Motor phenotype of LRRK2‐associated Parkinson's disease: A tunisian longitudinal study
Bibliographic record
Abstract
Mutations in the leucine-rich repeat kinase 2 gene (LRRK2) were found to be a significant cause of late-onset autosomal dominant forms of Parkinson's disease (PD). To determine the motor characteristics of LRRK2-related disease, we conducted a longitudinal study of 58 G2019S LRRK2-associated PD patients and compared them with genetically undefined (GU) PD patients. Fifty-eight patients diagnosed with PD-related LRRK2 G2019S mutation were included in the study and compared with 54 sporadic PD patients with negative tests for LRRK2 G2019S, PINK1, SNCA, PRKN, and DJ1 mutations. Patients were assessed at baseline and after a follow-up period of 6 years. The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the Hoehn and Yahr, and the Schwab and England scores were determined. Logistic regression was used to examine associations of G2019S mutation status with motor phenotype and rate of motor decline. The LRRK2-associated PD patients had a mean age of onset of 56.25 ± 12.05 years and in most cases (58.6%) a postural instability gait difficulty (PIGD) phenotype. The mean annual decline in the MDS-UDRS III motor score and the Hoehn and Yahr staging was of 1.3% and 2%, respectively. The PIGD phenotype predicted a more rapid progression of motor impairment. The PD motor phenotype and motor scores were similar in the LRRK2-associated PD group and in the GU PD group, with no significant differences in the progression rate of motor impairment. Motor phenotype seems to be similar in LRRK2-related PD and idiopathic PD.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".