Low-density Lipoprotein Cholesterol Measurement Research Articles

Abstract 4140140: Cardiology Follow-Up as a Determinant of LDL-C Management Success in Secondary Cardiovascular Prevention

Managing low-density lipoprotein (LDL) cholesterol is crucial for secondary cardiovascular prevention. Despite ACC/AHA recommendations for maintaining LDL below 70 mg/dL, achieving this target remains suboptimal. This study investigates the impact of consistent cardiologist involvement on LDL cholesterol management. Methods: We conducted a multicenter, cross-sectional cohort study within the Steward Healthcare System in Massachusetts, analyzing data from 10,211 patients hospitalized from January 2019 to March 2024. This study offers a detailed snapshot of data across the study period, capturing both recent and long-standing cases identified through ICD codes for conditions like NSTEMI, CAD, STEMI, or CABG, specifically as markers for secondary cardiovascular prevention. We utilized the most recent LDL cholesterol measurements for our analysis and compared the distribution of lipid-lowering medications across groups. Notably, follow-ups with cardiologists outside our network were not tracked, potentially omitting relevant data. Statistical analysis employed the Chi-square test for categorical variables and binary logistic regression to adjust for confounders. Results: showed that patients with regular cardiology visits more often achieved LDL levels below 70 mg/dL (57.45% vs. 46.67%; OR 1.54, 95% CI: 1.42-1.68; P<0.0001). These patients also had lower mean LDL levels (68.72 ± 27.02) compared to those without cardiology follow-up (75.82 ± 30.27; P<0.0001). Higher usage of PCSK9 inhibitors and non-statin medications was noted among the visiting group, with an adjusted OR of 1.43 (95% CI: 1.29-1.59; P<0.0001). Conclusion: Our study shows that cardiologist involvement significantly enhances cholesterol management in CAD patients, as evidenced by a higher proportion achieving optimal LDL levels and more aggressive use of lipid-lowering medications. Despite these benefits, some patients discontinue their follow-ups with cardiologists after coronary events, shifting cholesterol management to primary care providers (PCPs). This transition often results in less aggressive treatment strategies, evidenced by elevated LDL levels in patients lacking recent cardiology care. To sustain effective cholesterol management and stringent LDL targets, long-term follow-up with a cardiologist is crucial. Furthermore, equipping PCPs with the necessary tools and protocols to adopt more aggressive treatment approaches could bridge the care gap when specialist visits are infrequent.

Contemporary LDL-cholesterol management in male and female patients at high-cardiovascular risk: results from the European observational SANTORINI study

Abstract Background Middle aged women have a faster increase in atherosclerotic cardiovascular disease (ASCVD) events than men over time. Undertreatment with guideline-recommended therapy in women may be one of the drivers for this burden. Purpose To compare high- or very high-risk male and female patients regarding contemporary 1-year low-density lipoprotein cholesterol (LDL-C) goal attainment, lipid-lowering therapy (LLT) intensity, and major adverse cardiovascular event (MACE) rate. Methods SANTORINI is an observational, prospective study that enrolled high- and very high-cardiovascular risk patients between March 2020 and Feb 2021, across 623 sites and 14 countries in Europe from primary & secondary care settings, with a further 1-year prospective follow-up. We included all patients with an LDL-C measurement at baseline and 1-year follow up (1yFU) for the current analysis. LDL-C goal attainment was defined separately for high and very-high risk categories according to 2019 ESC/EAS guidelines. Results Overall, 5197 males with a mean age of 65 years, and 2013 females with a mean age 66 years were included. At baseline, male patients had higher prevalence of pre-existing ASCVD (81.6% vs. 63.5%), and a lower prevalence of familial hypercholesterolaemia (8.7% vs. 17.2%) than female patients (Table 1). The proportion of patients reaching LDL-C goal improved from baseline to 1yFU, but was greater in males (22.9% and 33.3%, respectively) than females (16.9% and 24.6%, respectively). Similarly, the proportion of patients receiving no LLT decreased from baseline to 1yFU for both sexes, however, more females than males received no LLT at 1yFU (male: 20.7% to 2.7%; female: 23.9% to 3.9%). High intensity statin use increased for both sexes but was higher for males (22.2% to 27.3%) than for females (15.5% to 19.5%) at 1yFU. By contrast, PCSK9i use at baseline and 1yFU was lower for males (6.6% to 9.3%) than for females (9.8% to 13.4%). Nevertheless, the use of combination LLT at 1yFU was lower among females than males (male: 27.8% to 42.2%; female: 26.7% to 40.2%). During follow-up, MACE-4 was higher in males (5.31/100 patient years [PY]; 95% confidence interval [CI]: 4.68–5.95) than in females (3.63/100PY; 95% CI: 2.79–4.47). Similar results were observed for MACE-3 (Table 2). Conclusions Despite similar guideline recommendations, use of combination LLT and high intensity statin therapy was lower in female patients at high or very high cardiovascular risk than in male patients over one year of follow-up. Accordingly, female patients had lower LDL-C goal attainment both at baseline and at one-year. Nevertheless, due to intrinsic risk factors, female patients had lower rates of MACE-4 and MACE-3 than male patients.

Sex differences in management of LDL-cholesterol in patients with chronic coronary syndrome

Abstract Background Effective management of low-density lipoprotein cholesterol (LDL-C) is crucial for preventing recurrent cardiovascular (CV) events in patients with chronic coronary syndrome (CCS). Sex may impact the LDL-C management, by gender bias and/or sex-specific responses to pharmacological interventions. Purpose We examined sex-specific LDL-C management in CCS patients, assessing target achievement rates and their implications for CV outcomes. Methods In the international CLARIFY registry, we included 22,134 CCS patients with baseline LDL-C measurements. LDL-C levels were monitored annually over the 5-year follow-up period. Target LDL-C was set at 100 mg/dL, in line with prevailing recommendations at that time. Sex-specific differences in LDL-C were adjusted for age, geographical region and indication for lipid lowering drugs (stroke, MI, PAD). The primary endpoint was the incidence of MACE, defined as CV death or MI during the 5-year follow-up, evaluated using multivariable analysis adjusted for known predictors of recurrent CV events in CCS patients. Results Of 22,134 patients, 21.6% were women. Upon inclusion (6.5 ± 6.3 years after CCS diagnosis), women were more likely than men to have LDL-C levels above the recommended threshold (45.6% vs. 37.4%; aOR 1.47, 95%CI 1.38-1.58, p<0.001) and less likely to receive statin treatment (82.7% vs. 85.4%, p<0.001). Although women and men had comparable numbers of LDL-C measurements during follow-up, the discrepancies endured over the 5-year observation period, with women consistently showing lower likelihoods of achieving LDL-C targets at 1, 2, 3, 4, and 5 years post-inclusion (p<0.001 for all time points). Overall, women were less likely than men to have all available LDL-C concentrations within the target range (37.8% vs. 44.6%; aOR 0.70, 95% CI 0.64-0.76, p<0.001) and more likely to never reach the target LDL-C goal during follow-up (22.6% vs. 17.5%; aOR 1.43, 95% CI 1.32-1.55, p<0.001). Failing to achieve at least one LDL-C concentration below 100 mg/dL was associated with an increased risk of subsequent MACE (adjusted HR 1.57, 95%CI 1.38-1.77, p<0.001), with similar associations observed in both men (aHR 1.66, 95% CI 1.44-1.91, p<0.001) and women (aHR 1.31, 95% CI 1.01-1.70, p=0.05). Conclusion In patients with CCS, women consistently showed lower likelihood of reaching LDL-C targets throughout follow-up compared to men, even after adjusting for age, geographical region and other statin indications. Notably, women were more likely to have no LDL-C concentration within recommended range during follow-up, which is particularly concerning given its association with an increased risk of CV events. A contributing factor to this sex disparity in LDL-C control is women's lower likelihood of receiving lipid-lowering drugs than men. These results highlight the need for tailored interventions to address sex-related disparities in LDL-C management and improve cardiovascular outcomes in CCS patients.

Lipid management among very-high-risk patients with atherosclerotic cardiovascular disease and type 2 diabetes

Abstract Background Patients with established atherosclerotic cardiovascular disease (ASCVD) and type 2 diabetes (DM2) often meet very-high-risk (VHR) criteria for recurrent ASCVD events and are recommended for aggressive low-density lipoprotein-cholesterol (LDL-C) lowering in guidelines. Purpose Our study aimed to evaluate the proportion of patients achieving guideline-based lipid goals and identify factors associated with achieving these goals among VHR patients with established ASCVD and DM2. Methods Electronic health record data were used to identify VHR patients with established ASCVD and DM2 across 14 large US healthcare systems between 1/1/2022-12/31/2022 with an available LDL-C measurement. We examined the percentage of patients achieving guideline-based lipid goals based on the 2018 AHA/ACC Multisociety Guideline, defined as either having an LDL-C <70 mg/dL or receiving maximal lipid-lowering therapy (i.e., on a PCSK9i monoclonal antibody (mAb)) at the time of the last LDL-C test, and performed multivariable logistic regression to evaluate factors associated with the achievement of those goals. Results Among 213,380 eligible VHR patients with ASCVD and DM2 (mean age 70.2 years, 42% women), 51.8% (110,452) patients achieved guideline-based lipid goals. This included 50.9% with an LDL-C <70 mg/dL and 1.7% on a PCSK9i mAb. Female sex (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.61-0.66), Black race (OR, 0.67; 95% CI, 0.63-0.72), Medicaid insurance (OR, 0.92; 95% CI, 0.86-0.97), and non-coronary artery disease forms of ASCVD including peripheral artery disease (OR, 0.67; 95% CI, 0.65-0.69) and cerebrovascular disease (OR, 0.80; 95% CI, 0.77-0.83) were associated with a lower likelihood of achieving guideline-based lipid goals. Conversely, having undergone percutaneous coronary intervention (OR, 1.31; 95% CI, 1.19-1.43) or coronary artery bypass graft (OR, 1.24; 95% CI, 1.06-1.45) in the previous year, and comorbidities including dialysis (OR, 1.38; 95% CI, 1.23-1.55), atrial fibrillation or flutter (OR, 1.09; 95% CI, 1.06-1.12), and systolic heart failure (OR, 1.11; 95% CI, 1.08-1.14) were associated with a higher likelihood of achieving these goals. Overall, 24.0% of patients were on no statin, 27.2% were on a low- or moderate-intensity statin, and only 5.8% were on a statin in combination with ezetimibe or a PCSK9i mAb. Conclusion Large gaps in care exist for VHR patients with ASCVD and DM2, particularly among women, Black individuals, and those with Medicaid. Targeted interventions are needed to improve the uptake of evidence-based secondary prevention therapies in these patients.

Lipid goal attainment across baseline socioeconomic and clinical factors comparing an "inclisiran first" implementation strategy and usual care: subgroup analysis of VICTORION-INITIATE

Abstract Background Addressing inequities in cardiovascular care has become a public health priority. Recent results from VICTORION-INITIATE, a pragmatically designed, randomised clinical trial showed the benefit of using inclisiran immediately if patients with atherosclerotic cardiovascular disease (ASCVD) fail to achieve low-density lipoprotein cholesterol (LDL-C) <70 mg/dL (1.8 mmol/L) on maximally tolerated statins. Purpose To evaluate effectiveness and safety of an "inclisiran first" implementation strategy (IF) versus usual care (UC) in subgroups that may be associated with healthcare inequities. Methods VICTORION-INITIATE was conducted at 45 representative clinical settings across 20 states in the USA. Patients with ASCVD randomised 1:1 (stratified by insurance status) received open-label inclisiran 284 mg at Days 0, 90 and 270) plus UC or UC alone (lipid management directed by treating physicians). Treating physicians had access to LDL-C measurements and were encouraged to intensify treatment per lipid guidelines. We compared efficacy and safety endpoints for IF and UC in prespecified subgroups (race, ethnicity, sex, renal function and statin intensity) and by income level (post-hoc analysis). Results The study randomised 450 patients. Baseline demographic and clinical parameters were balanced between study arms (≥65 years of age: IF: 63.1%, UC: 61.3%; non-White: IF: 15.6%, UC: 15.1%; Hispanic: IF: 13.8%, UC: 16.9%; female: IF: 29.8%, UC: 32.0%; income ≤$50,000: IF: 58.7%, UC: 58.2%; estimated glomerular filtration rate ≥30 to <60 mL/min/1.73m2: IF: 20.0%, UC: 17.8%; no statins at baseline: IF: 9.8%; UC: 10.2%). Across all subgroups, more patients achieved LDL-C goals at Day 330 with IF vs UC (Figure 1). Within the UC arm, the proportions of patients achieving LDL-C <70 mg/dL and <55 mg/dL, respectively, were numerically lower for non-White (8.8% and 2.9%) and Hispanic (10.5% and 2.6%) than White (24.6% and 10.2%) and non-Hispanic (24.9% and 10.3%) patients. We did not observe differences in LDL-C goal attainment for these subgroups in patients receiving IF. Compared with UC, IF resulted in greater mean percentage change in other lipids and lipoproteins from baseline to Day 330, irrespective of subgroup (Figure 2). Incidence of treatment-emergent adverse events (TEAEs) and serious TEAEs compared similarly between IF and UC for each subgroup (IF: 35.5−69.2%, UC: 34.2−84.2%, and IF: 3.2−16.9%, UC: 0.0−36.8%, respectively). Conclusions VICTORION-INITIATE enrolled a diverse population reflective of "real-world" US clinical practice. The IF strategy consistently resulted in higher rates of LDL-C goal attainment for all subgroups studied and did not lead to differences in lipid outcomes by race or ethnicity as compared to usual care. No additional safety concerns for the IF strategy were identified.

Low-density lipoprotein cholesterol goal attainment with "inclisiran first" versus usual care in patients with atherosclerotic cardiovascular disease

Abstract Background Rapid and sustained attainment of guideline-recommended low-density lipoprotein cholesterol (LDL-C) goals is critical for patients with atherosclerotic cardiovascular disease (ASCVD). In VICTORION-INITIATE, inclisiran administered twice-yearly by a healthcare professional earlier in the treatment pathway allowed more patients with ASCVD to achieve and sustain LDL-C goals vs current usual care (UC). Purpose To evaluate cumulative LDL-C exposure in the overall population and LDL-C goal attainment and safety in subgroups of participants (type of ASCVD, timing of ASCVD event, and history of statin intolerance) who received an "inclisiran first" implementation strategy (IF; adding inclisiran immediately on failure to achieve LDL-C <70 mg/dL [1.8 mmol/L] with maximally tolerated statins) compared with UC. Methods VICTORION-INITIATE was a 330-day, prospective, pragmatically designed trial that randomised participants 1:1 (stratified by insurance status) to IF (open-label inclisiran 284 mg at Days 0, 90 and 270 plus UC) or UC alone (lipid management directed by treating physician’s discretion). The study took place at 45 sites across 20 states in the USA. Treating physicians had access to LDL-C measurements and were encouraged to intensify treatment per clinical practice guidelines. This prespecified subgroup analysis evaluated LDL-C goal attainment by timing of the most recent ASCVD event (<1 year/≥1 year prior to consent), ASCVD subtype (coronary heart disease [CHD], peripheral arterial disease [PAD], and cerebrovascular disease [CVD]) and statin intolerance status. Cumulative LDL-C exposure over time in the overall population and safety by subgroup were also evaluated. Results Of 450 patients randomised to IF or UC, 11.1% and 84.2% had an ASCVD event <1 year or ≥1 year prior to consent, respectively; 91.8%, 18.2% and 14.7% had a history of CHD, CVD or PAD, and 25.8% were statin intolerant. Cumulative exposure to LDL-C to Day 330 was lower in patients treated with IF vs UC (mean time-adjusted LDL-C: 42.4 mg/dL vs 90.7 mg/dL, Figure). Significantly more patients who received IF achieved LDL-C goals of <70 mg/dL and <55 mg/dL at Day 330 vs UC, irrespective of subgroup (Table). Across subgroups, the incidence of treatment-emergent adverse events (TEAEs) and serious TEAEs were similar between IF and UC (IF: 52.6−71.2%, UC: 46.2−66.0% and IF: 10.7−28.3%, UC: 11.4−22.2%, respectively). Conclusions Participants with ASCVD and LDL-C >70 mg/dL who received IF had lower cumulative LDL-C exposure over the study period than those treated with UC. IF resulted in rapid and sustained achievement of LDL-C goals regardless of ASCVD subtype, event timing and statin intolerance. The safety profile of IF was consistent across the subgroups analysed.

NMR Insights into Lipoprotein Particles: analyzing correlations with traditional lipid measurements

Abstract Introduction Lipid metabolism plays a crucial role in various physiological processes. Lipid molecules are transported by lipoproteins, and the intricate involvement of lipoproteins in cardiovascular disease (CVD) is well-established, given their diverse size, density, and lipid composition. The emergence of Nuclear Magnetic Resonance (NMR) spectroscopy, a high-resolution analytical technique, promotes the assessment of lipoprotein particle numbers and sizes. Studies suggest that the measurement of total low-density lipoprotein particle numbers (LDL-P), small LDL-P (SLDL-P), and total high-density lipoprotein particle numbers (HDL-P) provides better evaluation of risk of CVD than enzymatic-based measurements of LDL cholesterol (LDL-C) and HDL cholesterol (HDL-C). Our study examined the correlation between NMR-derived lipoprotein profiles and traditional cholesterol measurements in control and patient populations. Methods Fasting serum samples were collected from healthy male and female donors (n=148), ages 21-64 years. The analysis also included the results from >20,000 patients’ samples submitted to our laboratory for NMR lipid testing. We assessed LDL-P, SLDL-P, HDL-P, large HDL (LHDL-P), and HDL size (HDL-S) by NMR. In addition, total cholesterol (TC) and HDL-C were measured using traditional automated enzymatic assays (Roche Diagnostics); LDL-C was calculated. Statistical analyses, including Spearman correlation, were performed using GraphPad Prism software. Spearman coefficient (r) ≥0.75 indicated a strong correlation, r <0.5 indicated a weak correlation. Results HDL-C only moderately correlated with total HDL-P in samples collected from controls (rcontrols=0.52) and patients (rpatients=0.68), while showing better correlation with LHDL-P (rcontrols=0.90, rpatients=0.89). Traditional LDL-C strongly correlated with total LDL-P (rcontrols=0.76, rpatients=0.81), but showed only weak correlation with SLDL-P (rcontrols=0.42, rpatients=0.28), which is considered more atherogenic and predictive of CVD risk than LDL-C or total LDL-P. Interestingly, among various lipoprotein parameters, SLDL-P correlated the strongest with HDL-S in both study populations (rcontrols=-0.87, rpatients=-0.84). Samples with higher number of SLDL-P also had smaller size of HDL-P, although the number of total HDL-P did not differ between high vs low SLDL-P samples. In contrast, only moderate negative correlation was observed between SLDL-P and traditional HDL-C (rcontrols=-0.74, rpatients=-0.68), suggesting that the size of HDL particles might add value in evaluating CVD risk. Conclusion The NMR technology has advantage over traditional measurements in stratifying an individual’s lipoprotein milieu. It provides insights into the number of small LDL particles and size of HDL particles, which are not included in standard lipid testing and may allow for more individualized patient care. Incorporation of lipoprotein size and particle number in clinical guidelines may help physicians with assessment CVD risk and treatment monitoring.

The Role of Urban Residence, Race and Ethnicity, and Glycemic Control in Receiving Standards of Care and Progression to Vision-Threatening Diabetic Retinopathy.

Among patients with diabetes living in the U.S. with newly detected mild or moderate nonproliferative diabetic retinopathy (NPDR) without diabetic macular edema (DME), we aimed to characterize determinants for receiving standards of care and progression to vision-threatening diabetic retinopathy (VTDR) (severe NPDR, proliferative diabetic retinopathy, DME). Electronic health records of patients newly detected with NPDR without DME between 2015 and 2023 were analyzed with use of the Epic Cosmos research platform. We characterized the adjusted associations of urban versus rural residence, race and ethnicity (Hispanic, non-Hispanic [NH] White, NH Black, other), and glycemic control (HbA1c <7.0%, 7.0%-8.9%, ≥9%, unavailable) separately with guideline-recommended care (two of three: ophthalmology visit, primary care visit, and measurement of HbA1c, blood pressure, and LDL cholesterol) in the 2 years after diagnosis and with progression to VTDR. Average (SD) age for the analytic sample (n = 102,919) was 63 (13.5) years, and 51% were female, 59% NH White, and 7% rural residents. Only 40% received guideline-recommended care, and 14% progressed to VTDR (median follow-up 35 months [interquartile range 18-63]). Urban residence was associated with receiving standards of care in both years (risk ratio 1.08 [95% CI 1.05-1.12]) and progression to VTDR (hazard ratio 1.07 [95% CI 0.99-1.15]). Racial and ethnic minority individulas were more likely to progress to VTDR. Individuals with poor or unknown glycemic control were less likely to receive standards of care and more likely to progress to VTDR. Understanding the management and progression of newly detected NPDR will require disentangling the independent and interdependent contributions of geography, race and ethnicity, and glycemia.

12626 Non-high-density Lipoprotein Cholesterol For Detecting Dyslipidemia Among Korean Adolescents

Abstract Disclosure: H. Nam: None. E. Kang: None. Y. Rhie: None. K. Lee: None. Objectives: Non-high-density lipoprotein (HDL) cholesterol is an alternative method to assess dyslipidemia. We aimed to assess the validity of non-HDL cholesterol for detecting dyslipidemia among Korean adolescents. Methods: Data for 6,989 adolescents aged 10 to 19 years (3,684 boys and 3,305 girls), were obtained from the Korean National Health and Nutrition Examination Surveys. Dyslipidemia was defined by having one of the followings; total cholesterol ≥200 mg/dL, triglyceride ≥130 mg/dL, low-density lipoprotein (LDL) cholesterol ≥130 mg/dL, or HDL cholesterol &amp;lt;40 mg/dL. Non-HDL cholesterol ≥145 mg/dL was used to detect dyslipidemia based on National Heart, Lung, and Blood Institute 2011. Results: The overall prevalence of dyslipidemia were 27% and 37% among Korean adolescents based on calculated and measured LDL cholesterol level, respectively. The prevalence of non-HDL cholesterol level ≥145 mg/dL were 7.1% and 8.5% in teenage boys and girls, respectively. Dyslipidemia was found in 97.1% and 97.7% of boys and girls with high non-HDL level, respectively. High non-HDL cholesterol level especially detected high measured LDL-cholesterol level with a sensitivity of 96.3%, and a specificity of 96.3%, and a sensitivity of 95.2%, and a specificity of 97.1%, in teenage boys and girls. Using non-HDL cholesterol was more detected high LDL-cholesterol level compared to using total cholesterol alone in teenage boys and girls. Conclusions: Screening dyslipidemia using non-HDL cholesterol level was more useful than using total cholesterol level alone, especially in detecting high LDL cholesterol level. Non-HDL cholesterol was not required fasting and was appeared to be a reliable screening test also in adolescents. Presentation: 6/1/2024

A-214 Evaluate LDL-C using NIH equation 2, Friedewald equation, and direct homogeneous measurement

Abstract Background It is essential to accurately assess Low-density lipoprotein cholesterol (LDL-C) levels, a key marker for cardiovascular disease often used for treatment recommendations. The Friedewald equation has been used for many years to calculate plasma LDL-C levels, but it has limitations. Therefore, before implementing the NIH equation, we compared LDL-C results from NIH Equation 2 to the Friedewald formula and then to Atellica direct homogeneous assay LDL-C results. Methods A retrospective study of 1200 randomly selected patients out of 53,258 data points pulled from the laboratory information (LIS) system between November 2021 and October 2023. The study evaluated triglycerides, LDL-C, total cholesterol, and HDL-C measurements. The LDL-C calculated using NIH equation 2 has been set in the LIS as a non-reportable test component since November 1, 2021. The results obtained from NIH equation 2 and Friedewald equation were compared. LDL-C levels were measured using an Atellica direct homogeneous assay for an additional 75 specimens. Deming regression analysis compared measured and calculated LDL-C using both formulae. Results The LDL-C calculated using the Friedewald equation has a mean of 106.1 mg/dL and SD 40.1 mg/dL, while the NIH equation has a mean of 108.5 mg/dL and SD 39.9 mg/dL. The average difference between both equations is 2.5 mg/dL, and there is a significant difference between both calculations using paired t-tests (p-value&amp;lt;0.0001). We first compared the calculated LDL-C derived from the Friedewald formula to the NIH equation 2. The regression analysis equation for the Friedewald formula was y = -2.7 + 1.001 X (r = 0.99). When the Triglyceride values &amp;lt;150 mg/dL (N=879), the average difference is 1.3, and the regression equation is -0.45+1.01X(r=0.99). However, when the Triglyceride value &amp;gt;= 150 mg/dL (N=321), the average bias is 5.4 mg/dL, and the regression equation is -11.2+1.05X(r=0.99). The Friedewald formula was compared to the measured LDL-C in 75 specimens; the regression analysis for the Friedewald formula was y = -19.6 + 1.06 X (r = 0.91, p-value &amp;lt;0.0001). The 75 measured LDL-C results were also compared with the NIH formula. The regression analysis of NIH LDL-C with measured LDL-C was y = -5.6 + 0.981 x (r = 0.90, p-value = 0.0002). Both formulae showed a linear relationship against measured LDL-C. The NIH formula outperformed the Friedewald formula; bias difference -7.8(-6.8%) compared to the Friedwald equation bias -12.9(-12.0%). If the NIH equation had been used during this period, an additional 1,116 patients would have had LDL-C results. This is because the Friedewald equation should not be used if the triglyceride value is above 400 mg/dL. Out of the additional patients, 513 (46%) had a high LDL (&amp;gt;100 mg/dL). Conclusions The NIH formula performed better than the Friedewald formula, with a less negative bias when both calculations were compared to direct homogenous measurement. The average difference between the two formulas showed the lowest value when triglyceride &amp;lt; 150 mg/dL. Moving to NIH equation 2 will benefit our population as we had 2% of our patients in the past two years have triglyceride &amp;gt;400 mg/dL.

A-223 Direct LDL or not Direct-LDL, that is the question

Abstract Background Management of Cardiovascular Disease (CVD) risk is dependent on Low Density Lipoprotein Cholesterol (LDL-C) levels; therefore LDL-C serves as the marker for the assessment of CVD risk and the focus of lipid lowering treatment. The gold standard reference method for measurement of LDL-C is beta-quantification. We compared calculated LDL-C with Friedewald (F-LDL-C), Martin-Hopkins (M-LDL-C) and Sampson (S-LDL-C) equations versus LDL-C directly measured (D-LDL-C). In CVD management also cholesterol ratios are evaluated. TC/HDL is associated with morbidity and mortality in the general population. Furthermore, several studies have stated that high triglycerides (TG) levels and low HDL-C (TG/HDL ratio) could function as an atherogenic index. Methods 11399 samples were analyzed on Siemens Atellica Solution® for the lipid profile determination measuring Total Cholesterol (TC), D-LDL-C, HDL-C and TG. In the absence of additional clinical parameters, based on desirable levels for LDL-C recommended by guidelines, CVD risk was evaluated by assigning to LDL-C a cut-off of 100 mg/dL. In presence of misclassifications, we used two other parameters to assess LDL-C results: TG/HDL-C ratio and CT/HDL-C. Results Patients cohort had a mean age of 57.7 (±16.8) years of which 53% (age=58.6, ±15.9) were males and 47% (age=56.5, ±17.8 years) were females. Of these, the 57.7% were outpatients and 42.3% inpatients (42.1% of infectious diseases - 24.4% of the cardiovascular department). Data about LDL-C misclassification and ratio data parameters are shown in table 1. Discordant patients for D-LDL-C vs F-LDL-C are 8.5%, that of D-LDL-C vs M-LDL-C are 7.7% and D-LDL-C vs S-LDL-C are 7.2%. Conclusions Is known that LDL plays a central role in the pathogenesis of atherosclerosis. Accurate estimation of LDL-C is a fundamental point for the stratification of CVD risk and the achievement of the therapeutic goal; however, we are still uncertain about the best and accurate way to measure it.

Real-world exploration of LDL-cholesterol management in patients with atherosclerotic cardiovascular disease

BackgroundAlthough guidelines recommend low-density lipoprotein cholesterol (LDL-C) to be <70mg/dL in patients with atherosclerotic cardiovascular disease (ASCVD), the rate of achieving this goal remains suboptimal. We sought to understand real world contemporary practice patterns of LDL-C management in patients with ASCVD, and whether LDL-C testing influenced management across US health systems. MethodsA retrospective cohort study utilizing electronic medical record data from five health systems participating in the CardioHealth Alliance was performed on patients with an LDL-C measurement in 2021 and prior ASCVD. Multivariable regression modeling was used to determine the relationship of clinical factors with achievement of guideline directed LDL-C target. Changes in lipid lowering therapy (LLT) after LDL-C testing were also described. ResultsAmong 216,074 patients with ASCVD, 129,886 (60.1%) had uncontrolled LDL-C (i.e. ≥70 mg/dL). Compared with participants with controlled LDL-C (<70mg/dL), those with uncontrolled LDL-C were more frequently female (50.9% vs 35.1%), or Black (13.7% vs. 10.3%), and less commonly had coronary artery disease as the form of vascular disease (73.0% vs. 83.5% %), heart failure (21.3% vs. 29.1% %), diabetes (34.1% vs. 48.2%), atrial fibrillation (19.3% vs. 26.1%), or chronic kidney disease (25.1% vs. 32.2%). In multivariable analyses, the factors most strongly associated with failure to achieve LDL-C control were female sex (RR 1.13 [95% CI 1.12-1.14] p <0.001) and Black race (1.15 [1.14-1.17] p <0.001). Among the 53,957 (41.5%) of those with uncontrolled LDL-C ≥70 mg/dL not on lipid lowering therapy (LLT) at baseline, only 21% were initiated on any LLT within 6 months of the uncontrolled LDL-C value. ConclusionsWithin five diverse large health systems in the CardioHealth Alliance, more than half of the patients with ASCVD had uncontrolled LDL-C with significant disparities based on sex and race at baseline. The vast majority were not initiated on any lipid lowering therapy within 6 months of an elevated test result indicating persistent gaps in care that will likely worsen health inequities in outcomes. This highlights the urgent need for implementation efforts to improve equitable care.

Comparison of ten formulae for calculating low-density lipoprotein cholesterol with direct low-density lipoprotein cholesterol measurement

ABSTRACT Background: Accurate lipid profile assessment, mainly low-density lipoprotein cholesterol (LDL-C) measurement, is crucial for diagnosing and managing cardiovascular disease (CVD). The widely used Friedewald formula for LDL-C calculation has limitations, prompting the exploration of alternative equations. Aims: This study aims to compare ten LDL-C calculation formulas with direct measurement among study participants attending a tertiary care centre. Materials and Methods: Conducted from September 2021 to July 2022 at a tertiary healthcare centre in India, the study involved 114 participants aged 18 years or older. The exclusion criteria were high-serum triglyceride (TG) levels, renal failure, diabetes, liver diseases or unwillingness to participate. Blood samples were analysed for total cholesterol, TG, high-density lipoprotein cholesterol and LDL-C. The very-low-density lipoprotein cholesterol level was calculated. The LDL-C formulas evaluated were Friedewald, Anandaraja, De Cordova, Vujovic, Ahmadi, Puavillai, Chen, Hattori, Martin–Hopkin and Sampson. Results: Vujovic’s formula showed a negligible mean difference and strong correlation (r = 0.916, P &lt; 0.001) with direct LDL-C estimation across TG concentrations. Sampson’s formula performed best for TG &lt;150 mg/dL, whereas Vujovic’s formula excelled for 151–399 mg/dL TG concentrations. All formulas were highly correlated with direct LDL-C levels (P &lt; 0.001). Bland–Altman analysis indicated Vujovic’s formula as the closest match to direct measurement, with a mean bias of −1.42 ± 20.59 mg/dL. Conclusion: Vujovic’s formula demonstrated the slightest difference and strong correlation with direct LDL-C measurement, outperforming other formulas. This finding enhances the accuracy of LDL-C assessment and improves CVD risk management in clinical practice.

Influence of lipoprotein(a) on the accuracy of LDL-cholesterol measurement

Influence of lipoprotein(a) on the accuracy of LDL-cholesterol measurement

Comparison of Performance of Various Calculated Low-Density Lipoprotein (LDL) Methods in the Indian Population: A Hospital-Based Study.

In recent times, there has been a surge in proposed alternative approaches to computing low-density lipoprotein cholesterol (LDL-C), with a focus on enhancing precision, particularly within diverse demographic and clinical groups. Our aim is to assess the agreement, precision, and practicality of these methods compared to direct LDL-C measurements, with the goal of identifying the most effective approach for estimating LDL-C in the Indian context. It is a retrospective analytical study. Lipid profile data were gathered from the laboratory and organized in Microsoft Excel for analysis. LDL-C was computed using three different methods: the Friedwald formula, the Martin-Hopkins formula, and Sampson's formula. These calculations were then compared with the direct method of LDL-C estimation in two distinct groups: when triglyceride (TG) levels were less than 400 mg/dL and when TG levels exceeded 400 mg/dL. Bland-Altman plots were generated, and concordance correlation coefficients (CCCs) were computed to determine the most suitable calculated method. Data from 1,776 participants were analysed and divided into two groups. In both Group 1 (TG < 400 mg/dL) and Group 2 (TG > 400 mg/dL) considering bias, limits of agreements, and correlation coefficient, as seen on the Bland-Altman and CCC, Martin-Hopkins equation was found to be performing better than Friedwald and Sampson's equation. In this study, the Martin-Hopkins formula appears to be the most appropriate choice for precise LDL-C level measurements and indicated improved accuracy and consistency in LDL-C measurements, especially in individuals with elevated TG levels. This underscores its importance in ensuring precise assessment and suitable clinical management.

Does LDL-C determination method affect statin prescribing for primary prevention? A register-based study in Southern Denmark.

Examine whether the low-density lipoprotein cholesterol (LDL -C) determination method influences the rate of statin initiation for primary prevention of cardiovascular disease. We conducted a register-based retrospective study in the Region of Southern Denmark. Two hospital-based laboratories in the region directly measure LDL -C whereas four laboratories calculate LDL -C using Friedewald's formula. Physicians do not choose which method is used. We included all statin-naïve patients ≥40 years with no history of cardiovascular disease, diabetes, or chronic kidney disease, who had their LDL -C determined during 2018-2019. There were 202807 people who had LDL -C determined during the study period (median age 59 years, 44% women) of which 37% had a direct LDL -C measurement. The median reported LDL -C was 3.40mmol/L [interquartile range (IQR) 2.90-4.00] for those with a direct measurement vs. 3.00mmol/L (IQR 2.40-3.50) for those with calculated LDL -C. For those with direct measurement, re-calculated LDL -C (using Friedewald's formula) was 0.35mmol/L lower than the reported direct LDL -C measurement. Among those with directly measured LDL -C, 3.6% initiated statins compared with 2.7% of those with a calculated LDL -C. Direct LDL -C measurement led to higher odds of having a statin initiated compared with calculated LDL -C (adjusted odds ratio 1.23, 95% CI 1.17-1.30); for those with triglycerides >1.7mmol/L the adjusted odds ratio was 1.41 (95% CI 1.30-1.52). Differences in the reporting of LDL -C from laboratories using different methods have a substantial influence on physician's decisions to prescribe statins.

Evaluation of 13 Formulae for Calculated LDL-C Using Direct Homogenous Assay in a South Indian Population.

LDL cholesterol (LDL-C) is regarded as a significant therapeutic target and a known risk factor for atherosclerosis. It can be calculated using the results of the other lipid tests or tested directly. Despite its shortcomings, the Friedewald formula is most frequently utilized since it is simple and practical. Until now, several formulae have been proposed for calculating LDL-C; however, their accuracy has not been evaluated across different populations. We sought to evaluate the validity of calculated LDL-C by comparing the findings with values acquired by the direct homogeneous technique, utilizing 13 distinct formulae from the literature. This study was a retrospective observational study conducted for a year at SRIHER, Chennai, Tamil Nadu, India. From the total 25 043 patients who had their serum lipid profile tested, 16 314 participants had their fasting blood sugar and fasting lipid profile measured simultaneously, and they were chosen for the research. The de Cordova, Chen, Martin/Hopkins (initial), and Teerakanchana equations correlated well with the direct LDL-C assay. When the dataset was stratified according to triglycerides, the Chen and Martin/Hopkins initial equations had the better measurement of agreement compared to other equations. The Martin/Hopkins initial equation outperformed all the other equations when the whole dataset irrespective of the triglyceride population was considered. Our study suggests that the Martin/Hopkins initial equation outperformed all the other equations and can be used as an alternative to direct LDL-C measurement in a South Indian population.

Intercomparison study between the measurement of LDL cholesterol in the Atellica Solution® analyser and the estimation of LDL cholesterol using the Martin-Hopkins equation

Intercomparison study between the measurement of LDL cholesterol in the Atellica Solution® analyser and the estimation of LDL cholesterol using the Martin-Hopkins equation

Intercomparison study between the measurement of LDL cholesterol in the atellica solution® analyser and the estimation of LDL cholesterol using the friedewald equation

Intercomparison study between the measurement of LDL cholesterol in the atellica solution® analyser and the estimation of LDL cholesterol using the friedewald equation

Integrating Patient-Based Real-Time Quality Control (PBRTQC) in a New Field: Inter-Comparison between Biochemical Instrumentations with LDL-C.

Patient-based real-time quality control (PBRTQC) can be a valuable tool in clinical laboratories due to its cost-effectiveness and constant monitoring. More focus is placed on discovering and improving algorithms that compliment conventional internal control techniques. The practical implementation of PBRTQC with a biochemical instrument comparison is lacking. We aim to evaluate PBRTQC's efficacy and practicality by comparing low-density lipoprotein cholesterol (LDL-C) test results to ensure consistent real-time monitoring across biochemical instrumentations in clinical laboratories. From 1 September 2021 to 30 August 2022, the First Affiliated Hospital of Xi'an Jiaotong University collected data from 158,259 both healthy and diseased patients, including 84,187 male and 74,072 female patients, and examined their LDL-C results. This dataset encompassed a group comprising 50,556 individuals undergoing health examinations, a group comprising 42,472 inpatients (IP), and a group comprising 75,490 outpatients (OP) for the PBRTQC intelligent monitoring platform to conduct daily tests, parameter configuration, program development, real-time execution, and performance validation of the patients' data. Moreover 40 patients' LDL-C levels were assessed using two biochemical analyzers, designated as the reference and comparator instruments. A total of 160 LDL-C results were obtained from 40 both healthy and diseased patients, including 14 OP, 16 IP, and 10 health examination attendees, who were selected to represent LDL-C levels broadly. Two biochemical instruments measured LDL-C measurements from the same individuals to investigate consistency and reproducibility across patient statuses and settings. We employed exponentially weighted moving average (EWMA) and moving median (MM) methods to calculate inter-instrument bias and ensure analytical accuracy. Inter-instrument bias for LDL-C measurements was determined by analyzing fresh serum samples, different concentrations of quality control (QC), and commercialized calibrators, employing both EWMA and MM within two assay systems. The assessment of inter-instrumental bias with five different methods adhered to the external quality assessment standards of the Clinical Laboratory Center of the Health Planning Commission, which mandates a bias within ±15.0%. We calculated inter-instrument comparison bias with each of the five methods based on patient big data. The comparison of fresh serum samples, different concentrations of QC, commercialized calibrators, and EWMA were all in the permissive range, except for MM. MM showed that the bias between two biochemical instruments in the concentration ranges of 1.5 mmoL/L-6.2 mmoL/L exceeded the permissible range. This was mainly due to the small number of specimens, affected by variations among individual patients, leading to increased false alarms and reduced effectiveness in monitoring the consistency of the inter-instrumental results. Moreover, the inter-comparison bias derived from EWMA was less than 3.01%, meeting the 15% range assessment criteria. The bias result for MM was lower than 24.66%, which was much higher than EWMA. Thus, EWMA is better than MM for monitoring inter-instrument comparability. PBRTQC can complement the use of inter-comparison bias between biochemical analyzers. EWMA has comparable inter-instrument comparability monitoring efficacy. The utilization of AI-based PBRTQC enables the automated real-time comparison of test results across different biochemical instruments, leading to a reduction in laboratory operating costs, enhanced work efficiency, and improved QC. This advanced technology facilitates seamless data integration and analysis, ultimately contributing to a more streamlined and efficient laboratory workflow in the biomedical field.