Primary progressive aphasia: Diagnosis, varieties, evolution
Bibliographic record
Abstract
A referred cohort of 67 clinically defined PPA patients were compared to 99 AD patients with formal language and nonverbal cognitive tests in a case control design. Language fluency was determined at the first and last follow up visits. Quantitation of sulcal and ventricular atrophy on MRI was carried out in 46 PPA and 53 AD patients. Most PPA patients (57%) are relatively fluent when first examined. Visuospatial and memory functions are initially preserved. Aphemic, stuttering, "pure motor" presentation, or agrammatic aphasia are seen less frequently. Later most PPAs become logopenic and nonfluent, even those with semantic aphasia (dementia). In contrast, AD patients were more fluent and had relatively lower comprehension, but better overall language performance. MRI showed significant left sided atrophy in most PPA patients. Subsequent to PPA, 25 patients developed behavioral manifestations of frontotemporal dementia and 15 the corticobasal degeneration syndrome, indicating the substantial clinical overlap of these conditions. Language testing, particularly fluency scores supported by neuroimaging are helpful differentiating PPA from AD. The fluent-nonfluent dichotomy in PPA is mostly stage related. The aphemic-logopenic-agrammatic and semantic distinction is useful, but the outcomes converge.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".