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find Author "YANG Zilin" 2 results
  • Preoperative localization indication of clinical peripheral pulmonary ground-glass nodules by Da Vinci robot surgery

    ObjectiveTo investigate the preoperative localization of pulmonary glabrous nodules.MethodsA total of 192 patients admitted to General Hospital of Northern Theater Command from April 2012 to September 2019 were selected for the study. There were 95 males and 97 females at an age of 56.47±11.79 years. All patients completed preoperative examination, and were divided into a positioning group (n=97) and a non-positioning group (n=95) according to whether the preoperative positioning was performed. And the surgical indicators between the two groups were compared. According to the substance of ground-glass opacity, they were divided into a pure ground-glass nodules group (n=23) and a mixed ground-glass nodules group (n=74) in the positioning group and a pure ground-glass nodules group (n=14) and a mixed ground-glass nodules group (n=81) in the non-positioning group . According to the size and distance of the nodules from the pleura and whether the nodules could be detected, the corresponding linear function was obtained.ResultsThe operative time of methylene blue localization group was shorter than that of the no localization group. In the scatter plot, the corresponding diameter and depth of the nodules and the corresponding coordinate points which can be explored were described. And linear regression was performed on all the coordinate points to obtain the linear function: depth=0.648×diameter–1.446 (mm). It can be used as an indication for the preoperative localization of pure ground-glass nodules in Da Vinci robotic surgery. Linear function: depth=0.559 5×diameter+0.56 (mm). It can be used as an indication of preoperative localization of mixed ground-glass nodules in Da Vinci robotic surgery.ConclusionThis equation can be used as a preoperative indication for clinical peripheral pulmonary ground-glass nodules.

    Release date:2020-02-26 04:33 Export PDF Favorites Scan
  • Influencing factors analysis of thoracic drainage time after da Vinci robot lung cancer surgery and preventive solution

    ObjectiveTo explore the factors that affect the drainage time of da Vinci robot lung cancer surgery, to analyze the coping strategies, and to provide a basis for shortening the drainage time of patients after surgery and speeding up the patients' recovery.MethodsThe clinical data of 131 patients who underwent da Vinci robot lung cancer surgery at the Department of Thoracic Surgery, General Hospital of Northern Theater Command from January 2019 to October 2019 were retrospectively analyzed. Among them, 68 were males and 63 were females, with an average age of 59.84±9.66 years. According to the postoperative thoracic drainage time, the patients were divided into two groups including a group A (drainage time≤ 5 days) and a group B (drainage time >5 days). Univariate analysis and logistic multivariate regression analysis were used to analyze the factors that may affect postoperative drainage time, and the correlation between different influencing factors and thoracic drainage time after da Vinci robot lung cancer surgery.ResultsLogistic multivariate analysis showed that age≥60 years (P=0.014), diabetes mellitus (P=0.035), operation time≥130 min (P=0.018), number of lymph node dissections≥15 (P=0.002), and preoperative albumin<38.45 g/L (P=0.010) were independent factors affecting the drainage time of da Vinci robot lung cancer surgery.ConclusionFor elderly patients with diabetes mellitus during the perioperative period, blood glucose should be actively controlled, reasonable surgical strategies should be formulated to ensure the safety and effectiveness of the operation, while reducing intraoperative damage and shortening the operation time. After the operation, patients should be guided to strengthen active coughing, expectoration and lung expansion. Thereby it can shorten drainage time and speed up the recovery of patients after operation.

    Release date:2021-06-07 02:03 Export PDF Favorites Scan
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