MétaCan
Menu
Back to cohort
Record W3134893694 · doi:10.1111/psyg.12675

Increased insulin resistance is associated with vascular cognitive impairment in <scp>Chinese</scp> patients with cerebral small vessel disease

2021· article· en· W3134893694 on OpenAlex
Xiaoming Guo, Yuting Zhu, Xinling Li, Zhenhui Lu, Zhiyong Cao, Xiao‐Yi Yi, Xiangyang Zhu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePsychogeriatrics · 2021
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
FundersScience and Technology Project of Nantong City
KeywordsInternal medicineInsulin resistanceOdds ratioQuartileMedicineConfoundingMontreal Cognitive AssessmentConfidence intervalLogistic regressionReceiver operating characteristicGastroenterologyRisk factorDiseaseInsulinCognitive impairment

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to investigate the association between insulin resistance (IR) and vascular cognitive impairment (VCI) in patients with cerebral small vessel disease (CSVD). METHODS: A total of 275 CSVD patients were enrolled in this retrospective case-control study. The homeostatic model assessment of insulin resistance (HOMA-IR) was used to measure the index of insulin resistance. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Spearman's correlation coefficient was used to evaluate the correlation between HOMA-IR and MoCA score. The variance inflation factor (VIF) was used to detect collinearity between variables. Multivariate logistic regression analysis was employed to confirm whether HOMA-IR is an independent risk factor for VCI in CVSD. Finally, receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic value of HOMA-IR in VCI. RESULTS: Of the 275 patients, 164 displayed VCI. VCI patients showed a significantly higher level of HOMA-IR compared to non-VCI patients (P < 0.001). HOMA-IR was negatively correlated with the MoCA score (r = -0.593, P < 0.001). After adjusting for potential confounding variables, using HOMA-IR quartile 1 (<1.11) as the reference, HOMA-IR quartile 3 (1.71-2.50) and quartile 4 (≥2.50) were independently associated with the occurrence of VCI; for each one unit increase in the HOMA-IR, the risk of VCI increased by 177.3% (odds ratio 2.773, 95% confidence interval: 1.050-7.324, P = 0.040) and 444.3% (odds ratio 5.443, 95% confidence interval: 2.109-14.050, P < 0.001), respectively. According to the ROC curve, the optimal cut-off point of HOMA-IR in predicting VCI was 1.55, and the area under the curve was 0.744, with a sensitivity of 71.3% and a specificity of 69.4%. CONCLUSION: This study demonstrated that increased IR is significantly associated with VCI in CSVD patients.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.242
Teacher spread0.233 · 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