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Record W4416207306 · doi:10.1302/1358-992x.2025.13.118

INITIAL FINDINGS AFTER THE IMPLEMENTATION OF A REGIONAL SHOULDER ARTHROPLASTY REGISTRY

2025· article· en· W4416207306 on OpenAlexaffabout
Jarret M. Woodmass, Stephen Harris, Sheila McRae, Christiaan H. Righolt, Éric Bohm

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsPan Am Clinic
Fundersnot available
KeywordsArthroplastyElbowJoint replacementHip arthroplastyArthroplasty replacementComplicationJoint arthroplastyKnee replacement

Abstract

fetched live from OpenAlex

The volume of shoulder replacement procedures worldwide has increased dramatically over the last decade with growth exceeding rates reported for hip and knee. Arthroplasty registries are widespread and have contributed to reducing revision and complication rates. The Canadian Joint Replacement Registry (CJRR) was established in 2001 to capture information on the outcomes of hip and knee replacement care in Canada. There is currently no national total shoulder arthroplasty (TSA) database in Canada. The provincial (Blinded for Review) was initiated for total shoulder arthroplasty in 2017 with the goal of providing a model for national expansion. This study outlines the characteristics and patient-reported outcomes of procedures captured in the registry. All patients undergoing primary or revision anatomic TSA (aTSA) and reverse TSA (rTSA) in the province since 2017 were included. Emergent and hemi-arthroplasty cases were excluded. Patient-reported data were collected in-clinic at baseline, and by mail-out one year postoperatively and included the American Society of Shoulder and Elbow Surgeon Score (ASES), EuroQol five-dimension health survey (EQ-5D), satisfaction, and self-reported complications. Intra-operative arthroplasty related details were collected at the time of surgery with the surgeon signature required for completeness. ASES and EQ-5D were compared for primary aTSA and rTSA subgroups pre-operatively and postoperatively using a two-sample two-sided t-test. The provincial shoulder database included 985 TSA, of which 67% were aTSA (661/985). Overall, 94% (927/985) were primary and 6% (58/985) were revision procedures. Four primary patients (0.43%) were linked with revision cases within the first year following surgery (4/927). Eighty-nine percent of primary TSA patients (aTSA=92%; rTSA=81%) and 63% of revision TSA patients (aTSA=58%; rTSA=73%) reported being “Satisfied” or “Very Satisfied” one year postoperatively. The rate of patient-reported complications (dislocation/superficial infection/deep infection/future surgery) was lower for primary procedures (aTSA=1%; rTSA=2%) than revision procedures (aTSA=12%; rTSA=5%). There was significant improvement in both ASES and EQ-5D scores from the preoperative to postoperative timepoints in primary aTSA (ASES mean change 48.5 [95% CI 45.4 to 51.6]; p Primary TSA provided significant improvement in ASES and EQ-5D scores one year postoperatively. Greater improvement was observed in the primary aTSA subgroup compared to rTSA. Lower satisfaction and a higher prevalence of self-reported complications was observed in patients undergoing revision TSA, specifically when revised to an aTSA. This study outlines the successful implementation of a regional TSA registry in Canada and demonstrates the potential for a shoulder arthroplasty database to be integrated within the current CJRR system. Integration with larger administrative databases, improving patient response rates, and national expansion to other provinces within Canada are next steps for the shoulder arthroplasty registry.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.337
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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