Background

The Canadian Cardiovascular Society Classification System for Angina Pectoris has two major severe Classes-III and -IV that needed a differentiation tool. Many metabolic pathways have been studied in the predic-tion of the form of severity of unstable angina (UA).

Objectives

In the present study, various arms of molecules have been studied in order to differentiate between Classes-III and -IV. These arms include insulin resistance (IR), lipid profile and atherogenic indices, lactosylcer-amides (CD17), toll-like receptor-4 (TLR4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and endogenous-opioid (EO) biomarkers.

Material and methods

Biomarkers were assayed in 51 Class-III UA patients and 39 Class-IV UA patients, in addi-tion to 52 controls. IR parameters were computed from fasting insulin and glucose by using the HOMA-calculator.

Results

UA patients exhibit IR state, dyslipidemia, higher TLR and CD17, as well as abnormal levels of EO bi-omarkers, compared with the control group. The results of the binary logistic regression analysis indicated that Class-IV was most accurately predicted by elevated systolic blood pressure, Castelli risk index-I (CRI-I), glucose, IL-6, and kappa-opioid receptor (KOR), all of which were positively correlated. Receiver operating characteristic (ROC) analysis shows that the top five parameters for prediction of Class-IV UA are elevations in serum glucose, IL-6, atherogenic coefficient, and IL-10 levels, together with a reduction in the IL-10/IL-6 ratio. CD17 and TLR4 have no capability to differentiate between UA groups.

Conclusions

The severe form of UA (Class IV) can be differentiated from Class-III UA by serum glucose, IL-6, IL-10, CRI-I, and KOR.