ArticleBMC geriatrics2025
Development and validation of a nomogram for predicting postoperative pulmonary complications in older patients undergoing noncardiac thoracic surgery: a prospective, bicentric cohort study.
Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Development and External Validation of an Explainable Machine-Learning Model for Predicting Postoperative Pulmonary Complications in Older Adults Undergoing Degenerative Spine Surgery.Journal of clinical medicine · 2026Article
- Can we predict postoperative complications in octogenarians undergoing lung resection?BMC geriatrics · 2026Article
- Risk factors, pathogenesis, and botanical drugs interventions for postoperative pulmonary complications after cardiothoracic surgery: a narrative review.Journal of thoracic disease · 2026Review
- Machine learning prediction of long-term postoperative pneumonia risk: a retrospective cohort study.BMC medical informatics and decision making · 2026Article
- Perioperative ΔNLR and ΔPNI independently predict postoperative pulmonary complications in non-small cell lung cancer: a difference analysis-based nomogram.American journal of cancer research · 2026Article
- Predicting Postoperative Pneumonia in ESCC After Neoadjuvant Chemo-Immunotherapy: Combined Use of ARISCAT Score and Inflammatory Biomarkers.Journal of inflammation research · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundThe ARISCAT score, a prospectively developed generic classification for postoperative pulmonary complications (PPCs), has shown excellent predictive performance in general surgery. However, there is no reliable classification instrument for PPCs prediciton in thoracic surgery.
objectiveThis study aimed to develop and validate a novel nomogram for estimating the risk of pulmonary complications in older patients (≥ 65 years) within 30 days after NCTS.
methodsA nomogram was developed using predefined candidate predictors of 30-day PPCs. It was fitted with least absolute shrinkage and selection operator and logistic regression methods. Internal validation was performed using a bootstrap-resampling approach, while external validation used an independent, temporally separated cohort. The model's performance was assessed based on its discriminative potential (area under the receiver operating characteristic curve [AUC]), predictive ability (calibration plots), and clinical utility (net benefit).
resultsIn the development (n = 1449) and validation (n = 449) cohorts, 34.9% and 31.4% of patients, respectively, developed pulmonary complications 30 days post-surgery. The final nomogram incorporated eight predictors (age, surgical approach, desaturation of < 92% for more than 2 min, duration of surgery, smoking status, FEV
conclusionsThis novel nomogram can reliably identify older patients with a high risk for pulmonary complications within 30 days after NCTS.
trial registrationChiCTR2100051170.
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