Machine learning based peri-surgical risk calculator for abdominal related emergency general surgery: a multicenter retrospective study.

BACKGROUND: Currently, there is a lack of ideal risk prediction tools in the field of emergency general surgery (EGS). The American Association for the Surgery of Trauma recommends developing risk assessment tools specifically for EGS-related diseases. In this study, we sought to utilize machine learning (ML) algorithms to explore and develop a web-based calculator for predicting five perioperative risk events of eight common operations in EGS. METHOD: This study focused on patients with EGS and utilized electronic medical record systems to obtain data retrospectively from five centers in China. Five ML algorithms, including Random Forest (RF), Support Vector Machine, Naive Bayes, XGBoost, and Logistic Regression, were employed to construct predictive models for postoperative mortality, pneumonia, surgical site infection, thrombosis, and mechanical ventilation >48 h. The optimal models for each outcome event were determined based on metrics, including the value of the Area Under the Curve, F1 score, and sensitivity. A comparative analysis was conducted between the optimal models and Emergency Surgery Score (ESS), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and American Society of Anesthesiologists (ASA) classification. A web-based calculator was developed to determine corresponding risk probabilities. RESULT: Based on 10,993 patients with EGS, we determined the optimal RF model. The RF model also exhibited strong predictive performance compared with the ESS, APACHE II score, and ASA classification. Using this optimal model, we developed an online calculator with a questionnaire-guided interactive interface, catering to both the preoperative and postoperative application scenarios. CONCLUSIONS: We successfully developed an ML-based calculator for predicting the risk of postoperative adverse events in patients with EGS. This calculator accurately predicted the occurrence risk of five outcome events, providing quantified risk probabilities for clinical diagnosis and treatment.

Observation and Analysis of the Postoperative Analgesic Effect of Subanaesthetic Dose of Ketamine in Kashin-Beck Disease Patients after Total Knee Arthroplasty.

With the transformation of modern medical models, the medical needs of patients have changed from treatment to safe, comfortable, and painless treatment. Therefore, it is clinically important to find an ideal analgesia model to reduce the pain after total knee arthroplasty and minimize the impact of surgical trauma on the body pressure. This article aims to study the effects of lower limb nerve block combined with local infiltration analgesia of the joint cavity on the hemodynamics and postoperative analgesia effects of knee joint replacement in elderly patients by comparing the effects of the subanaesthetic dose of ketamine on the hemodynamics and postoperative analgesia effect of knee joint replacement in elderly patients' intraoperative analgesia program. This article proposes that 90 patients requiring unilateral total knee replacement were randomly divided into 3 groups, with 30 patients in each group, age 65-85 years, average age 75 years, ASA I ∼ II grade, and body mass index 13.89 ∼ 37.26. Use a multifunctional monitor to monitor the patient's continuous blood pressure (SBP/DBP) and mean arterial pressure (MAP), heart rate (HR), electrocardiogram (ECG), intraoperative pulse oxygen saturation (SpO2), and end-tidal carbon dioxide (PETCO2). The following are monitored: record the heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure before induction of anesthesia (T0), before the upper tourniquet (T1), and after the upper tourniquet (T2), before tourniquet withdrawal (T3), and after tourniquet withdrawal (T4), mean arterial pressure (MAP). The three groups of patients had different degrees of itching, vomiting, nausea, and other adverse reactions. The experimental results in this article show that, in elderly patients with epidural anesthesia, the use of propofol and dexmedetomidine to maintain the patient's BIS value between 60 and 70 can meet the depth of sedation required for surgery without important surgical operation knowledge.

Oncological consequence of emergent resection of perforated colon cancer with complete obstruction after stent insertion as a bridge to surgery.

PURPOSE: Colonic perforation is a life-threatening complication after colonic stent insertion as a bridge to surgery for acute obstruction caused by colorectal cancer. The oncological consequence of colonic perforation after emergent surgical intervention was unknown. The aim of this short communication was to investigate whether or not the perforation and emergent surgery had obviously impact on the peritoneal recurrence and long-term survival of patients. METHODS: Data of the patients who underwent colorectal stenting as a bridge to surgery in 5 years from 2012 to 2017 was collected by the Endoscopical Surgery Group of Hubei. The perforated cases treated by emergent operation were retrospectively analyzed. RESULTS: During 5 years from 2012 to 2017, 116 cases of colorectal stenting as a bridge to surgery had been performed, and 7 patients had perforation after stent placement and treated by emergent surgery, including 1 case of synchronic liver metastasis treated by one-stage metastasectomy. One of the 7 patients died of septic shock after operation, and the remaining patients were followed up for 6-60 months. There was no evidence of abdominal implantation or extra-abdominal metastasis. CONCLUSION: This small case series implicated that colonic perforation after stent insertion for malignant colorectal obstruction treated by emergent surgery might not obviously increase the peritoneal implantation and metastasis.