Objective To review the progress in the features, early cl inical outcomes, and cl inical appl ication of axial lumbar interbody fusion (AxiaLIF) for the minimally invasive treatment of lumbosacral degenerative diseases. Methods The l iterature about the features, early cl inical outcomes, and cl inical appl ication of AxiaLIF for the minimally invasive treatment of lumbosacral degenerative diseases in recent years was reviewed. Results Almost 9 000 procedures performed globally in recent years, AxiaLIF has shown its safety and effectiveness because of high fusion rates, short hospital ization days, and less iatrogenic compl ications in comparison with standard fusion procedures. ConclusionPostoperative long-term outcomes, biomechanics stabil ity, and extended appl ication of AxiaLIF still need a further study,though it suggests an original minimally invasive treatment of lumbosacral degenerative diseases.
Objective To explore the application of combined optimized machine learning algorithm for predicting the risk model of postoperative infectious complications of gastric cancer and to compare the accuracy with other algorithms, so as to find reliable biomarkers for early diagnosis of postoperative infection of gastric cancer. Methods The clinical data of 420 patients with gastric cancer at the Third Affiliated Hospital of Anhui Medical University from May 2018 to April 2023 were retrospectively analyzed and the patients were randomly divided into training set and validation set. Univariate analysis was used to determine the risk factors of postoperative infectious complications. Six conventional machine learning models are constructed using the training set: linear regression, random forest, SVM, BP, LGBM, XGBoost, and MGA-XGBoost model. The validation set was used to evaluate the seven models through evaluation indicators such as ACC, precision, ROC and AUC. Results Postoperative infectious complications were significantly correlated with age, operation time, diabetes, extent of resection, combined resection, stage, preoperative albumin, perioperative blood transfusion, preoperative PNI, LCR and LMR. Among the seven machine learning models, the MGA-XGBoost model performed best. Among the seven machine learning models, the MGA-XGBoost model performed best, with AUC of 0.936, ACC of 0.889, recall of 0.6, F1-score of 0.682, and precision of 0.79 on the validation set. Diabetes had the greatest influence on the internal structure of the model. Conclusion This study proves that the MGA-XGBoost model incorporating comprehensive inflammation indicators can predict postoperative infectious complications in patients with gastric cancer.
Objective To analyze the risk factors for postoperative cognitive confusion in a surgical intensive care unit. Methods A total of 388 consecutive patients in Surgical Intensive Care Unit of General Hospital of PLA were retrospectively studied. We posed clinical questions according to the patients with older age and large dosage corticosteroid. Using “Postoperative cognitive confusion” and“Intensive Care” as key words, we searched for evidence from MEDLINE (1968-2004). Results We found 3.1% (10/388) of the patients developed postoperative cognitive confusion. Of the 10 postoperative cognitive confusion patients, 9 were over 65 years old. 6.6% (9/136) of the patients (≥ 65 years old) developed postoperative cognitive confusion. While 0.4%(1/252) of the patients (＜65 years old) developed postoperative cognitive confusion. Older age (≥ 65 years old) may induce more postoperative cognitive confusion (P＜0.05). While 7.0% (5/71) of the patients treated by large dose corticosteroids (≥1 000 mg) developed postoperative cognitive confusion. And 1.65% (5/317) of the patients received corticosteroid with large dosage (＜1 000 mg) developed postoperative cognitive confusion. Large dosage corticosteroid (≥1 000 mg) may induce more postoperative cognitive confusion (P＜0.05). Conclusion Older age (≥ 65 years old) and high dose corticosteroid (≥1 000 mg) may be the two main risk factors for postoperative cognitive confusion.
ObjectiveTo investigate the influencing factors of unplanned readmission in patients with chronic obstructive pulmonary disease (COPD) within 1 year, construct a risk prediction model and evaluate its effect. MethodsClinical data of 403 inpatients with COPD were continuously collected from January 2023 to May 2023, including 170 cases in the readmission group and 233 cases in the non readmission group. LASSO regression was applied to screen the optimized variables and multivariate logistic regression analyses were applied to explore the risk factors of unplanned readmission in patients with COPD within 1 year. After that a nomogram prediction model was constructed and evaluated its discrimination, calibration, and clinical applicability. ResultsThe incidence of unplanned readmission in patients with COPD within 1 year was 42.2%. Respiratory failure, number of acute exacerbation in the last year, creatinine and white blood cell count were risk factors for unplanned admission of patients with COPD within one year (P<0.05). Creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid were included in the nomogram model, the area under curve (AUC) and its 95% confidential interval (CI) of the nomogram model was 0.687 (0.636 - 0.739), with the sensitivity, specificity, and accuracy were 0.824, 0.742 and 0.603, respectively. The AUC of the nomogram after re-sampling 1 000 times was 0.687 (0.634 - 0.739). The calibration curve showed a high degree of three line overlap and the clinical decision curve showed that the nomogram model provided better net benefits than the treat-all tactics or the treat-none tactics with threshold probabilities of 15.0% - 55.0%. ConclusionThe nomogram model constructed based on creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid has good predictive value for unplanned readmission in patients with COPD within 1 year.
ObjectiveTo investigate the clinical significance of abnormal confluence of common bile duct (CBD) and pancreatic duct. MethodsFortyfive cases of biliary pancreatic confluence portion of cadavers were dissected and observed with microscope. ResultsThe lower end of CBD inserted normally into the medial posterior portion of descending duodenum with oblique angle (41.4±5.3)° and safeguarded by the sidelong wrinkle formed by mucous membrane of duodenum. In common, pancreatic duct ampulla inserted into CBD with oblique angle (28.5±7.9)° and jointed CBD in the medial wall of dudenum. The length ampulla of Vater was about 0.5-1.5 cm. The Vater’s ampulla was dilated obviously. ConclusionThe result indicates that pancreatic duct and CBD joint with a sharp angle. A number of abnormal anatomic factors may change the relation of oblique angle, and lead to the pancreatitis.
