Handgrip strength in Parkinson’s disease: A systematic review of observational studies
Bibliographic record
Abstract
Abstract Introduction People with Parkinson’s disease may pre-sent muscle weakness. The handgrip test is used to identify upper limbs strength. There are different protocol descriptions of this assessment. Objective To carry out a systematic review on the assessment of handgrip strength in people with Parkinson’s. Methods The review was carried out according to the PRISMA guidelines, the PubMed, SciELO, LILACS and Scopus literary databases, and registered at PROSPERO (CRD420201 9018). Quantitative analysis was performed using the Newcastle-Ottawa Scale. Twenty-seven articles were analyzed. Results The most referenced protocol is that of the American Society of Hand Therapists. The most used instrument is the hydraulic dynamometer. Of the sixteen studies that compared handgrip strength be-tween people with Parkinson’s and healthy people, seven identified a statistically significant difference. No article was classified as unsatisfactory. Conclusion It is not possible to affirm that handgrip strength is reduced in Parkinson’s disease, when compared to healthy subjects. Protocol and instrument standardization can help com-parisons between results from different studies. There are few longitudinal studies, making it difficult to under-stand what happens to handgrip strength as the disease progresses.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".