Surgical Risk Following Anatomic Lung Resection in Thoracic Surgery: A Prediction Model Derived from a Spanish Multicenter Database [Riesgo quirúrgico tras resección pulmonar anatómica en cirugía torácica. Modelo predictivo a partir de una base de datos nacional multicéntrica]

Gómez de Antonio, D. ; Crowley Carrasco, S. ; Romero Román, A. ; Royuela, A. ; Sánchez Calle, Á. ; Obiols Fornell, C. ; Call Caja, S. ; Embún, R. (Universidad de Zaragoza) ; Royo, Í. ; Recuero, J.L. ; Cabañero, A. ; Moreno, N. ; Bolufer, S. ; Congregado, M. ; Jimenez, M.F. ; Aguinagalde, B. ; Amor-Alonso, S. ; Arrarás, M.J. ; Blanco Orozco, A.I. ; Boada, M. ; Cal, I. ; Cilleruelo Ramos, Á. ; Fernández-Martín, E. ; García-Barajas, S. ; García-Jiménez, M.D. ; García-Prim, J.M. ; Garcia-Salcedo, J.A. ; Gelbenzu-Zazpe, J.J. ; Giraldo-Ospina, C.F. ; Gómez Hernández, M.T. ; Hernández, J. ; Illana Wolf, J.D. ; Jáuregui Abularach, A. ; Jiménez, U. ; López Sanz, I. ; Martínez-Hernández, N.J. ; Martínez-Téllez, E. ; Milla Collado, L. ; Mongil Poce, R. ; Moradiellos-Díez, F.J. ; Moreno-Basalobre, R. ; Moreno Merino, S.B. ; Quero-Valenzuela, F. ; Ramírez-Gil, M.E. ; Ramos-Izquierdo, R. ; Rivo, E. ; Rodríguez-Fuster, A. ; Rojo-Marcos, R. ; Sanchez-Lorente, D. ; Moreno, L.S. ; Simón, C. ; Trujillo-Reyes, J.C. ; López García, C. ; Fibla Alfara, J.J. ; Sesma Romero, J. ; Hernando Trancho, F.

Resumen: 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.

Idioma: Español

DOI: 10.1016/j.arbres.2021.01.037

Año: 2021

Publicado en: Archivos de Bronconeumologia 58, 5 (2021), 398-405
ISSN: 0300-2896

Factor impacto JCR: 6.333 (2021)

Categ. JCR: RESPIRATORY SYSTEM rank: 14 / 66 = 0.212 (2021) - Q1 - T1

Factor impacto CITESCORE: 2.0 - Medicine (Q3)

Factor impacto SCIMAGO: 0.262 - Pulmonary and Respiratory Medicine (Q3)

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Cirugía (Dpto. Cirugía)