Characteristics of Young-Onset and Late-Onset Dementia Patients at a Remote Memory Clinic
Bibliographic record
Abstract
BACKGROUND: Young-onset dementia (YOD) is defined as the onset of dementia symptoms before the age of 65 years and accounts for 2-8% of dementia. YOD patients and their caregivers face unique challenges in diagnosis and management. We aimed to compare the characteristics of rural YOD and late-onset dementia (LOD) patients at a rural and remote memory clinic in Western Canada. METHODS: A total of 333 consecutive patients (YOD = 61, LOD = 272) at a rural and remote memory clinic between March 2004 and July 2016 were included in this study. Each patient had neuropsychological assessment. Health, mood, function, behaviour and social factors were also measured. Both groups were compared using χ2 tests and independent sample tests. RESULTS: YOD patients were more likely to be married, employed, current smokers and highly educated. They reported fewer cognitive symptoms, but had more depressive symptoms. YOD patients were less likely to live alone and use homecare services. YOD caregivers were also more likely to be a spouse and had higher levels of distress than LOD caregivers. Both YOD and LOD patient groups were equally likely to have a driver's licence. CONCLUSIONS: Our findings indicate YOD and LOD patients have distinct characteristics and services must be modified to better meet YOD patient needs. In particular, the use of homecare services and caregiver support may alleviate the higher levels of distress found in YOD patients and their caregivers. Additional research should be directed to addressing YOD patient depression, caregiver distress and barriers to services.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".