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Record W4403098784 · doi:10.7759/cureus.70768

Understanding Insulin Resistance in NAFLD: A Systematic Review and Meta-Analysis Focused on HOMA-IR in South Asians

2024· review· en· W4403098784 on OpenAlexaboutno aff
Margeyi M. Mehta, Jigish Shah, Urvish Joshi

Bibliographic record

VenueCureus · 2024
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInsulin resistanceMeta-analysisInternal medicineResistance (ecology)Insulin

Abstract

fetched live from OpenAlex

Non-alcoholic fatty liver disease (NAFLD), a metabolic condition, is becoming increasingly common in South Asia. While its clinical diagnosis primarily relies on sonography and altered hepatic biomarkers, the significance of non-hepatic indicators, such as Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), in relation to NAFLD requires further examination in the South Asian population due to ethnic differences in these markers. This study examined the relationship between insulin resistance, quantified using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), and NAFLD, along with other non-hepatic biomarkers. A thorough literature review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched the PubMed, Embase, and Google Scholar databases, yielding 287 articles. After applying the selection criteria and screening, 22 studies were selected for inclusion in the analysis. We extracted and meta-analyzed the data on HOMA-IR in patients with NAFLD, along with other relevant parameters. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of observational studies, whereas the RoB 2.0 tool was employed for randomized controlled trials (RCTs). The systematic review uncovered that individuals with NAFLD demonstrated statistically significant elevations in HOMA-IR levels, with a weighted mean difference (WMD) of 1.28 (95% confidence interval (CI): 1.00-1.58, I² = 98%, p < 0.0001) when compared to healthy subjects. Additionally, NAFLD patients showed markedly higher fasting blood glucose (FBG) levels, with a combined mean difference of 15.64 mg/dL (95% CI: 11.03-20.25, I² = 92%, p < 0.0001). The analysis also revealed increased triglyceride levels in NAFLD patients, with a pooled mean difference of 42.49 mg/dL (95% CI: 29.07-55.91, I² = 97%, p < 0.0001), and elevated C-reactive protein (CRP) levels, with a pooled mean difference of 2.17 mg/L (95% CI: 2.01-2.33, I² = 23%, p < 0.0001). Interestingly, subgroup analysis indicated that obese NAFLD patients exhibited significantly higher HOMA-IR levels than their non-obese counterparts, with a weighted mean difference of 5.85 (95% CI: 4.88-6.81, I² = 0%, p < 0.0001). Variations in study methodology, diagnostic techniques, and subject demographics were identified as sources of heterogeneity. The analysis found little evidence of publication bias, which lends credibility to the results. In South Asian populations, higher HOMA-IR, triglyceride-glucose (TyG) index, and CRP levels are associated with an increased risk of NAFLD. To improve the understanding and treatment of NAFLD in this specific demographic group, it is necessary to establish uniform diagnostic criteria and conduct additional studies, particularly RCTs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.032
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.033
Bibliometrics0.0100.011
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.278
GPT teacher head0.382
Teacher spread0.104 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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