A Tale of Two Approaches

Correlations between coagulation abnormalities and inflammatory markers in trauma-induced coagulopathy

Introduction

In multiple trauma patients, the occurrence of trauma-induced coagulopathy (TIC) is closely associated with tissue damage and coagulation function abnormalities in the pathophysiological process.

Methods

This study established a multiple trauma and shock model in Sprague-Dawley (SD) rats and comprehensively utilized histological staining and radiographic imaging techniques to observe injuries in the intestine, liver, skeletal muscles, and bones. Monitoring activated partial thromboplastin time (APTT), platelet (PLT) count, respiratory rate, blood pressure, and other physiological indicators revealed time-dependent alterations in coagulation function and physiological indicators. Enzyme-linked immunosorbent assay (ELISA) measurements of inflammatory factors Tumor Necrosis Factor-alpha (TNF-α), Interleukin-6 (IL-6) and vascular endothelial injury marker (Syndecan-1) were also conducted.

Results

Experimental results demonstrated significant changes in tissue structure after multiple traumas, although widespread necrosis or hemorrhagic lesions were not observed. There were time-dependent alterations in coagulation function and physiological indicators. ELISA measurements showed a strong positive correlation between the significant decrease in PLT count and the increase in TNF-α and IL-6 concentrations.

Discussion

The study provides crucial information for the early diagnosis and treatment of TIC. The findings suggest that structured monitoring of coagulation and inflammatory indicators can help in understanding the pathophysiological changes and aid in the management of TIC in multiple trauma patients.

Assessing Performance of Martins's and Sampson's Formulae for Calculation of LDL-C in Indian Population: A Single Center Retrospective Study

Various formulae had been derived to calculate the LDL-C from other lipid profile parameters to supplant the need for direct estimation. Martin's, Sampson's, and Cordova's formulae are recently derived formulae for calculating LDL-C. However, no study has been undertaken till now to verify the newer formulae viz. Martins's and Sampson's in Indian population. The retrospective cross-sectional study was carried out after obtaining approval from the Institutional Ethics Committee on human subject research. The lipid profile data were collected for a period of 17 months from January 2020 to May 2021. The formulae proposed by Friedewald, Cordova, Anandaraja, Martin, and Sampson were used to assess calculated LDL-C. Intraclass correlations were performed to assess the effectiveness of each formula when compared with direct estimation. In our study, we observed that LDL-C calculated using Martin was observed to be closer to that of direct estimation. The bias observed was lowest for Martin's formulae, followed by Sampson's. Intraclass correlation analysis for absolute agreement demonstrated Cordova, Martin, and Sampson to have an average ICC > 0.9, with Martin, and Sampson having a p value < 0.05. Martin fared superior to other formulae in intraclass correlation in patients with LDL > 70. In patients with TG below 200 mg/dL, Martin, and Sampson had a significant correlation with comparable average ICC. However, in patients with TG > 300 mg/dL, Cordova appears to fare better than all other formulae. Our study demonstrated a distinctly superior performance of Martin's formula over Friedewald's formula in the Indian patient population.

Calculated LDL-cholesterol: comparability of the extended Martin/Hopkins, Sampson/NIH, Friedewald and four other equations in South African patients

AIMS

The reference method for low-density lipoprotein-cholesterol (LDL-C) is ultracentrifugation. However, this is unsuitable for routine use and therefore direct LDL-C assays and predictive equations are used. In this study, we compared the Friedewald, extended Martin/Hopkins, Sampson/NIH and four other equations to a direct assay.

METHODS

We analysed 44 194 lipid profiles from a mixed South African population. The LDL-C predictive equations were compared with direct LDL-C assay and analysed using non-parametric statistics and error grid analysis.

RESULTS

Both the extended Martin/Hopkins and Sampson/NIH equations displayed the best correlation with direct LDL-C in terms of desirable bias and total allowable error. The direct LDL-C assay classified 13.9% of patients in the low LDL-C (1.0-1.8 mmol/L) category, in comparison to the extended Martin/Hopkins equation (13.4%), the Sampson equation (14.6%) and the Friedewald equation (16.0%). The Sampson/NIH was least biased in the low LDL-C category (<1.8 mmol/L) and produced the least overall clinically relevant errors compared with the extended Martin/Hopkins and Friedewald equations in the low-LDL-C category.

CONCLUSIONS

Our findings suggest only a marginal difference between the extended Martin/Hopkins equation and the Sampson/NIH equation with the use of the Beckman Coulter DxC800 analyser in this population. The results favour the implementation of the Sampson/NIH equation when the Beckman Coulter DxC analyser is used, but the extended Martin/Hopkins may also be safely implemented. Both of these equations performed significantly better than the Friedewald equation. We recommend that patients be monitored using one of these methods and that each laboratory perform its own validation of either equation to ensure continuation and accuracy, and to prevent between-method variation.

Assessment of three equations to calculate plasma LDL cholesterol concentration in fasting and non-fasting hypertriglyceridemic patients

OBJECTIVES

Low-density lipoprotein cholesterol (LDL-C) concentration was calculated for many years using the Friedewald equation, but those from Sampson and extended-Martin-Hopkins perform differently. Their accuracy in fasting hypertriglyceridemia and non-fasting state were compared and the clinical impact of implementing these equations on risk classification and on the setting of lipid treatment goals was assessed.

METHODS

Seven thousand six standard lipid profiles and LDL-C concentrations measured after ultracentrifugation (uLDL-C) were retrospectively included. uLDL-C were compared to calculated LDL-C in terms of correlation, root mean square error, residual error, mean absolute deviations and cardiovascular stratification.

RESULTS

In fasting state (n=5,826), Sampson equation was the most accurate, exhibited the highest percentage of residual error lower than 0.13 mmol/L (67 vs. 57 % and 63 % using Friedewald, or extended-Martin-Hopkins equations respectively) and the lowest misclassification rate. However, the superiority of this equation was less pronounced when triglyceride concentration (TG) <4.5 mmol/L were considered. In post-prandial state (n=1,180), extended-Martin-Hopkins was the most accurate equation, exhibited the highest percentage of residual error lower than 0.13 mmol/L (73 vs. 39 % and 57 % using Friedewald and Sampson equation respectively). Overall, the negative bias with Sampson equation may lead to undertreatment. Conversely, a positive bias was observed with extended Martin-Hopkins.

CONCLUSIONS

None of the equations tested are accurate when TG>4.52 mmol/L. When TG<4.52 mmol/L both Sampson and Martin-Hopkins equations performed better than Friedewald. The switch to one or the other should take in account their limitations, their ease of implementation into the lab software and the proportion of non-fasting patients.

Assessing the Practical Differences in LDL-C Estimates Calculated by Friedewald, Martin/Hopkins, or NIH Equation 2: An Observation Cross-Sectional Study

Objective

Low-density lipoprotein-cholesterol (LDL-C) remains a clinically important cholesterol target in primary prevention of atherosclerotic cardiovascular disease. The present study aimed to assess the practical differences among three equations utilized for the estimation of LDL-C: the Friedewald, the Martin/Hopkins, and the NIH equation 2.

Methods

Blood lipid measurements from 4,556 noninstitutionalized participants, aged 12 to 80, were obtained from the 2017-2020 National Health and Nutrition Examination Survey study. We 1) assessed the differences between three calculated LDL-C estimates, 2) examined the correlations between LDL-C estimates using correlation coefficients and regression, and 3) investigated the degree of agreement in classifying individuals into the LDL-C category using weighted Kappa and percentage of agreement.

Results

The differences in LDL-C estimates between equations varied by sex and triglyceride levels (p<0.001). Overall, the mean of absolute differences between Friedewald and Martin/Hopkins was 3.17 mg/dL (median=2.0, 95% confidence interval [CI] [3.07-3.27]). The mean of absolute differences between Friedewald and NIH Equation 2 was 2.08 mg/dL (median=2.0, 95% CI [2.03-2.14]). Friedewald correlated highly with Martin/Hopkins (r=0.991, rho=0.989) and NIH Equation 2 (r=0.998, rho=0.997). Cohen's weighted Kappa=0.92 between Friedewald and Martin/Hopkins, and 0.95 between Friedewald and NIH equation 2. The percentage of agreement in classifying individuals into the same LDL-C category was 93.0% between Friedewald and Martin/Hopkins, and 95.4% between Friedewald and NIH equation 2.

Conclusion

Understanding the practical differences in LDL-C calculations can be helpful in facilitating decision-making during a paradigm shift.

Performance of equations for calculated LDL-C in hypertriglyceridaemia: which one correlates best with directly measured LDL-C?

BACKGROUND

The gold standard for measuring LDL-C is impractical and direct measurements have numerous shortcomings. Older predictive equations are used only with triglycerides (TG's) below 4.52mmol/L. We evaluated the newer equations validated for use in hypertriglyceridaemia by comparison with direct LDL-C.

MATERIALS AND METHODS

Datasets from two platforms (Abbott Architect and Roche Cobas) comprised of a large cohort of 64765 individuals were used to compare the Sampson-National Institutes of Health 2 (S-NIH2) and Extended Martin-Hopkins (E-MH) equations for LDL-C with direct LDL-C (dLDL-C) assays.

RESULTS

With TG's of 4.52-9.04 mmol/L the S-NIH2 equation tended to calculate lower values than measured by dLDL-C and the E-MH equation calculated higher values. Both equations correlated better with the dLDL-C measured on Abbott than Roche with the E-MH equation having more values falling within acceptable concordance levels on both platforms.

CONCLUSION

The E-MH equation correlates better with dLDL-C than the S-NIH2 on both platforms with TG levels up to 9.04mmol/L. With hypertriglyceridaemia, the E-MH equation is less likely than the S-NIH2 equation to underestimate LDL-C when compared to the dLDL-C and will be less likely to underdiagnose patients with LDL-C levels requiring treatment according to current guidelines.