ArticleJournal of chest surgery2024
Development of a Risk Scoring Model to Predict Unexpected Conversion to Thoracotomy during Video-Assisted Thoracoscopic Surgery for Lung Cancer.
Article in Journal of chest surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Factors influencing the difficulty of video-assisted thoracoscopic anterior mediastinal tumor resection via the subxiphoid approach.Journal of thoracic disease · 2025Article
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Authors and funding
6 authors.
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Abstract
Background: Unexpected conversion to thoracotomy during planned video-assisted thoracoscopic surgery (VATS) can lead to poor outcomes and comparatively high morbidity. This study was conducted to assess preoperative risk factors associated with unexpected thoracotomy conversion and to develop a risk scoring model for preoperative use, aimed at identifying patients with an elevated risk of conversion. Methods: A retrospective analysis was conducted of 1,506 patients who underwent surgical resection for non-small cell lung cancer. To evaluate the risk factors, univariate analysis and logistic regression were performed. A risk scoring model was established to predict unexpected thoracotomy conversion during VATS of the lung, based on preoperative factors. To validate the model, an additional cohort of 878 patients was analyzed. Results: Among the potentially significant clinical variables, male sex, previous ipsilateral lung surgery, preoperative detection of calcified lymph nodes, and clinical T stage were identified as independent risk factors for unplanned conversion to thoracotomy. A 6-point risk scoring model was developed to predict conversion based on the assessed risk, with patients categorized into 4 groups. The results indicated an area under the receiver operating characteristic curve of 0.747, with a sensitivity of 80.5%, specificity of 56.4%, positive predictive value of 1.8%, and negative predictive value of 91.0%. When applied to the validation cohort, the model exhibited good predictive accuracy. Conclusion: We successfully developed and validated a risk scoring model for preoperative use that can predict the likelihood of unplanned conversion to thoracotomy during VATS of the lung.
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