A Pilot Study to Unveiling the Link Between Physical Fitness and Cognitive Health in Early Vs. Late Diagnosed Diabetic Patients
Bibliographic record
Abstract
Introduction: Diabetes mellitus is a common chronic health condition that adversely affects various organ systems. However, its influence on physical fitness and cognitive health has yet to be thoroughly investigated, especially the timing of diagnosis. Material and Methods: For our analysis, we examined 40 diabetic patients and divided them into two groups based on how long they had been diagnosed: early (≤ 5 years) and late (≥ 6 years). Participants were subjected to a battery of physical fitness tests, including evaluations of upper and lower body strength, Coordination, and aerobic endurance. Additionally, cognitive assessments such as the Addenbrooke's Cognitive Examination, Mini-Mental State Examination, and Montreal Cognitive Assessment were administered. The data were analyzed by conducting independent sample t-tests to compare the two groups. Results: The study revealed notable disparities between the groups diagnosed early and those diagnosed late. Individuals who were diagnosed later experienced less favorable results in physical fitness evaluations, including handgrip strength, 6-minute walk distance aerobic endurance, and heart rate variability, as well as lower scores in all cognitive assessments. These findings suggest that a prolonged period of untreated diabetes can have detrimental effects on both physical and cognitive health outcomes. Conclusion: To preserve both physical and cognitive functions, it is crucial to diagnose and manage diabetes early. The significance of prompt intervention has the potential to shape future recommendations on the treatment and detection of diabetes to enhance health outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".