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.
ObjectiveTo analyze the relative position between lumbar plexus and access corridor of minimally invasive lateral transpsoas approach based on magnetic resonance imaging distribution of lumbar plexus by three dimensional reconstruction technique, so as to evaluate approach safety. MethodsThree-dimensional fast imaging employing steady-state acquisition sequences of lumbar spine were performed on 71 patients with lumbar degenerative diseases between July 2012 and January 2015. The axial image distance between the anterior edge of lumbar plexus and sagittal central perpendicular line (SCPL) of disc was determined using the distance formula at the mid-disc space from L1, 2 to L4, 5 level. SCPL was drawn perpendicularly to the sagittal plane of intervertebral disc and it passed through its central point, which is initial dilator trajectory for transpsoas approach. With respect to the SCPL of disc, the distance with a positive value indicated neural tissue posterior to it whereas anterior to it represented by a negative value. ResultsVarious branches of lumbar plexus which passed through the psoas major anterior to the SCPL of disc were identified in 42 (59.2%), 58 (81.7%), and 70 (98.6%) patients at L2, 3, L3, 4, and L4, 5 levels, respectively. It is possible to infer the presence of genitofemoral nerve in accordance with relevant anatomic research. A ventral migration of intrapsoas nerves is identified from L1, 2 to L4, 5 level. All differences between levels were statistically significant (P < 0.05). ConclusionWith respect to the SCPL of disc, a pass way of guide wire or a radiographic reference landmark to place working channel, lumbar plexus lie posterior to it from L1, 2 to L3, 4 level and shift anteriorly to it at L4, 5 level, while genitofemoral nerve locate anterior to the SCPL from L2, 3 to L4, 5 level. Neural retraction may take place during sequential dilation of working channel especially at L4, 5 level.
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.
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.
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.