Michal Svoboda, I. Čundrle, M. Plutinský, Pavel Homolka, L. Mitas, Z. Chovanec, L. Olson, K. Brat
{"title":"New Models for Prediction of Post-Operative Pulmonary Complications in Lung Resection Candidates","authors":"Michal Svoboda, I. Čundrle, M. Plutinský, Pavel Homolka, L. Mitas, Z. Chovanec, L. Olson, K. Brat","doi":"10.1183/23120541.00978-2023","DOIUrl":null,"url":null,"abstract":"In recent years, ventilatory efficiency (VE/VCO2slope) and partial pressure of end-tidal carbon dioxide (PETCO2) emerged as independent predictors of post-operative pulmonary complications (PPC). Single parameters may give only partial information regarding peri-procedural hazards. Accordingly, our aim was to create prediction models with improved ability to stratify PPC risk in patients scheduled for elective lung resection surgery.Thispost-hocanalysis was comprised of consecutive lung resection candidates from two prior prospective trials. All individuals completed pulmonary function tests and cardiopulmonary exercise testing (CPET). Logistic regression analyses were used for identification of risk factors for PPC that were entered into the final risk prediction models. Two risk models were developed; the first used rest PETCO2(for patients with no available CPET data), the second used VE/VCO2slope (for patients with available CPET data). ROC analysis with the De-Long test and area under the curve (AUC) were used for comparison of models.The dataset from 423 patients was randomly split into the derivation (n=310) and validation (n=113) cohorts. Two final models were developed, both including sex, thoracotomy, „atypical“ resection and FEV1/FVC ratio as risk factors. In addition, the first model also included rest PETCO2, while the second model used VE/VCO2slope from CPET. AUCs of risk scores were 0.795 (95% CI: 0.739–0.851) and 0.793 (95% CI: 0.737–0.849); both p<0.001. No differences in AUCs were found between the derivation and validation cohorts.We created two multicomponental models for PPC risk prediction, both having excellent predictive properties.","PeriodicalId":11739,"journal":{"name":"ERJ Open Research","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERJ Open Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1183/23120541.00978-2023","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, ventilatory efficiency (VE/VCO2slope) and partial pressure of end-tidal carbon dioxide (PETCO2) emerged as independent predictors of post-operative pulmonary complications (PPC). Single parameters may give only partial information regarding peri-procedural hazards. Accordingly, our aim was to create prediction models with improved ability to stratify PPC risk in patients scheduled for elective lung resection surgery.Thispost-hocanalysis was comprised of consecutive lung resection candidates from two prior prospective trials. All individuals completed pulmonary function tests and cardiopulmonary exercise testing (CPET). Logistic regression analyses were used for identification of risk factors for PPC that were entered into the final risk prediction models. Two risk models were developed; the first used rest PETCO2(for patients with no available CPET data), the second used VE/VCO2slope (for patients with available CPET data). ROC analysis with the De-Long test and area under the curve (AUC) were used for comparison of models.The dataset from 423 patients was randomly split into the derivation (n=310) and validation (n=113) cohorts. Two final models were developed, both including sex, thoracotomy, „atypical“ resection and FEV1/FVC ratio as risk factors. In addition, the first model also included rest PETCO2, while the second model used VE/VCO2slope from CPET. AUCs of risk scores were 0.795 (95% CI: 0.739–0.851) and 0.793 (95% CI: 0.737–0.849); both p<0.001. No differences in AUCs were found between the derivation and validation cohorts.We created two multicomponental models for PPC risk prediction, both having excellent predictive properties.
期刊介绍:
ERJ Open Research is a fully open access original research journal, published online by the European Respiratory Society. The journal aims to publish high-quality work in all fields of respiratory science and medicine, covering basic science, clinical translational science and clinical medicine. The journal was created to help fulfil the ERS objective to disseminate scientific and educational material to its members and to the medical community, but also to provide researchers with an affordable open access specialty journal in which to publish their work.