Background Non-high-density lipoprotein cholesterol （non-HDL-C） and Apolipoprotein B （apoB） increase car- diovascular disease （CVD） risk, but few studies have explored the correlations of non-HDL-C and apoB with...Background Non-high-density lipoprotein cholesterol （non-HDL-C） and Apolipoprotein B （apoB） increase car- diovascular disease （CVD） risk, but few studies have explored the correlations of non-HDL-C and apoB with cor- onary atherosclerosis in non-diabetes acute coronary syndrome （ACS）. Methods The study enrolled 443 sub- jects with non-diabetic ACS, and all subject check coronary angiography, and coronary atherosclerosis were eval- uated using Gensini Score （GS） scale including small （GS 1-15）, middle （GS16-43）, and severe （GS≥44）. All sub- jects were classified into 4 groups： High apoB （≥90 mg/dL） and High non-HDL-C （≥130 mg/dL）, High non-HDL -C alone, High apoB alone, and normal apoB and non-HDL-C. Results After adjusted for risk factors, non-HDL -C and apoB were positively correlated with GS （ r = 0.075, P = 0.002 and r = 0.092, P 〈 0.001）. In the GS 0-15, high non-HDL-C ＋ high apoB group 29.3% and high apoB alone group 28.2% were significantly lower than nor- mal non-HDL-C＋ normal apoB group 48% （p = 0.010）. In the GS 16-43, high non-HDL-C alone group 50.4% and high apoB alone group 47.6% were significantly more than high non-HDL-C＋ high apoB group 34.1% （P = 0.036）. In the GS ≥44, high non-HDL-C＋ high apoB group 36.6% was significantly higher than high non-HDL- C alone group 16% and normal non-HDL-C＋ normal apoB 14.2%（P 〈 0.001）. Conclusions The high non-HDL- C and apoB are the risk factors for coronary artery atherosclerosis in non-diabetic ACS.展开更多
Background:Current lung cancer screening guidelines recommend annual low-dose computed tomography(LDCT)for high-risk individuals.However,the effectiveness of LDCT in non-high-risk individuals remains inadequately expl...Background:Current lung cancer screening guidelines recommend annual low-dose computed tomography(LDCT)for high-risk individuals.However,the effectiveness of LDCT in non-high-risk individuals remains inadequately explored.With the incidence of lung cancer steadily increasing among non-high-risk individuals,this study aims to assess the risk of lung cancer in non-high-risk individuals and evaluate the potential of thin-section LDCT reconstruction combined with artificial intelligence(LDCT-TRAI)as a screening tool.Methods:A real-world cohort study on lung cancer screening was conducted at the West China Hospital of Sichuan University from January 2010 to July 2021.Participants were screened using either LDCT-TRAI or traditional thick-section LDCT without AI(traditional LDCT).The AI system employed was the uAI-ChestCare software.Lung cancer diagnoses were confirmed through pathological examination.Results:Among the 259121 enrolled non-high-risk participants,87260(33.7%)had positive screening results.Within 1 year,728(0.3%)participants were diagnosed with lung cancer,of whom 87.1%(634/728)were never-smokers,and 92.7%(675/728)presented with stage I disease.Compared with traditional LDCT,LDCT-TRAI demonstrated a higher lung cancer detection rate(0.3%vs.0.2%,P<0.001),particularly for stage I cancers(94.4%vs.83.2%,P<0.001),and was associated with improved survival outcomes(5-year overall survival rate:95.4%vs.81.3%,P<0.0001).Conclusion:These findings highlight the importance of expanding lung cancer screening to non-high-risk populations,especially never-smokers.LDCT-TRAI outperformed traditional LDCT in detecting early-stage cancers and improving survival outcomes,underscoring its potential as a more effective screening tool for early lung cancer detection in this population.展开更多
基金supported by the Natural Science Foundation of China(No.81070182)the Natural Science Foundation of Guangdong Province(No.10151008901000224)
文摘Background Non-high-density lipoprotein cholesterol （non-HDL-C） and Apolipoprotein B （apoB） increase car- diovascular disease （CVD） risk, but few studies have explored the correlations of non-HDL-C and apoB with cor- onary atherosclerosis in non-diabetes acute coronary syndrome （ACS）. Methods The study enrolled 443 sub- jects with non-diabetic ACS, and all subject check coronary angiography, and coronary atherosclerosis were eval- uated using Gensini Score （GS） scale including small （GS 1-15）, middle （GS16-43）, and severe （GS≥44）. All sub- jects were classified into 4 groups： High apoB （≥90 mg/dL） and High non-HDL-C （≥130 mg/dL）, High non-HDL -C alone, High apoB alone, and normal apoB and non-HDL-C. Results After adjusted for risk factors, non-HDL -C and apoB were positively correlated with GS （ r = 0.075, P = 0.002 and r = 0.092, P 〈 0.001）. In the GS 0-15, high non-HDL-C ＋ high apoB group 29.3% and high apoB alone group 28.2% were significantly lower than nor- mal non-HDL-C＋ normal apoB group 48% （p = 0.010）. In the GS 16-43, high non-HDL-C alone group 50.4% and high apoB alone group 47.6% were significantly more than high non-HDL-C＋ high apoB group 34.1% （P = 0.036）. In the GS ≥44, high non-HDL-C＋ high apoB group 36.6% was significantly higher than high non-HDL- C alone group 16% and normal non-HDL-C＋ normal apoB 14.2%（P 〈 0.001）. Conclusions The high non-HDL- C and apoB are the risk factors for coronary artery atherosclerosis in non-diabetic ACS.
基金supported by Non-communicable Chronic Diseases-National Science and Technology Major Project(Grant No.2023ZD0506102/2023ZD0506100)the National Natural Science Foundation of China(Grant No.92159302)+5 种基金the Science and Technology Project of Sichuan(Grant No.2022ZDZX0018)1·3·5 project for disciplines of excellence,West China Hospital,Sichuan University(Grant No.ZYGD22009)the Natural Science Foundation of Sichuan Province(Grant No.2023NSFSC1458),1·3·5 Project of State Key Laboratory of Respiratory Health and Multimorbidity,West China Hospital,Sichuan University(Grant No.RHM24204)the Science and Technology Project of Sichuan(Grant No.2020YFS0573)the Major research programs of the Natural Science Foundation of China(Grant No.91859203)Key R&D plan of Sichuan Provincial Department of science and technology(Grant No.2021YFS0072)。
文摘Background:Current lung cancer screening guidelines recommend annual low-dose computed tomography(LDCT)for high-risk individuals.However,the effectiveness of LDCT in non-high-risk individuals remains inadequately explored.With the incidence of lung cancer steadily increasing among non-high-risk individuals,this study aims to assess the risk of lung cancer in non-high-risk individuals and evaluate the potential of thin-section LDCT reconstruction combined with artificial intelligence(LDCT-TRAI)as a screening tool.Methods:A real-world cohort study on lung cancer screening was conducted at the West China Hospital of Sichuan University from January 2010 to July 2021.Participants were screened using either LDCT-TRAI or traditional thick-section LDCT without AI(traditional LDCT).The AI system employed was the uAI-ChestCare software.Lung cancer diagnoses were confirmed through pathological examination.Results:Among the 259121 enrolled non-high-risk participants,87260(33.7%)had positive screening results.Within 1 year,728(0.3%)participants were diagnosed with lung cancer,of whom 87.1%(634/728)were never-smokers,and 92.7%(675/728)presented with stage I disease.Compared with traditional LDCT,LDCT-TRAI demonstrated a higher lung cancer detection rate(0.3%vs.0.2%,P<0.001),particularly for stage I cancers(94.4%vs.83.2%,P<0.001),and was associated with improved survival outcomes(5-year overall survival rate:95.4%vs.81.3%,P<0.0001).Conclusion:These findings highlight the importance of expanding lung cancer screening to non-high-risk populations,especially never-smokers.LDCT-TRAI outperformed traditional LDCT in detecting early-stage cancers and improving survival outcomes,underscoring its potential as a more effective screening tool for early lung cancer detection in this population.
