Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19

• Published in: Annals of intensive care 2024-08, Vol.14 (1), p.129-11
• Main Authors: Maia, Gabriel, Martins, Camila Marinelli, Marques, Victoria, Christovam, Samantha, Prado, Isabela, Moraes, Bruno, Rezoagli, Emanuele, Foti, Giuseppe, Zambelli, Vanessa, Cereda, Maurizio, Berra, Lorenzo, Rocco, Patricia Rieken Macedo, Cruz, Mônica Rodrigues, Samary, Cynthia dos Santos, Guimarães, Fernando Silva, Silva, Pedro Leme
• Format: Article
• Language: English
• Subjects: Accuracy; Anesthesiology; COVID-19; Critical Care Medicine; Emergency Medicine; External validation; Intensive; Intensive care; Invasive mechanical ventilation; Medicine; Medicine & Public Health; Multiple logistic regression; SOFA score; SpO2; Ventilators
• ISSN: 2110-5820; 2110-5820
• DOI: 10.1186/s13613-024-01357-4

Background This study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index. Methods A retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong’s algorithm. Models were validated externally using an international database. Results Of 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO 2 ), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO 2 , and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p