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An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery

The aim of the study was to develop an algorithm to predict postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery. We analyzed 3,009 patients from the Thoracic Perioperative Database for Geriatrics in our hospital and finally enrolled 1,585 elderl...

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Autores principales: Song, Yanping, Liu, Jingjing, Lei, Mingxing, Wang, Yanfeng, Fu, Qiang, Wang, Bailin, Guo, Yongxin, Mi, Weidong, Tong, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712479/
https://www.ncbi.nlm.nih.gov/pubmed/34970491
http://dx.doi.org/10.3389/fonc.2021.777564
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author Song, Yanping
Liu, Jingjing
Lei, Mingxing
Wang, Yanfeng
Fu, Qiang
Wang, Bailin
Guo, Yongxin
Mi, Weidong
Tong, Li
author_facet Song, Yanping
Liu, Jingjing
Lei, Mingxing
Wang, Yanfeng
Fu, Qiang
Wang, Bailin
Guo, Yongxin
Mi, Weidong
Tong, Li
author_sort Song, Yanping
collection PubMed
description The aim of the study was to develop an algorithm to predict postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery. We analyzed 3,009 patients from the Thoracic Perioperative Database for Geriatrics in our hospital and finally enrolled 1,585 elderly patients (age≧65 years) with lung cancer treated with video-assisted thoracoscopic surgery. The included patients were randomly divided into a training group (n = 793) and a validation group (n = 792). Patients in the training group were used to develop the algorithm after screening up to 30 potential risk factors, and patients in the validation group were used to internally validate the algorithm. External validation of the algorithm was achieved in the external validation dataset after enrolling 165 elderly patients with lung cancer treated with video-assisted thoracoscopic surgery from two hospitals in China. Of all included patients, 9.15% (145/1,585) of patients suffered from postoperative pneumonia in the Thoracic Perioperative Database for Geriatrics, and 10.30% (17/165) of patients had postoperative pneumonia in the external validation dataset. The algorithm consisted of seven variables, including sex, smoking, history of chronic obstructive pulmonary disease (COPD), surgery duration, leukocyte count, intraoperative injection of colloid, and intraoperative injection of hormone. The C-index from the receiver operating characteristic curve (AUROC) was 0.70 in the training group, 0.67 in the internal validation group, and 0.71 in the external validation dataset, and the corresponding calibration slopes were 0.88 (95% confident interval [CI]: 0.37–1.39), 0.90 (95% CI: 0.46–1.34), and 1.03 (95% CI: 0.24–1.83), respectively. The actual probabilities of postoperative pneumonia were 5.14% (53/1031) in the low-risk group, 15.07% (71/471) in the medium-risk group, and 25.30% (21/83) in the high-risk group (p < 0.001). The algorithm can be a useful prognostic tool to predict the risk of developing postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery.
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spelling pubmed-87124792021-12-29 An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery Song, Yanping Liu, Jingjing Lei, Mingxing Wang, Yanfeng Fu, Qiang Wang, Bailin Guo, Yongxin Mi, Weidong Tong, Li Front Oncol Oncology The aim of the study was to develop an algorithm to predict postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery. We analyzed 3,009 patients from the Thoracic Perioperative Database for Geriatrics in our hospital and finally enrolled 1,585 elderly patients (age≧65 years) with lung cancer treated with video-assisted thoracoscopic surgery. The included patients were randomly divided into a training group (n = 793) and a validation group (n = 792). Patients in the training group were used to develop the algorithm after screening up to 30 potential risk factors, and patients in the validation group were used to internally validate the algorithm. External validation of the algorithm was achieved in the external validation dataset after enrolling 165 elderly patients with lung cancer treated with video-assisted thoracoscopic surgery from two hospitals in China. Of all included patients, 9.15% (145/1,585) of patients suffered from postoperative pneumonia in the Thoracic Perioperative Database for Geriatrics, and 10.30% (17/165) of patients had postoperative pneumonia in the external validation dataset. The algorithm consisted of seven variables, including sex, smoking, history of chronic obstructive pulmonary disease (COPD), surgery duration, leukocyte count, intraoperative injection of colloid, and intraoperative injection of hormone. The C-index from the receiver operating characteristic curve (AUROC) was 0.70 in the training group, 0.67 in the internal validation group, and 0.71 in the external validation dataset, and the corresponding calibration slopes were 0.88 (95% confident interval [CI]: 0.37–1.39), 0.90 (95% CI: 0.46–1.34), and 1.03 (95% CI: 0.24–1.83), respectively. The actual probabilities of postoperative pneumonia were 5.14% (53/1031) in the low-risk group, 15.07% (71/471) in the medium-risk group, and 25.30% (21/83) in the high-risk group (p < 0.001). The algorithm can be a useful prognostic tool to predict the risk of developing postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery. Frontiers Media S.A. 2021-12-14 /pmc/articles/PMC8712479/ /pubmed/34970491 http://dx.doi.org/10.3389/fonc.2021.777564 Text en Copyright © 2021 Song, Liu, Lei, Wang, Fu, Wang, Guo, Mi and Tong https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Song, Yanping
Liu, Jingjing
Lei, Mingxing
Wang, Yanfeng
Fu, Qiang
Wang, Bailin
Guo, Yongxin
Mi, Weidong
Tong, Li
An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title_full An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title_fullStr An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title_full_unstemmed An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title_short An External-Validated Algorithm to Predict Postoperative Pneumonia Among Elderly Patients With Lung Cancer After Video-Assisted Thoracoscopic Surgery
title_sort external-validated algorithm to predict postoperative pneumonia among elderly patients with lung cancer after video-assisted thoracoscopic surgery
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712479/
https://www.ncbi.nlm.nih.gov/pubmed/34970491
http://dx.doi.org/10.3389/fonc.2021.777564
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