Objective To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease.Methods This prospective cohort study inc...Objective To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease.Methods This prospective cohort study included 318,085 biobank participants from the UK.Physical activity was assessed using the short form of the International Physical Activity Questionnaire.The participants were stratified into low-,intermediate-,and high-genetic-risk groups based on their polygenic risk scores.Multivariate Cox regression models and multiplicative interaction analyses were used.Results During a median follow-up period of 13 years,9,209 participants were diagnosed with chronic obstructive pulmonary disease.For low genetic risk,compared to low physical activity,the hazard ratios(HRs)for moderate and high physical activity were 0.853(95%confidence interval[CI]:0.748–0.972)and 0.831(95%CI:0.727–0.950),respectively.For intermediate genetic risk,the HRs were 0.829(95%CI:0.758–0.905)and 0.835(95%CI:0.764–0.914),respectively.For participants with high genetic risk,the HRs were 0.809(95%CI:0.746–0.877)and 0.818(95%CI:0.754–0.888),respectively.A significant interaction was observed between genetic risk and physical activity.Conclusion Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups,highlighting the need to tailor activity interventions for genetically susceptible individuals.展开更多
Objective To evaluate the association between serum uric acid(SUA)and kidney function decline.Methods Data was obtained from the China Health and Retirement Longitudinal Study on the Chinese middle-aged and older popu...Objective To evaluate the association between serum uric acid(SUA)and kidney function decline.Methods Data was obtained from the China Health and Retirement Longitudinal Study on the Chinese middle-aged and older population for analysis.The kidney function decline was defined as an annual estimated glomerular filtration rate(e GFR)decrease by>3 mL/min per 1.73 m^(2).Multivariable logistic regression was applied to determine the association between SUA and kidney function decline.The shape of the association was investigated by restricted cubic splines.Results A total of 7,346 participants were included,of which 1,004 individuals(13.67%)developed kidney function decline during the follow-up of 4 years.A significant dose-response relation was recorded between SUA and the kidney function decline(OR 1.14,95%CI 1.03-1.27),as the risk of kidney function decline increased by 14%per 1 mg/d L increase in SUA.In the subgroup analyses,such a relation was only recorded among women(OR 1.22,95%CI 1.03-1.45),those aged<60 years(OR 1.22,95%CI 1.05-1.42),and those without hypertension and without diabetes(OR 1.22,95%CI 1.06-1.41).Although the dose-response relation was not observed in men,the high level of SUA was related to kidney function decline(OR 1.83,95%CI 1.05-3.17).The restricted cubic spline analysis indicated that SUA>5 mg/dL was associated with a significantly higher risk of kidney function decline.Conclusion The SUA level was associated with kidney function decline.An elevation of SUA should therefore be addressed to prevent possible kidney impairment and dysfunction.展开更多
Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospe...Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.展开更多
Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginn...Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginners to grasp the intricate composition rules of formulas.To address this gap,we introduce Formula-S,a situated visualization method for TCM formula learning in augmented reality(AR)and evaluate its performance.This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization.Methods Formula-S is an interactive AR tool designed for TCM formula learning,featuring three modes(3D,Web,and Table).The dataset included TCM formulas and herb properties extracted from authoritative references,including textbook and the SymMap database.In Formula-S,the hierarchical visualization of the formulas as herbal medicine compositions,is linked to the multidimensional herb attribute visualization and embedded in the real world,where real herb samples are presented.To evaluate its effectiveness,a controlled study(n=30)was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification,formula composition,and recognition.In the study,participants interacted with the AR tool through HoloLens 2.Data were collected on both task performance(accuracy and response time)and user experience,with a focus on task efficiency,accuracy,and user preference across the different learning modes.Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks.Regarding user experience,our new approach demonstrated the highest system usability and lowest task load,effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency.Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment,suggesting this approach offers usability advantages for TCM education.Conclusions The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods.Additionally,it provides superior contextual understanding of TCM formulas,making it a promising new solution for TCM learning.展开更多
Rehabilitation is described as interventions that aim to optimize functioning and reduce disability in individuals with health conditions,considering their environment[1].Global estimates of rehabilitation needs revea...Rehabilitation is described as interventions that aim to optimize functioning and reduce disability in individuals with health conditions,considering their environment[1].Global estimates of rehabilitation needs revealed that about one-third of the world's population could potentially benefit from rehabilitation in 2019,making a substantial 69%increase in years lived with disability(YLDs)since 1990[2].With the expanding global population,aging demographics,and shifts in health trends,the health burden of functional recovery is experiencing a significant escalation[3].展开更多
To the Editor:Assessment of data appropriateness is a process to answer whether electronic health records(EHRs)from routine healthcare practices couldt intended study purposes,for example,available to be proceeded,wit...To the Editor:Assessment of data appropriateness is a process to answer whether electronic health records(EHRs)from routine healthcare practices couldt intended study purposes,for example,available to be proceeded,with enough individual records,with relevant information able to be extracted from records,etc.[1-3]This has been increasingly underscored as a prerequisite when using EHRs(one important type of real-world data[RWD])for scientic purposes.[4-6]Although controversies remain on the denitions,types and assessment methods of the dimensions of RWD appropriateness,the latest ofcial guidelines(i.e.,from the U.S.Food and Drug Administration[FDA][4]and China National Medical Products Administration[NMPA][6])suggest that the assessment start from a preliminary stage on variable existence,and subsequently deepen into the issue of data value(such as missing value,outliers,etc.),as the preliminary assessment is the foundation of the overall RWD appropriateness.[7]Little is known about the appropriateness of EHRs in developing regions,which feature high visit volumes and a great number of hospitals.Therefore,this study aimed to preliminarily investigate RWD appropriateness from hospitals in developing regions from the perspective of core variables’comparison.展开更多
Objective:The aim of this study is to construct a curated bibliographic dataset for a landscape analysis on Health Artiffcial Intelligence(HAI)research.Data Source:We integrated HAI-related bibliographic records,inclu...Objective:The aim of this study is to construct a curated bibliographic dataset for a landscape analysis on Health Artiffcial Intelligence(HAI)research.Data Source:We integrated HAI-related bibliographic records,including publications,open research datasets,patents,research grants,and clinical trials from Medline and Dimensions.Methods:Searching:Relevant documents were identiffed using Medical Subject Headings(MeSH)and Field of Research(FoR)indexed by 2 bibliographic databases,Medline and Dimensions.Extracting:MeSH terms annotated from the aforementioned bibliographic databases served as the primary information for our processing.For document records lacking MeSH terms,we reextracted them using the Medical Text Indexer(MTI).Mapping:In order to enhance interoperability,HAI multi-documents were organized using a mapping system incorporating MeSH,FoR,The International Classiffcation of Diseases(ICD-10),and Systematized Nomenclature of Medicine Clinical Terms(SNOMED CT).Integrating:All documents were curated based on a pre-deffned ontology of health problems and AI technologies from the MeSH hierarchy.Results:We collected 96,332 HAI documents(publications:75,820,open research datasets:638,patents:11,226,grants:6,113,and clinical trials:2,535)during 2009 to 2021.On average,75.12%of the documents were tagged with at least one label related to either health problems or AI technologies(with 92.9%of publications tagged).Summary:This study presents a comprehensive pipeline for processing and curating HAI bibliographic documents following the FAIR(Findable,Accessible,Interoperable,Reusable)standard,offering a valuable multidimensional collection for the community.This dataset serves as a crucial resource for horizontally scanning the funding,research,clinical assessments,and innovations within the HAI ffeld.展开更多
BACKGROUND The electrocardiogram(ECG)is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure(HF).The application of artificial intelligence(AI)has con...BACKGROUND The electrocardiogram(ECG)is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure(HF).The application of artificial intelligence(AI)has contributed to clinical practice in terms of aiding diagnosis,prognosis,risk stratification and guiding clinical management.The aim of this study is to systematically review and perform a meta-analysis of published studies on the application of AI for HF detection based on the ECG.METHODS We searched Embase,PubMed and Web of Science databases to identify literature using AI for HF detection based on ECG data.The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2(QUADAS-2)criteria.Random-effects models were used for calculating the effect estimates and hierarchical receiver operating characteristic curves were plotted.Subgroup analysis was performed.Heterogeneity and the risk of bias were also assessed.RESULTS A total of 11 studies including 104,737 subjects were included.The area under the curve for HF diagnosis was 0.986,with a corresponding pooled sensitivity of 0.95(95%CI:0.86–0.98),specificity of 0.98(95%CI:0.95–0.99)and diagnostic odds ratio of 831.51(95%CI:127.85–5407.74).In the patient selection domain of QUADAS-2,eight studies were designated as high risk.CONCLUSIONS According to the available evidence,the incorporation of AI can aid the diagnosis of HF.However,there is heterogeneity among machine learning algorithms and improvements are required in terms of quality and study design.展开更多
Rheumatoid arthritis imposes a huge disease burden.Existing practice guidelines do not meet the needs of integrated traditional Chinese medicine and Western medicine in the treatment of rheumatoid arthritis.We establi...Rheumatoid arthritis imposes a huge disease burden.Existing practice guidelines do not meet the needs of integrated traditional Chinese medicine and Western medicine in the treatment of rheumatoid arthritis.We established a guideline working group consists of a steering committee,a secretary group,an evidence evaluation group,a consensus group and a review group and developed a guideline following the guidance of the World Health Organization Handbook and the Chinese Medical Association.The guideline includes 35 recommendations which reached consensus by the two rounds Delphi surveys.These recommendations were formulated to address the following themes of most concern to clinician:diagnostic imaging,disease staging,traditional Chinese medicine syndromes,effectiveness and toxicity of integrated traditional Chinese medicine and Western medicine.展开更多
Background:Climate change profoundly shapes the population health at the global scale.However,there was still insufficient and inconsistent evidence for the association between heat exposure and chronic kidney disease...Background:Climate change profoundly shapes the population health at the global scale.However,there was still insufficient and inconsistent evidence for the association between heat exposure and chronic kidney disease(CKD).Methods:In the present study,we studied the association of heat exposure with hospitalizations for cause-specific CKD using a national inpatient database in China during the study period of hot season from 2015 to 2018.Standard time-series regression models and random-effects Meta-analysis were developed to estimate the city-specific and national averaged associations at a 7 lag-day span,respectively.Results:A total of 768,129 hospitalizations for CKD was recorded during the study period.The results showed that higher temperature was associated with elevated risk of hospitalizations for CKD,especially in sub-tropical cities.With a 1℃ increase in daily mean temperature,the cumulative relative risks(RR)over lag 0-7 d were 1.008[95% confidence interval(CI)1.003-1.012]for nationwide.The attributable fraction of CKD hospitalizations due to high temperatures was 5.50%.Stronger associations were observed among younger patients and those with obstructive nephropathy.Our study also found that exposure to heatwaves was associated with added risk of hospitalizations for CKD compared to non-heatwave days(RR=1.116,95%CI 1.069-1.166)above the effect of daily mean temperature.Conclusions:Short-term heat exposure may increase the risk of hospitalization for CKD.Our findings provide insights into the health effects of climate change and suggest the necessity of guided protection strategies against the adverse effects of high temperatures.展开更多
To the Editor:Chronic kidney disease(CKD)is a global burden of the public health.The global prevalence of CKD exceeded 10%while the awareness was around 10%.[1]In the era of big data,improving the identification of CK...To the Editor:Chronic kidney disease(CKD)is a global burden of the public health.The global prevalence of CKD exceeded 10%while the awareness was around 10%.[1]In the era of big data,improving the identification of CKD using informatic tools is important.Computable phenotype is proven as an efficient tool to facilitate the process of patient identification using electronic health record(EHR)data.展开更多
Background:Missing data in electronic health records(EHRs)presents signiffcant challenges in medical studies.Many methods have been proposed,but uncertainty exists regarding the current state of missing data addressin...Background:Missing data in electronic health records(EHRs)presents signiffcant challenges in medical studies.Many methods have been proposed,but uncertainty exists regarding the current state of missing data addressing methods applied for EHR and which strategy performs better within speciffc contexts.Methods:All studies referencing EHR and missing data methods published from their inception until 2024 March 30 were searched via the MEDLINE,EMBASE,and Digital Bibliography and Library Project databases.The characteristics of the included studies were extracted.We also compared the performance of various methods under different missingness scenarios.Results:After screening,46 studies published between 2010 and 2024 were included.Three missingness mechanisms were simulated when evaluating the missing data methods:missing completely at random(29/46),missing at random(20/46),and missing not at random(21/46).Multiple imputation by chained equations(MICE)was the most popular statistical method,whereas generative adversarial network-based methods and the k nearest neighbor(KNN)classiffcation were the common deep-learning-based or traditional machine-learning-based methods,respectively.Among the 26 articles comparing the performance among medical statistical and machine learning approaches,traditional machine learning or deep learning methods generally outperformed statistical methods.Med.KNN and context-aware time-series imputation performed better for longitudinal datasets,whereas probabilistic principal component analysis and MICE-based methods were optimal for cross-sectional datasets.Conclusions:Machine learning methods show signiffcant promise for addressing missing data in EHRs.However,no single approach provides a universally generalizable solution.Standardized benchmarking analyses are essential to evaluate these methods across different missingness scenarios.展开更多
Importance:Climate change mitigation policies aimed at limiting greenhouse gas(GHG)emissions would bring substantial health co-benefits by directly alleviating climate change or indirectly reducing air pollution.As on...Importance:Climate change mitigation policies aimed at limiting greenhouse gas(GHG)emissions would bring substantial health co-benefits by directly alleviating climate change or indirectly reducing air pollution.As one of the largest developing countries and GHG emitter globally,China’s carbonpeaking and carbon neutrality goals would lead to substantial co-benefits on global environment and therefore on human health.This review summarized the key findings and gaps in studies on the impact of China’s carbon mitigation strategies on human health.Highlights:There is a wide consensus that limiting the temperature rise well below 2℃would markedly reduce the climaterelated health impacts compared with high emission scenario,although heat-related mortalities,labor productivity reduction rates,and infectious disease morbidities would continue increasing over time as temperature rises.Further,hundreds of thousands of air pollutant-related mortalities(mainly due to PM_(2.5)and O_(3))could be avoided per year compared with the reference scenario without climate policy.Carbon reduction policies can also alleviate morbidities due to acute exposure to PM_(2.5).Further research with respect to morbidities attributed to nonoptimal temperature and air pollution,and health impacts attributed to precipitation and extreme weather events under current carbon policy in China or its equivalent in other developing countries is needed to improve our understanding of the disease burden in the coming decades.Conclusions:This review provides upto-date evidence of potential health co-benefits under Chinese carbon policies and highlights the importance of considering these co-benefits into future climate policy development in both China and other nations endeavoring carbon reductions.展开更多
The global population is aging rapidly,with those aged 65 years and older projected to reach 2.2 billion by the 2070s,surpassing the number of children.1 This demographic shift presents profound healthcare and socioec...The global population is aging rapidly,with those aged 65 years and older projected to reach 2.2 billion by the 2070s,surpassing the number of children.1 This demographic shift presents profound healthcare and socioeconomic challenges,driven by the growing burden of chronic diseases such as diabetes,cardiovascular conditions,and neurodegenerative disorders among the elderly.展开更多
Health data and cutting-edge technologies empower medicine and improve healthcare.It has become even more true during the COVID-19 pandemic.Through coronavirus data sharing and worldwide collaboration,the speed of vac...Health data and cutting-edge technologies empower medicine and improve healthcare.It has become even more true during the COVID-19 pandemic.Through coronavirus data sharing and worldwide collaboration,the speed of vaccine development for COVID-19 is unprecedented.Digital and data technologies were quickly adopted during the pandemic,showing how those technologies can be harnessed to enhance public health and healthcare.A wide range of digital data sources are being utilized and visually presented to enhance the epidemiological surveillance of COVID-19.Digital contact tracing mobile apps have been adopted by many countries to control community transmission.Deep learning has been utilized to achieve various solutions for COVID-19 disruption,including outbreak prediction,virus spread tracking.展开更多
Improving population health by creating more equitable health systems is a major focus of health policy and planning today.However,before we can achieve equity in health,we must first begin by leveraging all we have l...Improving population health by creating more equitable health systems is a major focus of health policy and planning today.However,before we can achieve equity in health,we must first begin by leveraging all we have learned,and are continuing to discover,about the many social,structural,and environmental determinants of health.We must fully consider the conditions in which people are born,grow,learn,work,play,and age.The study of social determinants of health has made tremendous strides in recent decades.At the same time,we have seen huge advances in how health data are collected,analyzed,and used to inform action in the health sector.It is time to merge these two fields,to harness the best from both and to improve decision-making to accelerate evidence-based action toward greater health equity.展开更多
Background:Atopic dermatitis(AD)is a chronic inflammatory skin disorder impacting populations worldwide,although its clinical characteristics and patient demographics remain uncharacterized in China.The aim of this st...Background:Atopic dermatitis(AD)is a chronic inflammatory skin disorder impacting populations worldwide,although its clinical characteristics and patient demographics remain uncharacterized in China.The aim of this study was to investigate the demographics,comorbidities,aggravating factors,and treatments in AD patients across different age groups in China.Methods:This cross-sectional study included Chinese AD patients from 205 hospitals spanning 30 provinces.Patients completed dermatologist-led surveys of general medical history,comorbidities,AD-related aggravating factors,and medications.Two-level mixed-ordered logistic regression was used to evaluate aggravating factors.Results:Overall,16,838 respondents were included in the final analysis(aged 30.9±24.1 years).The proportion of severe AD was the highest in patients with AD onset at≥60 years(26.73%).Allergic rhinitis and hypertension were the most common atopic and metabolism-related non-atopic comorbidities,respectively.AD severity was significantly associated with chronic urticaria,food allergies,and diabetes.Aggravating factors including foods,seasonal changes,and psychological factors were also linked to AD severity.The cross-sectional survey implied that severe AD may be related to the undertreatment of effective systemic or topical interventions.Conclusion:To enhance the management of AD,it is crucial to consider both aggravating factors and the increased utilization of systemic immunotherapy.Registration:ClinicalTrials.gov,NCT05316805.展开更多
The past twenty years have seen the increasingly important role of ontology in traditional Chinese medicine(TCM).However,the development of TCM ontology faces many challenges.Since the epistemologies dramatically diff...The past twenty years have seen the increasingly important role of ontology in traditional Chinese medicine(TCM).However,the development of TCM ontology faces many challenges.Since the epistemologies dramatically differ between TCM and contemporary biomedicine,it is hard to apply the existing top-level ontology mechanically.“Data silos”are widely present in the currently available terminology standards,term sets,and ontologies.The formal representation of ontology needs to be further improved in TCM.Therefore,we propose a unified basic semantic framework of TCM based on in-depth theoretical research on the existing top・level ontology and a re-study of important concepts in TCM.Under such a framework,ontologies in TCM subdomains should be built collaboratively and be represented formally in a common format.Besides,extensive cooperation should be encouraged by establishing ontology research communities to promote ontology peer review and reuse.展开更多
Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measur...Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements.Design/methodology/approach:Taking cardiovascular research publications in China as a sample,we extracted subject-predicate-object triples(SPO triples)as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context.We introduced information entropy(IE)as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs(SO pairs)levels.Findings:The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples.After evaluating the uncertainty of biomedical knowledge with IE,we identified the Top 10 SO pairs with highest IE,which implied the epistemic status pluralism.Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research.Research limitations:The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words.The number of sentences surrounding a given triple may also influence the value of IE.Practical implications:Our approach identified major uncertain knowledge areas such as diagnostic biomarkers,genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China.These areas are suggested to be prioritized;new hypotheses need to be verified,while disputes,conflicts,and contradictions need to be settled.Originality/value:We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.展开更多
To the Editor:Thymic malignancies refer to a group of malignant tumors that originated from the thymic gland,including thymoma,thymic carcinoma,thymic carcinoid,andmalignancies from other uncommon histological origins...To the Editor:Thymic malignancies refer to a group of malignant tumors that originated from the thymic gland,including thymoma,thymic carcinoma,thymic carcinoid,andmalignancies from other uncommon histological origins.As a set of rare diseases,only a limitednumber of studies have reported incidences of malignancies in thymus.展开更多
基金supported by the Construction of High-level University of Guangdong(G624330242)the National Natural Science Foundation of China (82425052) to Dr. Chen Maothe Postdoctoral Fellowship Program of CPSF(GZC20231052) to Dr. Jin Yang
文摘Objective To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease.Methods This prospective cohort study included 318,085 biobank participants from the UK.Physical activity was assessed using the short form of the International Physical Activity Questionnaire.The participants were stratified into low-,intermediate-,and high-genetic-risk groups based on their polygenic risk scores.Multivariate Cox regression models and multiplicative interaction analyses were used.Results During a median follow-up period of 13 years,9,209 participants were diagnosed with chronic obstructive pulmonary disease.For low genetic risk,compared to low physical activity,the hazard ratios(HRs)for moderate and high physical activity were 0.853(95%confidence interval[CI]:0.748–0.972)and 0.831(95%CI:0.727–0.950),respectively.For intermediate genetic risk,the HRs were 0.829(95%CI:0.758–0.905)and 0.835(95%CI:0.764–0.914),respectively.For participants with high genetic risk,the HRs were 0.809(95%CI:0.746–0.877)and 0.818(95%CI:0.754–0.888),respectively.A significant interaction was observed between genetic risk and physical activity.Conclusion Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups,highlighting the need to tailor activity interventions for genetically susceptible individuals.
文摘Objective To evaluate the association between serum uric acid(SUA)and kidney function decline.Methods Data was obtained from the China Health and Retirement Longitudinal Study on the Chinese middle-aged and older population for analysis.The kidney function decline was defined as an annual estimated glomerular filtration rate(e GFR)decrease by>3 mL/min per 1.73 m^(2).Multivariable logistic regression was applied to determine the association between SUA and kidney function decline.The shape of the association was investigated by restricted cubic splines.Results A total of 7,346 participants were included,of which 1,004 individuals(13.67%)developed kidney function decline during the follow-up of 4 years.A significant dose-response relation was recorded between SUA and the kidney function decline(OR 1.14,95%CI 1.03-1.27),as the risk of kidney function decline increased by 14%per 1 mg/d L increase in SUA.In the subgroup analyses,such a relation was only recorded among women(OR 1.22,95%CI 1.03-1.45),those aged<60 years(OR 1.22,95%CI 1.05-1.42),and those without hypertension and without diabetes(OR 1.22,95%CI 1.06-1.41).Although the dose-response relation was not observed in men,the high level of SUA was related to kidney function decline(OR 1.83,95%CI 1.05-3.17).The restricted cubic spline analysis indicated that SUA>5 mg/dL was associated with a significantly higher risk of kidney function decline.Conclusion The SUA level was associated with kidney function decline.An elevation of SUA should therefore be addressed to prevent possible kidney impairment and dysfunction.
基金supported by the National Natural Science Foundation of China(grant No.72074011)the Real World Study Project of Hainan Boao Lecheng Pilot Zone(Real World Study Base of NMPA)(HNLC2022RWS012)+1 种基金the fundamental research funds for central public welfare research institutes(2023CZ-11)National Natural Science Foundation of China(No.82003536).
文摘Background:Patients with type 2 diabetes are at high risk for developing multiple chronic complications.However,there is a lack of studies of the cumulative number of diabetic complications in China.Methods:A retrospective cohort study was performed from 2009 to 2021.Type 2 diabetes patients who were first diagnosed after the age of 35 years between January 1,2009,and December 31,2017,were included.Five states were defined according to the number of chronic complications:no(S0),one(S1),two(S2),three(S3),and four or more complications(S4).A multi-state Markov model was constructed to estimate transition probability,transition intensity,mean sojourn time,and the possible factors for each state.Results:The study included 32653 type 2 diabetes patients(mean age,59.59 years;15929(48.8%)male),and mean follow-up time of 7.75 years.In all,4375 transitions were observed.The 12-year transition probability of from state S0 to S1 was the lowest at 16.4%,while that from S2 to S3 was the highest,at 45.6%.Higher fasting blood glucose,lower high-density lipoprotein cholesterol,higher total cholesterol,and an unhealthy diet were associated with higher risk of progression from S0 to S1.Being female,less than 60 years old,weekly physical activity,and vegetarian diet decreased this risk.Being female and less than 60 years old reduced the likelihood of transition from S1 to S2,whereas lower high-density lipoprotein cholesterol increased this likelihood.Conclusions:Following the occurrence of two complications in type 2 diabetes patients,the risk for accumulating a third complication within a short time is significantly increased.It is important to take advantage of the stable window period when patients have fewer than two complications,strengthen the monitoring of blood glucose and blood lipids,and encourage patients to maintain good living habits to prevent further deterioration.
文摘Objective The study of medicine formulas is a core component of traditional Chinese medicine(TCM),yet traditional learning methods often lack interactivity and contextual understanding,making it challenging for beginners to grasp the intricate composition rules of formulas.To address this gap,we introduce Formula-S,a situated visualization method for TCM formula learning in augmented reality(AR)and evaluate its performance.This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization.Methods Formula-S is an interactive AR tool designed for TCM formula learning,featuring three modes(3D,Web,and Table).The dataset included TCM formulas and herb properties extracted from authoritative references,including textbook and the SymMap database.In Formula-S,the hierarchical visualization of the formulas as herbal medicine compositions,is linked to the multidimensional herb attribute visualization and embedded in the real world,where real herb samples are presented.To evaluate its effectiveness,a controlled study(n=30)was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification,formula composition,and recognition.In the study,participants interacted with the AR tool through HoloLens 2.Data were collected on both task performance(accuracy and response time)and user experience,with a focus on task efficiency,accuracy,and user preference across the different learning modes.Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks.Regarding user experience,our new approach demonstrated the highest system usability and lowest task load,effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency.Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment,suggesting this approach offers usability advantages for TCM education.Conclusions The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods.Additionally,it provides superior contextual understanding of TCM formulas,making it a promising new solution for TCM learning.
基金supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project(2023ZD0509601)National Natural Science Foundation of China(L2324221 and 82202820)+1 种基金CAMS Innovation Fund for Medical Sciences(2021-I2M-5-003)Haihe Laboratory of Cell Ecosystem Innovation Fund(22HHXBSS00007)。
文摘Rehabilitation is described as interventions that aim to optimize functioning and reduce disability in individuals with health conditions,considering their environment[1].Global estimates of rehabilitation needs revealed that about one-third of the world's population could potentially benefit from rehabilitation in 2019,making a substantial 69%increase in years lived with disability(YLDs)since 1990[2].With the expanding global population,aging demographics,and shifts in health trends,the health burden of functional recovery is experiencing a significant escalation[3].
基金supported by grants from the National Natural Science Foundation of China(Nos.82173616 and 82003536)Peking University Medicine Fund of Fostering Young Scholars’Scientific&Technological Innovation(No.BMU2022PYB035)+1 种基金Fundamental Research Funds for the Central University,Key Clinical Projects of Peking University Third Hospital(No.BYSYZD2021030)Institute of Cultural Heritage and Innovation,Fuzhou Branch,Peking University(No.FZICIPKU20200010)
文摘To the Editor:Assessment of data appropriateness is a process to answer whether electronic health records(EHRs)from routine healthcare practices couldt intended study purposes,for example,available to be proceeded,with enough individual records,with relevant information able to be extracted from records,etc.[1-3]This has been increasingly underscored as a prerequisite when using EHRs(one important type of real-world data[RWD])for scientic purposes.[4-6]Although controversies remain on the denitions,types and assessment methods of the dimensions of RWD appropriateness,the latest ofcial guidelines(i.e.,from the U.S.Food and Drug Administration[FDA][4]and China National Medical Products Administration[NMPA][6])suggest that the assessment start from a preliminary stage on variable existence,and subsequently deepen into the issue of data value(such as missing value,outliers,etc.),as the preliminary assessment is the foundation of the overall RWD appropriateness.[7]Little is known about the appropriateness of EHRs in developing regions,which feature high visit volumes and a great number of hospitals.Therefore,this study aimed to preliminarily investigate RWD appropriateness from hospitals in developing regions from the perspective of core variables’comparison.
基金funded by the National Key R&D Program for Young Scientists(2022YFF0712000).
文摘Objective:The aim of this study is to construct a curated bibliographic dataset for a landscape analysis on Health Artiffcial Intelligence(HAI)research.Data Source:We integrated HAI-related bibliographic records,including publications,open research datasets,patents,research grants,and clinical trials from Medline and Dimensions.Methods:Searching:Relevant documents were identiffed using Medical Subject Headings(MeSH)and Field of Research(FoR)indexed by 2 bibliographic databases,Medline and Dimensions.Extracting:MeSH terms annotated from the aforementioned bibliographic databases served as the primary information for our processing.For document records lacking MeSH terms,we reextracted them using the Medical Text Indexer(MTI).Mapping:In order to enhance interoperability,HAI multi-documents were organized using a mapping system incorporating MeSH,FoR,The International Classiffcation of Diseases(ICD-10),and Systematized Nomenclature of Medicine Clinical Terms(SNOMED CT).Integrating:All documents were curated based on a pre-deffned ontology of health problems and AI technologies from the MeSH hierarchy.Results:We collected 96,332 HAI documents(publications:75,820,open research datasets:638,patents:11,226,grants:6,113,and clinical trials:2,535)during 2009 to 2021.On average,75.12%of the documents were tagged with at least one label related to either health problems or AI technologies(with 92.9%of publications tagged).Summary:This study presents a comprehensive pipeline for processing and curating HAI bibliographic documents following the FAIR(Findable,Accessible,Interoperable,Reusable)standard,offering a valuable multidimensional collection for the community.This dataset serves as a crucial resource for horizontally scanning the funding,research,clinical assessments,and innovations within the HAI ffeld.
基金supported by the National Natural Science Foundation of China(No.81970270&No.82170327)the Tianjin Natural Science Foundation(20JC ZDJC00340&20JCZXJC00130)the Tianjin Key Medical Discipline(Specialty)Construction Project(TJYXZDXK-029A)。
文摘BACKGROUND The electrocardiogram(ECG)is an inexpensive and easily accessible investigation for the diagnosis of cardiovascular diseases including heart failure(HF).The application of artificial intelligence(AI)has contributed to clinical practice in terms of aiding diagnosis,prognosis,risk stratification and guiding clinical management.The aim of this study is to systematically review and perform a meta-analysis of published studies on the application of AI for HF detection based on the ECG.METHODS We searched Embase,PubMed and Web of Science databases to identify literature using AI for HF detection based on ECG data.The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2(QUADAS-2)criteria.Random-effects models were used for calculating the effect estimates and hierarchical receiver operating characteristic curves were plotted.Subgroup analysis was performed.Heterogeneity and the risk of bias were also assessed.RESULTS A total of 11 studies including 104,737 subjects were included.The area under the curve for HF diagnosis was 0.986,with a corresponding pooled sensitivity of 0.95(95%CI:0.86–0.98),specificity of 0.98(95%CI:0.95–0.99)and diagnostic odds ratio of 831.51(95%CI:127.85–5407.74).In the patient selection domain of QUADAS-2,eight studies were designated as high risk.CONCLUSIONS According to the available evidence,the incorporation of AI can aid the diagnosis of HF.However,there is heterogeneity among machine learning algorithms and improvements are required in terms of quality and study design.
基金National Key Research and Development Program of China(No.2018YFC1705503).
文摘Rheumatoid arthritis imposes a huge disease burden.Existing practice guidelines do not meet the needs of integrated traditional Chinese medicine and Western medicine in the treatment of rheumatoid arthritis.We established a guideline working group consists of a steering committee,a secretary group,an evidence evaluation group,a consensus group and a review group and developed a guideline following the guidance of the World Health Organization Handbook and the Chinese Medical Association.The guideline includes 35 recommendations which reached consensus by the two rounds Delphi surveys.These recommendations were formulated to address the following themes of most concern to clinician:diagnostic imaging,disease staging,traditional Chinese medicine syndromes,effectiveness and toxicity of integrated traditional Chinese medicine and Western medicine.
基金This study was supported by the National Natural Science Foundation of China(82003529,72125009)the National Key Research and Development Program of the Ministry of Science and Technology of China(2019YFC2005000)+4 种基金the Chinese Scientific and Technical Innovation Project 2030(2018AAA0102100)the National High Level Hospital Clinical Research Funding(“Star of Outlook”Scientific Research Project of Peking University First Hospital,2022XW06)the CAMS Innovation Fund for Medical Sciences(2019-I2M-5-046)the Young Elite Scientists Sponsorship Program by CAST(2022QNRC001)the PKU-Baidu Fund(2020BD004,2020BD005 and 2020BD032).
文摘Background:Climate change profoundly shapes the population health at the global scale.However,there was still insufficient and inconsistent evidence for the association between heat exposure and chronic kidney disease(CKD).Methods:In the present study,we studied the association of heat exposure with hospitalizations for cause-specific CKD using a national inpatient database in China during the study period of hot season from 2015 to 2018.Standard time-series regression models and random-effects Meta-analysis were developed to estimate the city-specific and national averaged associations at a 7 lag-day span,respectively.Results:A total of 768,129 hospitalizations for CKD was recorded during the study period.The results showed that higher temperature was associated with elevated risk of hospitalizations for CKD,especially in sub-tropical cities.With a 1℃ increase in daily mean temperature,the cumulative relative risks(RR)over lag 0-7 d were 1.008[95% confidence interval(CI)1.003-1.012]for nationwide.The attributable fraction of CKD hospitalizations due to high temperatures was 5.50%.Stronger associations were observed among younger patients and those with obstructive nephropathy.Our study also found that exposure to heatwaves was associated with added risk of hospitalizations for CKD compared to non-heatwave days(RR=1.116,95%CI 1.069-1.166)above the effect of daily mean temperature.Conclusions:Short-term heat exposure may increase the risk of hospitalization for CKD.Our findings provide insights into the health effects of climate change and suggest the necessity of guided protection strategies against the adverse effects of high temperatures.
基金National Natural Science Foundation of China(Nos.82100741,82003529,91846101,81771938,81900665,82090021)Beijing Municipal Science and Technology Commission(Grant No.7212201)+5 种基金the University of Michigan Health System-Peking University Health Science Center Joint Institute for Translational and Clinical Research(Nos.BMU2020JI011,BMU2019JI005,BMU2018JI012)Beijing Nova Programme Interdisciplinary Cooperation Project(No.Z191100001119008)National Key R&D Program of the Ministry of Science and Technology of China(No.2019YFC2005000)the National Key Research and Development Program of China(No.2018AAA0102100)PKU-Baidu Fund(Nos.2020BD005,2019BD017)CAMS Innovation Fund for Medical Sciences(No.2019-I2M-5-046)
文摘To the Editor:Chronic kidney disease(CKD)is a global burden of the public health.The global prevalence of CKD exceeded 10%while the awareness was around 10%.[1]In the era of big data,improving the identification of CKD using informatic tools is important.Computable phenotype is proven as an efficient tool to facilitate the process of patient identification using electronic health record(EHR)data.
基金supported by the Research and Development Fund of Peking University People’s Hospital(Missing Data in Electronic Health Records program[MINDER])(RDX2023-11)the National Natural Science Foundation of China(No.62102008 and No.81602939).
文摘Background:Missing data in electronic health records(EHRs)presents signiffcant challenges in medical studies.Many methods have been proposed,but uncertainty exists regarding the current state of missing data addressing methods applied for EHR and which strategy performs better within speciffc contexts.Methods:All studies referencing EHR and missing data methods published from their inception until 2024 March 30 were searched via the MEDLINE,EMBASE,and Digital Bibliography and Library Project databases.The characteristics of the included studies were extracted.We also compared the performance of various methods under different missingness scenarios.Results:After screening,46 studies published between 2010 and 2024 were included.Three missingness mechanisms were simulated when evaluating the missing data methods:missing completely at random(29/46),missing at random(20/46),and missing not at random(21/46).Multiple imputation by chained equations(MICE)was the most popular statistical method,whereas generative adversarial network-based methods and the k nearest neighbor(KNN)classiffcation were the common deep-learning-based or traditional machine-learning-based methods,respectively.Among the 26 articles comparing the performance among medical statistical and machine learning approaches,traditional machine learning or deep learning methods generally outperformed statistical methods.Med.KNN and context-aware time-series imputation performed better for longitudinal datasets,whereas probabilistic principal component analysis and MICE-based methods were optimal for cross-sectional datasets.Conclusions:Machine learning methods show signiffcant promise for addressing missing data in EHRs.However,no single approach provides a universally generalizable solution.Standardized benchmarking analyses are essential to evaluate these methods across different missingness scenarios.
基金supported by grants from the National Natural Science Foundation of China(72125009,82204137,and 82003529)National Key R&D Program of the Ministry of Science and Technology of China(2022YFF1203001)Young Elite Scientists Sponsorship Program by CAST(2022QNRC001 and 2023QNRC001)。
文摘Importance:Climate change mitigation policies aimed at limiting greenhouse gas(GHG)emissions would bring substantial health co-benefits by directly alleviating climate change or indirectly reducing air pollution.As one of the largest developing countries and GHG emitter globally,China’s carbonpeaking and carbon neutrality goals would lead to substantial co-benefits on global environment and therefore on human health.This review summarized the key findings and gaps in studies on the impact of China’s carbon mitigation strategies on human health.Highlights:There is a wide consensus that limiting the temperature rise well below 2℃would markedly reduce the climaterelated health impacts compared with high emission scenario,although heat-related mortalities,labor productivity reduction rates,and infectious disease morbidities would continue increasing over time as temperature rises.Further,hundreds of thousands of air pollutant-related mortalities(mainly due to PM_(2.5)and O_(3))could be avoided per year compared with the reference scenario without climate policy.Carbon reduction policies can also alleviate morbidities due to acute exposure to PM_(2.5).Further research with respect to morbidities attributed to nonoptimal temperature and air pollution,and health impacts attributed to precipitation and extreme weather events under current carbon policy in China or its equivalent in other developing countries is needed to improve our understanding of the disease burden in the coming decades.Conclusions:This review provides upto-date evidence of potential health co-benefits under Chinese carbon policies and highlights the importance of considering these co-benefits into future climate policy development in both China and other nations endeavoring carbon reductions.
基金supported by the National Natural Science Foundation of China(72474010)Strategic Research and Consulting Project of Chinese Academy of Engineering(2022-XBZD-30).
文摘The global population is aging rapidly,with those aged 65 years and older projected to reach 2.2 billion by the 2070s,surpassing the number of children.1 This demographic shift presents profound healthcare and socioeconomic challenges,driven by the growing burden of chronic diseases such as diabetes,cardiovascular conditions,and neurodegenerative disorders among the elderly.
文摘Health data and cutting-edge technologies empower medicine and improve healthcare.It has become even more true during the COVID-19 pandemic.Through coronavirus data sharing and worldwide collaboration,the speed of vaccine development for COVID-19 is unprecedented.Digital and data technologies were quickly adopted during the pandemic,showing how those technologies can be harnessed to enhance public health and healthcare.A wide range of digital data sources are being utilized and visually presented to enhance the epidemiological surveillance of COVID-19.Digital contact tracing mobile apps have been adopted by many countries to control community transmission.Deep learning has been utilized to achieve various solutions for COVID-19 disruption,including outbreak prediction,virus spread tracking.
文摘Improving population health by creating more equitable health systems is a major focus of health policy and planning today.However,before we can achieve equity in health,we must first begin by leveraging all we have learned,and are continuing to discover,about the many social,structural,and environmental determinants of health.We must fully consider the conditions in which people are born,grow,learn,work,play,and age.The study of social determinants of health has made tremendous strides in recent decades.At the same time,we have seen huge advances in how health data are collected,analyzed,and used to inform action in the health sector.It is time to merge these two fields,to harness the best from both and to improve decision-making to accelerate evidence-based action toward greater health equity.
基金supported by the PKU-Baidu Fund(No.2020BD012)National Natural Science Foundation of China(No.81903213).
文摘Background:Atopic dermatitis(AD)is a chronic inflammatory skin disorder impacting populations worldwide,although its clinical characteristics and patient demographics remain uncharacterized in China.The aim of this study was to investigate the demographics,comorbidities,aggravating factors,and treatments in AD patients across different age groups in China.Methods:This cross-sectional study included Chinese AD patients from 205 hospitals spanning 30 provinces.Patients completed dermatologist-led surveys of general medical history,comorbidities,AD-related aggravating factors,and medications.Two-level mixed-ordered logistic regression was used to evaluate aggravating factors.Results:Overall,16,838 respondents were included in the final analysis(aged 30.9±24.1 years).The proportion of severe AD was the highest in patients with AD onset at≥60 years(26.73%).Allergic rhinitis and hypertension were the most common atopic and metabolism-related non-atopic comorbidities,respectively.AD severity was significantly associated with chronic urticaria,food allergies,and diabetes.Aggravating factors including foods,seasonal changes,and psychological factors were also linked to AD severity.The cross-sectional survey implied that severe AD may be related to the undertreatment of effective systemic or topical interventions.Conclusion:To enhance the management of AD,it is crucial to consider both aggravating factors and the increased utilization of systemic immunotherapy.Registration:ClinicalTrials.gov,NCT05316805.
文摘The past twenty years have seen the increasingly important role of ontology in traditional Chinese medicine(TCM).However,the development of TCM ontology faces many challenges.Since the epistemologies dramatically differ between TCM and contemporary biomedicine,it is hard to apply the existing top-level ontology mechanically.“Data silos”are widely present in the currently available terminology standards,term sets,and ontologies.The formal representation of ontology needs to be further improved in TCM.Therefore,we propose a unified basic semantic framework of TCM based on in-depth theoretical research on the existing top・level ontology and a re-study of important concepts in TCM.Under such a framework,ontologies in TCM subdomains should be built collaboratively and be represented formally in a common format.Besides,extensive cooperation should be encouraged by establishing ontology research communities to promote ontology peer review and reuse.
基金funded by the National Natural Science Foundation of China(nos.71603280,72074006,and 82070235)the Beijing Municipal Natural Science Foundation(7191013)+1 种基金Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases,Chinese Academy of Medical Sciences(2021RU003)Peking University Health Science Center and the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2017QNRC001).
文摘Purpose:Given the information overload of scientific literature,there is an increasing need for computable biomedical knowledge buried in free text.This study aimed to develop a novel approach to extracting and measuring uncertain biomedical knowledge from scientific statements.Design/methodology/approach:Taking cardiovascular research publications in China as a sample,we extracted subject-predicate-object triples(SPO triples)as knowledge units and unknown/hedging/conflicting uncertainties as the knowledge context.We introduced information entropy(IE)as potential metric to quantify the uncertainty of epistemic status of scientific knowledge represented at subject-object pairs(SO pairs)levels.Findings:The results indicated an extraordinary growth of cardiovascular publications in China while only a modest growth of the novel SPO triples.After evaluating the uncertainty of biomedical knowledge with IE,we identified the Top 10 SO pairs with highest IE,which implied the epistemic status pluralism.Visual presentation of the SO pairs overlaid with uncertainty provided a comprehensive overview of clusters of biomedical knowledge and contending topics in cardiovascular research.Research limitations:The current methods didn’t distinguish the specificity and probabilities of uncertainty cue words.The number of sentences surrounding a given triple may also influence the value of IE.Practical implications:Our approach identified major uncertain knowledge areas such as diagnostic biomarkers,genetic polymorphism and co-existing risk factors related to cardiovascular diseases in China.These areas are suggested to be prioritized;new hypotheses need to be verified,while disputes,conflicts,and contradictions need to be settled.Originality/value:We provided a novel approach by combining natural language processing and computational linguistics with informetric methods to extract and measure uncertain knowledge from scientific statements.
基金supported by grants from the National Natural Science Foundation of China(No.72125009)Peking University(No.BMU2022XTZ005)+1 种基金Beijing advanced discipline construction project(No.BMU2019GJJXK001)Project 2019BD017,2020BD004,2020BD005 supported by PKU-Baidu Fund.
文摘To the Editor:Thymic malignancies refer to a group of malignant tumors that originated from the thymic gland,including thymoma,thymic carcinoma,thymic carcinoid,andmalignancies from other uncommon histological origins.As a set of rare diseases,only a limitednumber of studies have reported incidences of malignancies in thymus.
