Objective To analysis causes of reoperation for primary hyperparathyroidism and its clinical characteristics. Method The clinical data of the patients with primary hyperparathyroidism who had undergone reoperation from January 1993 to May 2017 were retrospectively analyzed. Results A total of 11 patients underwent reoperation were collected in the 226 patients with primary hyperparathyroidism. Of the 11 cases, 8 cases underwent twice operations, 2 cases underwent thrice operations, 1 case underwent quintic operation. After the initial operation, 3 cases were persistent diseases and 7 cases were recurrent diseases, 1 patient was not defined as the persistent or recurrent disease. The main clinical manifestations before the reoperation were fatigue, pain in joints, bones, or muscle. The reasons for reoperation included 3 cases of ectopic parathyroid lesions, 3 cases of recurrent parathyroid carcinomas, 1 case of enlarged operation extent for parathyroid carcinoma, 2 cases of regrowth of double parathyroid aedomas, 1 case of missing adenoma, 1 case of parathyroid hyperplasia. Among the location examinations, the 99Tcm-MIBI was most sensitivity (8/9). Eight cases were received reoperation on the original incision, and the remaining 3 ectopic parathyroid lesions on the new incision. After the reoperation, 2 patients were lost of follow-up, 1 patient died, and the remaining 8 patients had no recurrences during follow-up period. Conclusion A comprehensive approach with multiple imageology examinations which attribute to accurate location of lesions, experienced surgeons and well knowledge of parathyroid anatomy and embryology help to descend reoperation ratio and improve success rate of reoperation.
目的 探讨胃切除术后近期上消化道大出血的原因及再手术治疗。 方法 对我院1986~2002年间收治的14例胃切除术后近期（24～72 h内）上消化道大出血行再手术治疗的病例资料进行回顾性分析。 结果 本组14例，术后吻合口出血4例，残胃粘膜损伤出血2例，残胃肠套叠出血2例，十二指肠残端出血1例，遗漏十二指肠球后溃疡及贲门粘膜撕裂出血各1例，原因不明出血3例，均经再次手术治疗后痊愈。 结论 胃切除术后近期上消化道大出血原因多为操作不当及病灶遗漏所致，出血灶直视下缝扎为有效止血方法。
ObjectiveTo explore risk factors and prognosis of unplanned reoperation in patients with malignant tumors of digestive tract. MethodsThe clinical data of patients with malignant tumors of digestive tract underwent unplanned reoperation who treated in the Department of General Surgery, the Northern District of the Shanghai Ninth People’s Hospital from January 2014 to December 2017 were retrospectively collected, and each operation was matched in a ratio of 1∶3 as a case-conontrol study object. The risk factors and prognosis of unplanned reoperation were analyzed by the basic information, surgical related informations, and postoperative relevant informations. ResultsThere were 33 cases of unplanned reoperation in the 588 patients with malignant tumors of digestive tract treated surgically, 8 cases died after the unplanned reoperation. The analysis results showed that the basic diseases, history of previous abdominal surgery, preoperative anemia, the first operative time >4 h and intraoperative blood loss ≥400 mL were the independent risk factors of the unplanned reoperations (P<0.050); the basic diseases, unplanned preoperative hemoglobin <90 g/L and intraoperative blood loss ≥400 mL were the independent factors of death for patients with unplanned reoperation (P<0.050). ConclusionsEffective intervention on independent risk factors associated with unplanned reoperation in patients with digestive tract malignant tumors can reduce incidence of unplanned reoperation in future and improve prognosis.
目的 探讨复发性结节性甲状腺肿再手术中喉返神经损伤的预防方法。方法 回顾性分析笔者所在单位1996年7月至2009年7月期间再次手术治疗的56例复发性结节性甲状腺肿患者的临床资料，术中行喉返神经解剖31例，未行喉返神经解剖25例。 结果 未行喉返神经解剖者中有3例出现暂时性喉返神经损伤，损伤率为12.0%；行喉返神经解剖者中无一例出现喉返神经损伤，损伤率为0；两者之间差异有统计学意义（χ2=3.931，P＜0.05）。 结论 复发性结节性甲状腺肿再手术时解剖喉返神经有助于降低喉返神经的损伤；术中精细的操作和细致的解剖是避免喉返神经损伤的关键。
Objective To explore prognostic factors of unplanned reoperation in Department of General Surgery. Methods The clinical data of 85 patients with unplanned reoperations who treated in the Northern District of the Shanghai Ninth People’s Hospital from January 2014 to May 2017 were retrospectively collected. The risk factors such as preoperative basic information, surgical related information, and postoperative information for death of unplanned reoperations were analyzed. Results There were 72 cured patients and 12 deaths in the 85 patients. The univariate analysis results showed that the age was older (P<0.05), the operative time was longer (P<0.05) in the patients with death as compared with the cured patients; the with basic diseases, selective operation, high grade of ASA, preoperative hemoglobin <90 g/L, admission to ICU after unplanned reoperations, postoperative complications, and multiple reoperations were correlated with the mortality of unplanned reoperations (P<0.05). The multivariate analysis results showed that the elderly patients, preoperative hemoglobin <90 g/L, and postoperative complications were the independent prognostic factors (P<0.05). The satisfaction of patients at discharge in the death group was significantly lower than that in the survival group (P<0.05). Conclusion Ederly patient, preoperative hemoglobin <90 g/L, and postoperative complications are independent prognostic factors of unplanned reoperations in Department of General Surgery.
ObjectiveTo develop a machine learning model to identify preoperative, intraoperative, and postoperative high-risk factors of laparoscopic inguinal hernia repair (LHR) and to predict recurrent hernia. Methods The patients after LHR from 2010 to 2018 were included. Twenty-nine characteristic variables were collected, including patient demographic characteristics, chronic medical history, laboratory test characteristics, surgical information, and postoperative status of the patients. Four machine learning algorithms, including extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and k-nearest neighbor algorithm (KNN), were used to construct the model. We also applied Shapley additive explanation (SHAP) for visual interpretation of the model and evaluated the model using the k-fold cross-validation method, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). ResultsA total of 1 178 patients with inguinal hernias were included in the study, including 114 patients with recurrent hernias. The XGBoost algorithm showed the best performance among the four prediction models. The ROC curve results showed that the area under the curve (AUC) value of XGBoost was 0.985 in the training set and 0.917 in the validation set, which showed high prediction accuracy. The K-fold cross-validation method, calibration curve, and DCA curve showed that the XGBoost model was stable and clinically useful. The AUC value in the independent validation set was 0.86, indicating that the XGBoost prediction model has good extrapolation. The results of SHAP analysis showed that mesh size, mesh fixtion, diabetes, hypoproteinemia, obesity, smoking history, low intraoperative percutaneous arterial oxygen saturation (SpO2), and low intraoperative body temperature were strongly associated with recurrent hernia. ConclusionThe predictive model of recurrent hernia after LHR in patients derived from the XGBoost machine learning algorithm in this study can assist clinicians in clinical decision making.