Data · dataset · 2025
Dataset on the Mediating Role of Insulin Resistance Between Hypertension and NAFLD and Risk Prediction Models: Evidence from Large-Scale Machine Learning and Mediation Analysis
Listed in ScienceDB
This dataset was derived from 280,976 individuals who underwent health examinations at the Health Management Center of the Third Xiangya Hospital, Central South University, between August 2017 and December 2021.
Description
It was used to investigate the mediating role of insulin resistance (IR) in the relationship between hypertension and non-alcoholic fatty liver disease (NAFLD), and to evaluate the predictive value of multiple IR surrogate indices in NAFLD risk modeling.The dataset contains:Figure S1: Correlation matrix heatmaps of IR surrogate indices and NAFLD in hypertensive and non-hypertensive groups;Table S1: Pearson correlation coefficients and significance levels between variables and NAFLD in the hypertensive group;Table S2: Pearson correlation coefficients and significance levels between variables and NAFLD in the non-hypertensive group;Table S3: Baseline characteristics of individuals with and without NAFLD.This dataset provides evidence for exploring the “hypertension–IR–NAFLD” pathway and supports large-scale mediation analysis and machine learning modeling for NAFLD risk prediction.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.xbyxb.00115 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Disease 75% · Medical biochemistry and metabolomics 74% · Tabular 65%
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.xbyxb.00115 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[disease].local:disease:disease | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3205 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |