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Record W4401594595 · doi:10.1177/2325967124s00097

Poster 128: Time to Achievement of Clinically Significant Outcomes Following Open Latarjet

2024· article· en· W4401594595 on OpenAlexaboutno aff
Vahram Gamsarian, Vikranth Mirle, Daanish Khazi-Syed, Joshua Chang, Christopher M. Brusalis, Adam B. Yanke, Brian J. Cole, Nikhil N. Verma, Gregory P. Nicholson, Grant E. Garigues, Brian Forsythe

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLatarjet procedureSurgeryAnterior shoulder

Abstract

fetched live from OpenAlex

Objective: To comprehensively define the time required to achieve outcomes (CSOs) after open Latarjet. The primary outcome was to identify an evidence-based timepoint for functional recovery, including the time needed to attain minimally clinically important difference (MCID) and patient acceptable symptomatic state (PASS) for open Latarjet. Methods: Patients who underwent open Latarjet between 2016 and 2022 were collected. Those with completed preoperative and at least 1 post-operative (3-month, 6-month, 1 year, and 2 years) Patient-Reported Outcome Measures (PROMs), including American Shoulder and Elbow Surgeons (ASES), Single Assessment Numeric Evaluation (SANE), or Western Ontario Shoulder Instability (WOSI) were included. Exclusion criteria included patients with significant concomitant procedures, or prior ipsilateral Latarjet procedure. MCID and PASS for each PROM were identified from prior literature and utilized as a threshold needed to attain functional recovery. The time needed to achieve CSO was then calculated and plotted using Kaplan-Meier survival analysis. Hazard ratios from multivariate Cox regression identified demographic and intraoperative factors predictive of the delayed time required to achieve MCID and PASS. Results: The average patient was 27 years old, male (85%), and white (87%). The majority of patients (62%) had prior ipsilateral arthroscopic instability repair, which had either failed to resolve subluxation symptoms or was successful for an extended period of time, until the patient suffered subsequent acute trauma. Of the 79 included patients, 69 patients had completed SANE forms, and 43 had completed WOSI forms. Patients attained SANE achievement rates of 68% for MCID and 49% for PASS, and WOSI achievement rates of 83.7% for MCID and 55.8% for PASS. Median achievement time across all surveys (SANE, WOSI, and ASES) ranged between 5.0-5.7 months for MCID, and between 5.2–5.9 months for PASS. Averages for achievement time for MCID ranged from 5.8–7.7 months, and for PASS from 6.4–8.2 months, in respective PRO surveys. Multivariate Cox regression identified workers’ compensation status, AC joint tenderness, and 3 prior shoulder dislocations as predictors of early clinically significant outcome achievement (hazard ratio: 3.20-43.2), whereas severe bone loss, higher preoperative scores, and root and flap tears predicted delays in clinically significant outcome achievement (hazard ratio: 0.17-0.82). Conclusions: The majority of patients (57.5%) undergoing open Latarjet achieved benefit within 6 months of surgery (overall median: 5.5 months; overall average: 7.4 months), with diminishing proportions at later timepoints. Several patient conditions that could be used as proxies for severity at presentation (bone loss, 2+ AC joint tenderness, and several dislocation events) illustrated improved time to CSO, specifically for MCID, but not for PASS. The timeline for achieving improvement that was established by this study may aid in setting patient expectations and designing future outcome studies involving open Latarjet.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.343
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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