Purpose: Aim of the present study was to assess the prognostic power of an early determination of metabolic markers after an ACS and to develop a "cardio-metabolic" score for the prediction of all-cause mortality.
Methods: A model was derived from a cohort of 510 patients (pts), admitted to an in-hospital cardiac rehabilitation program after an ACS; the model was then validated in an other similar cohort of 510 pts. A Cox regression analysis was used to identify independent prognostic predictors for 3-year mortality. A ROC analysis was used to identify the best cut-off of each independent marker, then points were assigned to each predictor by multiplying the regression coefficient by 10 and rounding to nearest integer, and a mortality score was developed. The predictive model based on this score was evaluated by a ROC analysis and the areas under the curves were calculated in both the derivation and validation cohorts.
Results: Main characteristics of the derivation cohort were age 64 ± 12 years, male gender in 75%, mean left ventricular ejection fraction 51 ± 11 %, revascularization in 80%; hypertension, smoking, diabetes and chronic obstructive pulmonary disease were present in the history in 301 (59%), 298 (58%), 107 (21%) and 33 (6%) respectively. At the cardiac rehabilitation admission, all patients received blood tests, in average 12 days after the ACS symptom onset. At a median follow-up of 3 years, all cause mortality was 8.6%.
A Cox regression analysis identified uric acid (HR 1.19, p=0.045), LDL-cholesterol (HR 1.016, p=0.017), age (HR 1.063, p=0.000) and LVEF (HR 0.950, p=0.000) as independent predictors of mortality. The best cut-off values were then identified and the following points were assigned to each variable in order to develop a predictive model: uric acid =7 mg/dl (7 points), LDL-cholesterol >102 mg/dl (11 points), age > 67 years (15 points) and LVEF <52% (9 points). The model showed an area under the curve of 0.811 (CI 0.744-0.878, p=0.000). In the validation cohort, the area under the curve was 0.744 (CI 0.691-0.798, p=0.000). The mortality rates in the derivation and validation cohorts were 2% and 1% in pts with a score of 0 to 11, 10% and 17% in pts with a score of 12 to 24 and 31% in both cohorts in pts with a score =25.
Conclusion: Seric levels of uric acid and LDL-cholesterol, early evaluated after an ACS, are strong predictors of long-term all-cause mortality, independent of age and LVEF. A "cardio-metabolic" score is useful for prediction of all-cause mortality after ACS and an aggressive management of metabolic risk early after ACS is advisable.