Cerebrovascular disease associated with Parkinson’s disease in Moldovan cohort study
Bibliographic record
Abstract
Background: Parkinson’s disease (PD) is frequently associated with brain vascular lesions (BVLs), which may influence the severity of the disease. Material and methods: BVLs on MRI were determined in 78.4% of 111 consecutive PD patients (mean age 64.87 ± 7.69 y.o.; disease duration 50.21 ± 38.61 mo.; 48 women (43.2%), 63 men (56.8%)). Results: White matter lesions were present in 73 patients (p.) (65.77%): 61p. (54.95%) – deep white matter, 46p. (41.44%) – periventricular white matter, and 41p. (36.94%) – both locations. Lacunas were determined in 19p. (17.12%), cerebral fissures deepening – 52p. (46.85) %), perivascular spaces dilation – 34p. (30.63%), ventricular system dilation – 29p. (26.13%). Patients with and without BVLs had similar ages, ages at PD onset and disease duration. They had insignificantly higher Beck (7.26 ± 5.62 vs 6.86 ± 4.34), PDQ39 (Parkinson’s Disease Questionnaire) (59.71 ± 20.38 vs 51.94 ± 27.69) and NMS (Non-Motor Symptoms) (75.06 ± 45.21 vs 71.67 ± 26.35) scores; and lower MoCA (Montreal Cognitive Assessment) scores (21.92 ± 4.25 vs 22.38 ± 4.57). QRISK3 scores (19.68 ± 16.16 vs 12.90 ± 6.58) and levodopa equivalent daily dose (639.98 ± 223.05 vs. 439.69 ± 404.87) were significantly higher in patients with BVLs. Conclusions: Brain vascular lesions were common in our PD patients, and were associated with higher QRISK3 scores and higher levodopa equivalent daily dose, suggesting more disease severity
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".