RISK STRATIFICATION OF PATIENTS WITH COVID-19 DISEASE THROUGH THE USE OF CLINICAL SCORES IN AN EMERGENCY DEPARTMENT. A review of the literature
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Abstract
The authors have withdrawn the manuscript because there are some errors in the Area Under the Curve values regarding to intensive care unit admission and mortality for some scores analyzed. The article must be revised in its conclusions in order to affirm that NEWS and NEWS2 are the best clinical scores to be used in Emergency to evaluate patients with Covid-19 disease.
Therefore, the authors do not wish this work to be cited as reference for one project. If you have any questions, please contact the corresponding author.
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SciScore for 10.1101/2022.02.03.22270401: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization Inclusion criteria were patients > 18 years with symptoms and diagnosed Covid-19 disease admitted to the ED or directly to the hospital, prospective and retrospective cohort studies, randomized studies, meta-analyses, use or analysis of a clinical score and articles published in English between January 2020 and August 2021 without countries restrictions. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources The research question was: What are the best clinical scores used to predict hospital mortality or worsening of clinical conditions with hospitalization in intensive … SciScore for 10.1101/2022.02.03.22270401: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization Inclusion criteria were patients > 18 years with symptoms and diagnosed Covid-19 disease admitted to the ED or directly to the hospital, prospective and retrospective cohort studies, randomized studies, meta-analyses, use or analysis of a clinical score and articles published in English between January 2020 and August 2021 without countries restrictions. Blinding not detected. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources The research question was: What are the best clinical scores used to predict hospital mortality or worsening of clinical conditions with hospitalization in intensive care in adult patients with Covid-19 who present in EDã PICO Question: Population: Adult population (> 18 years) with confirmed COVID-19 disease presenting in ED or directly hospitalized with symptoms Intervention: Clinical scores and scales Comparison: Clinical judgment Outcomes: Hospital mortality and clinical condition worsening with admission to intensive care Data sources, search strategy: The research of the articles and the consequent review of the literature were performed using databases such as Pubmed, Cochrane Database of Systematic Re-view and CINAHL Database (Cumulative Index to Nursing and Allied Health Literature). Pubmedsuggested: (PubMed, RRID:SCR_004846)Cochrane Database of Systematicsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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