BACKGROUND In diabetes, there is a lower concordance between estimated and directly measured low-density lipoprotein cholesterol (LDL-C) values. In previous studies, the Martin–Hopkins (MH) and the modified Sampson (mS) equations emerged as novel LDL-C estimating methods with a higher concordance with direct measurement than the Friedewald (F) equation. OBJECTIVE Our prior analysis of an entire population of inpatients showed a progressive decline in LDL-C target attainment from low to higher-risk categories, with only 32.5% of patients with diabetes reaching the target. This analysis aimed to compare LDL-C levels calculated using the F, MH, and mS equations in this population, and to evaluate the clinical implications of adopting these approaches on cardiovascular risk categorization — both in the overall cohort and within diabetes and non-diabetes subgroups. METHODS Retrospective real-world data were extracted from the Hospital Information System using automated data extraction strategies and stored in a patient-centered repository (the Dyslipidaemia Data Mart). LDL-C was calculated using the F, MH, and mS equations. Goal achievement for LDL-C was evaluated using the 3 equations, overall and for diabetic and nondiabetic subgroups. We then assessed the effect of the switch from the traditional method to these novel approaches on patient risk categorization. RESULTS A total of 13,834 patients were included. Overall, patients at goal were 35.8% with MH and 32.6% with mS, both lower compared with F (38.9%). The percentage of patients at goal (according to F) who were reclassified as not at goal (according to MH and mS) was significantly higher in diabetes compared with nondiabetes (5.1% vs 2.8% for reclassification from F to MH, P < .001; 8.3% vs 5.3% for reclassification from F to mS, P < .001). Distance to target was also higher with MH and mS, particularly among patients with diabetes. CONCLUSION Accurate LDL-C estimation is critical for the cardiovascular risk management of people with diabetes. The choice of calculation method can significantly influence both target achievement and therapeutic decisions, with the MH and mS equations identifying a larger proportion of patients with diabetes as not at goal compared with the F equation.
Capece, U., Iacomini, C., Morciano, C., Gugliandolo, S., Splendore, A., Cesario, A., Masciocchi, C., Di Giuseppe, G., Ciccarelli, G., Avolio, A., Brunetti, M., Soldovieri, L., Cinti, F., Mezza, T., Patarnello, S., Giaccari, A., Di Giorgi, N., Impact of the Friedewald equation vs 2 validated equations on LDL-C estimates and goal achievement in hospitalized patients with diabetes, <<JOURNAL OF CLINICAL LIPIDOLOGY>>, 2026; 2026 (Vol 20, Issue 6): 1166-1177. [doi:10.1016/j.jacl.2026.04.018] [https://hdl.handle.net/10807/340301]
Impact of the Friedewald equation vs 2 validated equations on LDL-C estimates and goal achievement in hospitalized patients with diabetes
Capece, Umberto;Morciano, Cassandra;Gugliandolo, Shawn;Splendore, Amelia;Cesario, Alfredo;Masciocchi, Carlotta;Di Giuseppe, Gianfranco;Ciccarelli, Gea;Avolio, Adriana;Brunetti, Michela;Soldovieri, Laura;Cinti, Francesca;Mezza, Teresa;Giaccari, Andrea
;
2026
Abstract
BACKGROUND In diabetes, there is a lower concordance between estimated and directly measured low-density lipoprotein cholesterol (LDL-C) values. In previous studies, the Martin–Hopkins (MH) and the modified Sampson (mS) equations emerged as novel LDL-C estimating methods with a higher concordance with direct measurement than the Friedewald (F) equation. OBJECTIVE Our prior analysis of an entire population of inpatients showed a progressive decline in LDL-C target attainment from low to higher-risk categories, with only 32.5% of patients with diabetes reaching the target. This analysis aimed to compare LDL-C levels calculated using the F, MH, and mS equations in this population, and to evaluate the clinical implications of adopting these approaches on cardiovascular risk categorization — both in the overall cohort and within diabetes and non-diabetes subgroups. METHODS Retrospective real-world data were extracted from the Hospital Information System using automated data extraction strategies and stored in a patient-centered repository (the Dyslipidaemia Data Mart). LDL-C was calculated using the F, MH, and mS equations. Goal achievement for LDL-C was evaluated using the 3 equations, overall and for diabetic and nondiabetic subgroups. We then assessed the effect of the switch from the traditional method to these novel approaches on patient risk categorization. RESULTS A total of 13,834 patients were included. Overall, patients at goal were 35.8% with MH and 32.6% with mS, both lower compared with F (38.9%). The percentage of patients at goal (according to F) who were reclassified as not at goal (according to MH and mS) was significantly higher in diabetes compared with nondiabetes (5.1% vs 2.8% for reclassification from F to MH, P < .001; 8.3% vs 5.3% for reclassification from F to mS, P < .001). Distance to target was also higher with MH and mS, particularly among patients with diabetes. CONCLUSION Accurate LDL-C estimation is critical for the cardiovascular risk management of people with diabetes. The choice of calculation method can significantly influence both target achievement and therapeutic decisions, with the MH and mS equations identifying a larger proportion of patients with diabetes as not at goal compared with the F equation.| File | Dimensione | Formato | |
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