P.064 Sex differences in patients referred to a rural and remote memory clinic
Bibliographic record
Abstract
Background: Dementia is more prevalent in women. Sex differences exist as the disease progresses (e.g. males are more likely to become aggressive). In many medical illnesses (e.g. cardiac disease), there are differences in presentation between men and women. The current study explores sex differences at the patients’ initial presentation to the Rural and Remote Memory Clinic (RRMC). Methods: Patients were referred to the RRMC in Saskatoon, Saskatchewan. Cognitive and demographic data were collected. Questionnaires included cognitive (e.g. Mini-Mental Status Examination) and daily living (e.g. Instrumental Activities of Daily Living) assessments. Results: Three hundred and seventy-five (159 male, 216 female) patients participated. Of these patients, 146 (49 male, 97 female) were diagnosed with Alzheimer’s disease. Males and females presented to the clinic at similar ages. Females were more likely to have a son or daughter caregiver and to live alone. Males were more likely to be currently working and to be a former smoker. No statistically significant differences were found for cognitive assessment scores. Conclusions: Analysis of the initial presentation of patients to the RRMC revealed females and males had similar presentation in measures of cognitive impairment. This may be reassuring for patients and their families knowing their family member, regardless of sex, is receiving equivalent referral to receive care.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".