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Development and validation of a nomogram for predicting pulmonary complications in elderly patients undergoing thoracic surgery

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机构: [1]Department of Anesthesiology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China [2]Department of Anesthesiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China [3]Department of Anesthesiology, Chinese People’s Armed Police Force Hospital of Beijing, Beijing 100027, China [4]National Clinical Research Center for Geriatric Diseases, The Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China [5]Department of Pain Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China [6]Department of Anesthesiology, The 71st Group Army Hospital of CPLA Army, Xuzhou 221004, China [7]Department of Anesthesiology, 947 Hospital of Chinese PLA, Kashi Prefecture, Xinjiang 844200, China
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关键词: Postoperative pulmonary complications (PPCs) Elderly patients Thoracic surgery Nomogram Prediction

摘要:
Postoperative pulmonary complications (PPCs) remain a prevalent concern among elderly patients undergoing surgery, with a notably higher incidence observed in elderly patients undergoing thoracic surgery. This study aimed to develop a nomogram to predict the risk of PPCs in this population.A total of 2963 elderly patients who underwent thoracic surgery were enrolled and randomly divided into a training cohort (80%, n = 2369) or a validation cohort (20%, n = 593). Univariate and multivariate logistic regression analyses were conducted to identify risk factors for PPCs, and a nomogram was developed based on the findings from the training cohort. The validation cohort was used to validate the model. The predictive accuracy of the model was evaluated by receiver operating characteristic (ROC) curve, area under ROC (AUC), calibration curve, and decision curve analysis (DCA).A total of 918 (31.0%) patients reported PPCs. Nine independent risk factors for PPCs were identified: preoperative presence of chronic obstructive pulmonary disease (COPD), elevated leukocyte count, higher partial pressure of arterial carbon dioxide (PaCO2) level, surgical site, thoracotomy, intraoperative hypotension, blood loss > 100 mL, surgery duration > 180 min, and malignant tumor. The AUC value for the training cohort was 0.739 (95% CI: 0.719-0.762), and it was 0.703 for the validation cohort (95% CI: 0.657-0.749). The P-values for the Hosmer-Lemeshow test were 0.633 and 0.144 for the training and validation cohorts, respectively, indicating a notable calibration curve fit. The DCA curve indicated that the nomogram could be applied clinically if the risk threshold was between 12% and 84%, which was found to be between 8% and 82% in the validation cohort.This study highlighted the pressing need for early detection of PPCs in elderly patients undergoing thoracic surgery. The nomogram exhibited promising predictive efficacy for PPCs in elderly patients undergoing thoracic surgery, enabling the identification of high-risk patients and consequently aiding in the implementation of preventive interventions.© 2024. The Author(s).

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出版当年[2023]版:
大类 | 3 区 医学
小类 | 4 区 老年医学
最新[2023]版:
大类 | 3 区 医学
小类 | 4 区 老年医学
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出版当年[2022]版:
Q2 GERIATRICS & GERONTOLOGY
最新[2023]版:
Q2 GERIATRICS & GERONTOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

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第一作者机构: [1]Department of Anesthesiology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China [2]Department of Anesthesiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China [3]Department of Anesthesiology, Chinese People’s Armed Police Force Hospital of Beijing, Beijing 100027, China [4]National Clinical Research Center for Geriatric Diseases, The Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China
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通讯机构: [1]Department of Anesthesiology, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China [4]National Clinical Research Center for Geriatric Diseases, The Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China
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