P.015 What Happens to the Worried Well? – Follow-up of Subjective Cognitive Impairment
Bibliographic record
Abstract
Background: Concern around perceived neurocognitive decline is increasing, leading to increased number of referrals and anxiety for patients. We aimed to explore the likelihood of the “worried well” experiencing neurocognitive decline. Methods: 166 “worried well” patients who attended the Rural and Remote Memory Clinic between 2004 and 2019 were included. Mini Mental Status Examination, Center for Epidemiologic Studies Depression Scale, and Functional Assessment Questionnaire scores were measured and compared at initial assessment and at 1-year follow-up. MMSE scores over time were assessed with a mean follow-up of 2.95 years (SD 2.87). Results: There was no statistically significant difference in MMSE, CESD, or FAQ scores between clinic day and one-year follow-up, and no consistent pattern of MMSE score over time. Of the 166 patients with SCI on initial assessment, nine were eventually given a neurological diagnosis. Conclusions: There is no pattern of neurologic decline observed in the “worried well”. Though the likelihood of a patient with SCI developing a neurological diagnosis is reassuringly low, (9/166), it is not irrelevant. This, along with the benefits of early diagnosis and treatment for dementia, leads us to believe that patients with SCI should still be seen in follow-up at least at the one-year mark.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".