Evidence map›Paper›PMID 40809256›Full record

ArticleJournal of thoracic disease2025

Establishment and validation of a risk prediction model for postoperative persistent cough in lung resection patients: a systematic review and meta-analysis-based approach.

Lei Ye, Guanghui Xia, Guanghong Wu, Jiefang Ding, Qin Wang

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Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Lei YeDepartment of Nursing, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
Guanghui XiaDepartment of Nursing, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
Guanghong WuDepartment of Nursing, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
Jiefang DingDepartment of Thoracic Surgery, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.
Qin WangDepartment of Thoracic Surgery, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative cough is a prevalent complication in lung resection patients, exacerbating postoperative pain, impairing sleep and communication, and thereby reducing overall quality of life. Early identification of high-risk patients and targeted preventive measures are essential to reduce cough frequency, alleviate symptoms, facilitate recovery, and enhance quality of life. This study aimed to develop a predictive model to identify patients at risk of persistent cough following pulmonary resection. Methods: A systematic review and meta-analysis were performed to identify risk factors associated with persistent cough after pulmonary resection. In the predictive model, the natural logarithm of the pooled risk estimate for each factor was used as a coefficient to assign risk prediction scores. Data from 294 patients who underwent pulmonary resection between October and December 2024 were used to evaluate the predictive accuracy of the model. Results: The meta-analysis included 13 studies with 3,669 patients who underwent pulmonary resection, of whom 1,115 developed postoperative chronic cough. Seven significant predictors of persistent cough were identified: lobectomy, right-sided surgery, right upper lobectomy, subcarinal lymph node dissection, lymph node dissection around the bronchial tree, tracheal intubation time (≥172 min), and postoperative acid reflux. The model was validated using logistic regression analysis with an external cohort, yielding an area under the receiver operating characteristic curve of 0.87 (95% confidence interval: 0.82-0.91). A cutoff value of 23.25 was selected with a sensitivity of 0.735 and specificity of 0.849. Conclusions: The predictive model for persistent cough following pulmonary resection, derived from meta-analysis, demonstrates strong predictive performance and shows potential as a valuable tool for clinical risk assessment.

Indexed as

external validationmeta-analysispersistent coughpredictive modelPulmonary resection

Identifiers

PMID40809256
PMCPMC12340329

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