Evidence map›Paper›PMID 34242916›Full record

ArticleClinical nutrition (Edinburgh, Scotland)2021

Who would benefit most from postprandial lipid screening?

Christina M Sciarrillo, Nicholas A Koemel, Bryant H Keirns, Nile F Banks, Emily M Rogers, Sara K Rosenkranz, Stephanie P Kurti, Nathaniel D M Jenkins, Sam R Emerson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical nutrition (Edinburgh, Scotland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

9 authors.

Christina M SciarrilloDepartment of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA. Electronic address: christina.sciarrillo@okstate.edu.
Nicholas A KoemelDepartment of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Boden Collaboration for Obesity, Nutrition, Exercise, and Eating Disorders, University of Sydney, Sydney, Australia; Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
Bryant H KeirnsDepartment of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA.
Nile F BanksDepartment of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA.
Emily M RogersDepartment of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA.
Sara K RosenkranzDepartment of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA.
Stephanie P KurtiDepartment of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA; Department of Kinesiology, James Madison University, Harrisonburg, VA, USA.
Nathaniel D M JenkinsDepartment of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Performance, Oklahoma State University, Stillwater, OK, USA; Department of Health and Human Physiology, University of Iowa, Iowa City, IA, USA.
Sam R EmersonDepartment of Nutritional Sciences, Oklahoma State University, Stillwater, OK, USA; Department of Food, Nutrition, Dietetics and Health, Kansas State University, Manhattan, KS, USA.

Funding

NHLBI NIH HHS L30 HL149066
6 · The paper itself

Abstract

BACKGROUND &

aimsIndividuals with fasting triglycerides (TG) <150 mg/dL can experience a deleterious postprandial TG response ≥220 mg/dL to a high-fat meal (HFM). The purpose of this study was to identify individuals based on fasting TG that would benefit most from additional postprandial screening.

methodsWe conducted a secondary analysis of 7 studies from our laboratories featuring 156 disease-free participants (64 M, 92 F; age 18-70 years; BMI 18.5-30 kg/m

resultsIn Method 1, 90% of individuals with fasting TG >130 mg/dL (>1.50 mmol/L) exhibited PPTG ≥220 mg/dL (≥2.50 mmol/L), while 100% of individuals with fasting TG <66 mg/dL (0.75 mmol/L) had PPTG that did not exceed 220 mg/dL (2.50 mmol/L). In Method 2, when sensitivity was ≈95%, the corresponding fasting TG concentration was 70 mg/dL (0.79 mmol/L). When specificity was ≈95%, the corresponding fasting TG concentration was 114 mg/dL (1.29 mmol/L). Based on methods 1 and 2, there was a moderate positive association (r = 0.37, p < 0.004) between fasting and PPTG for individuals with fasting TG between 70 and 130 mg/dL (0.79-1.50 mmol/L), in which 24% exhibited PPTG ≥220 mg/dL (≥2.50 mmol/L) while 76% did not.

conclusionsPostprandial TG testing is likely most useful for individuals with fasting TG concentrations between 70 and 130 mg/dL (0.79-1.50 mmol/L). Outside of this range, postprandial TG responses are largely predictable. Establishing a specific patient group for which postprandial TG testing is most useful may lead to earlier risk detection in these individuals.

Indexed as

Postprandial PeriodAdolescentAdultAgedFastingFemaleHealthy VolunteersHeart Disease Risk FactorsHumansHypertriglyceridemiaMaleMiddle AgedPredictive Value of TestsRisk AssessmentSensitivity and SpecificityTriglyceridesTriglyceridesAtherosclerosisCardiovascular diseasePostprandial periodRisk assessmentTriglycerides

Identifiers

PMID34242916
PMCPMC10198766

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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 OpenQuestion graph.