Objective:To analyze the clinical efficacy and learning curve for robot-assisted cortical bone trajectory (CBT) screw fixation performed by surgeons with different seniority in the treatment of lumbar degenerative disease.Methods:The clinical data of 91 lumbar degenerative disease patients underwent robot-assisted CBT screw fixation from August 2020 to December 2022 in Beijing Shijitan Hospital, Capital Medical University were retrospectively analyzed. Among them, 48 patients underwent surgery performed by the same senior surgeon (senior group), with a total of 234 CBT screws were placed; while 43 patients underwent surgery performed by the same junior surgeon (junior group), with a total of 206 CBT screws were placed. The surgical related indexes, functional improvement score, lower back pain and lower limb radiation pain scores, acceptable nail insertion rate, non invasion rate of facet joints and incidence of postoperative complications were compared between two groups. The functional improvement score was evaluated using the Japanese Orthopaedic Association (JOA) score, the pain score was evaluated using visual analog score (VAS). The cumulative sum (CUSUM) method was used to depict the learning curve with "single screw placement time" as the observation index.Results:There were no statistical difference in incision length, operation time, intraoperative blood loss and postoperative hospital stay between two groups ( P>0.05). The least squares means of JOA scores 1, 3 and 6 months after surgery in both groups increased significantly compared to baseline, while the least squares means of lower back pain VAS and lower limb radiation pain VAS decreased significantly compared to baseline; there were no statistical differences between two groups ( P>0.05). There were no statistical difference in acceptable nail insertion rate, non invasion rate of facet joints and incidence of postoperative complications between two group ( P>0.05). The CUSUM learning curves were fitting well and the inflection point for senior surgeon corresponded to 18 cases, while it was reached after performing surgery on 21 cases for junior surgeon. Conclusions:Robot-assisted CBT screw fixation performed by surgeons with different seniority could achieve similar clinical outcomes for treating lumbar degenerative disease. The senior surgeons are able to complete the initial learning stage faster than the junior surgeons, but there is not much difference in the number of surgeries performed the learning curve.

Objective To investigate the influencing factors of grade 3-4 multiple myeloma bone disease(MBD)in newly diagnosed multiple myeloma(NDMM)patients,and establish a risk prediction model based on a nomogram.Methods A total of 261 patients with NDMM who were treated in Ningbo Medical Center Lihuili Hospital from January 2015 to December 2021 were retrospectively selected.The patients were divided into group A(MBD grade 0-2,110 cases)and group B(MBD grade 3-4,151 cases)according to MBD grade at the time of initial diagnosis.Logistic regression analysis was used to screen the risk factors for grade 3-4 MBD in NDMM patients,and the risk prediction model was constructed.The receiver operating characteristic(ROC)curve was used for comprehensive evaluation.Results Multivariate regression analysis showed that age,serum phosphorus,C-reactive protein(CRP),globulin(GLB)and bone marrow plasma cell percentage(BMPCp)were independent risk factors for grade 3-4 MBD in NDMM patients(P<0.05).Based on this,risk prediction model was constructed as follows:logit(P)=-15.092+0.107(age)+1.150(serum phosphorus)+0.057(CRP)+0.040(GLB)+0.212(BMPCp).There was no significant difference between the predicted probability and the actual incidence by the Hosmer-Lemeshow goodness of fit test(P=0.770).The accuracy of the model in predicting grade 3-4 MBD in NDMM patients was 90.40%,and the area under the curve was 0.957(95%CI:0.932-0.981),indicating a reliable prediction ability.Conclusion Age,serum phosphorus,CRP,GLB and BMPCp were all independent risk factors for grade 3-4 MBD in NDMM patients,and the constructed risk prediction model has a relatively good predictive effect on the occurrence of grade 3-4 MBD in NDMM patients.

Objective A survival outcome prediction model for postoperative pancreatic cancer patients was constructed by applying large-scale data based on the new version of American Joint Committee on Cancer(AJCC)staging using different machine learning algorithms.Methods Based on the Surveillance,Epidemiology,and End Results(SEER)database,synthetic minority over-sampling technique(SMOTE)and synthetic minority over-sampling technique and edited nearest neighbors(SMOTE-ENN)algorithms were used to process unbalanced data,random forest,support vector machine,decision tree,and extreme gradient boosting(XGBoost)algorithms were used to build and compare prognostic models,and Shapley additive explanation(SHAP)was introduced to interpret the models.Results The SMOTE-ENN combined with XGBoost model had the best performance(accuracy rate was 86.2％,precision rate was 95.2％,recall rate was 71.2％,F1 value was 0.762,area under the curve was 0.884,Brier score was 0.108).The calibration curve and decision curve respectively showed that this model had good calibration effect and high clinical application value.In addition,SHAP analysis showed that the most important impact on prognostic outcomes was N stage.Conclusion The XGBoost model has the best performance and can be used as a new high-performance postoperative prognosis prediction model under AJCC staging that conforms to the current clinical staging system,providing theoretical support for predicting postoperative patient survival outcomes and formulating personalized treatment plans.

Objective:To evaluate the effect of acupuncture on postoperative delirium (POD) in diabetic patients undergoing surgery under general anesthesia.Methods:In this randomized controlled trial, 92 diabetic patients of either sex, aged 30-80 yr, with a body mass index of 18-28 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅱ or Ⅲ, scheduled for elective surgery under general anesthesia, were divided into 2 groups ( n=46 each) using a table of random numbers: control group (group C) and acupuncture group (group A). Group A received acupuncture at the Baihui (GV20), Shenting (GV24) and Sishencong (EX-HN1) acupoints before anesthesia. The needles were retained for 30 min, with manual stimulation applied every 10 min for 10 s each time. After 4 stimulations, routine anesthesia was carried out. Group C received routine anesthesia only. Regional cerebral oxygen saturation was recorded on admission to the operating room (T 0), after anesthesia induction (T 1), at the start of surgery (T 2), at the end of surgery (T 3), and immediately after tracheal extubation (T 4). The POD developed within 3 days after surgery was assessed. The occurrence of needle-related adverse effects such as fainting, subcutaneous bleeding, and local paresthesia was recorded. Results:Compared with group C, the incidence of POD was significantly reduced, and the regional cerebral oxygen saturation was increased at T 1, 4 in group A ( P<0.05). Conclusions:Acupuncture can decrease the development of POD in diabetic patients undergoing surgery under general anesthesia, which is related to an increase in regional cerebral oxygen saturation.

Objective:To conduct a scoping review on the current status, assessment tools and influencing factors of malnutrition in elderly stroke patients, so as to provide new ideas for the development of individualized nutritional intervention programs.Methods:Studies related to malnutrition in elderly stroke patients were searched in China National Knowledge Infrastructure, VIP, WanFang Data, China Biology Medicine disc, PubMed, Web of Science, Embase and Clinical Trial Registration Center. The search period was from the establishment of the database to January 2024. Two researchers independently screened the literature, extracted information based on inclusion and exclusion criteria, and finally categorized and reported the findings.Results:A total of 33 papers were included. In elderly stroke patients, the prevalence of malnutrition varied between studies. There was a wide range of tools to assess the nutritional status of patients, but there was an overall lack of multidimensional and specific tools. Commonly used was the Short-form Mini-nutritional Assessment. Factors influencing malnutrition in patients included general demographic, disease-related and lifestyle factors, physiologic and biochemical indicators, functional correlates, nutrient literacy-related factors, psychological and supportive factors.Conclusions:Malnutrition in elderly stroke patients is influenced by a variety of factors and seriously affects patient prognosis. Standardized assessment tools should be adopted to detect timely and accurately, take targeted measures for each factor, and carry out personalized intervention programs to promote benign changes in the nutritional status of elderly stroke patients.

BackgroundWith the acceleration of population aging in China， studies have documented an increased prevalence of dementia in the elderly. Behavioral and psychological symptoms and impaired cognitive function are important problems affecting the quality of life in the elderly with dementia. It has been noted that there are certain limitations on the management of problems mentioned above by drug treatment alone， while its combination with music intervention is emerging as an effective approach. However， the application of this approach in the elderly with moderate to severe dementia is still in its relative infancy. ObjectiveTo investigate the effect of music assisted drug treatment on behavioral and psychological symptoms and cognitive function in the elderly with moderate to severe dementia， so as to provide insights for the development of effective intervention. MethodsA randomized controlled study was utilized to enroll a coherent of 43 elderly patients with moderate to severe dementia who were hospitalized in Geriatric Psychiatry of Deyang Mental Health Center from January to July 2023 and met the International Classification of Diseases， tenth edition （ICD-10） diagnostic criteria for dementia. Eligible subjects were divided into study group （n=22） and control group （n=21） based on random allocation using SPSS 26.0. Both groups received routine drug treatment and nursing care， while the study group added music intervention， which consisted of two 30-minute sessions per week for 8 weeks. Neuro Psychiatric Inventory （NPI） and Mini-Mental State Examination （MMSE） were administered to all patients before and after intervention. ResultsA total of 36 patients completed the study， including 20 case in study group and 16 case in control group. No statistical difference was noted in baseline NPI score and MMSE score between two groups （P>0.05）. After intervention， study group reported a statistical reduction in NPI total score ［58.00 （49.00， 79.25） vs. 78.50 （55.00， 95.50）， Z=-3.902， P<0.01）］ along with a clinically unremarkable increase in MMSE score （P>0.05） compared with baseline data. After intervention， NPI total score and scores on sub-domains including agitation/aggression， depression/dysphoria， anxiety and aberrant motor behavior were all significantly lower in study group than those in control group （Z=-2.183， -2.438， -2.691， -3.716， -2.250， P<0.05 or 0.01）， while there was no significant difference in MMSE score between two groups （P>0.05）. ConclusionMusic assisted drugintervention may ameliorate behavioral and psychological symptoms in the elderly with moderate to severe dementia， while no significant improvement is documented on cognitive function. ［Fund by the "14^th Five Year Plan" for Philosophy and Social Sciences Research in Deyang （number， DY232C002）］

Salivary gland mucosa-associated lymphoid tissue lymphoma (SGML) is a subvariety of marginal zone B-cells that occurs outside of mucosal lymph nodes. The onset of SGML is closely related to immunity, chronic infections, and genetic factors, such as lymphoepithelial sialadenitis (LESA) and Sjogren’s syndrome (SS), as well as Helicobacter pylori, hepatitis C virus, Epstein-Barr virus, and human T-lymphocytic virus. The most common site of SGML is the parotid gland, followed by the submandibular gland, small salivary gland, and sublingual gland. SGML is more common in middle-aged and elderly women, and patients often have autoimmune diseases, such as Sjogren’s syndrome or rheumatoid arthritis. SGML can be diagnosed through clinical manifestations, imaging, and histopathology, but histopathological biopsy remains the main method for confirming SGML. Traditional treatment methods include anti-infective therapy and surgery combined with radiation or chemotherapy. In recent years, some new treatment methods, such as Bruton tyrosine kinase (BTK) inhibitors and programmed cell death protein-1 (PD-1) inhibitors, have been effective against recurrent or refractory SGML, but more clinical trial data are needed to support them. At present, the optimal treatment for SGML is not yet clear. Individualized treatment plans should be developed based on the location, staging, clinical characteristics, and overall health status of the patient. SGML progresses slowly and has a relatively good overall prognosis; however, the disease is recurrent, the treatment cycle is long, the recurrence rate is higher than that of other mucosa-associated lymphoid tissue lymphomas, and SGML may also cause other serious complications. Therefore, regular observation and follow-up are very important for its prognosis. This article reviews the etiology, diagnosis, treatment, and prognosis of SGML, with the aim of providing a reference for clinical diagnosis and treatment, and thus improve the survival rate of patients with SGML.

Objective To explore the medication rules of Professor Hua Baojin in the treatment of subsolid pulmonary nodules through retrospective analysis and data mining techniques. Methods The prescriptions of patients with subsolid pulmonary nodules who were diagnosed and treated by Professor Hua Baojin at Guang’anmen Hospital of the Chinese Academy of Chinese Medical Sciences from January 1, 2021 to December 31, 2024 were retrospectively collected. Data were imported into the Ancient and Modern Medical Case Cloud Platform for analysis of drug frequency, four natures and five flavors, meridian tropism, drug association, and hierarchical clustering. Results A total of 455 prescriptions were included, containing 205 kinds of traditional Chinese medicines, with a total frequency of 12048 times. Fifty-seven commonly used drugs were screened out, among which drugs with high frequencies included astragalus membranaceus (raw) and hawthorn fruit (charred). The nature of the drugs was mainly warm, cold, and neutral. The flavor of the drugs was mostly sweet, bitter, and pungent. The meridians they belonged to mainly included the lung, spleen, and liver meridians. Their efficacy was mainly tonifying deficiency, clearing heat, resolving phlegm, and relieving cough and asthma. Association analysis obtained 19 pairs of drug combinations, 21 groups of three-drug combinations, and four groups of four-drug combinations. Hierarchical clustering obtained 10 groups of drug combinations. Conclusion On the basis of the core pathogenesis of subsolid pulmonary nodule, Professor Hua applies the theory of regulating qi and detoxifying; regulating the qi of the liver, spleen, and lung; and detoxifying the toxins of phlegm and blood stasis, providing valuable experience for the clinical treatment of SSN.

Objective To explore the clinical information of female patients with pulmonary nodules and the distribution of traditional Chinese medicine (TCM) syndromes and their elements. Methods A cross-sectional study was conducted to collect the basic information, medical history data, image data, and four diagnostic information of female patients with pulmonary nodules. The distribution characteristics of TCM syndromes and their elements in female patients with pulmonary nodules were determined by KMO test, Bartlett spherical test, systematic cluster analysis, chi-square test, and other methods. Results A total of 721 female patients with pulmonary nodules were included in this study. The patients were mainly 45-59 years old, had secondary school education or above, and had a history of oil smoke exposure as clinical characteristics. The pulmonary nodules were mainly 6-10 mm in size and appeared as multiple and ground glass nodules. The clinical symptoms were mainly fatigue, emotional irritability, and shortness of breath. The main syndromes of disease location were the spleen, liver, and lung; and the main syndromes of disease were phlegm, dampness, and qi deficiency. The main complex syndromes were spleen deficiency and dampness, liver stagnation, and qi/yin deficiency. Conclusion Middle age, high education, and multiple small ground glass nodules are the clinical characteristics of female patients with pulmonary nodules. Exposure to oil smoke is an important cause of the occurrence of female pulmonary nodules. During treatment, attention should be paid to strengthening the spleen, removing dampness, soothing the liver, regulating and tonifying qi, and nourishing yin.

Objective A survival outcome prediction model for postoperative pancreatic cancer patients was constructed by applying large-scale data based on the new version of American Joint Committee on Cancer(AJCC)staging using different machine learning algorithms.Methods Based on the Surveillance,Epidemiology,and End Results(SEER)database,synthetic minority over-sampling technique(SMOTE)and synthetic minority over-sampling technique and edited nearest neighbors(SMOTE-ENN)algorithms were used to process unbalanced data,random forest,support vector machine,decision tree,and extreme gradient boosting(XGBoost)algorithms were used to build and compare prognostic models,and Shapley additive explanation(SHAP)was introduced to interpret the models.Results The SMOTE-ENN combined with XGBoost model had the best performance(accuracy rate was 86.2％,precision rate was 95.2％,recall rate was 71.2％,F1 value was 0.762,area under the curve was 0.884,Brier score was 0.108).The calibration curve and decision curve respectively showed that this model had good calibration effect and high clinical application value.In addition,SHAP analysis showed that the most important impact on prognostic outcomes was N stage.Conclusion The XGBoost model has the best performance and can be used as a new high-performance postoperative prognosis prediction model under AJCC staging that conforms to the current clinical staging system,providing theoretical support for predicting postoperative patient survival outcomes and formulating personalized treatment plans.