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Assessment of Human Adipose Tissue Microvascular Function Using Videomicroscopy
Published on: September 29, 2017
Prediction of microvascular complications in diabetic patients without obstructive coronary stenosis based on
Yarong Yu1, Xiaoying Ding2, Lihua Yu1
1Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, #85 Wujin Rd, Shanghai, 200080, China.
Insights
Peri-coronary adipose tissue (PCAT) attenuation predicts microvascular complications in diabetic patients. A model combining clinical factors and PCAT offers improved risk stratification for early intervention.
Area of Science:
- Cardiology
- Diabetology
- Radiology
Background:
- Diabetic microvascular complications pose a significant health risk.
- Early identification of at-risk patients is crucial for intervention.
- Peri-coronary adipose tissue (PCAT) is an emerging imaging biomarker.
Purpose of the Study:
- To assess the predictive value of PCAT attenuation for microvascular complications in diabetic patients without significant coronary stenosis.
- To develop and validate a risk prediction model for early stratification.
Main Methods:
- Retrospective analysis of patients with type 2 diabetes undergoing coronary computed tomography angiography (CCTA).
- Development of two prediction models: clinical factors alone vs. clinical factors + RCAPCAT.
- Internal and external validation of the models.
Main Results:
- Microvascular complications occurred in 69.1% of patients.
- The model incorporating RCAPCAT showed superior predictive power (AUC=0.820) compared to clinical factors alone (AUC=0.781).
- The PCAT-based model demonstrated lower prediction error and was validated in independent cohorts.
Conclusions:
- RCAPCAT attenuation is an independent predictor of microvascular complications in diabetic patients.
- A prediction model integrating clinical factors and RCAPCAT enables effective early risk stratification.
- This approach aids in managing diabetic patients with coronary artery disease.
Objectives:
To investigate the predictive value of peri-coronary adipose tissue (PCAT) attenuation for microvascular complications in diabetic patients without significant stenosis and to develop a prediction model for early risk stratification.
Methods:
This study retrospectively included patients clinically identified for coronary computed tomography angiography (CCTA) and type 2 diabetes between January 2017 and December 2020. All patients were followed up for at least 1 year. The clinical data and CCTA-based imaging characteristics (including PCAT of major epicardial vessels, high-risk plaque features) were recorded. In the training cohort comprising of 579 patients, two models were developed: model 1 with the inclusion of clinical factors and model 2 incorporating clinical factors + RCAPCAT using multivariable logistic regression analysis. An internal validation cohort comprising 249 patients and an independent external validation cohort of 269 patients were used to validate the proposed models.
Results:
Microvascular complications occurred in 69.1% (758/1097) of the current cohort during follow-up. In the training cohort, model 2 exhibited improved predictive power over model 1 based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) with lower prediction error (Brier score = 0.146 versus 0.164) compared to model 1. Model 2 accurately categorized 78.58% of patients with diabetic microvascular complications. Similar performance of model 2 in the internal validation cohort and the external validation cohort was further confirmed.
Conclusions:
The model incorporating clinical factors and RCAPCAT predicts the development of microvascular complications in diabetic patients without significant coronary stenosis.
Key Points:
• Hypertension, HbA1c, duration of diabetes, and RCAPCAT were independent risk factors for microvascular complications. • The prediction model integrating RCAPCAT exhibited improved predictive power over the model only based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) and showed lower prediction error (Brier score=0.146 versus 0.164).
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