A four-year trajectory of Alexithymia in Parkinson’s disease patients
Bibliographic record
Abstract
The aim of this study was to assess the presence of Alexithymia in Parkinson's disease (PD) patients compared to their caregivers (CG) and to investigate whether Alexithymia progressed over a 4-year observational period. Alexithymia in PD is a cognitive affective disturbance resulting in difficulty to identify, distinguish and describe feelings and it is known to be strongly associated with health-related quality of life and other cognitive/ neuropsychiatric symptoms. So far, there have been no longitudinal investigations of Alexithymia in PD. We recruited 34 moderately progressed PD patients (mean disease duration of 8.9 ± 5.3 years) and their caregivers in our neurological department and did a baseline and follow-up assessment using the validated Toronto Alexithymia Scale-26 (TAS-26). Our data show that Alexithymia is more abundant in the PD cohort compared to their caregivers (p = 0.007, PD 21 %, CG 6 % at follow-up). In the 4-year observational period, Alexithymia did not increase significantly in PD patients or caregivers. However, there was a high variance in Alexithymia scores in both groups. It remains unclear when Alexithymia appears during the disease course and whether there is a dynamic in Alexithymia scores later in PD progression. This should be the objective for future studies of Alexithymia in advanced PD patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".