentally accessible information available, to distinguish between two a priori progenitor models. Using a simple time-independent model, we demonstrate the information content scales strongly with the number of observations. The exact scaling depends on how significantly mass distributions change between similar models. We develop phenomenological diagnostics to estimate how many models can be distinguished, using first-generation and future instruments. Finally, we emphasize that multi-observable distributions can be fully exploited only with very precisely calibrated detectors, search pipelines, parameter estimation, and Bayesian model inference