1.Identification and infection rate of densovirus in Culex pipiens pallens in Beijing in 2023
Xiu-yan XU ; Ting YAN ; Si-jie ZHU ; Jing LI ; Mei-de LIU ; Hong-jiang ZHANG ; Ting LIU ; Qiu-hong LI ; Xiao-jie ZHOU ; Ying TONG ; Yong ZHANG
Acta Parasitologica et Medica Entomologica Sinica 2026;33(1):25-30
Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.
2.Influencing factors for sarcopenia in elderly hospitalized patients and construction and validation of a risk prediction model
Yilin ZHOU ; Qingqing FAN ; Peng PENG ; Xintong LIU ; Hong JIANG ; Pingfeng HE ; Dan DENG
Journal of Chongqing Medical University 2025;50(10):1434-1441
Objective:To investigate the influencing factors for sarcopenia in hospitalized patients,to construct a risk prediction model for sarcopenia in elderly hospitalized patients,and to provide a quantitative tool for early screening and intervention of sarcopenia based on the integration of multi-dimensional indicators.Methods:A retrospective analysis was performed for the data of 2105 elderly patients who were hospitalized in The First Affiliated Hospital of Chongqing Medical University from March 2016 to June 2023.The least absolute shrinkage and selection operator analysis was used for the screening of variables,and the logistic regression analysis was used to investigate the influencing factors for sarcopenia.A predictive model was constructed,and internal and external validation was performed.The Shapley additive explanations model was used to analyze feature contributions,and a nomogram model was constructed to visualize and interpret the results.Results:The 1259 patients from March 2016 to December 2020 were randomly divided into a training set with 882 patients and an internal test set with 377 patients at a ratio of 7∶3,and the 846 patients from January 2021 to June 2023 were established as the external validation set.A total of 489 cases of sarcopenia(55.44%)were detected in the training set.The logistic regression analysis based on the training set showed that asthenia,dependence on Activity of Daily Living,malnutrition,and in-creasing age were risk factors for sarcopenia(odds ratio[OR]>1,P<0.05),and male sex,normal body mass index,and overweight were protective factors against sarcopenia(OR<1,P<0.05).The model had an AUC of 0.876(95%CI=0.854-0.899)in the training set,0.883(95%CI=0.849-0.918)in the internal test set,and 0.750(95%CI=0.717-0.783)in the external validation set,suggesting that the model had good performance.The decision curve analysis showed that the nomogram model had a good clinical value.Conclu-sion:The predictive model for sarcopenia has good performance and holds promise for clinical application.
3.Efficacy of thoracic electrical impedance tomography-derived parameters for evaluating atelectasis in hospitalized patients
Wu LIU ; Lulu SUN ; Jiayun LI ; Ren ZHOU ; Beibei HU ; Jiaqian ZHOU ; Hong JIANG ; Rong HU
Academic Journal of Naval Medical University 2025;46(11):1439-1446
Objective To analyze the correlations between the thoracic electrical impedance tomography(EIT)-derived parameters global inhomogeneity(GI),center of ventilation(COV),regional ventilation delay(RVD),and atelectasis in hospitalized patients,and to explore their effectiveness in evaluating atelectasis.Methods The clinical data of 140 hospitalized patients monitored by thoracic EIT between Sep.2024 and Jan.2025 were retrospectively analyzed.Patients were assigned to 2 groups based on chest computed tomography confirmation of atelectasis within the preceding short-term period during EIT monitoring:non-atelectasis group or atelectasis group.The algorithm software designed with MATLAB was used to acquire GI and COV.RVD was obtained through analysis with the Dr?ger EIT Data Analysis Tool 6.3 software,and patients'general data were concurrently documented.Comparative analysis of EIT-derived parameters between groups was conducted.Multivariate logistic regression analysis was employed to investigate the correlations of GI,COV,and RVD with atelectasis,while receiver operating characteristic curve analysis was performed to assess the efficacy of EIT-derived parameters in evaluating atelectasis.Results A total of 140 patients were enrolled,with 19(13.6%)cases presenting atelectasis.Compared to the non-atelectasis group,the atelectasis group demonstrated significantly higher proportions of male patients and cardiovascular disease and thoracic surgery(non-pulmonary)histories,lower body mass index(BMI),and alongside elevated GI and RVD values with reduced COV(all P<0.05).Multivariate logistic regression analysis revealed that GI,COV,and RVD maintained independent associations with atelectasis after adjusting for age,gender,BMI,pleural effusion,and emphysema(odds ratio[OR]=1.39,95%confidence interval[CI]1.20-1.67;OR=0.85,95%CI 0.75-0.96;OR=1.22,95%CI 1.09-1.39;all P<0.05).The area under curve(AUC)values of GI,COV,and RVD for evaluating atelectasis in hospitalized patients were 0.82,0.80,and 0.82,respectively(while RVD demonstrated a higher AUC,its clinical applicability was influenced by respiratory patterns).Conclusion Thoracic EIT-derived parameters GI and COV demonstrate significant correlations with atelectasis and may serve as valuable indicators for evaluating atelectasis in hospitalized patients.
4.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.
5.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; Yunjian HU ; Xiaoman AI ; 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 ; Hong ZHANG ; Chun WANG ; 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(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
6.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; 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 ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; 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 ; 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 ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
7.Dual activation of GCGR/GLP1R signaling ameliorates intestinal fibrosis via metabolic regulation of histone H3K9 lactylation in epithelial cells.
Han LIU ; Yujie HONG ; Hui CHEN ; Xianggui WANG ; Jiale DONG ; Xiaoqian LI ; Zihan SHI ; Qian ZHAO ; Longyuan ZHOU ; JiaXin WANG ; Qiuling ZENG ; Qinglin TANG ; Qi LIU ; Florian RIEDER ; Baili CHEN ; Minhu CHEN ; Rui WANG ; Yao ZHANG ; Ren MAO ; Xianxing JIANG
Acta Pharmaceutica Sinica B 2025;15(1):278-295
Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.
8.Parabacteroides distasonis promotes liver regeneration by increasing β-hydroxybutyric acid (BHB) production and BHB-driven STAT3 signals.
Manlan GUO ; Xiaowen JIANG ; Hui OUYANG ; Xianglong ZHANG ; Shuaishuai ZHANG ; Peng WANG ; Guofang BI ; Ting WU ; Wenhong ZHOU ; Fengting LIANG ; Xiao YANG ; Shicheng FAN ; Jian-Hong FANG ; Peng CHEN ; Huichang BI
Acta Pharmaceutica Sinica B 2025;15(3):1430-1446
The liver regenerative capacity is crucial for patients with end-stage liver disease following partial hepatectomy (PHx). The specific bacteria and mechanisms regulating liver regeneration post-PHx remain unclear. This study demonstrated dynamic changes in the abundance of Parabacteroides distasonis (P. distasonis) post-PHx, correlating with hepatocyte proliferation. Treatment with live P. distasonis significantly promoted hepatocyte proliferation and liver regeneration after PHx. Targeted metabolomics revealed a significant positive correlation between P. distasonis and β-hydroxybutyric acid (BHB), as well as hyodeoxycholic acid and 3-hydroxyphenylacetic acid in the gut after PHx. Notably, treatment with BHB, but not hyodeoxycholic acid or 3-hydroxyphenylacetic acid, significantly promoted hepatocyte proliferation and liver regeneration in mice after PHx. Moreover, STAT3 inhibitor Stattic attenuated the promotive effects of BHB on cell proliferation and liver regeneration both in vitro and in vivo. Mechanistically, P. distasonis upregulated the expression of fatty acid oxidation-related proteins, and increased BHB levels in the liver, and then BHB activated the STAT3 signaling pathway to promote liver regeneration. This study, for the first time, identifies the involvement of P. distasonis and its associated metabolite BHB in promoting liver regeneration after PHx, providing new insights for considering P. distasonis and BHB as potential strategies for promoting hepatic regeneration.
9.VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data.
Liang ZHANG ; Hua PANG ; Chenghao ZHANG ; Song LI ; Yang TAN ; Fan JIANG ; Mingchen LI ; Yuanxi YU ; Ziyi ZHOU ; Banghao WU ; Bingxin ZHOU ; Hao LIU ; Pan TAN ; Liang HONG
Acta Pharmaceutica Sinica B 2025;15(5):2454-2467
In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (DMS) experiments that use surrogate readouts, which may not adequately capture the complex biochemical properties of interest. Many proteins and their functions cannot be assessed through high-throughput methods due to technical limitations or the nature of the desired properties, and this is particularly true for the real industrial application scenario. Therefore, the desired testing datasets, will be small-size (∼10-100) experimental data for each protein, and involve as many proteins as possible and as many properties as possible, which is, however, lacking. Here, we present VenusMutHub, a comprehensive benchmark study using 905 small-scale experimental datasets curated from published literature and public databases, spanning 527 proteins across diverse functional properties including stability, activity, binding affinity, and selectivity. These datasets feature direct biochemical measurements rather than surrogate readouts, providing a more rigorous assessment of model performance in predicting mutations that affect specific molecular functions. We evaluate 23 computational models across various methodological paradigms, such as sequence-based, structure-informed and evolutionary approaches. This benchmark provides practical guidance for selecting appropriate prediction methods in protein engineering applications where accurate prediction of specific functional properties is crucial.
10.Correlation between levels of low-density lipoprotein cholesterol and atrial fibrillation in patients with hypertension
Fang XIONG ; Hongdong JIANG ; Zhongjie HONG ; Wei ZHOU ; Huihui BAO ; Xiaoshu CHENG
Journal of China Medical University 2025;54(8):740-745,753
Objective To investigate the correlation between levels of low-density lipoprotein cholesterol(LDL-C)and atrial fibrillation in a hypertensive population.Methods Hypertension screening was performed in the Wuyuan County of Jiangxi Province from June to August 2022.Data were collected using face-to-face questionnaire surveys,physical measurements,and biochemical tests.Logistic regres-sion analysis was used to analyze the effect of LDL-C on atrial fibrillation.The restricted cubic spline method was used to fit the correlation curve.Results A total of 14 314 patients with hypertension were included in the analysis,with an average age of 65.7±9.2 years.There were 570 patients detected with atrial fibrillation(the rate of atrial fibrillation was 4.0%).The rates of atrial fibrillation for LDL-C<1.80 mmol/L,1.80-<2.60 mmol/L,2.60-<3.40 mmol/L and≥3.40 mmol/L were 10.2%(67/654),5.7%(216/3 807),3.3%(189/5 805),and 2.4%(98/4 048),respectively.Logistic regression analysis showed that,compared with LDL-C<1.80 mmol/L group,LDL-C 1.80-<2.60 mmol/L group,2.60-<3.40 mmol/L group,and ≥ 3.40 mmol/L group had a lower risk of atrial fibrillation(OR=0.53,95%CI:0.39-0.72,P<0.001;OR=0.32,95%CI:0.23-0.45,P<0.001;OR=0.22,95%CI:0.16-0.32,P<0.001).Curve-fitting results showed that LDL-C levels were negatively associated with the risk of atrial fibrillation.Subgroup analysis showed that LDL-C level was negatively associated with the risk of atrial fibrillation in patients without a history of stroke(OR=0.51,95%CI:0.44-0.58,P<0.001),while the association was not statistically significant in patients with a history of stroke(OR=0.80,95%CI:0.54-1.19,P=0.273).Conclusion In hyperten-sive patients without a history of stroke,LDL-C levels negatively correlated with the risk of atrial fibrillation.


Result Analysis
Print
Save
E-mail