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Record W4413799097 · doi:10.3389/fnins.2025.1620118

A high triglyceride-glucose index correlates with cognitive impairment in Parkinson’s disease: a cross-sectional study

2025· article· en· W4413799097 on OpenAlexaboutno aff
Yongqing Cheng, Xin Wang, Yingchao Ge, Lei Li, Songjie Chen, Guojun He, Shouru Xue

Bibliographic record

VenueFrontiers in Neuroscience · 2025
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentInternal medicineMedicineDementiaTriglycerideGastroenterologyCross-sectional studyLogistic regressionParkinson's diseaseCorrelationCognitionEndocrinologyDiseaseCholesterolPsychiatryPathology

Abstract

fetched live from OpenAlex

Background Insulin resistance (IR) is proved be involved in the pathophysiology of Parkinson’s disease (PD). As an effective surrogate marker of IR, the correlation between the triglyceride-glucose (TyG) index and PD remains unclear. This cross-sectional study aimed to explore the association between the TyG index and cognitive impairment in PD (PDCI). Methods Patients with sporadic PD were consecutively enrolled between May 2022 and October 2023. The cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA). The Spearman correlation analysis was used to evaluate the correlation between TyG index and MoCA score, Unified-Parkinson Disease Rating Scale (UPDRS) III and peripheral blood oxidative stress markers, respectively. Logistic regression analysis was performed to explore the correlation between TyG and PDCI and dementia in PD (PDD). Results A total of 78 patients were enrolled, of whom 50 (64.1%) were diagnosed with PDCI [26 with mild cognitive impairment (MCI) and 24 with PDD]. The TyG index in patients with dementia and MCI were higher than those with normal cognition (9.32 ± 0.43 vs. 8.90 ± 0.47 vs. 8.51 ± 0.46, P < 0.001). The Spearman correlation analysis demonstrated that TyG was negatively correlated with MoCA ( r = −0.704, P < 0.001) and superoxide dismutase ( r = −0.244, P = 0.031), but positively correlated with UPDRS III ( r = 0.246, P = 0.030). Multivariate logistic regression analysis showed that TyG was independently associated with PDCI regardless of whether it was used as a continuous variable (OR = 6.177, 95% CI = 1.590–24.000) or a tertile variable (OR = 5.478, 95% CI = 1.030–29.132). This association persisted after excluding patients with diabetes. The receiver operating characteristic (ROC) analysis suggested that the area under the curve (AUC) of TyG for predicting PDCI was 0.805 (95% CI = 0.707–0.903, P < 0.001). Conclusion Elevated TyG levels were associated with an increased likelihood of PDCI in patients with PD.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.279
Teacher spread0.268 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2025
Admission routes1
Has abstractyes

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