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Li J, Xiong D, Hong L, Lim J, Xu X, Xiao X, Guo R, Xu Z. Tongue color parameters in predicting the degree of coronary stenosis: a retrospective cohort study of 282 patients with coronary angiography. Front Cardiovasc Med 2024; 11:1436278. [PMID: 39280030 PMCID: PMC11392741 DOI: 10.3389/fcvm.2024.1436278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 08/05/2024] [Indexed: 09/18/2024] Open
Abstract
Purpose This retrospective cohort study aimed to analyze the relationship between tongue color and coronary artery stenosis severity in 282 patients after underwent coronary angiography. Methods A retrospective cohort study was conducted to collect data from patients who underwent coronary angiography in the Department of Cardiology, Shanghai Jiading District Central Hospital from October 1, 2023 to January 15, 2024. All patients were divided into four various stenosis groups. The tongue images of each patient was normalized captured, tongue body (TC_) and tongue coating (CC_) data were converted into RGB and HSV model parameters using SMX System 2.0. Four supervised machine learning classifiers were used to establish a coronary artery stenosis grading prediction model, including random forest (RF), logistic regression, and support vector machine (SVM). Accuracy, precision, recall, and F1 score were used as classification indicators to evaluate the training and validation performance of the model. SHAP values were furthermore used to explore the impacts of features. Results This study finally included 282 patients, including 164 males (58.16%) and 118 females (41.84%). 69 patients without stenosis, 70 patients with mild stenosis, 65 patients with moderate stenosis, and 78 patients with severe stenosis. Significant differences of tongue parameters were observed in the four groups [TC_R (P = 0.000), TC_G (P = 0.003), TC_H (P = 0.001) and TC_S (P = 0.024),CC_R (P = 0.006), CC_B (P = 0.023) and CC_S (P = 0.001)]. The SVM model had the highest predictive ability, with AUC values above 0.9 in different stenosis groups, and was particularly good at identifying mild and severe stenosis (AUC = 0.98). SHAP value showed that high values of TC_RIGHT_R, low values of CC_LEFT_R were the most impact factors to predict no coronary stenosis; high CC_LEFT_R and low TC_ROOT_H for mild coronary stenosis; low TC_ROOT_R and CC_ROOT_B for moderate coronary stenosis; high CC_RIGHT_G and low TC_ROOT_H for severe coronary stenosis. Conclusion Tongue color parameters can provide a reference for predicting the degree of coronary artery stenosis. The study provides insights into the potential application of tongue color parameters in predicting coronary artery stenosis severity. Future research can expand on tongue features, optimize prediction models, and explore applications in other cardiovascular diseases.
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Affiliation(s)
- Jieyun Li
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai key Laboratory of Health Identification and Evaluation, Shanghai, China
| | - Danqun Xiong
- Department of Cardiology, Jiading District Central Hospital, Shanghai, China
| | - Leixin Hong
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jiekee Lim
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiangdong Xu
- Department of Cardiology, Jiading District Central Hospital, Shanghai, China
| | - Xinang Xiao
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Rui Guo
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai key Laboratory of Health Identification and Evaluation, Shanghai, China
| | - Zhaoxia Xu
- School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai key Laboratory of Health Identification and Evaluation, Shanghai, China
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JIANG F, LIU XT, HU Z, LIAO W, LI SY, ZHU RF, MAO ZX, HOU J, Akhtar S, Ahmad F, Mehmood T, WANG CJ. Healthy life expectancy with cardiovascular disease among Chinese rural population based on the prospective cohort study. J Geriatr Cardiol 2024; 21:799-806. [PMID: 39308499 PMCID: PMC11411257 DOI: 10.26599/1671-5411.2024.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/25/2024] Open
Abstract
BACKGROUND Limited research has explored the impact of cardiovascular disease (CVD) on healthy life expectancy (HLE) especially in resource-limited areas. This study aimed to investigate the association between CVD and HLE in Chinese rural population. METHODS This study included 11,994 participants aged 45 years and older from the baseline and follow-up surveys of the Henan rural cohort study. Healthy status was measured via a Visual Analogue Scale. The multistate Markov model was applied to estimate the association between CVD and transitions in health, unhealthiness and death. Gender-specific total life expectancy, HLE and unhealthy life expectancy were calculated by the multistate life table method. RESULTS During a mean follow-up time of 3.85 (3.84-3.86) years, there were 588 deaths recorded. For individuals with CVD, the risk of switching from health to unhealthiness status was increased by 71% [hazard ratio (HR) = 1.71, 95% CI: 1.42-2.07], the chance of recovery was reduced by 30% (HR = 0.70, 95% CI: 0.60-0.82). Men aged 45 years without CVD could gain an extra 7.08 (4.15-10.01) years of HLE and lose 4.00 (1.60-6.40) years of unhealthy life expectancy compared to their peers with CVD, respectively. The corresponding estimates among women were 8.62 (5.55-11.68) years and 5.82 (2.59-9.04) years, respectively. CONCLUSIONS This study indicated that CVD was significantly associated with poorer health status and lower HLE among Chinese rural population. It is an important public health policy to adopt targeted measures to reduce the CVD burden and enhance the quality of life and HLE in resource-limited areas.
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Affiliation(s)
- Feng JIANG
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiao-Tian LIU
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ze HU
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei LIAO
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Shuo-Yi LI
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Rui-Fang ZHU
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhen-Xing MAO
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jian HOU
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Sohail Akhtar
- Department of Mathematics and Statistics, The University of Haripur, Haripur, Pakistan
| | - Fayaz Ahmad
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Tahir Mehmood
- School of Natural Sciences, National University of Sciences and Technology, Islamabad, Pakistan
| | - Chong-Jian WANG
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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Duan M, Mao B, Li Z, Wang C, Hu Z, Guan J, Li F. Feasibility of tongue image detection for coronary artery disease: based on deep learning. Front Cardiovasc Med 2024; 11:1384977. [PMID: 39246581 PMCID: PMC11377252 DOI: 10.3389/fcvm.2024.1384977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Accepted: 08/07/2024] [Indexed: 09/10/2024] Open
Abstract
Aim Clarify the potential diagnostic value of tongue images for coronary artery disease (CAD), develop a CAD diagnostic model that enhances performance by incorporating tongue image inputs, and provide more reliable evidence for the clinical diagnosis of CAD, offering new biological characterization evidence. Methods We recruited 684 patients from four hospitals in China for a cross-sectional study, collecting their baseline information and standardized tongue images to train and validate our CAD diagnostic algorithm. We used DeepLabV3 + for segmentation of the tongue body and employed Resnet-18, pretrained on ImageNet, to extract features from the tongue images. We applied DT (Decision Trees), RF (Random Forest), LR (Logistic Regression), SVM (Support Vector Machine), and XGBoost models, developing CAD diagnostic models with inputs of risk factors alone and then with the additional inclusion of tongue image features. We compared the diagnostic performance of different algorithms using accuracy, precision, recall, F1-score, AUPR, and AUC. Results We classified patients with CAD using tongue images and found that this classification criterion was effective (ACC = 0.670, AUC = 0.690, Recall = 0.666). After comparing algorithms such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and XGBoost, we ultimately chose XGBoost to develop the CAD diagnosis algorithm. The performance of the CAD diagnosis algorithm developed solely based on risk factors was ACC = 0.730, Precision = 0.811, AUC = 0.763. When tongue features were integrated, the performance of the CAD diagnosis algorithm improved to ACC = 0.760, Precision = 0.773, AUC = 0.786, Recall = 0.850, indicating an enhancement in performance. Conclusion The use of tongue images in the diagnosis of CAD is feasible, and the inclusion of these features can enhance the performance of existing CAD diagnosis algorithms. We have customized this novel CAD diagnosis algorithm, which offers the advantages of being noninvasive, simple, and cost-effective. It is suitable for large-scale screening of CAD among hypertensive populations. Tongue image features may emerge as potential biomarkers and new risk indicators for CAD.
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Affiliation(s)
- Mengyao Duan
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Boyan Mao
- School of Life Science, Beijing University of Chinese Medicine, Beijing, China
| | - Zijian Li
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Chuhao Wang
- School of Life Science, Beijing University of Chinese Medicine, Beijing, China
| | - Zhixi Hu
- School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China
| | - Jing Guan
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Feng Li
- School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
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Tao M, Yao X, Sun S, Qin Y, Li D, Wu J, Xiong Y, Teng Z, Zeng Y, Luo Z. Correlation Analysis Between Required Surgical Indexes and Complications in Patients With Coronary Heart Disease. Front Surg 2022; 9:948666. [PMID: 35874136 PMCID: PMC9299069 DOI: 10.3389/fsurg.2022.948666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
A total of 215 patients with coronary heart disease (CHD) were analyzed with SPSS. Samples of different genders showed significance in the obtuse marginal branch of the left circumflex branch × 1, the diagonal branch D1 × 1, and the ms PV representation. Patients with left circumflex branch occlusion are more male and tend to be younger. Age displayed a positive correlation with left intima-media thickness (IMT) and right IMT. This indicated that as age increases, the values of left IMT and right IMT increase. Samples of different CHD types showed significance in the obtuse marginal branch of the left circumflex branch × 1, the middle part of RCA × 1, and the middle part of the left anterior descending branch × 1.5. For non-ST-segment elevation angina pectoris with acute total vascular occlusion, the left circumflex artery is the most common, followed by the right coronary artery and anterior descending branch. Ultrasound of carotid IMT in patients with CHD can predict changes in left ventricular function, but no specific correlation between left and right common carotid IMT was found. Samples with or without the medical history of ASCVD showed significance in the branch number of coronary vessel lesions. The value of the branch number of coronary vessel lesions in patients with atherosclerotic cardiovascular disease (ASCVD) was higher than in those without ASCVD. The occurrence of complication is significantly relative with the distance of left circumflex branch × 1, the middle segment of left anterior descending branch × 1.5, and the distance of left anterior descending branch × 1. For patients without complications, the values in the distal left circumflex branch × 1, the middle left anterior descending branch × 1.5, and the distal left anterior descending branch × 1 were higher than those for patients with complications. The VTE scores showed a positive correlation with the proximal part of RCA × 1, the branch number of coronary vessel lesions, the posterior descending branch of left circumflex branch × 1, the distal part of left circumflex branch × 1, and the middle part of left anterior descending branch × 1.5.
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Affiliation(s)
- Meiyi Tao
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Xiaoling Yao
- Department of Respiratory Medicine, Hunan Provincial People's Hospital (The first-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Shengli Sun
- Department of Neurosurgery, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
- Correspondence: Shengli Sun Yuelan Qin Dandan Li
| | - Yuelan Qin
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
- Correspondence: Shengli Sun Yuelan Qin Dandan Li
| | - Dandan Li
- The Third Department of Cardiovascular Medicine, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
- Clinical Medicine Research Center of Heart Failure of Hunan Province, Changsha, China
- Correspondence: Shengli Sun Yuelan Qin Dandan Li
| | - Juan Wu
- The Third Department of Cardiovascular Medicine, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Yican Xiong
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Zhiyu Teng
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Yunfei Zeng
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Zuoheng Luo
- Department of Nursing, Hunan Provincial People's Hospital (The First-Affiliated Hospital of Hunan Normal University), Changsha, China
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