Coronary calcification measures predict mortality in symptomatic women and men

Klaske R Siegersma1,2, Floor Groepenhoff2,3, Anouk L M Eikendal2

  • 1Department of Cardiology, Amsterdam University Medical Center VUMC Site, Amsterdam, The Netherlands.

Open Heart
|December 29, 2022
PubMed

Insights

Absolute coronary artery calcium scoring effectively predicts mortality in symptomatic patients. Sex-specific, age-specific, and race/ethnicity-specific percentiles (Multi-Ethnic Study of Atherosclerosis, MESA) do not offer improved prognostic value over absolute scores.

Area of Science:

  • Cardiology
  • Preventive Cardiology
  • Medical Imaging

Background:

  • Coronary artery calcification (CAC) is a marker of atherosclerosis.
  • Assessing CAC is crucial for cardiovascular risk stratification.
  • The prognostic value of different CAC scoring methods needs evaluation in symptomatic individuals.

Purpose of the Study:

  • To evaluate the prognostic capability of absolute coronary artery calcium scores (CACS) versus Multi-Ethnic Study of Atherosclerosis (MESA) percentiles for predicting mortality.
  • To compare the performance of these scoring methods in symptomatic men and women.

Main Methods:

  • A cohort of 4985 symptomatic patients referred for cardiac CT was analyzed.
  • Coronary Artery Calcium Score (CACS) and MESA percentiles were calculated.
  • All-cause mortality data were linked and analyzed using Kaplan-Meier curves and Cox regression.

Main Results:

  • Absolute CACS demonstrated a moderately good performance in predicting mortality.
  • MESA percentiles showed no significant improvement in prognostic accuracy compared to absolute CACS in both women and men.
  • The C-statistics for MESA percentiles and absolute CACS were comparable.

Conclusions:

  • Absolute CACS is a valuable tool for mortality risk prediction in symptomatic patients.
  • There is no added benefit in using MESA percentiles over absolute CACS.
  • Further research may explore incorporating degree of stenosis for refined risk prediction, especially in women.
Abstract

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