The Impact of Medication Regimen Adjustment Ratio on Adherence and Glycemic Control in Patients with Type 2 Diabetes and Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: An antidiabetic medication regimen is crucial for maintaining glycemic control. Type 2 diabetes mellitus (T2DM) and cognitive dysfunction have a bidirectional relationship. This study aims to explore the impact that adjusting antidiabetic medication regimens has on medication adherence, glycemic control, and cognitive function in patients with T2DM and mild cognitive impairment (MCI). METHODS: This is an observational cross-sectional analysis that includes 364 consecutive inpatients with T2DM. Clinical data were collected, medication adherence was assessed using the Medication Adherence Report Scale (MARS-5), and cognitive status was evaluated using the Chinese version of the Montreal Cognitive Assessment (MoCA) and Mini-mental State Examination (MMSE). These data were obtained both during hospitalization and at a three-month follow-up. Multivariable logistic regression analysis was applied to determine the association between changes in medication regimens and medication adherence, glycemic control, and cognitive function. RESULTS: Baseline medication adherence was high across all three different cognitive status groups, with no significant difference in MARS-5 scores. At the 3-month follow-up, the group with a high adjustment ratio of antidiabetic medication regimens showed an increase in their hemoglobin A1c (HbA1c) level compared to the baseline, while the group with a low adjustment ratio showed a decrease in this level. In addition, the MoCA, MMSE, and MARS-5 scores of the high-adjustment group were significantly lower than those of the low-adjustment group. CONCLUSIONS: A high ratio of medication adjustment was significantly associated with worse medication adherence and glycemic control in T2DM patients with MCI. Patients with a low ratio of medication adjustment had good adherence and better glycemic control. Clinicians should take cognitive status into account when adjusting antidiabetic regimens for T2DM patients and may need to provide additional guidance to patients with cognitive impairment to improve adherence and glycemic outcomes.
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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".