Predictive value of biliverdin reductase‐A and homeostasis model assessment of insulin resistance on mild cognitive impairment in patients with type 2 diabetes
Bibliographic record
Abstract
AIMS/INTRODUCTION: To investigate the predictive value of the biliverdin reductase-A (BVR-A) and the homeostasis model assessment for insulin resistance (HOMA-IR) on mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus, and to establish a nomogram model. MATERIALS AND METHODS: This study included 140 patients with type 2 diabetes mellitus. Based on Montreal Cognitive Assessment (MoCA) scores, participants were categorized into the normal cognitive function (T2DM-NCF) group (65 cases) and the mild cognitive impairment (T2DM-MCI) group (75 cases). Multivariate logistic regression analysis was performed to identify the factors associated with MCI in patients with type 2 diabetes mellitus. A nomogram prediction model was developed using R software for the selected factors, and its predictability and accuracy were verified. RESULTS: Compared with the T2DM-NCF group, subjects with MCI were older, had a longer duration of diabetes, higher HOMA-IR, lower BVR-A, lower cognitive scores, and lower education levels (all P < 0.05). Multivariate logistic regression analysis showed that duration of diabetes (OR = 1.407, 95% CI: 1.163-1.701), HOMA-IR (OR = 1.741, 95% CI: 1.197-2.53), and BVR-A (OR = 0.528, 95% CI: 0.392-0.712) were significantly associated with the development of MCI in patients with type 2 diabetes mellitus. The C-index of the nomogram was 0.863 (95% CI: 0.752-0.937). CONCLUSIONS: Our findings suggest that BVR-A and HOMA-IR are significantly associated with the development of MCI in patients with type 2 diabetes mellitus. The nomogram incorporating BVR-A and HOMA-IR aids in predicting the risk of developing MCI in these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".