The latest research findings on bidirectional regulation of neuro-immunity through traditional neural circuits shed new light on the theoretical basis of the role of vidian neurectomy (VN). This article aims to provide a comprehensive understanding of VN, including the history of VN, the principle of neuroimmuno-interaction, the applied anatomy of VN as well as the methods of transnasal endoscopic surgery. Additionally, we introduce the concept of the nose-brain axis, which was proposed based on the advancement in the area of neuro-immune interactions.

Objective:To analyze the clinical features, prognosis and risk factors of SARS-CoV-2 associated acute pancreatitis (SAAP), and provide a basis for early prevention and treatment of SAAP.Methods:Patients with coronavirus disease 19 infection (COVID-19) admitted to Zhejiang Provincial People's Hospital from December 1, 2022 to January 31, 2023 were retrospectively analyzed. Clinical characteristics such as age, gender and other data were recorded, and the indexes of blood routine, liver and kidney function, inflammatory factor, coagulation function, blood gas analysis, immunoglobulin and complement were collected after admission. Patients were divided into pancreatic injury group and non-pancreatic injury group according to the level of serum amylase/lipase. The difference of prognosis and related hematological parameters between the two groups was compared. Multifactorial logistic regression equation was constructed to analyze the risk factors of SAAP.Results:A total of 2 101 patients with COVID-19 who met the criteria were included, including 298 patients in the pancreatic injury group and 1 803 patients in the non-pancreatic injury group. 17 cases (5.7%) in the pancreatic injury group met the diagnostic criteria for AP. The age, male percentage and mortality rate of the pancreatic injury group were all significantly higher than those of the non-pancreatic injury group (all P<0.05). In the pancreatic injury group, white blood cell count, neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), calcitoninogen, erythrocyte sedimentation rate, inflammatory cytokines, tumour necrosis factor, liver and kidney functions, coagulation (D-dimer and plasma fibrinogen degradation products), and lactate level were significantly higher than those in the non-pancreatic injury group (all P<0.05). Serum complement C3, albumin, albumin globule ratio and arterial oxygenation index were lower in the pancreatic injury group (all P<0.05). Multifactorial logistic regression analysis showed that gender, age, CRP, calcitoninogen, total bilirubin, creatinine, PaO 2, PaO 2/FiO 2 and lactate were independent risk factors for the occurrence of pancreatic injury in patients with COVID-19 (all P<0.05). Conclusions:Inflammation-related markers, D-dimer and fibrinogen degradation products were significantly higher in COVID-19 patients comorbid with pancreatic injury than in the patients without pancreatic injury. The risk of SAAP was significantly higher in male patients of senior age. Sex, age, CRP, calcitoninogen, total bilirubin, creatinine, oxygenation index, and lactic acid were independent risk factors for the onset of pancreatic injury in COVID-19 patients.

Objective:To evaluate the effect of low-dose esketamine for postoperative analgesia on the postoperative depression in patients with gastrointestinal tumors.Methods:This study was a prospective randomized controlled trial. Eighty patients, aged 18-64 yr, with a body mass index of 18-25 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅱ or Ⅲ, scheduled for elective radical resection of the gastrointestinal tumor under general anesthesia from June to November 2023 in our hospital, were divided into 2 groups ( n=40 each) using a random number table method: esketamine group (group E) and control group (group C). Each patient received postoperative patient-controlled intravenous analgesia(PCIA). The PCIA solution in group E contained esketamine 0.5 mg/kg, dezocine 0.5 mg/kg, dexmetomidine 1.5 μg/kg and flurbiprofen ester 100 mg in 100 ml of normal saline. The PCIA solution in group C contained dezocine 0.5 mg/kg, dexmetomidine 1.5 μg/kg and flurbiprofen ester 100 mg in 100 ml of normal saline. The Hospital Anxiety and Depression Scale (HADS) was used to assess the patients′ anxiety and depression at 1 day before operation (T 0) and 2 days after operation (T 1). The Quality of Recovery-15 scale was used to evaluate the early postoperative recovery quality. Visual analog scale scores, the pressing times of patient-controlled analgesia and the number of rescue analgesia were recorded within 2 days after operation. The occurrence of drug-related adverse reactions was also recorded. Results:Seventy-eight patients were finally included, with 39 cases in group E and 39 cases in group C. Compared with group C, the postoperative HADS-depression scale score and incidence of depression were significantly decreased, the Quality of Recovery-15 scale score was increased, the visual analog scale scores were decreased ( P<0.05), and no significant changes were found in the postoperative HADS-anxiety scale score and incidence of anxiety, the pressing times of patient-controlled analgesia and the number of rescue analgesia in group E ( P>0.05). Visual hallucination was found at 1 day after operation in one patient and relieved at 2 days after operation in group E. There was no significant difference in the incidence of postoperative dizziness, nausea and vomiting between the two groups ( P>0.05). Conclusions:Postoperative analgesia with 0.5 mg/kg esketamine can alleviate postoperative depressive symptoms, enhance the efficacy of analgesia and improve the early postoperative recovery quality in patients with gastrointestinal tumors.

Objective:To explore the feasibility and validity of constructing an intensity-modulated radiotherapy gamma pass rate prediction model after combining the SHAP values with the extreme gradient boosting tree (XGBoost) algorithm feature selection technique, and to deliver corresponding model interpretation.Methods:The dose validation results of 196 patients with pelvic tumors receiving fixed-field intensity-modulated radiotherapy using modality-based measurements with a gamma pass rate criterion of 3%/2 mm and 10% dose threshold in Hunan Provincial Tumor Hospital from November 2020 to November 2021 were retrospectively analyzed. Prediction models were constructed by extracting radiomic features based on dose files and using SHAP values combined with the XGBoost algorithm for feature filtering. Four machine learning classification models were constructed when the number of features was 50, 80, 110 and 140, respectively. The area under the receiver operating characteristic curve (AUC), recall rate and F1 score were calculated to assess the classification performance of the prediction models.Results:The AUC of prediction model constructed with 110 features selected based on the SHAP-valued features was 0.81, the recall rate was 0.93 and the F1 score was 0.82, which were all better than the other 3 models.Conclusion:For intensity-modulated radiotherapy of pelvic tumor, SHAP values can be used in combination with the XGBoost algorithm to select the optimal subset of radiomic features to construct predictive models of gamma pass rates, and deliver an interpretation of the model output by SHAP values, which may provide value in understanding the prediction by machine learning-dependent models.

Objective:To explore the feasibility of a classification prediction model for gamma pass rates (GPRs) under different intensity-modulated radiation therapy techniques for pelvic tumors using a radiomics-based machine learning approach, and compare the classification performance of four integrated tree models.Methods:With a retrospective collection of 409 plans using different IMRT techniques, the three-dimensional dose validation results were adopted based on modality measurements, with a GPR criterion of 3%/2 mm and 10% dose threshold. Then prediction were built models by extracting radiomics features based on dose documentation. Four machine learning algorithms were used, namely random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). Their classification performance was evaluated by calculating sensitivity, specificity, F1 score, and AUC value. Results:The RF, AdaBoost, XGBoost, and LightGBM models had sensitivities of 0.96, 0.82, 0.93, and 0.89, specificities of 0.38, 0.54, 0.62, and 0.62, F1 scores of 0.86, 0.81, 0.88, and 0.86, and AUC values of 0.81, 0.77, 0.85, and 0.83, respectively. XGBoost model showed the highest sensitivity, specificity, F1 score, and AUC value, outperforming the other three models. Conclusions:To build a GPR classification prediction model using a radiomics-based machine learning approach is feasible for plans using different intensity-modulated radiotherapy techniques for pelvic tumors, providing a basis for future multi-institutional collaborative research on GPR prediction.

Objective:To evaluate the effect of intravenous infusion of dexmedetomidine before induction of anesthesia on concentrations of blood potassium and blood glucose in the patients with gastrointestinal tumors.Methods:One hundred and twenty patients, irrespective of gender, aged 18-75 yr, with body mass index of 18-28 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅰ-Ⅲ, scheduled for elective radical gastrointestinal tumor surgery, were divided into 3 groups ( n=40 each) using a random number table method: control group (group C), dexmedetomidine 0.5 μg/kg group (group D 1), and dexmedetomidine 1.0 μg/kg group (group D 2). Dexmedetomidine 0.5 and 1.0 μg/kg were intravenously infused prior to anesthesia induction over 10 min in D 1 and D 2 groups, while the equal volume of normal saline 20 ml was intravenously infused instead in group C. Before intravenous infusion (T 0), at 15 min after intravenous infusion (T 1), and at 30 min after intravenous infusion (T 2), blood samples from the radial artery were collected for blood gas analysis, and concentrations of blood potassium and blood glucose were recorded. The occurrence of complications such as hyperglycemia, hypoglycemia, hyperkalemia, hypokalemia, hypotension, hypertension, tachycardia and bradycardia was also recorded. Results:Compared with C group, the blood glucose concentrations were significantly increased at T 1 in D 1 and D 2 groups and at T 2 in D 2 group ( P<0.05). The blood glucose concentrations were significantly higher at T 1, 2 in D 2 group than in D 1 group ( P<0.05). There was no significant difference in blood potassium concentrations at T 0-T 2 among the three groups ( P>0.05). No patients presented with complications such as hyperglycemia, hypoglycemia, hyperkalemia, hypokalemia, hypotension, hypertension, tachycardia and bradycardia. Conclusions:Intravenous infusion of dexmedetomidine before induction of anesthesia exerts no marked effect on blood potassium concentrations and can increase glucose concentrations to a certain extent, but the elevation has no clinical significance in the patients with gastrointestinal tumors.

Objective To quantify the setup errors for the different anatomical sites of patients who received intensity-modulated radiotherapy (IMRT) with linear accelerator on-board kilovolt fan beam CT(kV-FBCT) as non-isocenter IGRT and megavolt cone beam CT (MV-CBCT) as isocenter IGRT. Methods A retrospective analysis was performedon 70 patients who underwent radiotherapy, kV-FBCT, and/or MV-CBCT scans after each routine setup prior to IMRT. The average displacement (M), systematic error (Σ), and random error (б) at different treatment sites in the left-right, anterior-posterior, and cranial-caudal directions were calculated according to the individual displacements. The formula 2.5Σ+0.7б was used to estimate the PTV margin in respective direction. For each single patient, the root mean square in three directions was used as 3D displacement. Results A total of 1130 displacements were recorded in the 70 patients. The PTV margin was estimated to be 1.9-3.1 mm in head and neck cancer, 2.8-5.1 mm in thoracic cancer, 4.6-5.1 mm in breast cancer, 3.0-5.5 mm in upper abdominal cancer, and 3.5-6.8 mm in pelvic tumor. For the 3D mean displacements, the head and neck, thoracic, breast, upper abdominal, and pelvic cancer were 2.4±1.0, 4.0±1.6, 4.1±2.0, 4.6±2.1, and 4.6±2.1 mm, respectively. The average 3D displacement obtained by kV-FBCT and MV-CBCT were 4.1 and 3.4 mm, respectively (P=0.212). Conclusion The quantitative setup-error data can be obtained using linear accelerator on-board FBCT, and the non-isocenter IGRT induced set-up error cannot be negligible.

Humans ; Autistic Disorder ; China/epidemiology* ; Cohort Studies ; Autism Spectrum Disorder/genetics* ; Asian People

With the gradual improvement of medical informatization and the vigorous development of medical and health big data，the exploration and practice of real -world research are becoming more and more mature ，and real -world data have become an important source of evidence for post marketing re -evaluation of drugs . As an important high -quality real -world medical data ， electronic medical record data is an indispensable data source for post marketing re -evaluation of drugs . Most of the existing guidelines and norms of real -world research are designed from the perspective of prospective research ，and do not propose specific measures and methods in the implementation of retrospective research ，especially for the operation suggestions on the technical level of using conventionally collected electronic medical record data . In combination with the operational process framework formulated by the existing guidelines and norms ，this paper creatively adds the operating procedures for dataE- validation，data integration ，data verification ，and throughout quality control ，data management and storage of retrospectiveelectronic medical record data ，and describes the data analysis methods and key points involved in carrying out multi -center retrospective real -world research using electronic medical record data ，taking the post marketing safety research of drugs as an example. Finally，the full process operation procedure applicable to the use of multi -center retrospective electronic medical record data is established .

Objective:To develop the minimal clinically important difference (MCID) of Quality of Life Instruments for Cancer Patients-Leukemia (QLICP-LE) (V2.0).Methods:The quality of life of 101 patients with leukemia in First Affiliated Hospital of Kunming Medical University and First People′s Hospital of Yunnan Province from October 2011 to May 2012 were measured. The QLICP-LE (V2.0) was used for data collection, and the MCID for the overall score and scores of various domains of QLICP-LE (V2.0) were established by using the distribution-based approach including indexes of effect size, standard error of measurement (SEM), reliable change index, standardized response mean and responsiveness statistic, and the recommended values of MCID were determined through the consensus method.Results:The MCID formulated by the above five indexes were as follows: the total scale 1.4-9.3, physical functional domain 1.6-15.6, psychological functional domain 2.9-15.6, social functional domain 2.2-18.0, common symptoms and side-effects domain 1.7-17.1, common module 1.8-10.0, and the specific module 1.1-12.1. Through the expert consensus method, it was recommended to use the MCID results calculated by 1.96SEM: the total scale was 4, physical domain was 8, psychological domain was 8, social domain was 9, common symptoms and side-effects domain was 9, common module was 4, and the specific module was 6.Conclusion:Each index of distribution-based approach has its own advantages and disadvantages, which can be selected based on actual conditions. There is clinical significance when the score change of QLICP-LE (V2.0) of leukemia patients after treatment exceeds its MCID.