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Diaphragm excursion difference as an adjunct predictor marker of postoperative pulmonary complications in video-assisted thoracoscopic surgery: a prospective, observational study

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Video-assisted thoracoscopic surgery (VATS) often leads to a significant number of postoperative pulmonary complications (PPCs). The diaphragm is the primary muscle involved in respiration. Diaphragm ultrasound is increasingly used as a noninvasive and portable tool for evaluating diaphragmatic contractile function. The diaphragm excursion difference (DED) provides a valuable predictive measure for clinical outcomes. This prospective, observational study aimed to evaluate the predictive feasibility of DED in relation to PPCs in patients undergoing VATS. Methods: Between March and August 2023, a total of 151 patients undergoing VATS were enrolled in the study. Each patient underwent diaphragm ultrasound examinations both before anesthesia and within one hour after extubation. During these examinations, diaphragm excursion (DE) was recorded during quiet breathing (QB) and deep breathing (DB). The DED and diaphragm excursion fraction (DEF) were calculated at these two time points. The primary outcome measured was the incidence of major pulmonary complications occurring within seven days after surgery, while secondary outcomes included the rate of diaphragm dysfunction, duration of hospitalization, oxygenation status, and pain scores on the first and second postoperative days. Results: . 0.44±0.12, P<0.001) compared to those without PPCs. In receiver operating characteristic curve analysis, the postoperative DED demonstrated a high sensitivity of 90.6% and a lower specificity of 64.7% for predicting PPCs, with an area under the curve (AUC) of 0.860 and a 95% confidence interval (CI) ranging from 0.788 to 0.926. Conclusions: After VATS, lower postoperative DED may serve as an additional marker. This can help predict the risk of pulmonary complications.
Authors: Ruixue Yuan, Wanling Xiong, Wei Ran, Ning Liang, Jie Tang, Lin Cheng, Xia Yin, Jin Gao
Language: English
Field: Medicine
Open Access status: diamond
OpenAlex ID: W4408034690
FWCI: 2.302
Cites:
Cited by: 3
Related to: 10