Evidence mapPaperPMID 38438774Full record

ArticleDigestive diseases and sciences2024

Insulin Resistance/Sensitivity Measures as Screening Indicators of Metabolic-Associated Fatty Liver Disease and Liver Fibrosis.

Mohammad E Khamseh, Mojtaba Malek, Soodeh Jahangiri, Sohrab Nobarani, Azita Hekmatdoost, Marieh Salavatizadeh, Samira Soltanieh, Haleh Chehrehgosha, Hoda Taheri, Zeinab Montazeri and 3 more

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Article in Digestive diseases and sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
7.7field-weighted citation impact, top 2% 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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  7. Identification of pediatric MASLD using insulin resistance indices.JHEP reports : innovation in hepatology · 2025
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  14. ISIFrontiers in medicine · 2025
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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 3 institutions in 2 countries.

Mohammad E KhamsehEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Mojtaba MalekResearch Center for Prevention of Cardiovascular Disease, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Soodeh JahangiriEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Sohrab NobaraniEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Azita HekmatdoostDepartment of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Marieh SalavatizadehDepartment of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Samira SoltaniehDepartment of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Haleh ChehrehgoshaEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Hoda TaheriEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Zeinab MontazeriEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Fereshteh AttaranEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran.
Faramarz Ismail-BeigiDepartment of Medicine, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, USA.
Fariba Alaei-ShahmiriEndocrine Research Center, Institute of Endocrinology and Metabolism, Iran University of Medical Sciences (IUMS), Tehran, Iran. alaeishahmiri.f@iums.ac.ir.ORCID http://orcid.org/0000-0002-6401-8803
Iran University of Medical Sciences · IRNational Nutrition and Food Technology Research Institute · IRUniversity Hospitals of Cleveland · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasures of insulin resistance (IR)/sensitivity (IS) are emerging tools to identify metabolic-associated fatty liver disease (MAFLD). However, the comprehensive assessment of the performance of various indicators is limited. Moreover, the utility of measures of IR/IS in detecting liver fibrosis remains unclear.

aimsTo evaluate the predictive ability of seventeen IR/IS and two beta cell function indices to identify MAFLD and liver fibrosis.

methodsA cross-sectional study was conducted on individuals aged 25-75 years. Transient elastography was used to estimate liver stiffness and controlled attenuation parameter. The following measures were computed: homeostatic model assessment (HOMA/HOMA2) for IR, IS, and beta cell function; QUICKI; Bennett index; glucose/insulin; FIRI; McAuley index; Reynaud index; SPISE index; TyG; TyG-BMI; TyG-WC; TyG-WHtR; TG/HDL; and METS-IR. Subgroup analyses were performed according to age, gender, diabetes status, and body weight.

resultsA total of 644 individuals were included in our analysis. MAFLD and significant liver fibrosis were detected in 320 (49.7%) and 80 (12.4%) of the participants, respectively. All measures of IR/IS identified MAFLD and liver fibrosis. However, TyG-WC, TyG-BMI, and TyG-WHtR were the top three indicators that identified MAFLD. Measures that include insulin level in their mathematical calculation, namely, Raynaud index, HOMA-IR, HOMA 2-IR, FIRI, and QUICKI had the best performance in identifying liver fibrosis in the entire population, as well as among the study subgroups.

conclusionsTyG-WC, TyG-BMI, and TyG-WHtR were the best predictors of MAFLD. Insulin-based measures had better performances in the detection of advanced fibrosis. This was independent of age, gender, obesity, or diabetes status.

Indexed as

Diabetes MellitusInsulin ResistanceLiver DiseasesBiomarkersBlood GlucoseCross-Sectional StudiesGlucoseHumansInsulinLiver CirrhosisTriglyceridesBiomarkersBlood GlucoseGlucoseInsulinTriglyceridesBeta cell functionFatty liverInsulin resistanceInsulin sensitivityLiver fibrosisMAFLD

Identifiers

PMID38438774
OpenAlexW4392383367

What Socratic holds

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Registered trials

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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.