Friedewald-Estimated Versus Directly Measured Low-Density Lipoprotein Cholesterol and Treatment Implications

ObjectivesThe aim of this study was to compare Friedewald-estimated and directly measured low-density lipoprotein cholesterol (LDL-C) values.BackgroundLDL-C is routinely estimated by the Friedewald equation to guide treatment; however, compatibility with direct measurement has received relatively little scrutiny, especially at levels <70 mg/dl now targeted in high-risk patients.MethodsWe examined 1,340,614 U.S. adults who underwent lipid profiling by vertical spin density gradient ultracentrifugation (Atherotech, Birmingham, Alabama) from 2009 to 2011. Following standard practice, Friedewald LDL-C was not estimated if triglyceride levels were ≥400 mg/dl (n = 30,174), yielding 1,310,440 total patients and 191,333 patients with Friedewald LDL-C <70 mg/dl.ResultsPatients were 59 ± 15 years of age and 52% were women. Lipid distributions closely matched those in the National Health and Nutrition Examination Survey. A greater difference in the Friedewald-estimated versus directly measured LDL-C occurred at lower LDL-C and higher triglyceride levels. If the Friedewald-estimated LDL-C was <70 mg/dl, the median directly measured LDL-C was 9.0 mg/dl higher (5th to 95th percentiles, 1.8 to 15.4 mg/dl) when triglyceride levels were 150 to 199 mg/dl and 18.4 mg/dl higher (5th to 95th percentiles, 6.6 to 36.0 mg/dl) when triglyceride levels were 200 to 399 mg/dl. Of patients with a Friedewald-estimated LDL-C <70 mg/dl, 23% had a directly measured LDL-C ≥70 mg/dl (39% if triglyceride levels were concurrently 150 to 199 mg/dl; 59% if triglyceride levels were concurrently 200 to 399 mg/dl).ConclusionsThe Friedewald equation tends to underestimate LDL-C most when accuracy is most crucial. Especially if triglyceride levels are ≥150 mg/dl, Friedewald estimation commonly classifies LDL-C as <70 mg/dl despite directly measured levels ≥70 mg/dl, and therefore additional evaluation is warranted in high-risk patients

Interpretation of a 12-Lead Electrocardiogram by Medical Students: Quantitative Eye-Tracking Approach

BackgroundAccurate interpretation of a 12-lead electrocardiogram (ECG) demands high levels of skill and expertise. Early training in medical school plays an important role in building the ECG interpretation skill. Thus, understanding how medical students perform the task of interpretation is important for improving this skill. ObjectiveWe aimed to use eye tracking as a tool to research how eye fixation can be used to gain a deeper understanding of how medical students interpret ECGs. MethodsIn total, 16 medical students were recruited to interpret 10 different ECGs each. Their eye movements were recorded using an eye tracker. Fixation heatmaps of where the students looked were generated from the collected data set. Statistical analysis was conducted on the fixation count and duration using the Mann-Whitney U test and the Kruskal-Wallis test. ResultsThe average percentage of correct interpretations was 55.63%, with an SD of 4.63%. After analyzing the average fixation duration, we found that medical students study the three lower leads (rhythm strips) the most using a top-down approach: lead II (mean=2727 ms, SD=456), followed by leads V1 (mean=1476 ms, SD=320) and V5 (mean=1301 ms, SD=236). We also found that medical students develop a personal system of interpretation that adapts to the nature and complexity of the diagnosis. In addition, we found that medical students consider some leads as their guiding point toward finding a hint leading to the correct interpretation. ConclusionsThe use of eye tracking successfully provides a quantitative explanation of how medical students learn to interpret a 12-lead ECG

Understanding Cardiology Practitioners’ Interpretations of Electrocardiograms: An Eye-Tracking Study

BACKGROUND: Visual expertise refers to advanced visual skills demonstrated when performing domain-specific visual tasks. Prior research has emphasized the fact that medical experts rely on such perceptual pattern-recognition skills when interpreting medical images, particularly in the field of electrocardiogram (ECG) interpretation. Analyzing and modeling cardiology practitioners’ visual behavior across different levels of expertise in the health care sector is crucial. Namely, understanding such acquirable visual skills may help train less experienced clinicians to interpret ECGs accurately. OBJECTIVE: This study aims to quantify and analyze through the use of eye-tracking technology differences in the visual behavior and methodological practices for different expertise levels of cardiology practitioners such as medical students, cardiology nurses, technicians, fellows, and consultants when interpreting several types of ECGs. METHODS: A total of 63 participants with different levels of clinical expertise took part in an eye-tracking study that consisted of interpreting 10 ECGs with different cardiac abnormalities. A counterbalanced within-subjects design was used with one independent variable consisting of the expertise level of the cardiology practitioners and two dependent variables of eye-tracking metrics (fixations count and fixation revisitations). The eye movements data revealed by specific visual behaviors were analyzed according to the accuracy of interpretation and the frequency with which interpreters visited different parts/leads on a standard 12-lead ECG. In addition, the median and SD in the IQR for the fixations count and the mean and SD for the ECG lead revisitations were calculated. RESULTS: Accuracy of interpretation ranged between 98% among consultants, 87% among fellows, 70% among technicians, 63% among nurses, and finally 52% among medical students. The results of the eye fixations count, and eye fixation revisitations indicate that the less experienced cardiology practitioners need to interpret several ECG leads more carefully before making any decision. However, more experienced cardiology practitioners rely on their skills to recognize the visual signal patterns of different cardiac abnormalities, providing an accurate ECG interpretation. CONCLUSIONS: The results show that visual expertise for ECG interpretation is linked to the practitioner’s role within the health care system and the number of years of practical experience interpreting ECGs. Cardiology practitioners focus on different ECG leads and different waveform abnormalities according to their role in the health care sector and their expertise levels

Total cholesterol/HDL-cholesterol ratio discordance with LDL-cholesterol and non-HDL-cholesterol and incidence of atherosclerotic cardiovascular disease in primary prevention: The ARIC study

Aims: The total cholesterol (TC)/high-density lipoprotein (HDL) cholesterol ratio may carry additional information not available in more commonly used single cholesterol measures. Analysis of discordance between lipid parameters might help assess the impact of such additional information on the risk of atherosclerotic cardiovascular disease. We aimed to investigate the role of the TC/HDL-cholesterol ratio in determining atherosclerotic cardiovascular disease risk when discordant with low-density lipoprotein (LDL) cholesterol and non-HDL-cholesterol.Methods: We studied 14,403 Atherosclerosis Risk in Communities (ARIC) study participants who were free of atherosclerotic cardiovascular disease at baseline. TC/HDL-cholesterol discordance with LDL-cholesterol (estimated by the novel Martin/Hopkins method) and non-HDL-cholesterol was assessed at five visits and determined by being at or above the median for each lipid parameter. We constructed Cox proportional hazard models to estimate the risk for incident atherosclerotic cardiovascular disease events associated with each lipid concordance/discordance category using a time-varying approach.Results: Mean age of participants was 54.1 years, 56% women and 25% black. There were 2634 atherosclerotic cardiovascular disease events over a median (interquartile range) follow-up of 24.2 (16.0-25.4) years. Among individuals with LDL-cholesterol and non-HDL-cholesterol less than the median, 26% and 21% had discordant TC/HDL-cholesterol at or above the median, respectively. These individuals had a 24% (hazard ratio (HR) 1.24, 95% confidence interval (CI) 1.09, 1.41) and 29% (HR 1.29, 95% CI 1.13, 1.46) greater risk of incident atherosclerotic cardiovascular disease, respectively, compared to those with TC/HDL-cholesterol less than the median after multivariable adjustment. In individuals with diabetes with LDL-cholesterol or non-HDL-cholesterol less than the median, discordant TC/HDL-cholesterol at or above the median was more prevalent at 48% and 38%, respectively.Conclusion: Clinically significant discordance exists between TC/HDL-cholesterol, available from the standard lipid profile, and the routinely used non-HDL-cholesterol and LDL-cholesterol. Such discordance may help inform atherosclerotic cardiovascular disease risk management, particularly in individuals with diabetes in whom discordance is more common

Smart wearable devices in cardiovascular care: where we are and how to move forward.

Technological innovations reach deeply into our daily lives and an emerging trend supports the use of commercial smart wearable devices to manage health. In the era of remote, decentralized and increasingly personalized patient care, catalysed by the COVID-19 pandemic, the cardiovascular community must familiarize itself with the wearable technologies on the market and their wide range of clinical applications. In this Review, we highlight the basic engineering principles of common wearable sensors and where they can be error-prone. We also examine the role of these devices in the remote screening and diagnosis of common cardiovascular diseases, such as arrhythmias, and in the management of patients with established cardiovascular conditions, for example, heart failure. To date, challenges such as device accuracy, clinical validity, a lack of standardized regulatory policies and concerns for patient privacy are still hindering the widespread adoption of smart wearable technologies in clinical practice. We present several recommendations to navigate these challenges and propose a simple and practical 'ABCD' guide for clinicians, personalized to their specific practice needs, to accelerate the integration of these devices into the clinical workflow for optimal patient care

LDL-C Targets in Secondary Prevention: How Low Should We Go?

The benefits of lowering low-density lipoprotein cholesterol (LDL-C), mainly using high-intensity statin therapy, and its impact on decreasing the recurrence of atherosclerotic cardiovascular disease (ASCVD) in secondary prevention has been well established. With the advent of non-statin medications, particularly PCSK-9 inhibitors, which can lower LDL-C to very low levels not seen before, it is important to answer some important questions regarding LDL-C lowering and the uses of these medications in clinical practice: how low should we go with LDL-C reduction? Is there a threshold beyond which lower LDL-C is not associated with any benefit and possibly harm? Does the benefit derived from more aggressive LDL-C lowering justify the cost of additional therapies? Our review has found overwhelming evidence to support the conclusion that lower achieved LDL-C levels correlate with a decreased burden of atherosclerosis and better clinical outcomes in secondary prevention. The concern for adverse effects with very low LDL-C levels is not backed by the literature, and side effects appear to be medication-specific. There still remains a question of the cost-effectiveness of some non-statin therapies particularly PCSK9 inhibitors, in spite of recent price decreases, and whether the benefit is worth the cost. It is prudent to always pursue an individualized patient-level approach to LDL-C lowering that considers the patient’s global cardiovascular risk, their side effect profile, and the cost-effectiveness of therapies in order to derive maximal benefit from aggressive lipid lowering.Other Information Published in: Current Cardiovascular Risk Reports License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s12170-019-0619-8</p

Smart wearable devices in cardiovascular care: where we are and how to move forward.

Technological innovations reach deeply into our daily lives and an emerging trend supports the use of commercial smart wearable devices to manage health. In the era of remote, decentralized and increasingly personalized patient care, catalysed by the COVID-19 pandemic, the cardiovascular community must familiarize itself with the wearable technologies on the market and their wide range of clinical applications. In this Review, we highlight the basic engineering principles of common wearable sensors and where they can be error-prone. We also examine the role of these devices in the remote screening and diagnosis of common cardiovascular diseases, such as arrhythmias, and in the management of patients with established cardiovascular conditions, for example, heart failure. To date, challenges such as device accuracy, clinical validity, a lack of standardized regulatory policies and concerns for patient privacy are still hindering the widespread adoption of smart wearable technologies in clinical practice. We present several recommendations to navigate these challenges and propose a simple and practical 'ABCD' guide for clinicians, personalized to their specific practice needs, to accelerate the integration of these devices into the clinical workflow for optimal patient care

Accuracy of low-density lipoprotein cholesterol estimation at very low levels

Abstract Background As the approach to low-density lipoprotein cholesterol (LDL-C) lowering becomes increasingly intensive, accurate assessment of LDL-C at very low levels warrants closer attention in individualized clinical efficacy and safety evaluation. We aimed to assess the accuracy of LDL-C estimation at very low levels by the Friedewald equation, the de facto clinical standard, and compare its accuracy with a novel, big data-derived LDL-C estimate. Methods In 191,333 individuals with Friedewald LDL-C < 70 mg/dL, we compared the accuracy of Friedewald and novel LDL-C values in relation to direct measurements by Vertical Auto Profile ultracentrifugation. We examined differences (estimate minus ultracentrifugation) and classification according to levels initiating additional safety precautions per clinical practice guidelines. Results Friedewald values were less than ultracentrifugation measurement, with a median difference (25th to 75th percentile) of –2.4 (–7.4 to 0.6) at 50–69 mg/dL, –7.0 (–16.2 to –1.2) at 25–39 mg/dL, and –29.0 (–37.4 to –19.6) at < 15 mg/dL. The respective values by novel estimation were –0.1 (–1.5 to 1.3), –1.1 (–2.5 to 0.3), and –2.7 (–4.9 to 0.0) mg/dL. Among those with Friedewald LDL–C < 15, 15 to < 25, and 25 to < 40 mg/dL, the classification was discordantly low in 94.9%, 82.6%, and 59.9% of individuals as compared with 48.3%, 42.4%, and 22.4% by novel estimation. Conclusions Estimation of even lower LDL-C values (by Friedewald and novel methods) is even more inaccurate. More often than not, a Friedewald value < 40 mg/dL is underestimated, which translates into unnecessary safety alarms that could be reduced in half by estimation using our novel method