A Systematic Review of Shoulder Arthroplasty in Parkinson's Disease
Bibliographic record
Abstract
Background: Parkinson's disease is a degenerative neurological disorder that can cause both motor and nonmotor symptoms. Motor symptoms are associated with increasing the patient's falls risk. Shoulder arthroplasty surgery in this patient cohort is associated with more complications than non-Parkinsonian patients. We sought to identify any increase in complications associated with this patient cohort and any surgical considerations that ought to be taken in light of their disease process. Methods: We performed a systematic review of articles using PubMed, MEDLINE, Cochrane Central, and Google Scholar. All studies which included any shoulder arthroplasty surgery for patients with Parkinson's disease were included. Results: Complication rates were higher in patients with Parkinson's disease than in the normal arthroplasty cohort in all studies. There was significant heterogeneity between all 8 studies included in the systematic review. Complication rates ranged from 26% to 100%. Complications included subluxation, loosening, malunion, nonunion, scapular notching, stiffness, fracture, baseplate failure, dislocation, and infection. Reoperation rates ranged from 5% to 29%. Conclusion: Compared to patients without Parkinson's disease undergoing shoulder arthroplasty, patients with Parkinson's disease achieved similar reductions in pain but inferior clinical function. The range of movement was less predictable, and complication rates were significantly higher in Parkinson's disease patients. This study will aid the surgeon and patient regarding surgical intervention, informed consent, and allow the surgeon to anticipate potential complications of shoulder arthroplasty in this patient cohort.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".