Selected article for: "logistic regression analysis and ROC curve"
Author: Kafan, Samira; Tadbir Vajargah, Kiana; Sheikhvatan, Mehrdad; Tabrizi, Gholamreza; Salimzadeh, Ahmad; Montazeri, Mahnaz; Majidi, Fazeleh; Maghuli, Negin; Pazoki, Marzieh
Title: Predicting Risk Score for Mechanical Ventilation in Hospitalized Adult Patients Suffering from COVID-19
  • Cord-id: y766la18
  • Document date: 2021_4_21
    • ID: y766la18
    Snippet: BACKGROUND: COVID-19 has become a pandemic since December 2019, causing millions of deaths worldwide. It has a wide spectrum of severity, ranging from mild infection to severe illness requiring mechanical ventilation. In the middle of a pandemic, when medical resources (including mechanical ventilators) are scarce, there should be a scoring system to provide the clinicians with the information needed for clinical decision-making and resource allocation. OBJECTIVES: This study aimed to develop a
    Document: BACKGROUND: COVID-19 has become a pandemic since December 2019, causing millions of deaths worldwide. It has a wide spectrum of severity, ranging from mild infection to severe illness requiring mechanical ventilation. In the middle of a pandemic, when medical resources (including mechanical ventilators) are scarce, there should be a scoring system to provide the clinicians with the information needed for clinical decision-making and resource allocation. OBJECTIVES: This study aimed to develop a scoring system based on the data obtained on admission, to predict the need for mechanical ventilation in COVID-19 patients. METHODS: This study included COVID-19 patients admitted to Sina Hospital, Tehran University of Medical Sciences from February 20 to May 29, 2020. Patients' data on admission were retrospectively recruited from Sina Hospital COVID-19 Registry (SHCo-19R). Multivariable logistic regression and receiver operating characteristic (ROC) curve analysis were performed to identify the predictive factors for mechanical ventilation. RESULTS: A total of 681 patients were included in the study; 74 patients (10.9%) needed mechanical ventilation during hospitalization, while 607 (89.1%) did not. Multivariate logistic analysis revealed that age (OR,1.049; 95% CI:1.008-1.091), history of diabetes mellitus (OR,3.216; 95% CI:1.134-9.120), respiratory rate (OR,1.051; 95% CI:1.005-1.100), oxygen saturation (OR,0.928; 95% CI:0.872-0.989), CRP (OR,1.013; 95% CI:1.001-1.024) and bicarbonate level (OR,0.886; 95% CI:0.790-0.995) were risk factors for mechanical ventilation during hospitalization. CONCLUSIONS: A risk score has been developed based on the available data within the first hours of hospital admission to predict the need for mechanical ventilation. This risk score should be further validated to determine its applicability in other populations.

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