<p>Effect of Switching from Low-Dose Simvastatin to High-Dose Atorvastatin on Glucose Homeostasis and Cognitive Function in Type 2 Diabetes</p>
Bibliographic record
Abstract
Background: High-intensity statin is recommended in high-risk type 2 diabetes (T2D); however, statin dose dependently increases the risk of developing new-onset diabetes, can potentially worsen glycemic control in T2D, and may cause cognitive impairment. This study aimed to investigate the effect of statin intensification on glucose homeostasis and cognitive function in T2D. Materials and Methods: T2D patients who were taking simvastatin ≤ 20 mg/day were randomized to continue taking the same dosage of simvastatin (low-dose simvastatin group; LS, n=63) for 12 weeks, or to change to atorvastatin 40 mg/day for 6 weeks, and if tolerated, atorvastatin was increased to 80 mg/day for 6 weeks (high-dose atorvastatin group; HS, n=62). Fasting plasma glucose (FPG), glycated hemoglobin (HbA 1c ), plasma insulin, homeostatic model assessment of insulin resistance (HOMA-IR) and of β-cell function (HOMA-B), cognitive functions using Montreal Cognitive Assessment (MoCA), and Trail Making Test (TMT) were assessed at baseline, 6 weeks, and 12 weeks. Results: Mean age of patients was 58.8± 8.9 years, and 72% were female. Mean baseline FPG and HbA 1c were 124.0± 27.5 mg/dl and 6.9± 0.8%, respectively. No differences in baseline characteristics between groups were observed. Change in HbA 1c from baseline in the LS and HS groups was − 0.1% and +0.1% ( p =0.03) at 6 weeks, and − 0.1% and +0.1% ( p =0.07) at 12 weeks. There were no significant differences in FPG, fasting plasma insulin, HOMA-B, HOMA-IR, MoCA score, or TMT between groups at 6 or 12 weeks. Conclusion: Switching from low-dose simvastatin to high-dose atorvastatin in T2D resulted in a slight increase in HbA 1c (0.1%) without causing cognitive decline. Keywords: high-intensity statin, glucose homeostasis, cognitive function, type 2 diabetes, T2D
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".