Core set of unfavorable events of shoulder arthroplasty: an international Delphi consensus process
Bibliographic record
Abstract
BACKGROUND: Shoulder arthroplasty (SA) complications require standardization of definitions and are not limited to events leading to revision operations. We aimed to define an international consensus core set of clinically relevant unfavorable events of SA to be documented in clinical routine practice and studies. METHODS: A Delphi exercise was implemented with an international panel of experienced shoulder surgeons selected by nomination through professional societies. On the basis of a systematic review of terms and definitions and previous experience in establishing an arthroscopic rotator cuff repair core set, an organized list of SA events was developed and reviewed by panel members. After each survey, all comments and suggestions were considered to revise the proposed core set including local event groups, along with definitions, specifications, and timing of occurrence. Consensus was reached with at least two-thirds agreement. RESULTS: Two online surveys were required to reach consensus within a panel involving 96 surgeons. Between 88% and 100% agreement was achieved separately for local event groups including 3 intraoperative (device, osteochondral, and soft tissue) and 9 postoperative event groups. Experts agreed on a documentation period that ranged from 3 to 24 months after SA for 4 event groups (peripheral neurologic, vascular, surgical-site infection, and superficial soft tissue) and that was lifelong until implant revision for other groups (device, osteochondral, shoulder instability, pain, late hematogenous infection, and deep soft tissue). CONCLUSION: A structured core set of local unfavorable events of SA was developed by international consensus to support the standardization of SA safety reporting. Clinical application and scientific evaluation are needed.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".