Late-onset-psychosis: cognition
Bibliographic record
Abstract
BACKGROUND: The objectives of the study were to characterize and compare the cognitive profile and natural evolution of patients presenting late-onset psychotic symptoms (LOPS: onset ≥ 50 years old) to those of elderly patients (≥ 50 years old) with life-long/early-onset schizophrenia (EOS: onset <40 years old). METHODS: Neuropsychological profiles of 15 LOPS patients were compared to those of 17 elderly EOS patients and to those of two control groups (n = 11/group). The evolution of the two patient groups was compared using an independent diagnostic consensual procedure involving a geriatric psychiatry physician/clinician and a neuropsychologist blinded to the initial psychiatric diagnosis. RESULTS: EOS presented significant memory and executive impairments when compared to controls but there was no significant difference between LOPS and their controls when age and education were taken into account. However, a detailed inspection of normative data suggests more executive impairments in LOPS than in EOS. The clinical judgment of experts was in favour of significant cognitive deficits with or without dementia in most LOPS (82.3%-94.1%) and EOS (80.0%-93.3%) patients. Regarding evolution, mild cognitive impairment (MCI) and vascular cognitive impairment (VCI) were the most common clinical diagnoses made by geriatric psychiatry physicians/clinicians for the LOPS (40%). In addition, 20% of LOPS versus 5.9% of EOS patients met the diagnostic criteria for dementia by consensus of the experts. Cerebral abnormalities were confirmed (CT scan; SPECT) in 73.3% of LOPS patients. CONCLUSION: The present results suggest cognitive deficits (mostly of executive functions) and vascular and neurodegenerative vulnerability in LOPS. Further studies with larger samples are needed to confirm the present findings.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".