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Objective To compare the perioperative efficacy and safety of da Vinci robot-assisted thoracoscopic surgery (RATS) for treatment of anterior mediastinal tumors through subxiphoid versus lateral thoracic approaches under the laryngeal mask anesthesia. Methods We retrospectively analyzed the clinical data of 102 patients with anterior-mediastinal tumors treated by RATS under laryngeal mask anesthesia completed by the same operator. Forty-five patients underwent the subxiphoid approach (subxiphoid group), and 57 patients were treated with the lateral thoracic approach (lateral thoracic group). The operating time, intraoperative bleeding, and total postoperative drainage volume in the two groups were compared and analyzed. Results All patients successfully completed resection of the anterior mediastinal tumor without the occurrence of perioperative death. In terms of total postoperative drainage volume, postoperative drainage time, postoperative hospital stay, and VAS pain on postoperative days 2 and 3, the subxiphoid group was more advantages (P < 0.05). No statistically significant difference was found between the two groups in terms of operative time, docking time, total operative time, intraoperative bleeding volume, postoperative day 1 VAS pain score, or postoperative complications (P > 0.05). Conclusion The subxiphoid approach of RATS is safe and feasible for resection of anterior mediastinal tumors. Compared with the lateral thoracic approach, the subxiphoid approach has advantages in terms of rapid postoperative recovery and postoperative pain.
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@#Objective To evaluate the efficacy and safety of robot-assisted thymectomy (RATS) versus video-assisted thoracoscopic thymectomy (VATS). Methods Web of Science, PubMed, EMbase, The Cochrane Library, Wanfang, VIP and CNKI databases were searched by computer from inception to February 2022. Relevant literatures that compared the efficacy and safety of RATS with those of VATS were screened. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included cohort studies, and Review Manager 5.4 software was utilized to perform a meta-analysis. Results A total of 16 retrospective cohort studies were included, covering a total of 1 793 patients (874 patients in the RATS group and 919 patients in the VATS group). The NOS scores of the included studies were≥7 points. Meta-analysis results revealed that RATS had less intraoperative bleeding (MD=−22.45, 95%CI −34.16 to −10.73, P<0.001), less postoperative chest drainage (MD=−80.29, 95%CI −144.86 to −15.72, P=0.010), shorter postoperative drainage time (MD=−0.69, 95%CI −1.08 to −0.30, P<0.001), shorter postoperative hospital stay (MD=−1.14, 95%CI −1.55 to −0.72, P<0.001) and fewer conversion to thoractomy (OR=0.40, 95%CI 0.23 to 0.69, P=0.001) than VATS; whereas, the operative time (MD=8.37, 95%CI −1.21 to 17.96, P=0.090), incidence of postoperative myasthenia gravis (OR=0.85, 95%CI 0.52 to 1.40, P=0.530), overall postoperative complications rate (OR=0.80, 95%CI 0.42 to 1.50, P=0.480) and tumour size (MD=−0.18, 95%CI −0.38 to 0.03, P=0.090) were not statistically different between the two groups. Conclusion In the aspects of intraoperative bleeding, postoperative chest drainage, postoperative drainage time, postoperative hospital stay and conversion to thoracotomy, RATS has unique advantages over the VATS.
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@#Objective To systematically evaluate the accuracy of endoscopy-based artificial intelligence (AI)-assisted diagnostic systems in the diagnosis of early-stage esophageal cancer and provide a scientific basis for its diagnostic value. Methods PubMed, EMbase, The Cochrane Library, Web of Science, Wanfang database, VIP database and CNKI database were searched by computer to search for the relevant literature about endoscopy-based AI-assisted diagnostic systems for the diagnosis of early esophageal cancer from inception to March 2022. The QUADAS-2 was used for quality evaluation of included studies. Meta-analysis of the literature was carried out using Stata 16, Meta-Disc 1.4 and RevMan 5.4 softwares. A bivariate mixed effects regression model was utilized to calculate the combined diagnostic efficacy of the AI-assisted system and meta-regression analysis was conducted to explore the sources of heterogeneity. Results A total of 17 articles were included, which consisted of 13 retrospective cohort studies and 4 prospective cohort studies. The results of the quality evaluation using QUADAS-2 showed that all included literature was of high quality. The obtained meta-analysis results revealed that the AI-assisted system in the diagnosis of esophageal cancer presented a combined sensitivity of 0.94 (95%CI 0.91 to 0.96), a specificity of 0.85 (95%CI 0.74 to 0.92), a positive likelihood ratio of 6.28 (95%CI 3.48 to 11.33), a negative likelihood ratio of 0.07 (95%CI 0.05 to 0.11), a diagnostic odds ratio of 89 (95%CI 38 to 208) and an area under the curve of 0.96 (95%CI 0.94 to 0.98). Conclusion The AI-assisted diagnostic system has a high diagnostic value for early stage esophageal cancer. However, most of the included studies were retrospective. Therefore, further high-quality prospective studies are needed for validation.
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0.05),but incidence of recurrent angina was higher in NHT group(P
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0.05), although there were more patients with large area anterior infarction and enlarged left ventricle in the DEF group (P
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Alcohol-infusion. Conclusion: With the cell-wall-broken extraction process, a higher content of total flavones was obtained from Pollen Typhae .