Factors Affecting Pain in Patients with Parkinson's Disease: a Systematic Review
Bibliographic record
Abstract
Background Pain is a common non-motor symptom in patients with Parkinson's disease (PD) , which has a serious impact on patients' quality of life. Current scholars have explored the factors influencing the occurrence of pain in patients with PD, but there is some variability in the findings. Objective To evaluate the influencing factors of pain in PD patients. Methods We searched the CNKI, Wanfang Data, VIP, SinoMed, Web of Science, PubMed, Medline, Embase and Cochrane Library databases for studies on factors influencing pain in patients with PD from database establishment to April 12, 2022. Two researchers independently conducted literature screening and relevant information extraction. We used the Agency for Healthcare Research and Quality (AHRQ) Scale and the Newcastle-Ottawa Scale (NOS) to evaluate the risk of bias in cross-sectional studies and case-control studies, respectively. We performed a descriptive analysis of all influencing factors of pain, and implemented a meta-analysis of these influencing factors using RevMan 5.3. Results Sixteen studies were finally included, with a total sample size of 2 855 cases, and 24 influencing factors of pain identified. There were two protective factors and 22 risk factors in descriptive analysis. The meta-analysis showed that, female〔OR=3.73, 95%CI (1.75, 7.96) , P=0.000 7〕, long duration of PD〔OR=1.35, 95%CI (1.15, 1.60) , P=0.000 3〕, depressed mood 〔OR=1.14, 95%CI (1.07, 1.22) , P<0.000 01〕, high UPDRS Ⅲ score〔OR=1.07, 95%CI (1.03, 1.11) , P=0.000 2〕, advanced Hoehn-Yahr stages〔OR=2.28, 95%CI (1.28, 4.04) , P=0.005〕, and high NMSS score〔OR=1.68, 95%CI (1.46, 1.93) , P<0.000 01〕 were risk factors for pain in PD patients. The GRADE analysis showed that the quality of evidence for the effects of gender and NMSS score on pain was moderate, and that for the effects of duration of PD, depressed mood and UPDRSⅢ score on pain was low, and that for the effect of Hoehn-Yahr stage on pain was very low. Conclusion Female, long duration of PD, depressed mood, motor impairment, advanced Hoehn-Yahr stages and other severe non-motor symptoms (sleep disturbance, fatigue) are risk factors for pain in PD patients, which need to be further validated by high-quality, large-sample studies in the future.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".