AI Article Synopsis
- Researchers examined several health indicators in 114 chronic heart failure (CHF) patients to find predictors of mortality, including serum uric acid, cholesterol, and a specific immune marker (sTNF-R1).
- The study showed that all tested factors, particularly uric acid and sTNF-R1, effectively predicted survival and were even more reliable than standard clinical measures like left ventricular ejection fraction (LVEF).
- The combination of these metabolic and immunological indicators provided the best assessment of risk in CHF patients, leading to a recommendation for further testing on a larger scale to validate these findings.
Article Abstract
Background: A vast array of parameters has been proposed to predict mortality in chronic heart failure (CHF). Their applicability into clinical practice remains challenging due to economical and availability considerations.
Methods And Results: We studied serum uric acid, total cholesterol, and soluble tumour necrosis factor receptor 1 (sTNF-R1) in 114 CHF patients (63.0 ± 1.0 years, NYHA functional class I/II/III/IV: 11/34/54/15) recruited prospectively into a metabolic study program. All patients underwent assessment of left ventricular ejection fraction and measurement of peak oxygen consumption (pVO(2)). Patients were followed for 24 months or until death. A total of 31 patients died; cumulative survival was 78% (95% confidence interval [CI] 70-86%) and 73% (65-81%) at 12 and 24 months, respectively. In single predictor Cox proportional hazard analysis, uric acid, pVO2, sTNFR-1, LVEF (all p<0.0001) and cholesterol (p<0.02) all predicted survival. All parameters remained significant predictors of death after multivariable adjustment (all p<0.02). Receiver-operator characteristic (ROC) curve analyses showed that uric acid and sTNF-R1 are equally strong with regards to their prognostic performance in CHF like pVO(2,) but even better than LVEF. The combination of pVO(2), LVEF, uric acid, and sTNF-R1 in ROC statistics turned out as the best model with the highest prognostic value in CHF (AUC: 0.91, sensitivity: 90.4, specificity: 74.2, p=0.0001).
Conclusion: Including metabolic-immunological parameters into risk assessment might result in a better risk stratification than modeling based on clinical parameters alone, probably due to a better reflection of CHF as multisystem disease. We suggest metabolic-immunological parameters to be tested in larger populations.
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| http://dx.doi.org/10.1016/j.ijcard.2010.10.028 | DOI Listing |
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