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[Display omitted] • Enzymatic assays for directly measuring LDL-C have numerous shortcomings in terms of costing and accuracy, limiting the justification of their use over predictive equations. • LDL-C predictive equations are affected by choice of measurement platform. • Martin-Hopkins equation for predicting LDL-C shows the best correlation with directly measured LDL-C in uncontrolled adult diabetics. • Martin-Hopkins equation for predicting LDL-C can potentially be used as a safe alternative to directly measured LDL-C as a screening tool for paediatric dyslipidaemia. The gold standard for measuring LDL-C is impractical for routine use while direct measurements have numerous shortcomings. This study investigated the correlation of predictive equations with currently used enzymatic assays in populations where these have historically proven unreliable to determine whether equations may be used interchangeably. No reference measure was available for comparison in this study. We examined two analytical datasets from different platforms to evaluate the correlation of predictive equations for LDL-C (Friedewald, Sampson-NIH2, Martin-Hopkins, Extended Martin-Hopkins, Hattori and Anandaraja) with direct LDL-C assays in a large paediatric (n = 7598) and an adult cohort with uncontrolled diabetes (n = 57165). Non-parametric statistics were used for comparison. In the paediatric cohort, the Sampson-NIH2 equation correlated best with the direct LDL-C assays with the most values falling within desirable bias (35.9–44%) and TE a (68.6–72.9%) and the lowest RMSE (0.5904–0.6138) across platforms, but tended to underestimate LDL-C levels. The Martin-Hopkins equation is less likely to underestimate these values. In diabetes, the Martin-Hopkins equation correlated the best with values falling within acceptable bias (40.2–50.5%) and TE a (75–80.6%). In hypertriglyceridaemia the Extended Martin-Hopkins equation correlates best with the direct LDL-C assays. Different measurement platforms influence the results of predictive equations and directly measured LDL-C. We propose utilising the Martin-Hopkins equation as an alternative to dLDL-C assays in adults with diabetes and for screening purposes in paediatric populations to avoid underestimating cardiovascular risk. [ABSTRACT FROM AUTHOR]

• LDL-C predictive equations, especially the Friedewald,are affected by hypertriglyceridaemia. • LDL-C predictive equations are also affected by choice of measurement platform. • Abbott and Roche Cobas direct LDL Cholesterol (d-LDLC) was assessed. • In hypertriglyceridaemia, the e-MH correlates better with dLDL-C than the S-NIH2 equation. 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 4.52 mmol/L. We evaluated the newer equations validated for use in hypertriglyceridaemia by comparison with direct LDL-C. Datasets from two platforms (Abbott Architect and Roche Cobas) comprised of a large cohort of 64,765 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. 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. The E-MH equation correlates better with dLDL-C than the S-NIH2 on both platforms with TG levels up to 9.04 mmol/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. [ABSTRACT FROM AUTHOR]

Background: Concussions are an ever present risk for many sports. Underlying emotional disturbances and drowsiness are associated with worse post-concussion symptom scores. Yet, not study has examined associations of both emotional disturbances and drowsiness on concussion severity and symptomology. Objectives: Examine the associations between baseline sleepiness, emotional complaints, and concussion risk and symptom severity in adolescent athletes. Methods: A cohort of 626 adolescent athletes underwent baseline/pre-season concussion screening. Those who experienced a physician diagnosed concussion underwent follow up concussion symptomology assessment. Over 90% of players were seen within two weeks of the concussion incident. Linear regression examined for associations between concussion symptom scores and baseline drowsiness and baseline emotional symptoms. Logistic regression examined for association between each symptom and baseline drowsiness and baseline emotional symptoms. Results: Of the 626 athletes that underwent baseline testing, 292 experienced a concussion. Of those 292 athletes, 174 (59.6%) reported baseline drowsiness and 183 (62.7%) baseline emotional symptoms. Baseline drowsiness and emotional complaints were associated with a 2.6 (95% confidence interval = 1.9 to 3.6) and 2.8 (95% confidence interval = 2.0 to 3.9) times greater odds of sustaining a concussion respectively. Increased symptomology after concussion was associated with both baseline drowsiness (unstandardised b = 4.6, p < 0.01) and baseline emotional complaints (unstandardised b = 6.0, p < 0.01). Conclusion: Preseason drowsiness and emotional complaints in adolescent athletes are associated with higher risk of adverse clinical outcomes following concussion. Therefore, clinicians and coaches should be aware, and properly screen, for sleep and emotional problems as part of pre-season/baseline health screening. [ABSTRACT FROM AUTHOR]