Evidence mapPaperPMID 34709388Full record

ArticleJAMA network open2021

Comparison of Methods to Estimate Low-Density Lipoprotein Cholesterol in Patients With High Triglyceride Levels.

Aparna Sajja, Jihwan Park, Vasanth Sathiyakumar, Bibin Varghese, Vincent A Pallazola, Francoise A Marvel, Krishnaji Kulkarni, Alagarraju Muthukumar, Parag H Joshi, Eugenia Gianos and 11 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01698489 (The Very Large Database of Lipids), which is not on this map. Cited by 49 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 2 pooled it
14.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01698489 active not recruitingnot on this map

The Very Large Database of Lipids (VLDL): A Clinical Laboratory Big Data Project

TypeobservationalSponsorJohns Hopkins UniversityRan2006 to 2030Enrolled5,051,467ConditionsLipid Disorders and Lipid Measurement
3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 2 syntheses or guidelines pooled it, 109 citations in OpenAlex.

  1. Remnant cholesterol and two decades risk of incident hypertension: a prospective cohort study and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors at 9 institutions in 2 countries.

Aparna SajjaCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Jihwan ParkDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Vasanth SathiyakumarCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Bibin VargheseCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Vincent A PallazolaCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Francoise A MarvelCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Krishnaji KulkarniVAP Diagnostics Lab, Birmingham, Alabama.
Alagarraju MuthukumarDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas.
Parag H JoshiDivision of Cardiology, Department of Internal Medicine, University of Texas /Southwestern Medical Center, Dallas.
Eugenia GianosDepartment of Cardiology, North Shore University Hospital, Northwell Health, Zucker School of Medicine, New York, New York.
Benjamin HirshDepartment of Cardiology, North Shore University Hospital, Northwell Health, Zucker School of Medicine, New York, New York.
Guy MintzDepartment of Cardiology, North Shore University Hospital, Northwell Health, Zucker School of Medicine, New York, New York.
Anne GoldbergDivision of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine in St Louis, St Louis, Missouri.
Pamela B MorrisDepartment of Cardiology, Medical University of South Carolina, Columbia.
Garima SharmaCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Roger S BlumenthalCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Erin D MichosCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Wendy S PostCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Mohamed B ElshazlyCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Steven R JonesCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Seth S MartinCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Johns Hopkins University · USJohns Hopkins Medicine · USNorthwell Health · USThe University of Texas Southwestern Medical Center · USDiagnostics Research Group · USMedical University of South Carolina · USNorth Shore University Hospital · USWashington University in St. Louis · USWeill Cornell Medical College in Qatar · QA

Funding

NIDDK NIH HHS R01 DK084725
6 · The paper itself

Abstract

Importance: Low-density lipoprotein cholesterol (LDL-C) is typically estimated with the Friedewald or Martin/Hopkins equation; however, if triglyceride levels are 400 mg/dL or greater, laboratories reflexively perform direct LDL-C (dLDL-C) measurement. The use of direct chemical LDL-C assays and estimation of LDL-C via the National Institutes of Health Sampson equation are not well validated, and data on the accuracy of LDL-C estimation at higher triglyceride levels are limited. Objective: To compare an extended Martin/Hopkins equation for triglyceride values of 400 to 799 mg/dL with the Friedewald and Sampson equations. Design, Setting, and Participants: This cross-sectional study evaluated consecutive patients at clinical sites across the US with patient lipid distributions representative of the US population in the Very Large Database of Lipids from January 1, 2006, to December 31, 2015, with triglyceride levels of 400 to 799 mg/dL. Data analysis was performed from November 9, 2020, to March 23, 2021. Main Outcomes and Measures: Accuracy in LDL-C classification according to guideline-based categories and absolute errors between estimated LDL-C and dLDL-C levels. Patients were randomly assigned 2:1 to derivation and validation data sets. Levels of dLDL-C were measured by vertical spin-density gradient ultracentrifugation. The LDL-C levels were estimated using the Friedewald method, with a fixed ratio of triglycerides to very low-density lipoprotein cholesterol (VLDL-C ratio of 5:1), extended Martin/Hopkins equation with a flexible ratio, and Sampson equation with VLDL-C estimation by multiple least-squares regression. Results: A total of 111 939 patients (mean [SD] age, 52 [13] years; 65.0% male) with triglyceride levels of 400 to 799 mg/dL were included, representing 2.2% of 5 081 680 patients in the database. Across all individual guideline LDL-C classes (<40, 40-69, 70-99, 100-129, 130-159, 160-189, and ≥190), estimation of LDL-C by the extended Martin/Hopkins equation was most accurate (62.1%) compared with the Friedewald (19.3%) and Sampson (40.4%) equations. In classifying LDL-C levels less than 70 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (67.3%) compared with Friedewald (5.1%) and Sampson (26.4%) equations. In addition, for classifying LDL-C levels less than 40 mg/dL across all triglyceride strata, the extended Martin/Hopkins equation was most accurate (57.2%) compared with the Friedewald (4.3%) and Sampson (14.4%) equations. However, considerable underclassification of LDL-C occurred. The magnitude of error between the Martin/Hopkins equation estimation and dLDL-C was also smaller: at LDL-C levels less than 40 mg/dL, 2.7% of patients had 30 mg/dL or greater differences between dLDL-C and estimated LDL-C using the Martin/Hopkins equation compared with the Friedewald (92.5%) and Sampson (38.7%) equations. Conclusions and Relevance: In this cross-sectional study, the extended Martin/Hopkins equation offered greater LDL-C accuracy compared with the Friedewald and Sampson equations in patients with triglyceride levels of 400 to 799 mg/dL. However, regardless of method used, caution is advised with LDL-C estimation in this triglyceride range.

Indexed as

AdultAgedCohort StudiesCross-Sectional StudiesFemaleHumansHyperlipidemiasLipoproteins, LDLMaleMiddle AgedStatistics as TopicTriglyceridesUnited StatesLipoproteins, LDLTriglycerides

Identifiers

PMID34709388
PMCPMC8554644
OpenAlexW3209697344

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.