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Prognostic Factors for Mortality in Patients Infected with Hantavirus: A Systematic Review with GRADE Certainty Assessment

medrxiv(2024)

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摘要
Introduction One of the challenges in managing patients with hantavirus infection is accurately identifying individuals who are at risk of developing severe disease. Prompt identification of these patients can facilitate critical decisions, such as early referral to an intensive care unit. The identified prognostic factors could be incorporated into predictive models to enhance the management of hantavirus infection. Objective To identify and evaluate prognostic factors associated with mortality in hantavirus infection, providing a basis for a risk assessment model for hantavirus mortality Methods We conducted a systematic review following the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) guidelines. We conducted a comprehensive search in PubMed/MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), and Embase from their inception to January 2024. Furthermore, we included studies evaluating individual prognostic factors or risk assessment models of hantavirus infections, with no restrictions on study design, publication status, or language. When feasible, we conducted meta-analyses for prognostic factors using the inverse variance-based method with random effect model. We assessed the certainty of the evidence using the GRADE approach, Results We included 30 studies with a total of 92,183 participants. We identified the following key prognostic factors which predicted and increased mortality and disease severity: over 15 years, female gender, elevated creatinine levels (>1.4 mg/dL), increased hematocrit (>42%), and presence of infiltrates on chest radiographs. Discussion Our systematic review not only sheds light on the pivotal prognostic factors for hantavirus infection but also sets the stage for the development of comprehensive management strategies that are informed by robust empirical evidence. These strategies, underpinned by predictive modeling and regional customization, can significantly enhance outcomes for individuals at risk of severe hantavirus disease, aligning with global health objectives aimed at zoonotic disease control and prevention. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Protocols ### Funding Statement The author(s) received no specific funding for this work. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All relevant data are within the manuscript and its Supporting Information files.
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