Coronary artery calcium to predict all-cause mortality in elderly men and women.
OBJECTIVE
We sought to study the prognostic utility of coronary artery calcium (CAC) in the elderly.


BACKGROUND
The prognostic significance of CAC in the elderly is not well known.


METHODS
All-cause mortality was assessed in 35,388 patients (3,570 were >or=70 years old at screening, and 50% were women) after a mean follow-up of 5.8 +/- 3 years.


RESULTS
In older patients, risk factors and CAC were more prevalent. Overall survival was 97.9% at the end of follow-up. Mortality increased with each age decile with a relative hazard of 1.09 (95% confidence interval: 1.08 to 1.10, p < 0.0001), and rates were greater for men than women (hazard ratio: 1.53; 95% confidence interval: 1.32 to 1.77, p < 0.0001). Increasing CAC scores were associated with decreasing survival across all age deciles (p < 0.0001). Survival for a <40-year and >or=80-year-old man with a CAC score >or=400 was 88% and 19% (95% and 44% for a woman, p < 0.0001), respectively. Among the 20,562 patients with no CAC, annual mortality rates ranged from 0.3% to 2.2% for patients age 40 to 49 years or >or=70 years (p < 0.0001). The use of CAC allowed us to reclassify more than 40% of the patients >or=70 years old more often by excluding risk (i.e., CAC <400) in those with >3 risk factors.


CONCLUSIONS
Despite their limited life expectancy, the use of CAC discriminates mortality risk in the elderly. Furthermore, the use of CAC allows physicians to reclassify risk in the elderly.
Raggi
Paolo
P
Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA. praggi@emory.edu
Gongora
Maria C
MC
Gopal
Ambarish
A
Callister
Tracy Q
TQ
Budoff
Matthew
M
Shaw
Leslee J
LJ
D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002114:Calcinosis / Q000191:economics / Q000401:mortality*; D009202:Cardiomyopathies / Q000191:economics / Q000401:mortality*; D003324:Coronary Artery Disease / Q000191:economics / Q000401:mortality*; D003362:Cost-Benefit Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D017678:Sex Distribution; D012737:Sex Factors; D016019:Survival Analysis; D015996:Survival Rate; D014481:United States / Q000453:epidemiology