Evidence map›Paper›PMID 38863519›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2024

Association Between the Hepatic Steatosis Index and Risk of Incident Type 2 Diabetes Mellitus in the Normoglycemic Population:A Longitudinal Prospective Study in Japan.

Rite Si, Jingyi Xiao, Keyang Zheng, Yuzhe Yin, Yamin Li

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Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

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0cells of the map it votes in
13citing 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

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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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

5 authors.

Rite Si *Emergency Intensive Care Unit, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Jingyi Xiao *Sixth Clinical Medical School, Capital Medical University, Beijing, People's Republic of China.
Keyang ZhengCenter of Hypertension, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Yuzhe YinSixth Clinical Medical School, Capital Medical University, Beijing, People's Republic of China.
Yamin LiEmergency Intensive Care Unit, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The Hepatic Steatosis Index (HSI) is a reliable predictor of non-alcoholic fatty liver disease (NAFLD), which can increase the risk of type 2 diabetes mellitus (T2DM). However, limited research has directly predicted HSI's association with T2DM occurrence at normal blood glucose levels. Hence, this study aimed to assess the link between baseline HSI and T2DM development under euglycemic conditions while also exploring potential sex differences. Methods: Using data from the NAGALA cohort study, a Cox regression model analyzed the relationship between HSI and T2DM risk, calculating hazard ratios (HR) and 95% confidence intervals (CI). Subgroup analyses were conducted to investigate factors influencing HSI's prediction of incident T2DM. Results: During a mean 6.1-year follow-up, 238 individuals (1.65% of participants) developed T2DM. After adjusting for age, ethanol consumption, smoking status, SBP, DBP, TG, and TC, HSI showed a significant association with incident T2DM in individuals with normal glucose levels, consistent across sexes. Compared to the lowest quartile group (Q1), the HR and 95% CI for Q2, Q3, and Q4 were 1.09 (0.61, 1.93), 1.16 (0.68, 1.98), and 3.30 (2.04, 5.33), respectively (P for trend < 0.001). Subgroup analysis indicated that elevated HSI significantly increased the risk of incident T2DM in individuals with normal TG levels (P for interaction = 0.0170). Conclusion: This study highlights the significant association between elevated HSI levels and the likelihood of developing incident T2DM in individuals with normal glucose levels. Furthermore, it offers a simple and valuable screening tool for predicting T2DM.

Indexed as

hepatic steatosis indexlongitudinal studyNon-alcoholic fatty liver diseaserisk predictionType 2 Diabetes Mellitus

Identifiers

PMID38863519
PMCPMC11166155

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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 OpenQuestion graph.