Constipation in Parkinson’s Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Constipation is a common nonmotor symptom of Parkinson's disease (PD) and has been reported to increase the risk of developing PD. However, previous studies have yielded conflicting results. Understanding this correlation may promote early diagnosis and treatment of PD, which could help patients improve their quality of life. This study aimed to investigate the association between constipation and PD onset. METHODS: The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines. We searched the Medline, Embase, Scopus, SINOMED, and Cochrane databases as well as specific journals from inception to September 2021 for observational studies that evaluated the association between constipation and the risk of PD. The Newcastle-Ottawa Scale was used to evaluate the methodological quality of the included studies. Associations were summarized as odds ratios (ORs) using a random-effects model. Subgroup, meta-regression, and sensitivity analyses were performed. RESULTS: Seventeen studies comprising 3,024,193 participants (case-control = 1,636,831; cohort = 1,387,362) were eligible for inclusion. The pooled OR for the association between constipation and PD was 2.36 (95% confidence interval: 1.93-2.88), although strong heterogeneity was observed (I2 = 90%, p < 0.01). Subgroup and meta-regression analyses indicated that study design and disease duration were the major sources of heterogeneity. A sensitivity analysis confirmed the stability of the outcomes. In addition, the prevalence of among those with prodromal PD was 20%, whereas it was only 11% in the control group (p < 0.01). Moreover, there were no significant age-based differences in constipation between the prodromal stage of PD patients and the controls (p > 0.05). CONCLUSION: Constipation has a relatively high incidence in the prodromal phase of PD and is associated with an increased risk of developing PD.
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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 | 0.015 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".