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Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
[Factors related to the poor coronary collateral circulation in patients with coronary artery disease]
Ming-ping He1, Yong Li1, Wei Shen1
1Department of Cardiology, Huashan Hospital, Fudan University, Shanghai 200040, China.
Insights
High fasting blood glucose (FBG) and low estimated glomerular filtration rate (eGFR) are independent predictors of poor coronary collateral circulation (CCC) in coronary artery disease (CAD) patients. These factors work together, showing a synergistic effect that increases the risk of poor CCC.
Area of Science:
- Cardiovascular Medicine
- Nephrology
- Metabolic Disorders
Context:
- Coronary artery disease (CAD) affects millions globally, with coronary collateral circulation (CCC) playing a crucial role in myocardial protection.
- Poor CCC is associated with adverse cardiovascular outcomes in CAD patients.
- Identifying factors influencing CCC is vital for risk stratification and therapeutic strategies.
Purpose:
- To investigate the independent predictors of poor CCC in CAD patients.
- To explore the synergistic effects of various factors, specifically fasting blood glucose (FBG) and estimated glomerular filtration rate (eGFR), on CCC.
- To determine optimal cut-off values for FBG in predicting poor CCC.
Summary:
- A study of 180 CAD patients revealed that higher FBG levels and lower eGFR were significantly associated with poor CCC (Rentrop 0-1).
- Multivariate analysis confirmed FBG and eGFR as independent predictors of poor CCC, even after adjusting for other risk factors.
- A synergistic effect was observed, with combined high FBG and low eGFR substantially increasing the risk of poor CCC.
Impact:
- This research identifies high FBG and low eGFR as key, independent risk factors for poor CCC in CAD.
- The findings highlight a significant synergistic interaction between FBG and eGFR in exacerbating poor CCC.
- These results can inform clinical practice for better risk assessment and management of CAD patients.
Objective:
To explore the factors related to poor coronary collateral circulation (CCC) and the synergy effects among various factors in patients with coronary artery disease (CAD).
Methods:
A total of 180 patients with coronary angiography confirmed CAD (at least one major coronary artery stenosis equal to or greater than 95%) were included in this study. Coronary collateral circulation was graded according to the Rentrop scoring system. There were in 54 patients with Rentrop 0 and 1 (poor CCC) and 126 patients with Rentrop 2 and 3 (good CCC). Clinical data including age, weight, gender, history of smoking, and factors that were known to influence the development of collateral s, such as hypertension, diabetes mellitus, fasting blood glucose (FBG), hemoglobin A1c (HbA1c), serum total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and estimate glomerular filtration rate(eGFR) levels were also documented. Multivariate logistic regression was performed to detect possible factors related to CCC.
Results:
(1) FBG levels and the incidence of eGFR < 60 ml·min(-1)·1.73 m(-2) were significant higher in Rentrop 0 and 1 group than in Rentrop 2 and 3 group (P = 0.001, P = 0.034, respectively). (2) After adjusting for age, gender, smoking habits, hypertension, diabetes and dyslipidemia, FBG levels (OR = 1.374, P = 0.005) and eGFR levels (OR = 2.412, P = 0.013) remained as independent risk factors for CCC. (3) The ROC curve showed that the optimal cut-off point for FBG to predict poor CCC was 5.8 mmol/L. The area under the ROC curve was 0.656 (P = 0.001). (4) According to FBG and eGFR, patients were further divided into FBG ≥ 5.8 mmol/L and eGFR < 60 ml·min(-1)·1.73 m(-2) group (group A), FBG ≥ 5.8 mmol/L and eGFR ≥ 60 ml·min(-1)·1.73 m(-2) group (group B), FBG < 5.8 mmol/L and eGFR < 60 ml·min(-1)·1.73 m(-2) group (group C), and FBG<5.8mmol/L and eGFR ≥ 60 ml·min(-1)·1.73 m(-2) group (group D). The frequencies of poor CCC of the four groups were 51.7% (15/29) , 36.7% (18/49), 35.5% (11/31) and 12.7% (8/63) respectively (P < 0.001). After adjusting for age, gender, smoking habits, hypertension and dyslipidemia, the risk of poor CCC in group A, B and C patients were 7.494 (95%CI = 1.410-7.551, P = 0.001), 3.921 (95%CI = 1.061-6.910, P = 0.005) and 3.474 (95%CI = 0.160-4.477, P = 0.047) times higher than patients in group D.
Conclusions:
Our results show that higher FBG levels and lower eGFR are independent predictors of poor CCC in CAD patients. Higher FBG levels and lower eGFR evoke a synergistic effect on poor CCC in CAD patients.
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