Premorbid and current intellectual performance reflects different backgrounds in patients with Parkinson's disease
Bibliographic record
Abstract
• JART and NART are used to estimate premorbid IQ. • We compared correlated factors between premorbid and current intellectual performance. • Estimated premorbid IQ correlated with education. • Current cognitive function correlated with current age motor symptoms in PD. • Premorbid and current intellectual performance reflect different background factors in PD. There is growing interest in targeting Parkinson's Disease (PD) at an earlier stage, especially before emergence of motor symptoms. Cognitive dysfunction is a non-motor symptom in PD, whereas the Japanese version of the National Adult Reading Test (JART) is a validated battery to estimate the premorbid intellectual quotient (IQ). Therefore, the results of JART and current cognitive assessment after onset of PD may reflect different background factors. The goal of the study was to compare factors correlated with estimated premorbid intellectual performance using JART and current cognitive function after onset of PD. Current motor symptoms (Unified Parkinson's Disease Rating Scale; UPDRS Part III) and cognitive function (Montreal Cognitive Assessment; MoCA) were assessed in 48 patients with PD. Premorbid IQs (verbal IQ: VIQ, performance IQ: PIQ, and full scale IQ: FIQ) were estimated using JART. Spearman correlation coefficients were calculated for background factors (current age, years of education, UPDRS Part III, and levodopa equivalent dose of prescribed drugs (LED)) with MoCA scores and estimated IQs. Estimated VIQ ( r = 0.451, p = 0.001), PIQ ( r = 0.445, p = 0.002) and FIQ ( r = 0.453, p = 0.001) were significantly correlated with years of education that was fixed until adolescence (i.e. 20 s). MoCA was significantly correlated with current age ( r =−0.401, p = 0.005) and UPDRS part III ( r =−0.374, p = 0.009), both of which continue to progress gradually after onset of PD. In multiple regression analyses, these correlations were significant and independent. Premorbid and current intellectual performance reflect different background factors in patients with PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| 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".