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Comparison of Novel Martin/Hopkins and Sampson Equations for Calculation of Low-Density Lipoprotein Cholesterol in Diabetic Patients

Abstract

Background

The accurate determination of low-density lipoprotein cholesterol (LDL-C) is important to reach guideline-recommended LDL-C concentrations and to reduce adverse cardiovascular outcomes in diabetic patients. The commonly used Friedewald equation (LDL-Cf), gives inaccurate results in diabetic patients due to accompanying diabetic dyslipidemia. Recently two new equations – Martin/Hopkins (LDL-Cmh) and Sampson (LDL-Cs) – were developed to improve the accuracy of LDL-C estimation, but data are insufficient to suggest the superiority of one equation over the other one.

Objective

The present study compared the accuracy and clinical usefulness of novel Martin/Hopkins and Sampson equations in diabetic patients.

Methods

This study included 402 patients with diabetes. Patients’ cardiovascular risk and LDL-C targets were calculated per European guidelines. Calculated LDL-Cmh, LDL-Cs, and LDL-Cf concentrations were compared with direct LDL-C concentration (LDL-Cd) to test agreement between these equations and LDL-Cd. A p-value <0.05 was accepted as statistically significant.

Results

Both LDL-Cmh and LDL-Cs had a better agreement with LDL-Cd as compared to LDL-Cf, but no statistical differences were found among novel equations for agreement with LDL-Cd (Cronbach’s alpha 0.955 for both, p=1). Likewise, LDL-Cmh and LDL-Cs showed a similar degree of agreement with LDL-Cd in determining whether a patient was in a guideline-recommended LDL-C target (96.3% for LDL-Cmh and 96.0% for LDL-Cs), which were marginally better than LDL-Cf (94.6%). In patients with a triglyceride concentration >400 mg/dl, agreement with LDL-Cd was poor, regardless of the method used.

Conclusion

Martin/Hopkins and Sampson’s equations show a similar accuracy for calculating LDL-C concentrations in patients with diabetes, and both equations were marginally better than the Friedewald equation.

Metabolic Diseases; Atherosclerosis, Dyslipidemias; Coronary Artery Disease; Diabetes Mellitus; Lipoproteins, LDL; Cholesterol, LDL

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