Neuropsychological differentiation of late onset schizophrenia and frontotemporal dementia
Bibliographic record
Abstract
Frontaltemporal dementia (FTD) and schizophrenia are characterised by disturbances in cognition, personality, behaviour, and social functioning often leading to a decline in activities in daily living. Deterioration of comportment and disturbances in attention are typical in both disorders and manifest behaviourally in terms of withdrawal, isolation, lack of volition, emotional unresponsiveness, and poverty of speech. Accordingly, the considerable overlap in behavioural expression between patients with schizophrenia and FTD makes a differential diagnosis difficult. This different diagnosis is especially difficult when the age of onset of schizophrenia is late (i.e., 45 +). The purpose of this study was to identify which neuropsychological tests best differentiate patients with late onset schizophrenia from patients with FTD. Hence, neurocognitive test results from a total of 12 patients with FTD and 32 patients with schizophrenia were analysed using test sensitivity statistics (i.e., Cohen's U2% overlap). The results support a test battery composed of the WAIS-R Vocabulary, Information, Digit Span, and Comprehension subtests, and the Hooper Visual Organisation test as being the most sensitive measures to diagnostic differentiation between patients with FTD and those with late onset schizophrenia.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".