DIAGNOSTIC AND TREATMENT DIFFERENCES AMONG EXPERIENCED SHOULDER SURGEONS FOR INSTABILITY CONDITIONS OF THE SHOULDER
Bibliographic record
Abstract
Expert North American shoulder surgeons were poled on the diagnosis and treatment of five shoulder conditions. To quantify inter-observer agreement in the diagnosis and treatment of shoulder instabilities, they chose one of five diagnostic conditions and one or more of seven treatment options. The greatest diagnostic and treatment differences were noted for a painful shoulder in a throwing athlete with subtle anterior instability and a patient with voluntary posterior instability with an asymptomatic sulcus sign. An arthroscopic approach was consistently preferred to open surgery. These inconsistencies highlight the need for standardized diagnostic criteria and more universal treatment plans. To quantify inter-observer agreement in the diagnosis and treatment of shoulder instabilities among expert North American shoulder surgeons. These inconsistencies, particularly in diagnosis, highlight the need for standardization of diagnostic criteria and guidelines working towards more universal treatments and evaluations of outcomes. The greatest diagnostic differences were noted for a painful shoulder in a throwing athlete with subtle anterior instability(Ksc0.46, 55% agreement) and a patient with voluntary posterior instability with an asymptomatic sulcus sign(Ksc0.41, 50% agreement). The presence of an asymptomatic sulcus sign alone may have been mistakenly interpreted as inferior instability rather than inferior laxity. There was a high level of agreement in diagnosing anterior and bi-directional instability. An arthroscopic approach to treatment was consistently preferred to open surgery. The greatest differences in treatment choice were for the throwing athlete(Ksc0.38, 47% agreement on arthroscopic repair), a patient with voluntary posterior instability(Ksc0.34, 43% agreement on arthroscopic capsular repair) and a patient with bi-directional instability(Ksc0.23, 34% agreement on arthroscopic anterior Bankart repair). Active members of the American Shoulder and Elbow Surgeons and JOINTS Canada (Orthopaedic Initiatives for National Trials of the Shoulder) were poled on the diagnosis and treatment of five shoulder conditions. They were to choose one of five conditions and one or more of seven treatment options. A Kappa coefficient of agreement was used to assess inter-observer reliability; a Ksc of 1 denotes perfect agreement on a category and a Ksc of −1 denotes perfect agreement on not endorsing a category.
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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 | 0.020 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".