BACKGROUND: Spatiotemporal disparities exist in the disease burden of non-communicable diseases (NCDs) attributable to kidney dysfunction, which has been poorly assessed. The present study aimed to evaluate the spatiotemporal trends of the global burden of NCDs attributable to kidney dysfunction and to predict future trends. METHODS: Data on NCDs attributable to kidney dysfunction, quantified using deaths and disability-adjusted life-years (DALYs), were extracted from the Global Burden of Diseases Injuries, and Risk Factors (GBD) Study in 2019. Estimated annual percentage change (EAPC) of age-standardized rate (ASR) was calculated with linear regression to assess the changing trend. Pearson's correlation analysis was used to determine the association between ASR and sociodemographic index (SDI) for 21 GBD regions. A Bayesian age-period-cohort (BAPC) model was used to predict future trends up to 2040. RESULTS: Between 1990 and 2019, the absolute number of deaths and DALYs from NCDs attributable to kidney dysfunction increased globally. The death cases increased from 1,571,720 (95% uncertainty interval [UI]: 1,344,420-1,805,598) in 1990 to 3,161,552 (95% UI: 2,723,363-3,623,814) in 2019 for both sexes combined. Both the ASR of death and DALYs increased in Andean Latin America, the Caribbean, Central Latin America, Southeast Asia, Oceania, and Southern Sub-Saharan Africa. In contrast, the age-standardized metrics decreased in the high-income Asia Pacific region. The relationship between SDI and ASR of death and DALYs was negatively correlated. The BAPC model indicated that there would be approximately 5,806,780 death cases and 119,013,659 DALY cases in 2040 that could be attributed to kidney dysfunction. Age-standardized death of cardiovascular diseases (CVDs) and CKD attributable to kidney dysfunction were predicted to decrease and increase from 2020 to 2040, respectively. CONCLUSION NCDs attributable to kidney dysfunction remain a major public health concern worldwide. Efforts are required to attenuate the death and disability burden, particularly in low and low-to-middle SDI regions.
Humans ; Noncommunicable Diseases/epidemiology* ; Global Burden of Disease ; Disability-Adjusted Life Years ; Male ; Female ; Risk Factors ; Middle Aged ; Kidney Diseases/epidemiology* ; Bayes Theorem ; Adult ; Aged ; Global Health ; Quality-Adjusted Life Years

BACKGROUND: As an essential part of health services, rehabilitation is of great significance to improve the health and quality of life of the whole population. Accelerating aging calls for a significant expansion of rehabilitation services in China, but rehabilitation needs remain unclear. We conducted the study to explore the rehabilitation needs in China and project the trend of rehabilitation needs from 2020 to 2034. METHODS: The data of health conditions that might potentially benefit from rehabilitation were obtained from Global Burden of Disease (GBD) study. Estimated annual percentage changes (EAPCs) were calculated to quantify the trends of the age-standardized rates. Projections of rehabilitation needs were made until 2034 using Bayesian age-period-cohort analysis (BAPC). RESULTS: Approximately 460 million persons (33.3% of the total population) need rehabilitation in China, contributing to 63 million years lived with disabilities (YLDs) in 2019. The number of prevalent cases that need rehabilitation increased from around 268 (95% uncertainty interval [UI]: 257-282) million in 1990 to almost 460 (95% UI: 443-479) million in 2019, representing an increase of 71.3%. The highest contribution to the need for rehabilitation was musculoskeletal disorders with about 322 (95% UI: 302-343) million persons in seven aggregate disease and injury categories, and hearing loss with over 95 (95% UI: 84-107) million people among 25 health conditions. Based on the projection results, there will be almost 636 million people (45% of the total population) needing rehabilitation services in China by 2034, representing an increase of 38.3%. The rehabilitation needs of neoplasms, cardiovascular diseases, and neurological disorders are expected to increase significantly from 2019 to 2034, with increases of 102.3%, 88.8% and 73.2%, respectively. CONCLUSIONS The need for rehabilitation in China substantially increased over the last 30 years. It is predicted that over two in five people will require rehabilitation by 2034, thus suggesting the need to develop rehabilitation services that meet individuals' rehabilitation needs.
Humans ; China/epidemiology* ; Global Burden of Disease ; Female ; Male ; Musculoskeletal Diseases/epidemiology* ; Rehabilitation/trends* ; Quality of Life ; Middle Aged ; Aged ; Bayes Theorem

BACKGROUND: Research has indicated that the disease burden of alopecia areata (AA) in China exceeds the global average. Therefore, accurate and updated epidemiological information is crucial for policymakers. In this study, we aimed to comprehensively assess the disease burden of AA in China. METHODS: The following four key indicators were utilized: the prevalence of cases; disability-adjusted life-years (DALYs); the age-standardized prevalence rate (ASPR); and the age-standardized DALY rate (ASDR) of AA according to the Global Burden of Disease (GBD) study 2021. We analyzed the epidemiological burden of AA in China during 2021, examined changes between 1990 and 2021, and performed a Bayesian age-period-cohort analysis to predict trends over the course of the next decade (2022-2030). Additionally, a Gaussian process regression model was applied to estimate the relationship between the gross domestic product (GDP) and the ASPR and ASDR of AA at the provincial level between 1992 and 2021. RESULTS: In 2021, the estimated number of patients with AA in China was approximately 3.49 million (95% uncertainty interval [UI], 3.37-3.62 million); of these patients, 1.20 million (95% UI, 1.16-1.25 million) were male and 2.29 million (95% UI, 2.20-2.37 million) were female. This large number of patients with AA resulted in a total of 114,431.25 DALYs (95% UI, 74,780.27-160,318.96 DALYs). Additionally, the ASPR and ASDR were 224.61 per 100,000 population (95% UI, 216.73-232.65 per 100,000 population) and 7.41 per 100,000 population (95% UI, 4.85-10.44 per 100,000 population), respectively; both of these rates were higher than the global averages. The most affected demographic groups were young and female individuals 25-39 years of age. Slight regional disparities were observed, with the northern and central regions of China bearing comparatively higher burdens. Between 1990 and 2021, the health loss and disease burden caused by AA in China remained relatively stable. The ASPR and ASDR of AA increased with the GDP when the annual GDP was less than 2 trillion Chinese yuan; however, a downward trend was observed as the GDP surpassed 2 trillion Chinese yuan. A slight upward trend in the disease burden of AA in China is predicted to occur over the next decade. CONCLUSIONS AA continues to be a public health concern in China that shows no signs of declining. Targeted efforts for young individuals and females are necessary because they experience a disproportionately high burden of AA.
Humans ; China/epidemiology* ; Alopecia Areata/epidemiology* ; Global Burden of Disease ; Female ; Male ; Adult ; Disability-Adjusted Life Years ; Middle Aged ; Prevalence ; Adolescent ; Young Adult ; Bayes Theorem ; Child ; Quality-Adjusted Life Years ; Child, Preschool

BACKGROUND: Asthma, one of the most widespread chronic respiratory diseases, has placed a considerable economic and social stress on China. This study examines the burden of asthma in China from 1990 to 2021 and forecasts future trends, providing guidance for establishing focused preventive and regulatory strategies. METHODS: Utilizing data from the Global Burden of Disease Database 2021, the analysis of trends in asthma burden was conducted for China from 1990 to 2021. Key indicators such as incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were analysed. The investigation applied the estimated annual percentage change (EAPC), average annual percentage change (AAPC), and age-period-cohort model (APCM) to evaluate these trends. Furthermore, predictions for incidence and mortality in 2035 were generated using the Bayesian APCM and the Nordpred model. RESULTS: In 2021, there were 25,015,668 prevalent asthma cases in China, alongside 3,934,875 new cases and 26,233 deaths. The age-standardized incidence rate and age-standardized death rate for 2021 were 364.17 (95% uncertainty interval [95% UI]: 283.22-494.1) per 100,000 population and 1.47 (95% UI: 1.15-1.79) per 100,000 population, respectively. The age-standardized rates (ASRs) for incidence were detected to be elevated in the 0-4 years age group, and the prevalence was significantly higher in the 5-9 years age group compared to other cohorts. ASR for incidence and prevalence of asthma in China were lower than that in the global average. Between 1990 and 2021, the ASR of incidence, prevalence, mortality, and DALYs demonstrated a downward trajectory, with EAPC values of -1.17, -1.57, -4.69, and -2.98, respectively. People aged 0-9 years and over 60 years experienced a disproportionately higher disease burden. Projections indicate that the ASRs for incidence will continue to rise, whereas the death will continue to decline by 2035. CONCLUSIONS Between 1990 and 2021, a general reduction in the asthma burden in China was observed. However, the burden remains particularly high among people aged 0-9 years and over 60 years, underscoring the need for targeted interventions and policies to address the ongoing challenges of asthma.
Humans ; Asthma/mortality* ; China/epidemiology* ; Global Burden of Disease ; Incidence ; Disability-Adjusted Life Years ; Male ; Adult ; Middle Aged ; Child ; Adolescent ; Female ; Prevalence ; Child, Preschool ; Infant ; Aged ; Young Adult ; Infant, Newborn ; Bayes Theorem

Basket trial, as an innovative clinical trial design concept, marks the transformation of medical research from the traditional large-scale and single-disease treatment to the precise and individualized treatment. By gradually incorporating the Bayesian method during development, the trial design becomes more scientific and reasonable and increases its efficiency. The fundamental principle of the Bayesian method is the utilization of prior knowledge in conjunction with new observational data to dynamically update the posterior probability. This flexibility enhances the basket trial's capacity to effectively adapt to variations during the research process. Consequently, it enables researchers to dynamically adjust research strategies based on accumulated data and improve the predictive accuracy regarding treatment responses. In addition, the design concept of the basket trial aligns with the traditional Chinese medicine(TCM) principle of "homotherapy for heteropathy". The principle of "homotherapy for heteropathy" emphasizes that under certain conditions, different diseases may have the same treatment. Similarly, basket trials allow using a uniform trial design across multiple diseases, offering enhanced operational and significant practical value in the realm of TCM, particularly within the context of syndrome-based disease research. By introducing basket trials, the design of TCM clinical studies will be more scientific and yield higher-quality evidence. This study systematically categorized various Bayesian methods and models utilized in basket trials, evaluated their strengths and weaknesses, and identified their appropriate application contexts, so as to offer a practical guide for designing basket trials in the realm of TCM.
Bayes Theorem ; Humans ; Medicine, Chinese Traditional/methods* ; Research Design ; Clinical Trials as Topic/methods* ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVES: To analyze the disease burden of melanoma among middle-aged and elderly populations in China, and to predict the future trend. METHODS: Data from the Global Burden of Disease (GBD) 2021 were utilized to collect incidence and mortality rates of melanoma, disability-adjusted life years (DALYs), and corresponding age crude rates among the middle-aged and elderly population in China during 1990 and 2021. Additionally, the estimated annual percentage change (EAPC) was employed to assess the temporal trends. Age-period-cohort (APC) and Bayesian age-period-cohort (BAPC) models were utilized to compute age, period, and cohort effects on incidence and mortality rates of melanoma, as well as to predict future trends up to 2035. RESULTS: During 1990-2021, the incidence rate of melanoma for males was higher than that for females among the middle-aged and elderly population in China, and the overall incidence rate increased annually with an EAPC of 2.13 (1.90-2.36), while the overall mortality rate and DALY rate showed a declining trend with an EAPC of －0.28 (－0.41-－0.15) and －0.54 (－0.68-－0.41), respectively. The results of the APC model analysis revealed that age effects on both incidence and mortality rates of melanoma in China's middle-aged and elderly population were significant, with both increasing with age. Period and cohort effects showed an upward trend for incidence rates but a downward trend for mortality rates. Moreover, the period and cohort effects for mortality rates were not significant among females. In the BAPC prediction model, the number of incidences of melanoma in middle-aged and elderly people in China would increase dramatically. By 2035, the number of incidence cases is expected to reach approximately 9600 (males) and 10 300 (females), corresponding to an incidence rate of 2.66/10⁵ and 2.67/10⁵, respectively. The number of deaths is projected to be about 2600 (males) and 3500 (females) by 2035, corresponding to a mortality rate of 0.72/10⁵ and 0.91/10⁵, respectively. CONCLUSIONS The disease burden of melanoma among the middle-aged and elderly population in China remains substantial and is expected to increase over the next decade.
Humans ; Melanoma/mortality* ; China/epidemiology* ; Aged ; Middle Aged ; Male ; Female ; Incidence ; Disability-Adjusted Life Years ; Bayes Theorem ; Cost of Illness ; Skin Neoplasms/epidemiology*

OBJECTIVE: The relationship between benign prostatic hyperplasia (BPH) and the oxidative balance score (OBS) will be discussed in this study. METHODS: The clinical data on 16 dimensions of diet and 4 dimensions of lifestyle from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2008 were used to calculate OBS. We considered BPH as the outcome and investigated the linear and nonlinear relationships between the two. Additionally, subgroup analyses and interaction tests were conducted as well. Furthermore, the methods of machine learning including XGBoost, support vector machine (SVM) and naive Bayes (NB) were used to establish a predictive model for BPH. RESULTS: Higher OBS was consistently associated with an increased prevalence of BPH, with Restricted Cubic Splines highlighting a significant positive nonlinear association (P=0.015). Subgroup analyses revealed differences and interactive relationships based on alcohol consumption. Among the seven machine learning models that we included the OBS score in, the XGBoost model emerged as the best, with an AUC value of 0.769. CONCLUSION There is a significant association between OBS and the prevalence of BPH in the American population, which provides a valuable insight for further diagnosis and research of the disease.
Humans ; Male ; Prostatic Hyperplasia/epidemiology* ; Machine Learning ; Bayes Theorem ; Nutrition Surveys ; Support Vector Machine ; Life Style ; Oxidative Stress ; Aged ; Diet ; Prevalence

OBJECTIVE: To enhance the reliability of medical equipment, this study aims to develop a failure cause diagnosis model and provide rational suggestions for efficient equipment use. METHODS: Combine fault tree analysis (FTA) to identify basic events causing equipment failure and calculate their prior probabilities. Obtain conditional probability tables for each node through expert assessment. Integrate triangular fuzzy number theory with Bayesian network (BN) to construct a fuzzy Bayesian network (FBN) for posterior probability inference and sensitivity analysis. RESULTS: Using endoscopes as the subject, the analysis shows that the model accurately calculates the endoscope failure probability at 0.385%, and identifies the key causes: improper cleaning ( X5, posterior probability 0.36064), untimely fault detection ( X8, posterior probability 0.23571), irregular transportation ( X6, posterior probability 0.11344), and natural aging ( X10, posterior probability 0.11377). Sensitivity analysis also confirms their influence weights (mutual information values are 0.00749, 0.00591, 0.00202, 0.00174). CONCLUSION The model can accurately perform quantitative analysis and rapid fault location of medical equipment failures, enabling effective preventive measures.
Bayes Theorem ; Fuzzy Logic ; Equipment Failure Analysis/methods* ; Equipment Failure ; Algorithms

OBJECTIVES: Nasopharyngeal carcinoma is often diagnosed at a late stage due to its concealed location and exhibits marked regional clustering, posing a significant public health challenge in China. This study aims to analyze the disease burden of nasopharyngeal carcinoma in China using the latest 2021 Global Burden of Diseases (GBD) database, providing epidemiological evidence for precise prevention and control of nasopharyngeal carcinoma. METHODS: Age-standardized incidence rate (ASIR), mortality rate, and disability-adjusted life year (DALY) rate were used as indicators of disease burden. Stratified analyses were conducted by age, sex, socio-demographic index (SDI), and relevant risk factors. The autoregressive integrated moving average (ARIMA) model and Bayesian age-period-cohort (BAPC) model were employed to project ASIR trends through 2050. RESULTS: In 2021, China's age-standardized incidence, mortality, and DALY rates of nasopharyngeal carcinoma were 3.4/100 000, 1.5/100 000, and 48.7/100 000, respectively, all higher than the global average. Across all age groups, Chinese males exhibited higher ASIR, mortality, and DALY rates than females. From 1990 to 2021, the disease burden of nasopharyngeal carcinoma in China decreased gradually with rising SDI. The proportion of nasopharyngeal carcinoma burden attributed to alcohol consumption, smoking, and occupational formaldehyde exposure in China exceeded global levels, especially among males. Projections from both models indicate a rising trend in ASIR for males, females, and the general population in China and globally from 2022 to 2050. CONCLUSIONS Over the past 30 years, the disease burden of nasopharyngeal carcinoma in China has decreased with the increasing SDI values but remains higher than the global average. Furthermore, ASIR is projected to increase over the next 30 years. It is imperative for China to enhance healthcare resource allocation for nasopharyngeal carcinoma prevention, diagnosis, and treatment, particularly among high-risk male populations.
Humans ; China/epidemiology* ; Male ; Nasopharyngeal Carcinoma/mortality* ; Female ; Middle Aged ; Nasopharyngeal Neoplasms/mortality* ; Adult ; Incidence ; Global Burden of Disease ; Disability-Adjusted Life Years ; Aged ; Risk Factors ; Adolescent ; Databases, Factual ; Young Adult ; Cost of Illness ; Child ; Bayes Theorem

OBJECTIVES: Global epidemiological data indicate that 20% to 30% of intensive care unit (ICU) sepsis patients progress to deep vein thrombosis (DVT) due to coagulopathy, with an associated mortality rate of 25% to 40%. Existing prognostic tools have limitations. This study aims to develop and validate nomogram and machine learning models to predict in-hospital mortality in sepsis patients with DVT and assess their clinical applicability. METHODS: This multicenter retrospective study drew on data from the Medical Information Mart for Intensive Care IV (MIMIC-IV; n=2 235), the eICU Collaborative Research Database (eICU-CRD; n=1 274), and the Patient Admission Dataset from the ICU of Third Xiangya Hospital, Central South University (CSU-XYS-ICU; n=107). MIMIC-IV was split into a training set (n=1 584) and internal validation set (n=651), with the remaining datasets used for external validation. Predictors were selected via least absolute shrinkage and selection operator (LASSO) regression and Bayesian Information Criterion (BIC), and a nomogram model was constructed. An extreme gradient boosting (XGBoost) algorithm was used to build the machine learning model. Model performance was assessed by the concordance index (C-index), calibration curves, Brier score, decision curve analysis (DCA), and net reclassification improvement index (NRI). RESULTS: Five key predictors, age [odds ratio (OR)=1.02, 95% CI 1.01 to 1.03, P<0.001], minimum activated partial thromboplastin (APTT; OR=1.09, 95% CI 1.08 to 1.11, P<0.001), maximum APTT (OR=1.01, 95% CI 1.00 to 1.01, P<0.001), maximum lactate (OR=1.56, 95% CI 1.39 to 1.75, P<0.001), and maximum serum creatinine (OR=2.03, 95% CI 1.79 to 2.30, P<0.001), were included in the nomogram. The model showed robust performance in internal validation (C-index=0.845, 95% CI 0.811 to 0.879) and external validation (eICU-CRD: C-index=0.827, 95% CI 0.800 to 0.854; CSU-XYS-ICU: C-index=0.779, 95% CI 0.687 to 0.871). Calibration curves indicated good agreement between predicted and observed outcomes (Brier score<0.25), and DCA confirmed clinical benefit. The XGBoost model achieved an area under the receiver operating characteristic curve (AUC) of 0.982 (95% CI 0.969 to 0.985) in the training set, but performance declined in external validation (eICU-CRD, AUC=0.825, 95% CI 0.817 to 0.861; CSU-XYS-ICU, AUC=0.766, 95% CI 0.700 to 0.873), though it remained above clinical thresholds. Net reclassification improvement was slightly lower for XGBoost compared with the nomogram (NRI=0.58). CONCLUSIONS Both the nomogram and XGBoost models effectively predict in-hospital mortality in sepsis patients with DVT. However, the nomogram offers superior generalizability and clinical usability. Its visual scoring system provides a quantitative tool for identifying high-risk patients and implementing individualized interventions.
Humans ; Sepsis/complications* ; Machine Learning ; Nomograms ; Venous Thrombosis/complications* ; Retrospective Studies ; Hospital Mortality ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units ; Prognosis ; Bayes Theorem