Objective To evaluate the safety and feasibility of remote robot-assisted thoracoscopic surgery utilizing 5G technology. Methods Clinical data from five patients who underwent 5G remote robot-assisted thoracoscopic surgery at the Thoracic Surgery Center of Gansu Provincial People's Hospital from May to October 2024 were retrospectively analyzed. Results Finally, five patients were included. There were 2 males and 3 females at median age of 50 (42-63) years. All five surgeries (including 1 patient of lobectomy, 3 patients of partial lung resection and 1 patient of mediastinal lesion resection) were successfully completed without conversion to thoracotomy, complications, or mortality. The median intraoperative signal delay across the patients was 39 (37-42) ms. The median psychological load score for the surgeons was 9 (3-13). The median operation time was 100 (80-122) minutes with a median intraoperative blood loss of 100 (30-200) mL. Catheter drainage lasted a median of 4 (3-5) days, and the median drainage volumes on the first, second, and third postoperative day were 200 (100-300) mL, 150 (60-220) mL, and 80 (30-180) mL, respectively. The median postoperative hospital stay was 4 (3-7) days, and the median pain scores on the third postoperative day were 3 (1-4), 3 (0-3), and 1 (0-3), respectively. Conclusion 5G remote robot-assisted thoracoscopic surgery is safe and effective, with good surgical experience, smooth operation and small intraoperative delay.
ObjectiveTo explore the predictive value of the modified frailty index-11 (mFI-11) for postoperative complications in elderly lung cancer patients undergoing robot-assisted lobectomy. MethodsRetrospective collection of clinical data from lung cancer patients aged ≥65 years who underwent robot-assisted lobectomy at the Department of Thoracic Surgery, Gansu Provincial Hospital, from January 2022 to June 2025. Based on the optimal grouping threshold of 0.27 in previous studies for the mFI-11 score, patients were divided into a frail and a non-frail group. Postoperative complications of the two groups were analyzed, and multivariate logistic regression was used to assess the relationship between mFI-11 and postoperative complications. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive efficiency of mFI-11 for postoperative complications. ResultsA total of 161 patients were included, with 77 males and 84 females, and an average age of (68.48±2.90) years. Among them, 103 (64.0%) patients were in the non-frail group and 58 (36%) in the frail group. Differences between the two groups in terms of independent functional status, hypertension requiring drug control, history of type 2 diabetes, history of chronic obstructive pulmonary disease, American Society of Anesthesiologists classification, and tumor staging were all statistically significant (P<0.05). The length of postoperative hospital stay in the frail group was longer than that in the non-frail group [5.50 (5.00, 8.25) d vs. 5.00 (4.00, 5.00) d, P<0.001]. The incidence rates of general respiratory diseases (25.9% vs. 8.7%), hypoproteinemia (15.5% vs. 4.9%), arrhythmia (12.1% vs. 1.9%), bronchopleural fistula (5.2% vs. 0.0%), transfer to ICU for severe complications (10.3% vs. 1.0%), and readmission within 30 days after discharge (12.1% vs. 1.9%) were all higher in the frail group compared to the non-frail group (P<0.05). Multivariate logistic regression analysis found that mFI-11 had a better predictive efficiency for postoperative complications: general respiratory diseases [area under the curve (AUC)=0.759], hypoproteinemia (AUC=0.723), arrhythmia (AUC=0.795), transfer to ICU for severe complications (AUC=0.713), and readmission within 30 days after discharge (AUC=0.702). ConclusionmFI-11 can effectively predict postoperative complications in elderly lung cancer patients undergoing robot-assisted lobectomy and can serve as an objective indicator for identifying high-risk elderly lung cancer patients.
Lung cancer is the malignant tumor with the highest incidence and mortality in China and even worldwide. Non-small cell lung cancer (NSCLC) constitutes the vast majority of cases. The current innovation in lung cancer diagnosis and treatment systems is progressively transitioning from traditional pathological classification to molecular characteristic-guided precision medicine. However, the conventional gold standard for molecular detection, tissue biopsy, faces limitations including invasive procedures and non-repeatable sample acquisition. The breakthrough in liquid biopsy technology has provided new clinical pathways, particularly through circulating tumor DNA (ctDNA) detection for molecular residual disease (MRD) monitoring, which has emerged as a research hotspot in the liquid biopsy field. Through continuous optimization, this approach has achieved breakthroughs in high sensitivity and specificity. Its non-invasive nature eliminates the risks associated with tissue puncture, demonstrating significant potential in various clinical applications including early and advanced NSCLC diagnosis, treatment response monitoring, drug resistance evaluation, and prognosis prediction.