Longitudinal performance of a case of semantic variant primary progressive aphasia: a case report
Bibliographic record
Abstract
Case Presentation: The semantic variant of Primary Progressive Aphasia (svPPA) is marked by a progressive impairment in the comprehension of words and concepts. Longitudinal follow-up cases are relevant to understanding the clinical and functional progression of language over time. Patient SFL, male, 43 years old, right-handed, with 11 years of education, began multidisciplinary follow-up in 2022 with complaints of increasing word-finding difficulties, initially noticed during his sermons as a pastor. He was assessed until 2024 at three time points, approximately six months apart, using the Montreal-Toulouse Battery (oral and written sentence comprehension), the Cambridge Test (oral word comprehension), and the Boston Naming Test. A progressive decline was observed across all tasks, with notable decreases in the Cambridge Test (from 56/64 to 10/64) and written sentence comprehension (from 7/8 to 1/8). Discussion: The findings are consistent with the expected profile of svPPA, characterized by deterioration of conceptual and lexical knowledge. Notably, the abrupt decline observed in the final seven months in the Cambridge Test suggests a possible acceleration of semantic deterioration in that period, which warrants further investigation. The assessment data are better visualized in the accompanying graph. Final Comments: The findings reinforce the importance of language assessment and longitudinal monitoring to define the cognitive profile and identify changes in the clinical course, enabling the adaptation of interventions to communicative needs with the involvement of communication partners, aiming to maintain functionality throughout the progression of the disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".