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

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

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

Characterizing Entanglement Sources

We discuss how to characterize entanglement sources with finite sets of measurements. The measurements do not have to be tomographically complete, and may consist of POVMs rather than von Neumann measurements. Our method yields a probability that the source generates an entangled state as well as estimates of any desired calculable entanglement measures, including their error bars. We apply two criteria, namely Akaike's information criterion and the Bayesian information criterion, to compare and assess different models (with different numbers of parameters) describing entanglement-generating devices. We discuss differences between standard entanglement-verificaton methods and our present method of characterizing an entanglement source.Comment: This submission, together with the next one, supersedes arXiv:0806.416

On designing observers for time-delay systems with nonlinear disturbances

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2002 Taylor & Francis LtdIn this paper, the observer design problem is studied for a class of time-delay nonlinear systems. The system under consideration is subject to delayed state and non-linear disturbances. The time-delay is allowed to be time-varying, and the non-linearities are assumed to satisfy global Lipschitz conditions. The problem addressed is the design of state observers such that, for the admissible time-delay as well as non-linear disturbances, the dynamics of the observation error is globally exponentially stable. An effective algebraic matrix inequality approach is developed to solve the non-linear observer design problem. Specifically, some conditions for the existence of the desired observers are derived, and an explicit expression of desired observers is given in terms of some free parameters. A simulation example is included to illustrate the practical applicability of the proposed theory.The work of Z. Wang was supported in part by the University of Kaiserslautern of Germany and the Alexander von Humboldt Foundation of Germany

Probability Models for Degree Distributions of Protein Interaction Networks

The degree distribution of many biological and technological networks has been described as a power-law distribution. While the degree distribution does not capture all aspects of a network, it has often been suggested that its functional form contains important clues as to underlying evolutionary processes that have shaped the network. Generally, the functional form for the degree distribution has been determined in an ad-hoc fashion, with clear power-law like behaviour often only extending over a limited range of connectivities. Here we apply formal model selection techniques to decide which probability distribution best describes the degree distributions of protein interaction networks. Contrary to previous studies this well defined approach suggests that the degree distribution of many molecular networks is often better described by distributions other than the popular power-law distribution. This, in turn, suggests that simple, if elegant, models may not necessarily help in the quantitative understanding of complex biological processes.