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Record W4386446554 · doi:10.1016/j.jseint.2023.08.005

Preoperative planning with three-dimensional CT vs. three-dimensional magnetic resonance imaging does not change surgical management for shoulder instability

2023· article· en· W4386446554 on OpenAlexaff
Alexandra V. Paul, Imoh Udoh, Ananyaa Bharadwaj, Steven L. Bokshan, Brett D. Owens, William N. Levine, Grant E. Garrigues, Jeffrey S. Abrams, Patrick J. McMahon, Anthony Miniaci, Sameer Nagda, Jonathan P. Braman, Peter B. MacDonald, Jonathan C. Riboh, Scott G. Kaar, Brian C. Lau

Bibliographic record

VenueJSES International · 2023
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversity of ManitobaPan Am Clinic
Fundersnot available
KeywordsMagnetic resonance imagingInstabilityMedicineSurgical planningRadiologyPhysicsMechanics

Abstract

fetched live from OpenAlex

Background This study aims to determine the effect of time and imaging modality (three-dimensional (3D) CT vs. 3D magnetic resonance imaging (MRI)) on the surgical procedure indicated for shoulder instability. The hypothesis is there will be no clinical difference in procedure selection between time and imaging modality. Methods Eleven shoulder surgeons were surveyed with the same ten shoulder instability clinical scenarios at three time points. All time points included history of present illness, musculoskeletal exam, radiographs, and standard two-dimensional MRI. To assess the effect of imaging modality, survey 1 included 3D MRI while survey 2 included a two-dimensional and 3D CT scan. To assess the effect of time, a retest was performed with survey 3 which was identical to survey 2. The outcome measured was whether surgeons made a "major" or "minor" surgical change between surveys. Results The average major change rate was 14.1% (standard deviation: 7.6%). The average minor change rate was 12.6% (standard deviation: 7.5%). Between survey 1 to the survey 2, the major change rate was 15.2%, compared to 13.1% when going from the second to the third survey ( P = .68). The minior change rate between the first and second surveys was 12.1% and between the second to third interview was 13.1% ( P = .8). Discussion The findings suggest that the major factor related to procedural changes was time between reviewing patient information. Furthermore, this study demonstrates that there remains significant intrasurgeon variability in selecting surgical procedures for shoulder instability. Lastly, the findings in this study suggest that 3D MRI is clinically equivalent to 3D CT in guiding shoulder instability surgical management. Conclusion This study demonstrates that there is significant variability in surgical procedure selection driven by time alone in shoulder instability. Surgical decision making with 3D MRI was similar to 3D CT scans and may be used by surgeons for preoperative planning.

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)0.003
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.338
Teacher spread0.292 · 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 designNon-randomized trial
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

Citations3
Published2023
Admission routes1
Has abstractyes

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