Antidepressants Effects on Pain in Parkinson Disease: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Pain in Parkinson disease (PD) is complex as this symptom can be multifactorial in origin because deficits in dopaminergic but also other neurotransmitters are involved. Pain and depression are increasingly recognized to have clinical importance for the quality of life of people living with PD. This systematic review aims to summarize the existing evidence on the potential benefit of using prescribed antidepressants for decreasing or controlling pain associated with PD. METHODS: PubMed databases were searched for relevant studies using keywords and our exclusion/inclusion criteria and targeting only randomized placebo-controlled trials for antidepressants in PD. RESULTS: After screening 108 articles, only 3 focused articles were analyzed. Two of the included studies reported were on nortriptyline and paroxetine antidepressants. Unfortunately, included studies did not align in their outcome measures and did not directly compare the drug groups against each other or the placebo. Therefore, the complex nature of the unaligned outcome measures is inadequate for interpreting the efficacy of antidepressants in treating pain symptoms in PD. The third study focused solely on observing the effects of duloxetine but showed no favorable effects of this drug on pain. CONCLUSIONS: Prospective studies with a direct comparison of antidepressants and placebo should be conducted, focusing on pain-related scales and questions to understand further the role of antidepressants in treating pain in PD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".