Objective: To investigate the implementation and evaluate the effectiveness of health management services for patients with type 2 diabetes mellitus (T2DM) in Urumqi City from 2017 to 2021, so as to provide the reference for enhancing T2DM patients management. Methods: Data on the rates of record establishment, health management and standardized management for T2DM patients, and blood glucose control rate in managed patients in Urumqi City from 2017 to 2021 were collected through the quarterly reports on basic public health service management from the Weining Health Platform System. The trends in the four management indicators, and the differences between urban and rural areas were analyzed. Results: The rates of record establishment, health management and blood glucose control rate in managed patients in Urumqi City were 46.94%, 38.37% and 59.92%, respectively, showing upward trends from 2017 to 2021 (all P<0.05). The rate of standardized management was 75.89%, showing a downward trend (P<0.05). The rate of record establishment was higher in urban areas than in rural areas (47.76% vs. 40.56%, P<0.05). The rates of standardized management and blood glucose control in managed patients were lower in urban areas than in rural areas (75.18% vs. 81.46%, 58.93% vs. 67.64%, both P<0.05). The rate of health management was 38.39% in urban areas and 38.24% in rural areas, with no statistically significant difference (P>0.05). The trends in the rates of record establishment, health management and standardized management in both urban and rural areas were consistent with those in the overall population. Conclusions From 2017 to 2021, the rates of record establishment, health management and blood glucose control in managed patients in Urumqi City showed upward trends, while the rate of standardized management exhibited a downward trend. There were urban-rural differences in the rates of record establishment, standardized management and blood glucose control in managed patients.

The incidence of type 2 diabetes mellitus (T2DM) has been continuously rising, severely impacting health and increasing the medical burden. With the development of medical big data and artificial intelligence, research into constructing T2DM and its complications prediction models using machine learning methods based on multidimensional data such as genetic information, health records and laboratory testing data have increased, providing new ideas and means for the prevention and control of T2DM. This article reviewed the research progress in prediction models related to the risk of T2DM to understand the classification, modeling methods and applications by retrieving literature on T2DM and its complications prediction models from domestic and international databases including CNKI, Web of Science, and PubMed from 2003 to 2024, so as to provide the reference for early screening and intervention of T2DM.

Objective Starting from the actual numbers of health personnel of tertiary public hospitals of Traditional Chinese Medicine(TCM),to quantitatively analyze the influencing factors on the allocation of human resources and obtain a prediction model.Methods The balanced panel data from 517 Tertiary Public TCM Hospitals in the period of 2011-2020 were collected,and the two-way fixed effects model was used to empirically analyze the impact of scale,demand and other factors on the actual number of health personnel in these hospitals.Result The number of beds is a key factor affecting the human resource allocation of Public TCM Hospitals,and various factors such as de-mand,policy,price,efficiency,and administrative management also have significant impacts on the allocation.The demand for outpatient services,government financial support,and efficiency of resource utilization are all promoting factors,while the increase in human resource prices,income generation efficiency,and administrative manage-ment levels have negative effects.A prediction model is proposed.Conclusion The planning principle of matching bed numbers with human resources allocation is in line with the actual environment.When predicting the total personnel allocation or authorized strength,various factors should also be fully considered,which can provide reference for the formulation of human resource policies in Public TCM Hospitals.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Objective To develop a health-promoting lifestyle scale for women with polycystic ovary syndrome(PCOS),and to test its reliability and validity,and preliminarily apply it.Methods Based on the Pender health promotion model,the item pool of the scale was constructed through literature research,semi-structured interviews and group discussions.After 2 rounds of Delphi expert consultation and pre-survey,the initial scale was formed.From April to July 2022,316 patients with PCOS in the health management center,reproductive medicine center and endocrinology department of a tertiary hospital in Nanjing were selected for item analysis,exploratory factor analysis and reliability test,respectively.From August to October 2022,358 PCOS patients were selected for confirmatory factor analysis.From November 2022 to February 2013,294 PCOS patients were selected,and the scale was used to investigate the status of health-promoting lifestyle in PCOS patients.Results The health-promoting lifestyle scale for PCOS patients included 5 dimensions and 33 items.The total content validity index of the scale was 0.942,and the content validity index of each item was 0.810-1.000.5 common factors were extracted by 2 exploratory factor analyses,and the cumulative variance contribution rate was 62.399％.Confirmatory factor analysis showed that the model fit was good.The Cronbach's a coefficient of the total scale was 0.930;the split-half reliability was 0.842;the test-retest reliability was 0.888.The preliminary application results showed that the total score of health-promoting lifestyle in PCOS patients was(96.925±14.273),and the average score of items was(2.937±0.433),which was at a medium level.Conclusion The health-promoting lifestyle scale for PCOS patients has good reliability and validity,which can be used as a tool for medical staff to assess the level of health-promoting lifestyle of PCOS patients,and can help nurses to quickly identify the level and dimensions of health-promoting lifestyle of patients,so as to formulate individualized precise health management plans.

OBJECTIVE To investigate the ameliorative effects and mechanism of Sanwei ganlu on hepatic fibrosis in rats. METHODS The rats were randomly divided into normal group， model group， silibinin group （positive control， 50 mg/kg）， and Sanwei ganlu low-dose， medium-dose， and high-dose groups （80， 250， 800 mg/kg）. Except for normal group， hepatic fibrosis rat models were established by intraperitoneal injection of CCl4 in the other groups of rats. Starting from the 6th week of modeling administration， they were given normal saline or corresponding drugs intragastrically at the same time. At the end of the ninth-week experiment， liver and spleen indexes of rats were calculated； the pathological structure and fibrosis changes of liver tissue were observed by HE， Masson and Sirus Red staining. The contents of alanine transaminase （ALT）， aspartate transaminase （AST）， procollagen type Ⅲ （PC Ⅲ）， collagen type Ⅳ （COL-Ⅳ）， interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α） and IL-1β in serum， and hyaluronic acid （HA） and laminin （LN） in liver tissue were all detected. RESULTS Compared with the model group， the liver injury and collagen fiber deposition of rats were improved to different extents in Sanwei ganlu groups and silibinin group； the contents of ALT， AST， PC Ⅲ， COL-Ⅳ， IL-6， TNF-α and IL-1β in serum as well as the contents of HA and LN in liver tissue significantly decreased （P＜0.05 or P＜0.01）. CONCLUSIONS Sanwei ganlu can alleviate the progression of hepatic fibrosis in rats， possibly by inhibiting the synthesis of collagen fiber， reducing transaminase content， down-regulating the levels of HA， LN， PC Ⅲ and COL-Ⅳ， and reducing the inflammatory response.

Objective:To explore the causal association of glucose-lipid metabolism and obesity indicators with myocardial infarction by a two-sample Mendelian randomization analysis.Methods:Single nucleotide polymorphisms (SNPs) related to phenotypes were obtained from genome-wide association study databases. The body mass index (BMI) and glycated hemoglobin dataset includes 99 998 samples and 8 126 035 SNPs; the waist-to-hip ratio dataset includes 224 459 samples and 2 562 516 SNPs; the waist circumference and hip circumference dataset includes 462 166 samples and 9 851 867 SNPs; the fasting glucose dataset includes approximately 12 million SNPs; the low-density lipoprotein cholesterol (LDL-C) dataset includes 201 678 samples and 12 321 875 SNPs; the high-density lipoprotein cholesterol (HDL-C), and triglycerides dataset includes 156 109 samples and 15 784 414 SNPs; and the body fat percentage, whole-body fat mass, trunk fat percentage, and trunk fat mass dataset includes 454 588 samples and 9 851 867 SNPs. This study primarily used inverse-variance weighted method to analyze the associations between various exposure factors and outcomes. Heterogeneity among SNPs was assessed using Cochran′s Q test, and horizontal pleiotropy of SNPs was examined using the MR-Egger method. Additionally, a multivariable MR approach was used to adjust for BMI, further validating associations between exposure factors and the risk of myocardial infarction. Results:Higher BMI ( OR=1.070, 95% CI: 1.041-1.100), waist-to-hip ratio ( OR=1.366, 95% CI: 1.113-1.677), LDL-C ( OR=1.638, 95% CI: 1.488-1.803), triglycerides ( OR=1.445, 95% CI: 1.300-1.606), waist circumference ( OR=1.841, 95% CI: 1.650-2.055), hip circumference ( OR=1.247, 95% CI: 1.132-1.372), body fat percentage ( OR=1.795, 95% CI: 1.568-2.055), whole-body fat mass ( OR=1.519, 95% CI: 1.381-1.670), trunk fat percentage ( OR=1.538, 95% CI: 1.374-1.723), and trunk fat mass ( OR=1.421, 95% CI: 1.294-1.561), as well as lower HDL-C ( OR=0.799, 95% CI: 0.729-0.875), have causal effects on myocardial infarction (all P<0.05). After adjusting for BMI, hip circumference, trunk fat percentage, and trunk fat mass were no longer associated with myocardial infarction. However, waist-to-hip ratio ( OR=1.457, 95% CI: 1.132-1.877), fasting glucose ( OR=1.191, 95% CI: 1.024-1.383), glycated hemoglobin ( OR=1.129, 95% CI: 1.034-1.233), LDL-C ( OR=1.592, 95% CI: 1.314-1.929), triglycerides ( OR=1.410, 95% CI: 1.279-1.553), waist circumference ( OR=1.922, 95% CI: 1.448-2.551), body fat percentage ( OR=1.421, 95% CI: 1.072-1.884), and whole-body fat mass ( OR=1.295, 95% CI: 1.031-1.626) remained positively associated with myocardial infarction, while HDL-C ( OR=0.809, 95% CI: 0.729-0.897) remained negatively associated. Conclusions:Abdominal obesity and dysregulation of glucose-lipid metabolism are risk factors for myocardial infarction. Screening for glucose-lipid metabolism (fasting glucose, HDL-C, LDL-C, triglycerides) and obesity-related indicators (waist circumference, waist-to-hip ratio, body fat percentage, and whole-body fat mass) is of great importance for the primary prevention of myocardial infarction.