Evidence map›Paper›PMID 28427464›Full record

ArticleBMC medicine2017

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

Renato Quispe, Aditya Hendrani, Mohamed B Elshazly, Erin D Michos, John W McEvoy, Michael J Blaha, Maciej Banach, Krishnaji R Kulkarni, Peter P Toth, Josef Coresh and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.2field-weighted citation impact, top 4% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 46 citations in OpenAlex.

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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

13 authors at 7 institutions in 2 countries.

Renato QuispeCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA. jquispe1@jhmi.edu.
Aditya HendraniDepartment of Medicine, Medstar Good Samaritan/Union Memorial Hospital, Baltimore, MD, USA.
Mohamed B ElshazlyDepartment of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA.
Erin D MichosCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
John W McEvoyCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Michael J BlahaCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Maciej BanachDepartment of Hypertension, Chair of Nephrology and Hypertension, Medical University of Lodz, Lodz, Poland.
Krishnaji R KulkarniAtherotech Diagnostics Laboratory, Birmingham, AL, USA.
Peter P TothCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Josef CoreshWelch Center for Prevention, Epidemiology, and Clinical Research, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Roger S BlumenthalCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Steven R JonesCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Seth S MartinCiccarone Center for the Prevention of Heart Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Carnegie 591, Baltimore, MD, 21287, USA.
Johns Hopkins Medicine · USJohns Hopkins University · USAC Diagnostics (United States) · USCGH Medical Center · USCleveland Clinic · USMedical University of Lodz · PLMedStar Union Memorial Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs 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.

methodsIn 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.

resultsFriedewald 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.

conclusionsEstimation 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.

Indexed as

Cholesterol, LDLDatabases, FactualFemaleHematologic TestsHumansMaleNutrition SurveysTriglyceridesUltracentrifugationCholesterol, LDLTriglyceridesAccuracyClinical decision makingFriedewald estimationLow-density lipoprotein cholesterolNovel methodVery low

Identifiers

PMID28427464
PMCPMC5399386
OpenAlexW2607417681

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.