Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery

Background Postoperative pulmonary complications (PPCs) after thoracoscopic surgery are common. This retrospective study aimed to develop a nomogram to predict PPCs in thoracoscopic surgery. Methods A total of 905 patients who underwent thoracoscopy were randomly enrolled and divided into a training...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Bin Wang, Zhenxing Chen, Ru Zhao, Li Zhang, Ye Zhang
Formato:	article
Lenguaje:	EN
Publicado:	PeerJ Inc. 2021
Materias:	Thoracoscopic surgery Nomograms Postoperative pulmonary complications Medicine R
Acceso en línea:	https://doaj.org/article/396c94ebafcd404b83cc45327f9f898e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:396c94ebafcd404b83cc45327f9f898e
record_format	dspace
spelling	oai:doaj.org-article:396c94ebafcd404b83cc45327f9f898e2021-11-06T15:05:29ZDevelopment and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery10.7717/peerj.123662167-8359https://doaj.org/article/396c94ebafcd404b83cc45327f9f898e2021-11-01T00:00:00Zhttps://peerj.com/articles/12366.pdfhttps://peerj.com/articles/12366/https://doaj.org/toc/2167-8359Background Postoperative pulmonary complications (PPCs) after thoracoscopic surgery are common. This retrospective study aimed to develop a nomogram to predict PPCs in thoracoscopic surgery. Methods A total of 905 patients who underwent thoracoscopy were randomly enrolled and divided into a training cohort and a validation cohort at 80%:20%. The training cohort was used to develop a nomogram model, and the validation cohort was used to validate the model. Univariate and multivariable logistic regression were applied to screen risk factors for PPCs, and the nomogram was incorporated in the training cohort. The discriminative ability and calibration of the nomogram for predicting PPCs were assessed using C-indices and calibration plots. Results Among the patients, 207 (22.87%) presented PPCs, including 166 cases in the training cohort and 41 cases in the validation cohort. Using backward stepwise selection of clinically important variables with the Akaike information criterion (AIC) in the training cohort, the following seven variables were incorporated for predicting PPCs: American Society of Anesthesiologists (ASA) grade III/IV, operation time longer than 180 min, one-lung ventilation time longer than 60 min, and history of stroke, heart disease, chronic obstructive pulmonary disease (COPD) and smoking. With incorporation of these factors, the nomogram achieved good C-indices of 0.894 (95% confidence interval (CI) [0.866–0.921]) and 0.868 (95% CI [0.811–0.925]) in the training and validation cohorts, respectively, with well-fitted calibration curves. Conclusion The nomogram offers good predictive performance for PPCs after thoracoscopic surgery. This model may help distinguish the risk of PPCs and make reasonable treatment choices.Bin WangZhenxing ChenRu ZhaoLi ZhangYe ZhangPeerJ Inc.articleThoracoscopic surgeryNomogramsPostoperative pulmonary complicationsMedicineRENPeerJ, Vol 9, p e12366 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Thoracoscopic surgery Nomograms Postoperative pulmonary complications Medicine R
spellingShingle	Thoracoscopic surgery Nomograms Postoperative pulmonary complications Medicine R Bin Wang Zhenxing Chen Ru Zhao Li Zhang Ye Zhang Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
description	Background Postoperative pulmonary complications (PPCs) after thoracoscopic surgery are common. This retrospective study aimed to develop a nomogram to predict PPCs in thoracoscopic surgery. Methods A total of 905 patients who underwent thoracoscopy were randomly enrolled and divided into a training cohort and a validation cohort at 80%:20%. The training cohort was used to develop a nomogram model, and the validation cohort was used to validate the model. Univariate and multivariable logistic regression were applied to screen risk factors for PPCs, and the nomogram was incorporated in the training cohort. The discriminative ability and calibration of the nomogram for predicting PPCs were assessed using C-indices and calibration plots. Results Among the patients, 207 (22.87%) presented PPCs, including 166 cases in the training cohort and 41 cases in the validation cohort. Using backward stepwise selection of clinically important variables with the Akaike information criterion (AIC) in the training cohort, the following seven variables were incorporated for predicting PPCs: American Society of Anesthesiologists (ASA) grade III/IV, operation time longer than 180 min, one-lung ventilation time longer than 60 min, and history of stroke, heart disease, chronic obstructive pulmonary disease (COPD) and smoking. With incorporation of these factors, the nomogram achieved good C-indices of 0.894 (95% confidence interval (CI) [0.866–0.921]) and 0.868 (95% CI [0.811–0.925]) in the training and validation cohorts, respectively, with well-fitted calibration curves. Conclusion The nomogram offers good predictive performance for PPCs after thoracoscopic surgery. This model may help distinguish the risk of PPCs and make reasonable treatment choices.
format	article
author	Bin Wang Zhenxing Chen Ru Zhao Li Zhang Ye Zhang
author_facet	Bin Wang Zhenxing Chen Ru Zhao Li Zhang Ye Zhang
author_sort	Bin Wang
title	Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
title_short	Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
title_full	Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
title_fullStr	Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
title_full_unstemmed	Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
title_sort	development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery
publisher	PeerJ Inc.
publishDate	2021
url	https://doaj.org/article/396c94ebafcd404b83cc45327f9f898e
work_keys_str_mv	AT binwang developmentandvalidationofanomogramtopredictpostoperativepulmonarycomplicationsfollowingthoracoscopicsurgery AT zhenxingchen developmentandvalidationofanomogramtopredictpostoperativepulmonarycomplicationsfollowingthoracoscopicsurgery AT ruzhao developmentandvalidationofanomogramtopredictpostoperativepulmonarycomplicationsfollowingthoracoscopicsurgery AT lizhang developmentandvalidationofanomogramtopredictpostoperativepulmonarycomplicationsfollowingthoracoscopicsurgery AT yezhang developmentandvalidationofanomogramtopredictpostoperativepulmonarycomplicationsfollowingthoracoscopicsurgery
_version_	1718443660919439360

Development and validation of a nomogram to predict postoperative pulmonary complications following thoracoscopic surgery

Ejemplares similares