Background: To investigate directional deviations between pilot holes and final pedicle screw trajectories in freehand placement and analyze risk factors for misplacement. While pedicle screws are widely used in thoracolumbosacral surgery, directional deviations between pilot holes and final screw trajectories remain understudied as potential risk factors for misplacement. Methods: Thirty-three patients undergoing posterior fixation were prospectively enrolled. Inertial measurement units (IMUs) tracked the spatial positions of pedicle finders and screwdrivers via custom software. Surgeons (n = 6) were stratified into senior, middle, and junior groups. Analyzed variables included the use of tapping, surgeon experience, spinal deformity status, screw tip morphology, and surgical parameters. Results: Among 198 implanted screws (6.00 ± 2.88/patient), all exhibited trajectory deviations (8.12° ± 3.47°). Tapping significantly reduced deviations (7.23° ± 3.23° vs. 8.87° ± 3.31°, p < 0.01). Senior surgeons achieved smaller deviations (7.34° ± 3.33°) than the middle group (8.60° ± 3.51°, p = 0.039) and junior group (8.68° ± 3.49°, p = 0.022). Multivariate analysis confirmed tapping (p = 0.001) and senior experience (p = 0.023) as protective factors. No significant associations emerged for spinal deformity (8.43° ± 3.73° vs. 7.97° ± 3.35°, p = 0.377), screw tip type (cylindrical, 8.43° ± 3.26° vs. tapered, 8.07 ± 3.51°; p = 0.637), obesity, or surgical position parameters. Conclusions Freehand pedicle screw placement consistently produces trajectory deviations from pilot holes, and surgeon experience and tapping are modifiable protective factors. The IMU-based tracking system enables quantitative surgical motion analysis, suggesting its utility for training optimization and technique standardization.

Autism Spectrum Disorder （ASD） is a neurodevelopmental disorder with rapidly increasing global prevalence， characterized by core symptoms of social communication deficits and stereotyped repetitive behaviors. Although genetic predisposition， abnormal epigenetic regulation， perinatal environmental exposure， and nutritional-metabolic imbalances are recognized as major risk factors， the precise etiological mechanisms remain incompletely understood. Current clinical management primarily relies on behavioral interventions， with limited pharmacological options accompanied by adverse effects. Recent studies have demonstrated the unique therapeutic value of active components from Chinese herbal medicine in ASD intervention. This article reviews the mechanisms underlying various Chinese herbal active components in ASD treatment， including improvements in synaptic dysfunction， blood-brain barrier impairment， neurotransmitter regulation， cerebellar dysfunction， immune dysregulation and neuroinflammation， oxidative stress， programmed neuronal cell death， and lipid metabolism. These bioactive components exhibit multi-target and multi-pathway regulatory effects， providing novel therapeutic strategies and directions for ASD.

ObjectiveTo investigate the application value of a multimodal model integrating radiomics features， deep learning features， and clinical structured data in predicting severe acute pancreatitis （SAP）， and to provide more accurate tools for the early identification of SAP in clinical practice. MethodsThe patients with acute pancreatitis （AP） who attended The First Affiliated Hospital of Soochow University， Jintan Hospital Affiliated to Jiangsu University， and Suzhou Yongding Hospital from January 1， 2017 to December 31， 2023 were included. Related data were collected， including demographic information， previous medical history， etiology， laboratory test data， and systemic inflammatory response syndrome （SIRS） within 24 hours after admission， as well as imaging data within 72 hours after admission， while related scores were calculated， including Ranson score， modified CT severity index （MCTSI）， bedside index for severity in acute pancreatitis （BISAP）， and systemic inflammatory response syndrome， albumin， blood urea nitrogen and pleural effusion （SABP） score. The model was constructed in the following process： （1） three-dimensional CT images were used to extract and identify radiomics features， and a radiomics classification model was established based on the extreme gradient Boost （XGBoost） algorithm； （2） U-Net is used to perform semantic segmentation of three-dimensional CT images， and then the results of segmentation were imported into 3D ResNet50 to construct a deep learning classification model； （3） the predicted values of the above two models were integrated with clinical structured data to establish a multimodal model based on the XGBoost algorithm. The variable importance plot and local interpretability plot were used to perform visual interpretation of the model. The independent samples t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the chi-square test or Fisher’s exact test was used for comparison of categorical data between groups. The receiver operating characteristic （ROC） curve was plotted for each model and existing scoring systems， and the area under the ROC curve （AUC） was calculated to assess their performance； the Delong test was used for comparison of AUC. ResultsA total of 609 patients who met the criteria were included， among whom 114 （18.7%） developed SAP. In this study， the data of 426 patients from The First Affiliated Hospital of Soochow University was used as the training set， and the data of 183 patients from Jintan Hospital Affiliated to Jiangsu University and Suzhou Yongding Hospital were used as the independent test set. The multimodal model had an AUC of 0.914 in the test set， which was significantly higher than the AUC of traditional scoring systems such as MCTSI （AUC=0.827）， Ranson score （AUC=0.675）， BISAP （AUC=0.791）， and SABP score （AUC=0.648）； in addition， the multimodal model showed a significant improvement in performance compared with the radiomics classification model （AUC=0.739） and the deep learning classification model （AUC=0.685） （the Delong test： Z=-3.23， -4.83， -3.48， -4.92， -4.31， and -4.59， all P <0.01）. The top 10 variables in terms of importance in the multimodal model were pleural effusion， predicted value of the deep learning model， predicted value of the radiomics model， triglycerides， calcium ions， SIRS， white blood cell count， age， platelets， and C-reactive protein， suggesting that the above variables had significant contributions to the performance of the model in predicting SAP. ConclusionBased on structured data， radiomic features， and deep learning features， this study constructs a multicenter prediction model for SAP based on the XGBoost algorithm， which has a better predictive performance than existing traditional scoring systems and unimodal models.

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

Objective To explore the application effect of the"ASK-T"aspiration prevention management model in reducing the risk of aspiration in elderly patients with chronic obstructive pulmonary disease(COPD)complicated by dysphagia.Methods 196 of 409 COPD patients with aspiration risk admitted to the Respiratory Disease Department of Guangdong Provincial Hospital of Chinese Medicine,Higher Education Mega Center Hospital from July 2021 to June 2024 were selected as the study object,and 102 COPD patients with aspiration risk admitted from July 2021 to December 2022 were set as the pre-improvement group.The patients in this group received the original nursing process and management mode of the department during hospitalization.94 COPD patients with aspiration risk admitted from January 2023 to June 2024 were set as the improved group,and the patients in this group were introduced into the department and implemented an innovative improvement project:"ASK-T"anti-aspiration management mode and then received nursing management.Patients in both groups were observed and followed up for 4 weeks.The risk grade of aspiration,SSA score,DHI score,aspiration pneumonia and aspiration pneumonia,nutritional status and satisfaction after intervention were compared between the two groups.Result in the improved group was significantly lower than that in the pre-improvement group(P<0.05),and the SSA score,DHI score and total DHI score of patients in the 2 groups were significantly lower than that before intervention(P<0.05).The SSA score,DHI score and DHI total score in the improved group were lower than those in the pre-improved group(P<0.05).The results of 4-week follow-up showed that the scores of NRS-2002 for nutritional risk screening in 2 groups were lower than before intervention(P<0.05),and the scores of NRS-2002 for nutritional risk screening in the improved group were significantly lower than those in the pre-improvement group(P<0.05).The comparison showed that the incidence of aspiration and aspiration pneumonia in the improved group was lower than that in the pre-improved group(P<0.05),and the satisfaction score of patients with the relevant preventive measures was higher than that in the pre-improved group(P<0.05).Conclusion The"ASK-T"aspiration preven-tion management model,when applied in the nursing of elderly patients with COPD complicated by dysphagia,can significantly reduce the risk of aspiration and the incidence of aspiration pneumonia,effectively improve patients' swallowing function and quality of life,and enhance their nutritional status.Furthermore,this model significantly improves patient satisfaction with intervention measures,providing a scientific and effective management strategy for clinical nursing of elderly patients with COPD complicated by dysphagia.It is worthy of promotion and application in clinical practice.

Objective:To explore the application value of part-cut jejunal transection in digestive tract reconstruction of totally laparoscopic total gastrectomy.Methods:The propensity score matching and retrospective cohort study was conducted. The clinicopathological data of 112 patients with gastric cancer who underwent totally laparoscopic total gastrectomy in The Second Affiliated Hospital of Anhui Medical University from June 2018 to September 2022 were collected. There were 81 males and 31 females, aged (70±8)years. Among the 112 patients, 60 patients undergoing diges-tive tract reconstruction by Roux-en-Y anastomosis with part-cut jejunum were set as the part-cut group, and 52 patients undergoing digestive tract reconstruction by traditional Roux-en-Y anasto-mosis were set as the traditional group. Observation indicators: (1) propensity score matching status and comparison of clinical data of patients between the two groups after matching; (2) intraopera-tive and postoperative conditions; (3) follow-up. Comparison of measurement data with normal dis-tribution between groups was conducted using the independent sample t test. Comparison of count data between groups was conducted using the chi-square test or Fisher exact probability. Com-parison of ordinal data was conducted using the nonparametic rank sum test. Propensity score matching was performed using the 1∶1 nearest neighbor matching method, with the caliper value of 0.02. Results:(1) Propensity score matching status and comparison of clinical data of patients between the two groups after matching. Of the 112 patients, 90 patients were successfully matched, with 45 cases in each of the part-cut group and the traditional group. After propensity score matching, the elimination of body mass index, clinical TNM staging confounding bias ensured comparability. (2) Intraoperative and postoperative conditions. After propensity score matching, the total operation time and digestive tract reconstruction time of patients in the part-cut group were (217.0±15.1)minutes and (34.7±1.8)minutes, versus (252.6±21.9)minutes and (52.6±7.4)minutes in the traditional group, respectively, showing significant differences in the above indicators between the two groups ( t=?8.97, ?15.66, P<0.05). (3) Follow-up. After propensity score matching, 90 patients were followed up postoperatively for (47±15)months. During the follow-up, no patient in either group received secondary surgery, and there was no death. There were 3 cases and 10 cases of Roux stasis syndrome in the part-cut group and the traditional group, respectively, showing a significant difference between the two groups ( χ2=4.41, P<0.05). Conclusion:Compared with traditional Roux-en-Y anastomosis, the Roux-en-Y anastomosis with part-cut jejunum in totally laparoscopic total gastrectomy can signifi-cantly shorten the time for digestive tract reconstruction and reduce the incidence of postoperative Roux stasis syndrome.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

OBJECTIVE To observe the effects of silicone oil removal detergent and multi-enzyme detergent on re-moving the residual silicone oil from digestive endoscopes so as to provide bases for clinical cleaning of digestive endoscopes.METHODS Totally 60 colonoscopes that were used in the endoscopy center of Shenzhen Hospital of Southern Medical University in Jul.2024 were chosen as the research subjects and were randomly divided in to the experimental group with 30 colonoscopes(the silicone-removing multi-enzyme detergent group)and the control group with 30 colonoscopes(the multi-enzyme detergent group),the two groups were respectively treated with sil-icone-removing multi-enzyme detergent and multi-enzyme detergent during the cleaning process.The average bac-terial colony counts of rinsed endoscopes,residual water droplet counts of the cleaned endoscopes and absorbance values of residual methyl silicone oil in the biopsy forceps channels of the endoscopes were observed and compared between the two groups so as to evaluate the effect on removing silicone oil.RESULTS The median average bacteri-al colony counts were 3.05(1.62,4.68)× 103 CFU/piece in the experimental group,36.70(34.66,38.10)× 103 CFU/piece in the control group(Z=-6.654,P＜0.001).The median counts of residual water droplets on the en-doscopes were 7.00(5.00,16.50)in the experimental group,31.50(12.00,43.00)in the control group(Z=-3.940,P＜0.001).The median absorbance value of residual methyl silicone oil in the biopsy forceps chan-nels of the endoscopes was 6.85(5.58,7.85)× 10-3 in the experimental group,36.50(35.50,43.65)× 10-3 in the control group(Z=-6.655,P＜0.001).CONCLUSION The silicone-removing multi-enzyme detergent shows more remarkable effect on removing the residual silicone oil on the endoscopes than the multi-enzyme detergent,it improves the cleaning effect of the endoscopes and is worthy to be verified and promoted in the hospital.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective:To establish and validate a multimodal model based on radiomics and deep learning for predicting acute pancreatitis (AP) complicated with acute respiratory distress syndrome (ARDS).Methods:Patients diagnosed with AP from The First Affiliated Hospital of Soochow University, Donghai County People's Hospital and Jintan Affiliated Hospital of Jiangsu University between January 2017 and December 2023 were enrolled. Based on the diagnosis of ARDS within 1 week after admission, the patients were classified into the ARDS group and the non-ARDS group. Patients in the First Affiliated Hospital of Soochow University ( n=406) was used as the training set (non-ARDS group n=212 vs ARDS group n=194), while Donghai and Jintan hospitals served as the test set ( n=175; non-ARDS group n=104 vs ARDS group n=71). Clinical data, laboratory tests and the occurrence of systemic inflammatory response syndrome (SIRS) within 24 hours after admission were collected. Scoring systems such as bedside index for severity in acute pancreatitis (BISAP), Ranson score and modified CT severity index (MCTSI) were calculated. Radiomics features were extracted from three-dimensional CT images to develop a radiomics model based on XGBoost algorithm. At the same time, a deep learning model was constructed using deep convolutional networks to extract deep features. Finally, clinical features and the predictions from the aforementioned models were integrated to establish a multimodal model based on XGBoost algorithm. To enhance model visualization, variable importance ranking and local interpretable visualization were used. The receiver operating characteristic (ROC) curves of the three models and the three scores including BISAP, Ranson and MCTSI were plotted and the area under the curves (AUCs) were calculated to evaluate the prediction performance for ARDS in AP patients, as well as sensitivity and specificity. Results:In the multimodal model for predicting ARDS in AP patients, predictions of the deep learning model and the radiomics model were the most important variables, followed by SIRS, C-reactive protein, procalcitonin, albumin, glucose, creatinine, neutrophil, and Ca 2+. In the training set, the multimodal model achieved an AUC of 0.933 for predicting ARDS in AP patients, higher than the radiomics model (0.727), the deep learning model (0.877), MCTSI (0.870), Ranson (0.620) and BISAP (0.898). In the test set, the model's AUC was 0.916 for predicting ARDS in AP patients, higher than the radiomics model (0.660), the deep learning model (0.864), MCTSI (0.851), Ranson (0.609), and BISAP (0.860). Conclusions:Based on clinical structured data, radiomics and deep learning features, the multimodal model could predict the risk of ARDS in AP patients at an early stage, whose performance is better than the single-modal models and the traditional scoring systems.