P3–176: High prevalence of multiple brain pathologies in dementia
Bibliographic record
Abstract
Multiple pathological processes have been reported at autopsy in dementia series, and may increase cognitive deficits. We present findings from a well–characterized memory clinic population, prospectively followed to autopsy. The Canadian Collaborative Cohort of Related Dementia (ACCORD) study evaluated the clinical diagnosis, natural history and treatment outcomes of individuals newly referred from the community to 8 university–based dementia clinics in Canada. In each case there was one primary clinical diagnosis and up to one further secondary clinical diagnosis made using DSM–III–R criteria. In patients who came to autopsy, neuropathological examination followed a standardized protocol in which semiquantitative assessment of a wide range of pathological changes was mandatory. The pathologist indicated all conditions that fulfilled current diagnostic criteria (primary pathological diagnosis) or that were judged to be of sufficient severity to potentially have contributed to dementia (secondary pathological diagnosis). Other pathological findings were also recorded, even if felt to be unlikely to have contributed to the dementia. This study is based on data from 32 cases that have come to autopsy at a single site (Vancouver). Multiple significant pathologies were identified in 12 cases (37.5%); including those with two primary pathological diagnoses (n=4), one primary and one secondary diagnosis (n=5) or two primary and one secondary diagnosis (n=3). The primary diagnoses in these mixed cases included AD (n=9), DLB (n=6), FTD with MND inclusions (n=2), PSP (n=1) and argyrophilic grain disease (n=1). Significant secondary diagnoses included cerebrovascular disease (n=4), hippocampal sclerosis (n=3) and PSP–like tauopathy (n=1). In only one of the 7 cases with more than one primary pathological diagnosis were all diagnoses also reflected in the premorbid clinical diagnoses. Additional pathology was frequently found and included large vessel stenoses (2), microinfarction (4), advanced cerebral amyloid angiopathy (3) and severe white matter disease (8). It is uncertain whether this additional pathology contributed to the symptomatology. Multiple pathological processes are frequently found in a well–defined population with dementia but that the multiple pathological processes are rarely reflected in the clinical diagnoses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".