tetano
Editor, Senior Moderator
Clin Microbiol Infect
. 2020 Aug 8;S1198-743X(20)30479-1.
doi: 10.1016/j.cmi.2020.08.003. Online ahead of print.
Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study)
Michele Bartoletti[SUP] 1 [/SUP], Maddalena Giannella[SUP] 2 [/SUP], Luigia Scudeller[SUP] 3 [/SUP], Sara Tedeschi[SUP] 4 [/SUP], Matteo Rinaldi[SUP] 4 [/SUP], Linda Bussini[SUP] 4 [/SUP], Giacomo Fornaro[SUP] 4 [/SUP], Renato Pascale[SUP] 4 [/SUP], Livia Pancaldi[SUP] 4 [/SUP], Zeno Pasquini[SUP] 5 [/SUP], Filippo Trapani[SUP] 4 [/SUP], Lorenzo Badia[SUP] 4 [/SUP], Caterina Campoli[SUP] 4 [/SUP], Marina Tadolini[SUP] 4 [/SUP], Luciano Attard[SUP] 4 [/SUP], Massimo Puoti[SUP] 6 [/SUP], Marco Merli[SUP] 6 [/SUP], Cristina Mussini[SUP] 7 [/SUP], Marianna Menozzi[SUP] 7 [/SUP], Marianna Meschiari[SUP] 7 [/SUP], Mauro Codeluppi[SUP] 8 [/SUP], Francesco Barchiesi[SUP] 5 [/SUP], Francesco Cristini[SUP] 9 [/SUP], Annalisa Saracino[SUP] 10 [/SUP], Alberto Licci[SUP] 11 [/SUP], Silvia Rapuano[SUP] 12 [/SUP], Tommaso Tonetti[SUP] 13 [/SUP], Paolo Gaibani[SUP] 14 [/SUP], Vito Marco Ranieri[SUP] 13 [/SUP], Pierluigi Viale[SUP] 4 [/SUP], PREDICO study group
Collaborators, Affiliations
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 February 22 to April 3 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 (RR)>30bpm, 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 analyzed 1113 patients (644 derivation, 469 validation cohort). Mean (?standard deviation)age was 65.7(?15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in derivation and validation cohort, 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)], RR ≥22bpm [OR 3.75 (95%CI 2.01-7.01)], lymphocytes ≤900/mm[SUP]3[/SUP] [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 ≥10mg/dl [OR 5.91 (95%CI 4.88-7.17)], and lactate dehydrogenase ≥350IU/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 receiver-operator curve (AUROC) was 0.89 (0.86-0.92). At score of >3, sensitivity, specificity, 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: AUROC 0.85 (0.81-0.88). At score of >3, sensitivity, specificity, 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 COVID-19 pandemic.
Keywords: COVID-19; SARS-CoV-2; prognostic tool; severe respiratory failure.
. 2020 Aug 8;S1198-743X(20)30479-1.
doi: 10.1016/j.cmi.2020.08.003. Online ahead of print.
Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-Cov-2 infection: a multicenter cohort study (PREDI-CO study)
Michele Bartoletti[SUP] 1 [/SUP], Maddalena Giannella[SUP] 2 [/SUP], Luigia Scudeller[SUP] 3 [/SUP], Sara Tedeschi[SUP] 4 [/SUP], Matteo Rinaldi[SUP] 4 [/SUP], Linda Bussini[SUP] 4 [/SUP], Giacomo Fornaro[SUP] 4 [/SUP], Renato Pascale[SUP] 4 [/SUP], Livia Pancaldi[SUP] 4 [/SUP], Zeno Pasquini[SUP] 5 [/SUP], Filippo Trapani[SUP] 4 [/SUP], Lorenzo Badia[SUP] 4 [/SUP], Caterina Campoli[SUP] 4 [/SUP], Marina Tadolini[SUP] 4 [/SUP], Luciano Attard[SUP] 4 [/SUP], Massimo Puoti[SUP] 6 [/SUP], Marco Merli[SUP] 6 [/SUP], Cristina Mussini[SUP] 7 [/SUP], Marianna Menozzi[SUP] 7 [/SUP], Marianna Meschiari[SUP] 7 [/SUP], Mauro Codeluppi[SUP] 8 [/SUP], Francesco Barchiesi[SUP] 5 [/SUP], Francesco Cristini[SUP] 9 [/SUP], Annalisa Saracino[SUP] 10 [/SUP], Alberto Licci[SUP] 11 [/SUP], Silvia Rapuano[SUP] 12 [/SUP], Tommaso Tonetti[SUP] 13 [/SUP], Paolo Gaibani[SUP] 14 [/SUP], Vito Marco Ranieri[SUP] 13 [/SUP], Pierluigi Viale[SUP] 4 [/SUP], PREDICO study group
Collaborators, Affiliations
- PMID: 32781244
- PMCID: PMC7414420
- DOI: 10.1016/j.cmi.2020.08.003
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 February 22 to April 3 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 (RR)>30bpm, 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 analyzed 1113 patients (644 derivation, 469 validation cohort). Mean (?standard deviation)age was 65.7(?15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in derivation and validation cohort, 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)], RR ≥22bpm [OR 3.75 (95%CI 2.01-7.01)], lymphocytes ≤900/mm[SUP]3[/SUP] [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 ≥10mg/dl [OR 5.91 (95%CI 4.88-7.17)], and lactate dehydrogenase ≥350IU/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 receiver-operator curve (AUROC) was 0.89 (0.86-0.92). At score of >3, sensitivity, specificity, 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: AUROC 0.85 (0.81-0.88). At score of >3, sensitivity, specificity, 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 COVID-19 pandemic.
Keywords: COVID-19; SARS-CoV-2; prognostic tool; severe respiratory failure.