Association between Body Mass Index and Cognitive Performance
Bibliographic record
Abstract
Background and Purpose: Because of well-established role of obesity in brain lesions, progressing cognitive deficits in obese patients has been recently suggested. In current study and for the first time, we aimed to assess cognition status in Iranian obese people and to compare it with non-obese individuals. Methods: One hundred and eighteen consecutive patients with the different cardiovascular and metabolic primary complaints were assigned to obese group (n=25, 21.2%) and non-obese group (n=93, 78.8%). Cognitive status was assessed at initial visit using the Montreal Cognitive Assessment (MoCA) questionnaire. Results: Mean of total cognitive score in obese patients was 20.04±4.57 and in non-obese ones was 20.19±5.32 with no difference (p=0.886). In total, 8.0% of obese patients and 20.4% of non-obese patients had normal cognitive function (p=0.149). No significant difference was also found in different subdomains of cognitive ability between obese and non-obese groups. None of the cognitive domains had significant association with BMI as the considered indicator for defining obesity. Based on multivariate linear regression modeling, obesity could not predict cognitive deficit (beta=0.034, SE:1.10 p=0.973). Conclusion: Our survey could not demonstrate an association between obesity and cognitive impairment in a sample of Iranian patients.
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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 | 0.000 | 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 | 0.001 |
| 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".