Gastrointestinal Dysfunctions in Parkinson’s Disease: Symptoms and Treatments
Bibliographic record
Abstract
A diagnosis of Parkinson's disease is classically established after the manifestation of motor symptoms such as rigidity, bradykinesia, and tremor. However, a growing body of evidence supports the hypothesis that nonmotor symptoms, especially gastrointestinal dysfunctions, could be considered as early biomarkers since they are ubiquitously found among confirmed patients and occur much earlier than their motor manifestations. According to Braak's hypothesis, the disease is postulated to originate in the intestine and then spread to the brain via the vagus nerve, a phenomenon that would involve other neuronal types than the well-established dopaminergic population. It has therefore been proposed that peripheral nondopaminergic impairments might precede the alteration of dopaminergic neurons in the central nervous system and, ultimately, the emergence of motor symptoms. Considering the growing interest in the gut-brain axis in Parkinson's disease, this review aims at providing a comprehensive picture of the multiple gastrointestinal features of the disease, along with the therapeutic approaches used to reduce their burden. Moreover, we highlight the importance of gastrointestinal symptoms with respect to the patients' responses towards medical treatments and discuss the various possible adverse interactions that can potentially occur, which are still poorly understood.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".