The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective To systematically evaluate influence factors hospitalization infections in multiple myeloma(MM)patients after chemotherapy.Methods Computer searches were conducted on relevant literature in CNKI,China Biology Medicine disc,VIP,Wanfang Data Knowledge Service Platform,PubMed,Web of Science,Embase,Cochrane Library and CINAHL from the database inception until December 16,2024.Two researchers independently screened and assessed the quality of the literature,obtained the necessary information,and a Meta-analysis of risk factors was conducted by using RevMan 5.4 software.Results 19 articles were included in total.Meta-analysis results showed that high body mass index,length of stay,smoking history,Eastern Cooperative Oncology Group(ECOG)score,granulocyte deficiency,neutropenia,Durie-Salmon stage,international staging system(ISS)stage and combined with diabetes,renal insufficiency,anemia,hypoalbuminemia were the risk factors for hospitalization infections in patients with MM after chemotherapy(P＜0.05).Conclusion This study provides a reference for intervening in the risk factors of hospitalization infections in MM patients after chemotherapy.Medical staff should prevent infections early based on relevant factors,identify high-risk populations,and maximize the protection of patient health outcomes and good prognosis.

Objective To systematically evaluate the risk factors for metabolic syndrome in hospitalized patients with schizophrenia in China.Methods Relevant observational studies were retrieved for Chinese schizophrenia patients with metabolic syndrome in Databases,with a retrieval period from the database establishment date to January 12 2025.Two researchers independently screened the literature,extracted data and evaluated the quality of the studies,and a total of 16 articles were included for Meta analysis.Results Age,body mass index,smoking history,disease duration,family history of metabolic syndrome,diabetes history,hypertension history,chlorantraniliprole use,olanzapine use,interleukin-6 levels,leptin levels,triglyceride levels,and high-density lipoprotein cholesterol levels were significant risk factors for metabolic syndrome in hospitalized Chinese schizophrenia patients(P＜0.05).Moderate recreational exercise served as a protective factor(P＜0.05).Conclusion There are many influencing factors for the association of metabolic syndrome in hospitalized patients with schizophrenia in China,and moderate exercise is a protective factor for the association of metabolic syndrome in schizophrenia.In clinical practice,high-risk groups of metabolic syndrome can be actively screened according to relevant risk factors.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To comprehensively evaluate the cost and cost-effectiveness of the colorectal cancer screening program for key populations in Zhejiang Province from 2020 to 2022, and provide reference for optimizing colorectal cancer screening strategies.Methods:Based on the colorectal cancer screening program for key populations in Zhejiang Province from 2020 to 2022, parameters such as initial screening positivity rates, colonoscopy compliance rates, and detection rates for colorectal-related lesions among residents aged 50-74 were obtained. Questionnaire surveys assessed program costs and direct medical costs associated with colorectal cancer-related lesions. From a health system perspective, the cost-effectiveness ratio was calculated using the Early Detection Cost Index (EDCI) and the cost per detected case, followed by sensitivity analysis.Results:A total of 5 881 364 screenings were completed from 2020 to 2022. The initial screening positive rate (positive for either questionnaire or fecal immunochemical testing ) was 16.83%, with a colonoscopy compliance rates of 33.96% ( n=336 150). Detection rates for non-advanced adenomas, advanced adenomas, and colorectal cancer were 24.83% ( n=83 453), 11.91% ( n=40 033), and 1.01% ( n=3 397), respectively. Initial screening positivity rates and detection rates increased with age, while colonoscopy compliance rates decreased with age. Cost analysis showed a total project investment of 378 730 457 yuan, with initial screening costing 146 633 103 yuan (38.72%) and diagnostic colonoscopy 232 097 354 yuan (61.28%). The average cost per initial screening and diagnostic colonoscopy was 24.93 and 690.46 yuan, respectively. Direct medical costs for non-advanced adenomas, advanced adenomas, and colorectal cancer at stages Ⅰ, Ⅱ, Ⅲ, and Ⅳ were 4 921, 8 380, 42 547, 62 156, 66 720, and 72 334 yuan, respectively. Cost-effectiveness analysis indicated that screening needed to detect one case of colorectal cancer required 1 731 people and cost 111 490 yuan; the cost per detected advanced adenoma was 9 460 yuan, and the EDCI was 0.09. Costs decreased with increasing age per detected colorectal lesion. Sensitivity analysis showed that increasing colonoscopy compliance could reduce the cost-effectiveness ratio. Conclusions:The colorectal cancer screening program for key populations in Zhejiang Province demonstrates cost-effectiveness. Improving colonoscopy compliance can enhance overall screening effectiveness and economic benefits.

Objective To investigate the diagnostic value of optic nerve damage in glaucoma patients caused by abnormal expression of(Klotho)and C-C chemokine receptor type 7(CXCR7).Methods A prospective study was conducted,totally 120 glaucoma patients treated in the hospital from January 2020 to December 2023 were selected as the study group,and 120 volunteers who underwent physical examination during the same period were selected as the control group.The expression levels of Klotho and CXCR7 in patients with glaucoma caused by abnormal expression of Klotho and CXCR7 were compared between the study group and the control group,the group with or without nerve function injury,and the patients with different degrees of nerve function injury,respectively,and the diagnostic value of optic nerve degree damage in glaucoma patients caused by abnormal expression of KlothO and CXCR7 was studied.Results Klotho and CXCR7 in study group were significantly higher than those in control group(t=93.175,33.855,both P＜0.001).Klotho and CXCR7 in patients with optic nerve damage was significantly higher than that in patients without optic nerve damage(t=5.619,6.507,both P＜0.001).There were statistically significant differences in the expression of Klotho and CXCR7 among patients with different degrees of optic nerve damage(F=12.332,11.209,both P＜0.001).The results of multivariate Logistic analysis showed that both Klotho(OR=3.353)and CXCR7(OR=3.102)were risk factors causing optic nerve damage in glaucoma patients(P＜0.05).According to re-ceiver operating characteristic(ROC)curve analysis,the combined detection of Klotho and CXCR7 showed significantly larger area under the curve for diagnosing glaucomatous optic nerve damage than that of single detection.Conclusion The abnormal expression of Klotho and CXCR7 could be used as an important diagnos-tic basis for the degree of optic nerve damage in glaucoma patients.

Objective To explore the relationship between axillary artery and axillary vein by combining computed tomography angiography computed tomography angiography(CTA)and computed tomography venography(CTV),and to provide imaging data for establishing an effective blood circulation pathway for vascular injury in clinical transaxillary surgery.Methods The image data of 30 patients who underwent left upper limb and axillary CTA and CTV at the same time were collected.After three-dimensional reconstruction of the images by GE AW4.6 workstation,the course,branch type and variation of axillary artery,the course of axillary vein,the reflux of subordinate branches and the relationship between axillary artery and axillary vein were observed.The length of the whole segment,the length of segment and the inner diameter of the starting point of each segment were measured and statistically analyzed.Results According to the number of branches from the main trunk,the axillary artery was divided into 7 types.According to the variation of the number of blood vessels,the axillary vein was divided into 5 types;The unknown vein branches converge into 32 branches,of which the first segment accounted for 37.5％,the second segment accounted for 46.9％,and the third segment accounted for 15.6％.According to the absence of arterial branches,the relationship between axillary artery and axillary vein was divided into 2 types.Conclusion There are many types of branches of axillary arteries and branches of axillary veins,and the variation types are complex.The changes of branches of axillary arteries affect the distribution of branches of axillary veins.Combined with CTA and CTV images,the relationship between axillary vessels can be reflected clearly and intuitively,which can provide imaging reference for the establishment of new ways of blood supply and reflux in clinical axillary treatment.

Objective:To analyze risk factors associated with false-positive results of quantitative fecal immunochemical testing (FIT), evaluate its performance for detecting advanced colorectal neoplasia across different subgroups, and explore the optimal positivity thresholds for each subgroup.Methods:Individuals who participated in the Zhejiang Colorectal Cancer Screening Program in 2020-2021, completed questionnaire-based risk assessment and quantitative FIT for initial screening, and undertook colonoscopy for confirmed diagnosis were included in this study. The information of individuals, including demographic characteristics, lifestyles, history of diseases, and family history of colorectal cancer (CRC), was collected by using questionnaires. The diagnostic outcomes of the individuals were obtained through colonoscopy and pathological examination. Multivariate logistic regression analyses were conducted to identify factors associated with false-positive FIT results. The optimal threshold of FIT was determined based on the receiver operating characteristic (ROC) curve and 10-fold cross-validation. The effectiveness of FIT screening in different subgroups was compared using the unified threshold of 100 ng/ml or optimal positivity thresholds.Results:There were 25 874 individuals included in the analysis, with 14 694 (56.79%) having fecal hemoglobin concentrations ≥100 ng/ml. A total of 3 830 advanced adenoma cases (14.80%) and 362 CRC cases (1.40%) were identified. Age below 60 years old, females, underweight, smoking, drinking, use of nonsteroidal anti-inflammatory drugs, no family history of CRC, no history of intestinal disease, no history of hypertension, and physical inactivity were associated with an elevated risk of false-positive results in FIT ( P<0.05). Compared to the predetermined threshold of 100 ng/ml, the false positive rate (FPR) of quantitative FIT decreased from 52.3% to 37.3% in all individuals, and decreased by more than 20% in females, individuals with normal weight, smokers, and those without a history of intestinal disease when adopting the optimal threshold (all P<0.001). Conclusion:The risk of false-positive results in quantitative FIT varies across different subgroups. Adopting the optimal thresholds could improve the specificity and reduce the FPR of quantitative FIT for CRC screening.

Objective: To investigate the current status and influencing factors for cognitive frailty among the elderly in community, so as to provide the evidence for early identification and prevention of cognitive frailty among the elderly. Methods: Residents aged 60 years and above with local household registration from 11 counties (cities, districts) in Zhejiang Province from 2021 to 2023 were selected as study participants using a multistage random sampling method. Demographic information, lifestyle, and health status were collected through questionnaire surveys. Depressive symptoms were assessed using the Patient Health Questionnaire. Cognitive frailty was evaluated using the FRAIL Scale and the Mini-Mental State Examination. Factors affecting cognitive frailty among the elderly in community were identified using a multivariable logistic regression model. Results: A total of 16 613 individuals were surveyed, including 7 465 males (44.93%) and 9 148 females (55.07%). The average age was (70.97±7.29) years. A total of 784 individuals were detected with depressive symptoms, with a detection rate of 4.72%. A total of 724 individuals were detected with cognitive frailty, with a detection rate of 4.36%. Multivariable logistic regression analysis showed that females (OR=1.419, 95%CI: 1.179-1.708), aged ≥70 years (70-<80 years old, OR=1.869, 95%CI: 1.490-2.345; ≥80 years old, OR=5.017, 95%CI: 3.935-6.398), without a spouse (OR=1.495, 95%CI: 1.234-1.810), sedentary (OR=2.420, 95%CI: 1.829-3.202), chronic diseases (1 type, OR=1.456, 95%CI: 1.175-1.804; ≥2 types, OR=1.639, 95%CI: 1.314-2.045), and depressive symptoms (OR=4.191, 95%CI: 3.361-5.225) were associated with a higher risk of cognitive frailty among the elderly in community. Conversely, a lower risk of cognitive frailty was seen among the elderly in community who had primary school or above (primary school, OR=0.512, 95%CI: 0.389-0.676; junior high school or above, OR=0.464, 95%CI: 0.354-0.608), engaged in physical exercise (OR=0.396, 95%CI: 0.291-0.539), and were reported average or good self-rated health status (average, OR=0.641, 95%CI: 0.475-0.866; good, OR=0.150, 95%CI: 0.109-0.208). Conclusions The detection rate of cognitive frailty among the elderly in community is relatively low and is influenced by demographic factors such as gender, age, education level, as well as lifestyle like sedentary and physical exercise, and health status. It is recommended to reduce the risk of cognitive frailty among the elderly through multidimensional interventions, including health education, promotion of healthy lifestyles, and enhanced mental health support.

Objective: To establish a nomogram prediction model for Alzheimer's disease (AD) among the elderly in community, so as to provide the evidence for early screening and prevention of AD. Methods: Based on the Zhejiang Healthy Aging Cohort Study, the elderly aged 60-90 years who completed the baseline survey were selected as the study subjects. Follow-up surveys were conducted from 2015 to 2016 and from 2019 to 2021. Sociodemographic characteristics, lifestyle factors, medical history, and waist circumference were collected through questionnaire surveys and physical examinations. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and a diagnosis of AD was made based on the Alzheimer's Disease Assessment Scale-Cognitive Subscale and medical history. The participants were randomly divided into training and validation sets at 8∶2 ratio. LASSO regression was used to screen for predictive factors. Multivariable logistic regression model was used to analyze predictive factors and construct a nomogram. The model was analyzed and evaluated using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 6 988 elderly were included at baseline, with a mean age of (68.19±6.63) years. There were 3 438 males (49.20%), and 3 550 females (50.80%). The median follow-up duration was 4.90 (interquartile range, 3.80) years, with 817 new cases of AD were identified, yielding an incidence of 11.69%. LASSO regression and multivariable logistic regression showed that age (OR=1.017, 95%CI: 1.005-1.030), gender (female, OR=1.820, 95%CI: 1.533-2.165), educational level (primary school, OR=0.813, 95%CI: 0.673-0.980), physical exercise (not active, OR=1.572, 95%CI: 1.260-1.980), dining companions (spouse and children, OR=0.771, 95%CI: 0.598-0.995), baseline MMSE score (OR=0.843, 95%CI: 0.821-0.866), and waist circumference (OR=0.981, 95%CI: 0.973-0.989) were risk predictors for AD among the elderly in community. The prediction model demonstrated an area under the ROC curve of 0.740 (95%CI: 0.698-0.783) in the validation set, with a sensitivity of 0.731 and a specificity of 0.667. DCA indicated that when the probability threshold was 0.060 to 0.325, the clinical net benefit was relatively high. Conclusion The AD risk prediction model constructed in this study has good discrimination and clinical practicability, can be used for early screening of AD among the elderly in the community.