Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-CoV-2 infection: a multicentre cohort study (PREDI-CO study)

PREDICO Study Group, Michele Bartoletti, Maddalena Giannella, Luigia Scudeller, Sara Tedeschi, Matteo Rinaldi, Linda Bussini, Giacomo Fornaro, Renato Pascale, Livia Pancaldi, Zeno Pasquini, Filippo Trapani, Lorenzo Badia, Caterina Campoli, Marina Tadolini, Luciano Attard, Massimo Puoti, Marco Merli, Cristina Mussini, Marianna MenozziMarianna Meschiari, Mauro Codeluppi, Francesco Barchiesi, Francesco Cristini, Annalisa Saracino, Alberto Licci, Silvia Rapuano, Tommaso Tonetti, Paolo Gaibani, Vito M. Ranieri, Pierluigi Viale

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: We aimed to develop and validate a risk score to predict severe respiratory failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19). Methods: We performed a multicentre cohort study among hospitalized (>24 hours) patients diagnosed with COVID-19 from 22 February to 3 April 2020, at 11 Italian hospitals. Patients were divided into derivation and validation cohorts according to random sorting of hospitals. SRF was assessed from admission to hospital discharge and was defined as: SpO2 <93% with 100% FiO2, respiratory rate >30 breaths/min or respiratory distress. Multivariable logistic regression models were built to identify predictors of SRF, β-coefficients were used to develop a risk score. Trial Registration NCT04316949. Results: We analysed 1113 patients (644 derivation, 469 validation cohort). Mean (±SD) age was 65.7 (±15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in the derivation and validation cohorts, respectively. At multivariate analysis, risk factors for SRF in the derivation cohort assessed at hospitalization were age ≥70 years (OR 2.74; 95% CI 1.66–4.50), obesity (OR 4.62; 95% CI 2.78–7.70), body temperature ≥38°C (OR 1.73; 95% CI 1.30–2.29), respiratory rate ≥22 breaths/min (OR 3.75; 95% CI 2.01–7.01), lymphocytes ≤900 cells/mm3 (OR 2.69; 95% CI 1.60–4.51), creatinine ≥1 mg/dL (OR 2.38; 95% CI 1.59–3.56), C-reactive protein ≥10 mg/dL (OR 5.91; 95% CI 4.88–7.17) and lactate dehydrogenase ≥350 IU/L (OR 2.39; 95% CI 1.11–5.11). Assigning points to each variable, an individual risk score (PREDI-CO score) was obtained. Area under the receiver-operator curve was 0.89 (0.86–0.92). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 71.6% (65%–79%), 89.1% (86%–92%), 74% (67%–80%) and 89% (85%–91%), respectively. PREDI-CO score showed similar prognostic ability in the validation cohort: area under the receiver-operator curve 0.85 (0.81–0.88). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 80% (73%–85%), 76% (70%–81%), 69% (60%–74%) and 85% (80%–89%), respectively. Conclusion: PREDI-CO score can be useful to allocate resources and prioritize treatments during the COVID-19 pandemic.

Original languageEnglish
Pages (from-to)1545-1553
Number of pages9
JournalClinical Microbiology and Infection
Volume26
Issue number11
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Age
  • C-reactive proteine
  • Coronavirus disease 2019
  • Lactate dehydrogenase
  • Obesity
  • Prognostic tool
  • Severe acute respiratory syndrome coronavirus 2
  • Severe respiratory failure

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

Fingerprint Dive into the research topics of 'Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-CoV-2 infection: a multicentre cohort study (PREDI-CO study)'. Together they form a unique fingerprint.

Cite this