Top motor and non-motor complaints in patients with Parkinson's disease
Bibliographic record
Abstract
Background Parkinson's disease (PD) is characterized by several motor and non-motor manifestations. These variable neurological complaints have diverse intensity and cause various degrees of disability. Objective methods We aimed to assess the top three most troublesome neurological complaints in patients with PD and correlated them with demographic and clinical variables, including the cognitive status assessed by the Montreal Cognitive Assessment (MoCA). Patients were asked about their three most troublesome neurological complaints after reviewing all motor and non-motor symptoms. Responses were divided into three tiers. Results We studied 230 consecutive patients with PD. There were 130 (56.5%) male patients, with the mean age at evaluation of 67.7 ± 11.06 years. The most common neurological complaints in the top tier were (1) tremor ( n = 80, 34.8%), (2) gait problems ( n = 37, 16.1%), and (3) dyskinesia ( n = 17, 7.4%). Speech difficulties, dyskinesia, and insomnia became more prominent 5 or 10 years after disease onset. A total of 159 (69.1%) patients reported “at least one non-motor symptom” among their top-3 tier complaints. Pain ( n = 29, 12.6%), anxiety ( n = 25, 10.8%), and insomnia ( n = 25, 10.8%) were the most common non-motor symptoms. The presence of non-motor symptoms in the top three tiers was associated with decreased cognitive status (MoCA <25 points), but not with age, sex, or disease evolution time. Cognitive impairment was a significant predictor of non-motor symptoms in their top three tiers [odds ratio [OR]: 3.88 (95% CI: 1.647 to 9.169)]. Cluster analysis of patients with at least one non-motor symptom identified four groups: male or female patients with short evolution time, a postural-instability gait difficulty (PIGD) phenotype, and a dyskinetic group. The latter two were associated with a higher frequency of fatigue, insomnia, pain, and anxiety. Conclusion Overall, tremor was the most troublesome symptom in patients with PD, though high variability was observed. Approximately 69% of patients had at least one non-motor symptom among their top-3 complaints, which was associated with abnormal cognitive status. Speech difficulties, dyskinesia, and insomnia became more prominent with disease progression. Among patients with non-motor symptoms in the top three tiers, those with a PIGD phenotype or prominent dyskinesia exhibited a higher frequency of fatigue, insomnia, pain, and anxiety, suggesting a clustering effect of non-motor symptoms with these motor presentations.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".