1. Development and Validation of a Nomogram for Predicting Postoperative Pulmonary Infection in Patients Undergoing Lung Surgery
- Author
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Jing-Yun Wang, Qian-Yun Pang, Ya-Jun Yang, Yu-Mei Feng, Ying-Ying Xiang, Ran An, and Hong-Liang Liu
- Subjects
Adult ,Nomograms ,Anesthesiology and Pain Medicine ,Lung Neoplasms ,Postoperative Complications ,Humans ,Cardiology and Cardiovascular Medicine ,Lung ,Retrospective Studies - Abstract
To develop and validate a nomogram for predicting postoperative pulmonary infection (PPI) in patients undergoing lung surgery.Single-center retrospective cohort analysis.A university-affiliated cancer hospital PARTICIPANTS: A total of 1,501 adult patients who underwent lung surgery from January 2018 to December 2020.Observation for PPI within 7 days after lung surgery.A complete set of demographics, preoperative variables, and postoperative follow-up data was recorded. The primary outcome was PPI; a total of 125 (8.3%) out of 1,501 patients developed PPI. The variables with p0.1 in univariate logistic regression were included in the multivariate regression, and multivariate logistic regression analysis showed that surgical procedure, surgical duration, the inspired fraction of oxygen in one-lung ventilation, and postoperative pain were independent risk factors for PPI. A nomogram based on these factors was constructed in the development cohort (area under the curve: 0.794, 95% CI 0.744-0.845) and validated in the validation cohort (area under the curve: 0.849, 95% CI 0.786-0.912). The calibration slope was 1 in the development and validation cohorts. Decision curve analysis indicated that when the threshold probability was within a range of 0.02-to-0.58 and 0.02-to-0.42 for the development and validation cohorts, respectively, the nomogram model could provide a clinical net benefit.The authors developed and validated a nomogram for predicting PPI in patients undergoing lung surgery. The prediction model can predict the development of PPI and identify high-risk groups.
- Published
- 2022