Title :

Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry.

Author(s) :

Izadi, Z. [Auteur]
Gianfrancesco, M. A. [Auteur]
Aguirre, A. [Auteur]
Strangfeld, A. [Auteur]
Mateus, E. F. [Auteur]
Hyrich, K. L. [Auteur]
Gossec, L. [Auteur]
Carmona, L. [Auteur]
Lawson-Tovey, S. [Auteur]
Kearsley-Fleet, L. [Auteur]
Schaefer, M. [Auteur]
Seet, A. M. [Auteur]
Schmajuk, G. [Auteur]
Jacobsohn, L. [Auteur]
Katz, P. [Auteur]
Rush, S. [Auteur]
Al-Emadi, S. [Auteur]
Sparks, J. A. [Auteur]
Hsu, T. Y. [Auteur]
Patel, N. J. [Auteur]
Wise, L. [Auteur]
Gilbert, E. [Auteur]
Duarte-García, A. [Auteur]
Valenzuela-Almada, M. O. [Auteur]
Ugarte-Gil, M. F. [Auteur]
Ribeiro, S. L. E. [Auteur]
De Oliveira Marinho, A. [Auteur]
De Azevedo Valadares, L. D. [Auteur]
Giuseppe, D. D. [Auteur]
Hasseli, R. [Auteur]
Richter, J. G. [Auteur]
Pfeil, A. [Auteur]
Schmeiser, T. [Auteur]
Isnardi, C. A. [Auteur]
Reyes Torres, A. A. [Auteur]
Alle, G. [Auteur]
Saurit, V. [Auteur]
Zanetti, A. [Auteur]
Carrara, G. [Auteur]
Labreuche, Julien [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Centre Hospitalier Régional Universitaire [CHU Lille] [CHRU Lille]
Barnetche, T. [Auteur]
Herasse, M. [Auteur]
Plassart, S. [Auteur]
Santos, M. J. [Auteur]
Rodrigues, A. M. [Auteur]
Robinson, P. C. [Auteur]
Machado, P. M. [Auteur]
Sirotich, E. [Auteur]
Liew, J. W. [Auteur]
Hausmann, J. S. [Auteur]
Sufka, P. [Auteur]
Grainger, R. [Auteur]
Bhana, S. [Auteur]
Costello, W. [Auteur]
Wallace, Z. S. [Auteur]
Yazdany, J. [Auteur]

Journal title :

ACR Open Rheumatology

Abbreviated title :

ACR Open Rheumatol

Volume number :

4

Pages :

872-882

Publication date :

2022-10-12

ISSN :

2578-5745

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Objective Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in ...
Show more >Objective Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

Université de Lille
CHU Lille

Collections :

• METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694

Submission date :

2023-11-15T03:38:36Z
2024-01-11T11:38:21Z