Clinical features and relative factors of constipation in a cohort of Chinese patients with Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Constipation as a most common non-motor symptom of Parkinson's disease (PD), has a higher prevalence compared to the general population. The etiologies of constipation in PD are diverse. In addition to physical weakness and other factors of disease, the lifestyles and eating habits are also important factors. Therefore, the prevalence and influencing factors of constipation may vary among different populations. AIM: To determine the prevalence of constipation and analyze relative factors in a cohort of Chinese patients with PD. METHODS: All the patients diagnosed with PD according to the movement disorders society criteria were consecutively collected by a self-developed questionnaire. Rome III diagnostic criteria were used to assess functional constipation and Wexner score was used to estimate the severity of constipation. Non-motor symptoms (NMS) were assessed with the non-motor symptoms assessment scale (NMSS). Unified Parkinson's disease Rating Scale III (UPDRS III) was used to evaluate the severity of motor symptoms. The modified Hoehn-Yahr stage was used to evaluate the severity of PD. Cognitive function was assessed using Montreal cognitive assessment (MoCA). Depression and anxiety were rated with the Hamilton depression scale (HAMD) and the Hamilton anxiety scale (HAMA). Quality of life was assessed using the Parkinson's disease Questionnaire-39 items (PDQ-39). RESULTS: < 0.001). CONCLUSION: Our findings confirm that constipation has a relatively high frequency in patients with PD. PD patients with constipation have a higher incidence of depression, which leads to worse quality of life.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".