The Influence of Diabetes Mellitus Duration and Type of Therapy on Cognitive Decline
Bibliographic record
Abstract
© 2016, Springer Science+Business Media New York.We studied 120 patients with compensated diabetes mellitus type 2 (DM-2). The inclusion criterion was the absence of memory loss complaints from the patient and/or his/her relatives. The exclusion criteria were diabetes decompensation, myocardial infarction and/or stroke in anamnesis, glomerular filtration rate below 60 ml/min, the presence of proliferative retinopathy, and/or other endocrine diseases. To diagnose the cognitive decline (CD) we used Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA test), Trail Making Test (parts A and B). 77.5 % patients with type 2 diabetes out of 120 had moderate CD; 5 % had a significant CD (dementia). The control group consisted of 50 patients with arterial hypertension, which was comparable with the DM-2 group. In assessing the correlations, we found that the CD in DM-2 group is independent of disease duration and the type of diabetic therapy. We discovered a positive correlation between the age of patients and the speed of cognitive decline. Comparison of patients in DM-2 group with the control group showed that results in patients with hypertension (MMSE, MoCA test) were significantly higher (p < 0.01), and the test time of TMT part A and part B was significantly lower (p < 0.01) than that in patients with DM-2. The authors believe that the CD in DM-2 has different pathogenic mechanisms than other complications of type 2 diabetes mellitus, in particular, the insulin resistance of brain tissue.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".