ABSTRACT
@#Objective To compare the safety and efficacy of the da Vinci robot and thoracoscopic subxiphoid approach for the treatment of anterior mediastinal tumors. Methods The clinical data of patients who underwent anterior mediastinal tumor resection through the subxiphoid approach admitted to the same medical group in the Department of Thoracic Surgery of the First Hospital of Lanzhou University between June 2020 and April 2022 were retrospectively analyzed. According to the surgery approach, the patients were divided into a robot-assisted thoracoscopic surgery (RATS) group and a video-assisted thoracoscopic surgery (VATS) group. The perioperative data and the incidence of postoperative complications were compared between the two groups. Results A total of 79 patients were enrolled. There were 41 patients in the RATS group, including 13 males and 28 females, with an average age of 45.61±14.99 years. There were 38 patients in the VATS group, including 14 males and 24 females, with an average age of 47.84±15.05 years. All patients completed the surgery successfully. Hospitalization cost and operative time were higher or longer in the RATS group than those in the VATS group, and the difference was statistically significant (P<0.05). Intraoperative bleeding, postoperative hospital stay, postoperative water and food intake time, postoperative off-bed activity time, white blood cell count, neutrophil percentage and visual analogue scale (VAS) score on the first postoperative day, white blood cell count and neutrophil percentage on the third postoperative day, duration of analgesic pump use, the number of voluntary compressions of the analgesic pump, and mediastinal drainage volume were all superior to those in the VATS group (P<0.05). The differences in VAS scores on the third postoperative day, duration of drainage tube retention and postoperative complication rates were not statistically different between the two groups (P>0.05). Conclusion RATS subxiphoid anterior mediastinum tumor resection is a safe and feasible surgical method with less injury and higher safety, which is conducive to rapid postoperative recovery and has wide clinical application prospects.
ABSTRACT
@#Objective To evaluate the clinical radiological features combined with circulating tumor cells (CTCs) in the diagnosis of invasiveness evaluation of subsolid nodules in lung cancers. Methods Clinical data of 296 patients from the First Hospital of Lanzhou University between February 2019 and February 2021 were retrospectively included. There were 130 males and 166 females with a median age of 62.00 years. Patients were randomly divided into a training set and an internal validation set with a ratio of 3 : 1 by random number table method. The patients were divided into two groups: a preinvasive lesion group (atypical adenomatoid hyperplasia and adenocarcinoma in situ) and an invasive lesion group (microinvasive adenocarcinoma and invasive adenocarcinoma). Independent risk factors were selected by regression analysis of training set and a Nomogram prediction model was constructed. The accuracy and consistency of the model were verified by the receiver operating characteristic curve and calibration curve respectively. Subgroup analysis was conducted on nodules with different diameters to further verify the performance of the model. Specific performance metrics, including sensitivity, specificity, positive predictive value, negative predictive value and accuracy at the threshold were calculated. Results Independent risk factors selected by regression analysis for subsolid nodules were age, CTCs level, nodular nature, lobulation and spiculation. The Nomogram prediction mode provided an area under the curve (AUC) of 0.914 (0.872, 0.956), outperforming clinical radiological features model AUC [0.856 (0.794, 0.917), P=0.003] and CTCs AUC [0.750 (0.675, 0.825), P=0.001] in training set. C-index was 0.914, 0.894 and corrected C-index was 0.902, 0.843 in training set and internal validation set, respectively. The AUC of the prediction model in training set was 0.902 (0.848, 0.955), 0.913 (0.860, 0.966) and 0.873 (0.730, 1.000) for nodule diameter of 5-20 mm, 10-20 mm and 21-30 mm, respectively. Conclusion The prediction model in this study has better diagnostic value, and is more effective in clinical diagnosis of diseases.