ArticleMedicina intensiva2023
The Bayes factor in the analysis of mechanical power in patients with severe respiratory failure due to SARS-CoV-2.
Article in Medicina intensiva, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Mechanical Power as a Predictor of Outcomes During Mechanical Ventilation in Coronavirus Disease 2019 (COVID-19): An Updated Systematic Review.Journal of clinical medicine · 2026Review
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo specify the degree of probative force of the statistical hypotheses in relation to mortality at 28 days and the threshold value of 17 J/min mechanical power (MP) in patients with respiratory failure secondary to SARS-CoV-2.
designCohort study, longitudinal, analytical.
settingIntensive care unit of a third level hospital in Spain. PATIENTS: Patients admitted for SARS-CoV-2 infection with admission to the ICU between March 2020 and March 2022.
interventionsBayesian analysis with the beta binomial model. MAIN VARIABLES OF INTEREST: Bayes factor, mechanical power.
resultsA total of 253 patients were analyzed. Baseline respiratory rate (BF
conclusionsA MP ≥ 17 J/min value is associated with extreme evidence with 28-day mortality in patients requiring MV due to respiratory failure secondary to SARS-CoV-2 disease.
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