Commentary on: “Effects of Regular Physical Activity on the Cognitive Performance of Type 2 Diabetic Patients: A Systematic Review” by Podolski et al. (Metab Syndr Relat Disord 2017;15:481–493)
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) imparts an increased risk for cognitive decline, specifically executive function, which is important to maintain for diabetes self-management. There is evidence to suggest that exercise improves cognition in healthy older adults; however, the literature in adults with T2DM is lacking. This commentary is in complement to Podolski et al.'s systematic review evaluating the effects of physical activity on cognitive function in adults with T2DM. We have included eight additional studies and further highlight their conclusions on the heterogeneity of the literature thus far. Three current issues with the literature are as follows: (1) variability in interventions (e.g., aerobic, resistance, lifestyle, and yoga), (2) variability in cognitive outcome measures, and (3) lack of detailed description of the population studied, for example, baseline glycated hemoglobin (A1C) values. Overall, making it difficult to compare these studies and draw final conclusions. Thus, the efficacy for exercise to improve cognition in adults with T2DM is not yet well understood. Potential ways to mitigate these limitations could be for future studies that (1) use robust methodology whenever possible, that is, randomized controlled trials, (2) to follow current guideline-derived exercise recommendations for adults with T2DM, and (3) utilize cognitive outcome measures that are consistent across studies. The hope is that these consistencies in turn will help to determine the efficacy of exercise on cognitive function in adults with T2DM and therefore, allow national organizations to develop recommendations and guidelines for healthcare practitioners to follow.
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 | 0.014 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.026 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.007 |
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".