Motor and non-motor predictors of freezing of gait in Parkinson's disease: A retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Freezing of gait (FOG) is a debilitating episodic gait disorder that significantly reduces the quality of life (QoL) in patients with Parkinson's disease (PD). Diagnosing and treating FOG remains a major medical challenge. This study aimed to assess the correlation between FOG and both motor and non-motor clinical characteristics in patients with PD. METHODS: In this retrospective cohort study, 112 patients with PD were divided into two groups using the New Freezing of Gait Questionnaire (NFOG-Q): one group with FOG (PD-FOG, 53 patients) and one group without FOG (PD-nFOG, 59 patients). The severity of PD and FOG was assessed using the Unified Parkinson's Disease Rating Scale (UPDRS), the Hoehn-Yahr (H-Y) staging system, and the NFOG-Q. The study also analyzed non-motor symptoms, including sleep disturbances, cognitive impairments, depression, anxiety, apathy, fatigue, and QoL. RESULT: The prevalence of FOG was 47.3%. The PD-FOG group exhibited a longer duration of PD (P = 0.002), a higher H-Y stage indicating PD progression (P = 0.003), and elevated anxiety levels (P = 0.003) compared to the PD-nFOG group. According to binary logistic regression analysis, the higher H-Y stage (P = 0.022), anxiety level (P = 0.005), UPDRS part II (P = 0.001), and part III (P = 0.008) were significant predictors for the occurrence of FOG. CONCLUSION: Patients with Parkinson's disease who have a higher Hoehn-Yahr (H-Y) stage, higher UPDRS score, and elevated levels of anxiety are more likely to experience FOG.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".