Parkinson's Disease-related Pains are Not Equal: Clinical, Somatosensory and Cortical Excitability Findings in Individuals With Nociceptive Pain
Bibliographic record
Abstract
Chronic pain is a frequent and burdensome nonmotor symptom of Parkinson's disease (PD). PD-related chronic pain can be classified as nociceptive, neuropathic, or nociplastic, the former being the most frequent subtype. However, differences in neurophysiologic profiles between these pain subtypes, and their potential prognostic and therapeutic implications have not been explored yet. This is a cross-sectional study on patients with PD (PwP)-related chronic pain (ie, started with or was aggravated by PD). Subjects were assessed for clinical and pain characteristics through questionnaires and underwent quantitative sensory tests and motor corticospinal excitability (CE) evaluations. Data were then compared between individuals with nociceptive and non-nociceptive (ie, neuropathic or nociplastic) pains. Thirty-five patients were included (51.4% male, 55.7 ± 11.0 years old), 20 of which had nociceptive pain. Patients with nociceptive PD-related pain had lower warm detection threshold (WDT, 33.34 ± 1.39 vs 34.34 ± 1.72, P = .019) and mechanical detection threshold (MDT, 2.55 ± 1.54 vs 3.86 ± .97, P = .007) compared to those with non-nociceptive pains. They also presented a higher proportion of low rest motor threshold values than the non-nociceptive pain ones (64.7% vs 26.6%, P = .048). In non-nociceptive pain patients, there was a negative correlation between WDT and non-motor symptoms scores (r = -.612, P = .045) and a positive correlation between MDT and average pain intensity (r = .629, P = .038), along with neuropathic pain symptom scores (r = .604, P = .049). It is possible to conclude that PD-related chronic pain subtypes have distinctive somatosensory and CE profiles. These preliminary data may help better frame previous contradictory findings in PwP and may have implications for future trial designs aiming at developing individually-tailored therapies. PERSPECTIVE: This work showed that PwP-related nociceptive chronic pain may have distinctive somatosensory and CE profiles than those with non-nociceptive pain subtypes. These data may help shed light on previous contradictory findings in PwP and guide future trials aiming at developing individually-tailored management strategies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".