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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
A new coronary artery disease grading system correlates with numerous routine parameters that were associated with
Michael Sponder1, Monika Fritzer-Szekeres2, Rodrig Marculescu2
1Department of Cardiology, Medical University of Vienna, Vienna, Austria.
Insights
A new coronary score accurately quantifies coronary artery disease (CAD) severity. This score correlates with various lab parameters, highlighting the link between CAD and metabolic, coagulation, and immune status, especially in diabetic patients.
Area of Science:
- Cardiology
- Biomarkers
- Medical Diagnostics
Background:
- Coronary artery disease (CAD) severity assessment is crucial for understanding its relationship with laboratory parameters.
- Existing scoring systems aim to quantify CAD severity but may lack precision.
Purpose of the Study:
- To develop and validate a simple yet precise coronary score for quantifying CAD severity.
- To investigate the correlation between the developed coronary score and various laboratory parameters.
- To identify significant predictors of CAD severity.
Main Methods:
- Angiography was used to assess stenosis grade in 17 coronary segments for 264 CAD patients (189 male, 75 female).
- A point system was devised based on stenosis severity (<30% to <50% = 1 point, 50% to <70% = 2 points, >70% = 3 points).
- The total points represented the coronary score, reflecting overall CAD severity.
Main Results:
- The coronary score showed positive correlations with systolic blood pressure, creatinine, BUN, lipase, glucose, HbA1c, triglycerides, CRP, fibrinogen Clauss, and leukocytes.
- Negative correlations were observed with Cl(-), iron, and HDL cholesterol.
- Diabetes status, sex, and fibrinogen Clauss were identified as significant predictors of the coronary score via regression analysis.
Conclusions:
- The developed coronary score is a simple and precise tool for quantifying CAD severity.
- CAD severity is linked to lipid, glucose, coagulation, and immunologic status, emphasizing the need for adequate treatment, particularly for type 2 diabetes mellitus patients.
- The coronary score can facilitate research on CAD and novel biomarkers, with further studies needed on outcome correlations.
Background:
Several scoring systems have tried to determine the severity of coronary artery disease (CAD) to investigate the connection between CAD severity and laboratory parameters.
Methods:
In total, 189 male (mean age: 61.86±10.77 years) and 75 female CAD patients (mean age: 67.84±7.70 years) were recruited and underwent angiography, which determined stenosis grade, of 17 coronary segments: no points for each nonstenosed segment or only calcified segments, one point for each stenosis from <30% to <50%, two points for each stenosis from 50% to <70%, and three points for each stenosis >70%. The points were added and should represent the severity of patients' CAD.
Results:
The coronary score correlated positively with systolic blood pressure, creatinine, blood urea nitrogen, lipase, glucose, glycated hemoglobin, triglycerides, C-reactive protein, fibrinogen Clauss, and leukocytes, and correlated negatively with Cl(-), iron, and high-density lipoprotein cholesterol. Stepwise multiple regression analysis with backward elimination revealed diabetes status, sex, and fibrinogen Clauss as significant predictors of coronary score.
Conclusion:
The coronary score delivers a quite simple but very precise tool for the quantification of CAD severity. These results show plainly the connection between CAD severity and the lipid, glucose, coagulation, and immunologic status of CAD patients, and substantiate the importance of sufficient treatment in this group of patients - in particular, CAD patients suffering from type 2 diabetes mellitus. The coronary score would offer a suitable tool for the investigation of the connection between CAD and new biomarkers. Further studies are needed to investigate the correlation of the coronary score with outcome parameters (e.g., death).
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