Background: Diabetic kidney disease (DKD) is a prevalent and severe complication of diabetes that significantly impacts global health and quality of life. Most DKD is attributable to type 2 diabetes; therefore, chronic type 2 DKD warrants further examination.Objective: To deliver targeted assistance in alleviating the worldwide, regional, and national burden of chronic type 2 DKD, we executed a survey assessing the prevalence of chronic type 2 DKD utilizing the Global Burden of Disease, Injury, and Risk Factors (GBD) database.Methods: We examined the temporal trends of chronic type 2 DKD prevalence over the past 30 years using the 2021 GBD database, analyzed the trends by population, epidemiological change, and aging, and quantified cross‐country health inequalities. Additionally, we forecasted the trend during the subsequent two decades.Results: In 2021, there were over 107 million cases of chronic type 2 DKD globally, reflecting an 85.11% rise from 58 million cases in 1990. The age‐standardized rate (ASR) declined with an estimated annual percentage change of 0.17% per annum. Epidemiological change and population expansion are the primary factors influencing the alterations. The contributions of epidemiological change, population, and aging vary with alterations in the sociodemographic index (SDI). Significant health inequalities were observed across 204 countries and territories, with the slope index of inequality increasing over time. The forecast for the worldwide burden of chronic type 2 DKD from 2020 to 2040 suggests a significant rise in case numbers, while the alterations in ASR remain largely stable.Conclusions: These findings indicate the significant disease burden of chronic type 2 DKD, necessitating more targeted and effective interventions for its prevention and management.

Objectives Colon and rectum cancer, the third most common cancer globally, is a considerable health challenge worldwide. Despite the excellent insights offered by the global burden of disease (GBD) study, comprehensive assessments of colon and rectum cancer remain limited. This study utilises the most recent GBD dataset to examine the impacts of colon and rectum cancer, incorporating contemporary data alongside projections for 2036. Methods We analysed data from the 2021 GBD database, focusing on metrics pertaining to colon and rectum cancer: prevalence, incidence, mortality and disability-adjusted life years (DALYs) across 204 countries and territories, classified into 21 GBD regions and five sociodemographic index (SDI) regions. The data analysis encompassed computations of relative change, annual percentage change and estimated annual percentage change. This research also employed the Pearson algorithm to investigate the relationship between disease burden and SDI, conduct cross-country inequality analysis, perform age-period-cohort analysis and execute decomposition analysis. Finally, an autoregressive integrated moving average model was utilised to project trends over the next 15 years. Results From 1990 to 2021, the global prevalence of colon and rectum cancer increased significantly, from approximately 4.27 million to 11.68 million cases (age-standardised prevalence rate increased from ~108.25 to 134.84 per 100 000). Incident cases rose by 139.38% (age-standardised incidence rate increased by 6.52%). Mortality increased by 83.07% but with a significant decrease in age-standardised mortality rate (−20.33%), and DALYs increased by 69.49% with a corresponding decrease in age-standardised DALYs (−20.73%). Data on gender from 1990 to 2021 indicates that men experience a greater disease burden than women. A significant correlation exists between the illness burden of SDI and colon and rectum cancer, and the age-period-cohort model has provided further insights. Decomposition analysis reveals that population growth is the primary factor affecting the burden of colon and rectum cancer disease. The predictive study for the forthcoming 15 years indicates that while the mortality and DALYs for both genders will persist in their reduction, the prevalence and incidence rates for males will continue to increase, whereas those for women will remain relatively stable. Conclusions The burden of colon and rectum cancer has markedly escalated worldwide in the last 30 years. Essential methods to mitigate this trend encompass the reduction of modifiable risk factors, enhancement of early identification and treatment, and augmentation of early screening, particularly for high-risk male populations under 50 years of age. The rising incidence rate among youth underscores the necessity to enhance comprehension of developing risk factors and mechanisms, as well as to advance research on disease prevention and control techniques.

Background: A comprehensive assessment of disease burden is critical for optimizing management strategies for chronic kidney disease (CKD) due to type 2 diabetes (T2DM) in China. This study analyzes 30-year trends (1990–2021) in T2DM-related CKD burden, epidemiological characteristics, 15-year projections and dietary risk factors in China. Methods: Data from the Global Burden of Disease Study (GBD) were used to examine prevalence, incidence, deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs) and years of life lost (YLLs) stratified by age, sex and year. Analytical methods included joinpoint regression to identify trend changes, age-period-cohort modeling to disentangle demographic effects, decomposition analysis to assess drivers (aging, population growth, epidemiological shifts), autoregressive integrated moving average (ARIMA) forecasting for 2022–36 projections and dietary risk factor analysis focusing on seven modifiable dietary factors. Results: From 1990 to 2021, T2DM-related CKD burden showed a consistent upward trend. In 2021, prevalence reached 20.91 million cases [age-standardized rate (ASR) 1053.92/100 000], a 75.87% increase from 1990. Incidence and mortality rose by 177.64% and 147.26%, respectively, with 354 000 new cases and 108 000 deaths. Males exhibited higher ASRs than females across all outcomes, and the 70–94 years age group bore the highest burden. Aging was the primary driver of burden growth. Projections (2022–36) indicate declining age-standardized prevalence but rising trends in incidence, mortality, DALYs and YLLs, with stable YLDs. Key dietary risks included high red-meat consumption and low intake of whole grains and fruits. Conclusions: While age-standardized rates for some outcomes may decline, absolute burdens of T2DM-related CKD in China are increasing, driven by population aging. Strengthening healthcare systems, enhancing risk factor screening (e.g. dietary interventions) and improving diabetes management are imperative for prevention and control.

Background: Migraine is a prevalent neurological condition that causes significant disability and has a profound impact on sufferers' ability to work and their overall quality of life. The efficacy of acupuncture in the treatment of migraines has been confirmed via extensive clinical research. However, because each acupoint generates various analgesic processes, and different acupuncture physicians select different acupoints, there is still uncertainty regarding the optimal acupoint selection. Objective: Our purpose is to conduct the initial thorough data mining analysis to determine the optimal acupoint selection and combinations for the treatment of migraines. Methods: We will conduct a search of eight electronic bibliographic databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Database) from the inception of the databases to July 2024. Clinical trials that evaluate the efficacy of acupuncture therapy in migraine management will be chosen. Literature will be rigorously reviewed in accordance with inclusion and exclusion criteria, and pertinent data will be extracted for analysis. Excel 2021 will be utilized to conduct descriptive statistics. SPSS Modeler 14.1 will be employed to conduct the association rule analysis. SPSS Statistics 26.0 will be employed to conduct exploratory factor analysis, cluster analysis, and decision tree analysis. Results: This study aims to investigate the optimal acupoint selection and combinations for people suffering from migraines. Conclusion: Our research will offer empirical support for the efficacy and possible therapeutic recommendations of acupoint application in treating migraine patients, facilitating collaborative decision -making between physicians and patients.

Background: Abundant clinical investigations have attested to the efficacy of acupuncture in treating migraines. However, as each acupoint elicits distinct analgesic pathways and acupuncturists vary in their acupoint selection, there is currently an absence of evidence-based guidance for determining the optimal acupoint selection. Objective: The aim of this study was to conduct an initial comprehensive data mining analysis to identify the most effective acupoints and their combinations for migraine treatment. Methods: A comprehensive search was carried out in eight electronic bibliographic databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Database) from their inception up to May 2025. Studies evaluating the effectiveness of acupuncture in treating migraines were selected. The literature was rigorously evaluated according to predefined inclusion and exclusion criteria, and relevant data were then extracted for analysis. Excel 2021 was used for descriptive statistical analysis. Association rule analysis was performed using SPSS Modeler 14.1. Exploratory factor analysis, cluster analysis, and decision tree analysis were conducted using SPSS Statistics 26.0. Results: A total of 911 trials were identified, from which 1610 groups of effective prescriptions involving 181 acupoints were extracted. The most commonly used acupoints were Feng-chi (GB20), Tai-yang (EX-HN5), Shuai-gu (GB8), Bai-hui (GV20), and He-gu (LI4). The gallbladder meridian was the most frequently utilized meridian. Specific points, mainly crossing points, were predominantly used, with head and neck acupoints being the most common. The combination of “Feng-chi (GB20), Tai-yang (EX-HN5), and Shuai-gu (GB8)” was frequently used as the core acupoints group. Additionally, several acupoint combinations were obtained through exploratory factor analysis, cluster analysis, and decision tree analysis. Conclusion: This research provides evidence-based support for the effectiveness of acupoint selection in migraine treatment and offers potential therapeutic recommendations, thereby facilitating collaborative decision-making between healthcare providers and patients.

Background: Trigeminal neuralgia is a prevalent neurological disorder within neuropathic pain. It severely impairs patients’ quality of life, disrupting daily activities with intense facial pain. While acupuncture has proven effective in treating it, there’s no consensus on acupoint selection. Different acupuncturists use various acupoints based on personal theories and experiences, and the optimal acupoints remain unclear due to varied analgesic mechanisms. This lack of clarity obstructs the standardization of acupuncture treatment, emphasizing the need for further research. Objective: Our purpose is to conduct the first thorough data mining analysis to identify the most effective acupoint selection and combinations for treating trigeminal neuralgia from published clinical trials. Methods: We will search 8 electronic bibliographic databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database and Chongqing VIP Database) from inception to May 2025. Clinical trials assessing the effectiveness of acupuncture therapy on the management of trigeminal neuralgia will be selected. We will strictly screen literature according to inclusion and exclusion criteria, and then extract relevant data for analysis. Descriptive statistics will be performed in Excel 2021. Association rule analysis will be performed in SPSS Modeler 14.1. Exploratory factor analysis, cluster analysis, and decision tree analysis will be performed in SPSS Statistics 26.0. Since the study was based on published studies, no ethical approval was required. Results: This study will investigate the most effective acupoint selection and combinations for patients with trigeminal neuralgia. Conclusion: Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with trigeminal neuralgia, helping clinicians and patients make a more informed decision together.