1.Influence of environment and genetic factors on axis length in children and adolescents
ZHENG Jie, ZHANG Jian, FENG Lixia
Chinese Journal of School Health 2026;47(6):869-872
Objective:
To investigate the heritability of axial length (AL) by comparing the consistency of AL in monozygotic (MZ) and dizygotic (DZ) twins, thereby providing data support for research on the genetic mechanisms and prevention and control practices of myopia in children and adolescents.
Methods:
A total of 137 twin pairs aged 3 to 16 years who attended the Optometry Center of the First Affiliated Hospital of Anhui Medical University from January 2021 to December 2024 were enrolled, comprising 79 DZ pairs and 58 MZ pairs. Biometry was used to measure children s axial length, and structural equation modeling within the OpenMx package was applied to calculate the heritability of axial length.
Results:
The overall mean axial length of the twin cohort was (23.7±1.5) mm. The intraclass correlation coefficient (ICC) for axial length in all twins was 0.82 (95% CI =0.76-0.87) ( P < 0.05 ). The ICC for MZ twins was 0.97 (95% CI =0.94-0.98), which was higher than that for DZ twins ( ICC =0.71, 95% CI =0.58-0.80) (both P <0.05). Maximum likelihood estimation using OpenMx revealed that the additive genetic plus unique environmental (AE) model provided the best fit. Specifically, additive genetic factors (A) accounted for 93.63% (95% CI =90.31%-95.69%) of the total variance, while unique environmental factors (E) accounted for 6.37% (95% CI =4.31%-9.69%).
Conclusion
Axial length in children is predominantly influenced by genetic factors, while unique environmental factors also play a contributory role.
2.Application of ERAS nursing combined with isokinetic muscle strength visual feedback training in knee joint injury
Jiabin HONG ; Yingmei ZHANG ; Lixia ZHENG
China Modern Doctor 2025;63(17):38-41
Objective To explore the effect of enhanced recovery after surgery(ERAS)nursing combined with isokinetic muscle strength visual feedback training on postoperative patients with knee joint injury.Methods A total of 100 patients with knee joint injury who were treated in 909th Hospital(Southeast Hospital Affiliated of Xiamen University)from May 2022 to May 2023 were selected as the subjects.According to a random number table method,the patients were divided into control group(n=50)and observation group(n=50).The control group received ERAS nursing,and observation group received isokinetic muscle strength visual feedback training on the basis of control group.The pain,knee function recovery,quality of life and complications of two groups were compared.Results At 1 day,1 month,3 months and 6 months after operation,the pain visual analogue scale scores of observation group were lower than those of control group(P<0.05).At 6 months after operation,the scores of knee joint function scale and World Health Organization quality of life scale in two groups were higher than before operation,and observation group were higher(P<0.05).The total incidence of complications in observation group was lower than chat in control group(P<0.05).Conclusion ERAS nursing combined with isokinetic muscle strength visual feedback training can significantly reduce postoperative pain in patients with knee joint injury,effectively promote the recovery of knee joint function.
3.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
4.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
5.Construction and Clinical Application of a Machine Learning-Based Early Pre-diction Model for Gestational Diabetes Mellitus
Jiaqi LIU ; Jiazhen GAO ; Yanni MENG ; Chang WANG ; Dongying ZHENG ; Lixia WANG
Journal of Practical Obstetrics and Gynecology 2025;41(11):915-921
Objective:To develop an economical,simple,and accessible method for early identification of high-risk pregnant women with gestational diabetes mellitus(GDM),this study developed and evaluated multiple machine learning models,identified the optimal prediction model,and constructed a clinical decision support sys-tem(CDSS)based on this model.Methods:A total of 464 pregnant women who visited the Second Affiliated Hospital of Dalian Medical University from January 1,2023 to December 30,2024 were included,of which 386 were used to establish a prediction model(231 in the training set and 155 in the testing set),and the remaining 78 were used as a validation.Adopting the methods of double-point sequence correlation and chi-square test,four machine learning models were constructed after selecting feature variables:Logistic Regression,Random Forest,Support Vector Machine,and eXtreme Gradient Boosting(XGBoost).Preliminary judgment of the maximum weight mod-el,further comparison of the discriminative ability,calibration ability,and clinical practicality of each model to evalu-ate and select the optimal model,develop its CDSS,and verify the accuracy of the model.Results:①Correlation analysis identified predictors of GDM:age,pre-pregnancy body mass index(BMI),systolic/diastolic blood pres-sure,white blood cell count,hemoglobin,lymphocyte ratio,fasting plasma glucose,uric acid,direct bilirubin,chronic hypertension complicating pregnancy,and assisted reproductive technology conception.②XGBoost dominated the ensemble model and demonstrated the best performance in discrimination(AUC 0.931,95%CI 0.910-0.967),cali-bration,and clinical utility among the four models.③The CDSS achieved an accuracy of 78.2%,sensitivity of 64.7%,and specificity of 82.0%in the XGBoost model.Conclusions:The XGBoost model has the highest ability to predict GDM in the early stage.Developing its CDSS not only facilitates doctors to quickly assess GDM risk,but also is suitable for promotion to remote areas,where high-risk population screening can be achieved through re-mote data.
6.A study on the congenital hypodysfibrinogenemia family and its pathogenic mechanism
Jiawei ZHENG ; Xiaomei LU ; Lixia HAO ; Linna LU ; Jia YANG ; Lidong ZHAO ; Dongyan FU ; Duanyang WANG ; Gang WANG ; Linhua YANG
Chinese Journal of Hematology 2025;46(6):571-574
The proband was a 32-year-old female patient who sought medical attention for over 9 months of pregnancy, reduced fetal movement, and discomfort in the lower abdomen. The proband and her father had normal activated partial thromboplastin time and prothrombin time, decreased fibrinogen activity and antigen levels, and prolonged thrombin time, whereas the test results of her mother were normal. Ultrasonography showed intermuscular vein thrombosis in the left calf of the proband. Peripheral blood DNA was extracted from the proband and her parents, and Sanger sequencing was performed to detect the base sequences of the FGA, FGB, and FGG genes. The proband and her father had heterozygous missense mutations in exon 6 c.615A > C (p. Leu205Phe) and exon 8 c.1121A > C (p. Tyr374Ser) of the FGG gene. Bioinformatics analysis suggested that the two gene mutations may be the pathogenic mechanism of this congenital hypodysfibrinogenemia family.
7.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
8.Development and application on a full process disease diagnosis and treatment assistance system based on generative artificial intelligence.
Wanjie YANG ; Hao FU ; Xiangfei MENG ; Changsong LI ; Ce YU ; Xinting ZHAO ; Weifeng LI ; Wei ZHAO ; Qi WU ; Zheng CHEN ; Chao CUI ; Song GAO ; Zhen WAN ; Jing HAN ; Weikang ZHAO ; Dong HAN ; Zhongzhuo JIANG ; Weirong XING ; Mou YANG ; Xuan MIAO ; Haibai SUN ; Zhiheng XING ; Junquan ZHANG ; Lixia SHI ; Li ZHANG
Chinese Critical Care Medicine 2025;37(5):477-483
The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence
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Humans
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Delivery of Health Care
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Generative Artificial Intelligence
9.New diterpenoids from Euphorbia wallichii with antioxidant activity.
Yali WANG ; Juan CHEN ; Wenshuo ZHENG ; Ziyan GAO ; Yuxin GAN ; Hua LI ; Lixia CHEN
Chinese Journal of Natural Medicines (English Ed.) 2025;23(10):1248-1258
Thirteen novel diterpenoids, comprising seven tiglianes (walliglianes G-M, 1-7), four rhamnofolanes (wallinofolanes A-D, 8-11), and two daphnanes (wallaphnanes A and B, 12 and 13), together with two known rhamnofolane diterpenoids (euphorwallside H and euphorwallside I, 14 and 15), were isolated and characterized from Euphorbia wallichii(E. wallichii). The chemical structures of these compounds were elucidated through nuclear magnetic resonance (NMR), mass spectrometry (MS), and quantum chemical calculations. Compounds 9 and 11 demonstrated protective effects against H2O2-induced BV-2 microglial cell damage. Molecular docking analyses indicated that compound 9 exhibited binding affinity to the anti-oxidant-related targets HMGCR, GSTP1, and SHBG.
Euphorbia/chemistry*
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Antioxidants/isolation & purification*
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Diterpenes/isolation & purification*
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Molecular Structure
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Mice
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Molecular Docking Simulation
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Animals
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Hydrogen Peroxide/toxicity*
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Cell Line
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Microglia/drug effects*
10.Variability of remnant cholesterol inflammation index exhibits a dose-response relationship with stroke risk:Evidence from the Chinese Kailuan cohort
Liuliu CAO ; Man LI ; Zhaohui WU ; Maolin ZHAO ; Baohua WANG ; Li ZHANG ; Peng LI ; Yongna YANG ; Weiguo ZHENG ; Haiyan ZHAO ; Shuohua CHEN ; Shouling WU ; Lixia SUN
Journal of Army Medical University 2025;47(22):2847-2857
Objective To investigate the association between the variability of remnant cholesterol inflammatory index(RCII),a novel composite biomarker,and the risk of stroke,in order to provide a theoretical basis for stroke prevention.Methods A prospective cohort study was conducted on 38 659 Kailuan individuals who took annual physical examinations in 2006,2008,and 2010.These subjects were grouped based on the quartiles of RCII variability,which was represented by standard deviation(SD)and average real variability(ARV),and were followed up every 2 years,with the occurrence of stroke(including ischemic and hemorrhagic strokes),death,or the end of follow-up on December 31,2022 as the endpoints.Kaplan-Meier method was used to calculate the cumulative incidence rate of endpoint events across different groups,and log-rank test was used to compare the difference of cumulative incidence of endpoint events in each group.Multivariate Cox proportional hazards regression model was adopted to analyze the association between RCII variability and risk of stroke.Results Among the 38 659 participants,a total of 2 539 strokes occurred during a mean follow-up period of 11.22±2.26 years.After adjusting confounding factors,when the participants were grouped by the quartiles of RCII-SD,the hazard ratio(HR)for stroke was 1.034(95%CI:0.917~1.167,P=0.584),1.146(95%CI:1.018~1.290,P=0.025),and 1.209(95%CI:1.066~1.370,P=0.003),respectively in the Q2,Q3,and Q4 groups,when compared with the Q1 group(Ptrend<0.05).When they were grouped by the quartiles of RCII-ARV,the HR for stroke was 1.008(95%CI:0.894~1.136,P=0.901),1.109(95%CI:0.986~1.248,P=0.085),and 1.152(95%CI:1.018~1.303,P=0.025),respectively,in the Q2,Q3,and Q4 groups,when compared with the Q1 group.Furthermore,both sensitivity and stratified analyses yielded similar results.Conclusion RCII variability is significantly associated with stroke,and the risk of stroke is gradually increasing with increment of the variability.Countermeasures Relevant authorities can focus on reducing RCII variability as a central objective by establishing regular monitoring mechanism,strengthening lifestyle interventions,and standardizing dietary,exercise,and weight management in order to suppress the index fluctuations.The principle of stable lipid-lowering in medication and optimization of therapeutic regimens with stable efficacy should be emphasized to prevent the risk of additional vascular damage.


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