The relationship between the severity of obsessive compulsive disorder (OCD) and Alzheimer's disease (AD) and frontotemporal dementia (FTD)
Bibliographic record
Abstract
Abstract Introduction: Given the prevalence of obsessive-compulsive disorder(OCD), we investigated the association between the severity of OCD and Alzheimer's and frontotemporal dementia.Method: This case-control study included patients referred to the dementia clinic of Firoozgar Hospital and the Brain and Cognition Clinic, who had a Montreal Cognitive Assessment (MOCA) test score less than 26 based on assessments of known Alzheimer's or frontotemporal dementia. The control group also consisted of people who referred to the neurology clinic without complaining of psychiatric disorders. For evaluating the severity of OCD we used the Yale – Brown Obsessive Compulsive Scale (Y-BOCS) questionnaire. Results: This study was performed on 13 patients with Alzheimer's disease, 13 patients with FTD and 26 healthy controls. The MOCA score in the two groups of patients was significantly lower than the control group (P <0.001) and is was not statistically significant between the two groups (P> 0.05). The severity of OCD was significantly higher in FTD )25.76±7.16 (and Alzheimer's patients )18.15±9.50( compared to the control group (7.07±5.70) (P <0.001). Also, the severity of OCD was was higher in the FTD group compared to the Alzheimer's group (P = 0.03). Conclusion: Thus, the severity of OCD in the group of FTD and Alzheimer's patients was higher compared to the control group and also the severity of OCD was higher in the FTD group compared to the Alzheimer's group.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".