Evidence map›Paper›PMID 22511259›Full record

ArticleDiabetes care2012

Defining insulin resistance from hyperinsulinemic-euglycemic clamps.

Charmaine S Tam, Wenting Xie, William D Johnson, William T Cefalu, Leanne M Redman, Eric Ravussin

3 registry-linked trialsAbstract read
In one paragraph

Article in Diabetes care, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 218 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
218citing papers in PubMed, 7 pooled it
–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.

NCT05478707 phase2recruitingstarted 2023, after this paper: background citation

Therapeutic Strategies for Microvascular Dysfunction in Type 1 Diabetes

Ran2023Enrolled47Registered outcomes5Posted comparisons0ConditionsDiabetes Mellitus, Type 1, Endothelial DysfunctionArmsDulaglutide, Placebo
Open the trial in the graph
NCT04730882 completednot on this mapstarted 2021, after this paper: background citation

Effect of Postprandial Hyperglycemia on Vasculature in Type 1 Diabetes and Healthy Adults

TypeobservationalSponsorUniversity of VirginiaRan2021 to 2024Enrolled36ConditionsType 1 Diabetes, Hyperglycemia, PostprandialArmsMixed Meal
NCT06424652 nacompletednot on this mapstarted 2024, after this paper: background citation

Effect of Physiologic Insulin Administration on Cognition

TypeinterventionalSponsorPennington Biomedical Research CenterRan2024 to 2025Enrolled1ConditionsAlzheimer DiseaseArmsBlood draws, Hyperinsulinemic Euglycemic Clamp Technique Insulin Sensitivity test, Resting Metabolic Rate (RMR)
3 · Its place in the literature

Who cites it

218 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  9. Optimizing measures of insulin-regulated lipolysis in humans.American journal of physiology. Endocrinology and metabolism · 2025
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158 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Charmaine S TamPennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
Wenting Xie
William D Johnson
William T Cefalu
Leanne M Redman
Eric Ravussin

Funding

Research BaseP30DK072476 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI ROBERT A KESTERSON · 2005 to 2026
$26.5M
Fat Cell Size, Overfeeding & Ectopic FatR01DK060412 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI RAVUSSIN, ERIC · 2001 to 2011
$5.4M
Expecting Success: Personalized management of body weight during pregnancyU01DK094418 · NIDDK · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI REDMAN, LEANNE MAREE · 2011 to 2015
$2.8M
Effects of weight and insulin sensitivity on reproductive function in PCOSR00HD060762 · NICHD · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · PI REDMAN, LEANNE MAREE · 2011 to 2013
$717k
NICHD NIH HHS R00 HD060762NICHD NIH HHS R00HD060762NIDDK NIH HHS P30 DK072476NIDDK NIH HHS P30DK072476NIDDK NIH HHS R01 DK060412NIDDK NIH HHS R01DK060412NIDDK NIH HHS U01 DK094418NIDDK NIH HHS U01DK094418
6 · The paper itself

Abstract

objectiveThis study was designed to determine a cutoff point for identifying insulin resistance from hyperinsulinemic-euglycemic clamp studies performed at 120 mU/m(2)·min in a white population and to generate equations from routinely measured clinic and blood variables for predicting clamp-derived glucose disposal rate (GDR), i.e., insulin sensitivity. RESEARCH DESIGN AND

methodsWe assembled data from hyperinsulinemic-euglycemic clamps (120 mU/m(2)·min insulin dose) performed at the Pennington Biomedical Research Center between 2001 and 2011. Subjects were divided into subjects with diabetes (n = 51) and subjects without diabetes (n = 116) by self-report and/or fasting glucose ≥126 mg/dL.

resultsWe found that 75% of individuals with a GDR <5.6 mg/kg fat-free mass (FFM) + 17.7·min were truly insulin resistant. Cutoff values for GDRs normalized for body weight, body surface area, or FFM were 4.9 mg/kg·min, 212.2 mg/m(2)·min, and 7.3 mg/kgFFM·min, respectively. Next, we used classification tree models to predict GDR from routinely measured clinical and biochemical variables. We found that individual insulin resistance could be estimated with good sensitivity (89%) and specificity (67%) from the homeostasis model assessment of insulin resistance (HOMA-IR) >5.9 or 2.8< HOMA-IR <5.9 with HDL <51 mg/dL.

conclusionsWe developed a cutoff for defining insulin resistance from hyperinsulinemic-euglycemic clamps. Moreover, we now provide classification trees for predicting insulin resistance from routinely measured clinical and biochemical markers. These findings extend the clamp from a research tool to providing a clinically meaningful message for participants in research studies, potentially providing greater opportunity for earlier recognition of insulin resistance.

Indexed as

InsulinInsulin ResistanceAdultAgedBody Mass IndexDecision TreesGlucose Clamp TechniqueHumansMiddle AgedModels, BiologicalReference ValuesInsulin

Identifiers

PMID22511259
PMCPMC3379600

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.