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Title: | Riesgo quirúrgico tras resección pulmonar anatómica en cirugía torácica. Modelo predictivo a partir de una base de datos nacional multicéntrica |
Author: | Gómez-de Antonio, David Crowley Carrasco, Silvana Romero Román, Alejandra Royuela, Ana Sánchez Calle, Álvaro Call Caja, Sergi Embun, Raul Royo-Crespo, Iñigo Obiols Fornell, Carme Recuero Díaz, José Luis Cabañero Sánchez, Alberto Moreno-Mata, Nicolas Bolufer, Sergio Congregado, Miguel Jimenez, Marcelo F. Aguinagalde, Borja Amor-Alonso, Sergio Arrarás, Miguel Jesús Blanco Orozco, Ana Isabel Boada, Marc Cal Vázquez, Isabel Cilleruelo Ramos, Ángel Fernández-Martín, Elena García-Barajas, Santiago García-Jiménez, Maria Dolores García-Prim, Jose María Garcia-Salcedo, Jose Alberto Gelbenzu-Zazpe, Juan José Giraldo-Ospina, Carlos Fernando Gómez Hernández, María Teresa Hernández, Jorge Illana Wolf, Jennifer D. Jauregui Abularach, Alberto Jiménez, Unai López Sanz, Iker Martínez-Hernández, Néstor J. Martínez-Téllez, Elisabeth Milla Collado, Lucía Mongil Poce, Roberto Ramos Izquierdo, Ricard |
Keywords: | Pulmó Cirurgia Mortalitat Lung Surgery Mortality |
Issue Date: | 24-Feb-2021 |
Publisher: | Elsevier |
Abstract: | Introduction: the aim of this study was to develop a surgical risk prediction model in patients undergoing anatomic lung resections from the registry of the Spanish Video-Assisted Thoracic Surgery Group (GEVATS). Methods: data were collected from 3,533 patients undergoing anatomic lung resection for any diagnosis between December 20, 2016 and March 20, 2018. We defined a combined outcome variable: death or Clavien Dindo grade IV complication at 90 days after surgery. Univariate and multivariate analyses were performed by logistic regression. Internal validation of the model was performed using resampling techniques. Results: the incidence of the outcome variable was 4.29% (95% CI 3.6-4.9). The variables remaining in the final logistic model were: age, sex, previous lung cancer resection, dyspnea (mMRC), right pneumonectomy, and ppo DLCO. The performance parameters of the model adjusted by resampling were: C-statistic 0.712 (95% CI 0.648-0.750), Brier score 0.042 and bootstrap shrinkage 0.854. Conclusions: the risk prediction model obtained from the GEVATS database is a simple, valid, and reliable model that is a useful tool for establishing the risk of a patient undergoing anatomic lung resection. |
Note: | Versió postprint del document publicat a: https://doi.org/10.1016/j.arbres.2021.01.037 |
It is part of: | Archivos de Bronconeumologia, 2021, vol. S0300-2896, num. 21, p. 00070-00073 |
URI: | http://hdl.handle.net/2445/176538 |
Related resource: | https://doi.org/10.1016/j.arbres.2021.01.037 |
ISSN: | 0300-2896 |
Appears in Collections: | Articles publicats en revistes (Patologia i Terapèutica Experimental) Articles publicats en revistes (Cirurgia i Especialitats Medicoquirúrgiques) |
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