Posterior cortical atrophy in Southeast Asia: Clinical and biomarker profile
Bibliographic record
Abstract
Abstract Background Posterior Cortical Atrophy (PCA) has been widely studied internationally, but there is limited data on its clinical and biomarker characteristics among Southeast Asians. We aim to describe a case series of PCA patients in this part of the world and explore how the new PCA consensus classification (Crutch et al., 2017) could be applied in this cohort. Method A retrospective review of the Singapore Young Onset Dementia (YOD) research database from a tertiary neurology center was performed. Available demographic, clinical and biomarker data of patients with a clinical diagnosis of PCA were extracted. Result Of 290 patients with YOD, ten patients (5 males; 5 females) with a clinical diagnosis of PCA were identified. Mean (SD) age of onset was 54.70 (4.11), duration between symptom onset and neurological consultation was 3.90 (1.45) years. All patients reported insidious onset and gradual progression of symptoms. Upon neurological examination, principle types of cognitive deficits seen were acalculia (80%), finger agnosia (70%), simultagnosia (60.0%) and agraphia (50%). In another sub‐group with available MRI scans (n=7), all showed biparietal cortical atrophy, five (71.0%) had concomitant bilateral medial temporal lobe atrophy and white matter hyperintensities of varying severity was noted in four (57.0%) patients. Among patients with known APOE genotyping (n=8), there was one e2e3 six e3e3 and one e4e4. Findings on cerebrospinal Ab‐42 and tau levels was available (n=7), mean (SD) of Ab‐42, phosphor‐tau and total tau levels were 525.1 (195.5)pg/ml, 72.1 (22.9)pg/ml and 611.3 (246.9)pg/ml respectively. Based on the new consensus classification for PCA (Crutch et al., 2017) and incorporating the CSF Ab‐42 criterion cut‐off for AD by Dubois et al. (2014), our series consists of one PCA‐AD (10.0%) and nine PCA‐pure (90.0%) However, if the CSF tau/ Ab‐42 ratio >0.52 (Duits et al., 2014) for biomarker diagnosis of AD is used, there would be seven PCA‐AD (70%) and three PCA‐plus (30%). Conclusion PCA patients tend to present late in clinic and greater awareness on the presentation of PCA is needed for earlier diagnosis and timely intervention. Also, the sensitivity of the different CSF criteria for AD in diagnosing PCA‐AD would require further analyses in larger cohorts.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".