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Record W2955615011 · doi:10.1016/j.jses.2019.05.001

Reliability of a novel 3-dimensional computed tomography method for reverse shoulder arthroplasty postoperative evaluation

2019· article· en· W2955615011 on OpenAlexafffund
Gabriel Venne, Michael Pickell, Randy E. Ellis, Ryan T. Bicknell

Bibliographic record

VenueJSES Open Access · 2019
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsKingston General HospitalQueen's UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScapulaRadiographyMedicineIntraclass correlationReliability (semiconductor)Nuclear medicineArthroplastyImplantOrthodonticsRadiologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Long-term function and survival of reverse shoulder arthroplasties (RSAs) are reliant on component positioning and fixation. Conventional postoperative analysis is performed using plain radiographs or 2-dimensional (2D) computed tomography (CT) images. Although 3-dimensional (3D) CT would be preferred, its use is limited by metal artifacts. This study proposes a new 3D CT method for postoperative RSA evaluation and compares its interobserver reliability with conventional methods. MATERIALS AND METHODS: Preoperative and postoperative CT scans, as well as postoperative radiographs, were obtained from 18 patients who underwent RSA implantation; the scapula, implant, and screws were reconstructed as 3D CT models. The postoperative 3D scapula and implant were imported into preoperative coordinates and matched to the preoperative scapula. Standardized scapula coordinates were defined, in which the glenoid baseplate version and inclination angle were measured. The percentage of screw volume in bone was measured from a Boolean intersection operation between the preoperative scapula and screw models. Four independent reviewers performed the measurements using 3D CT and conventional 2D methods. Intraclass correlation coefficients (ICCs) were used to compare the reliability of the methods. RESULTS: The 3D CT method showed excellent reliability (ICC > 0.75) in baseplate inclination (ICC = 0.92), version (ICC = 0.97), and screw volume in bone (ICC = 0.99). Conventional 2D methods demonstrated poor reliability (ICC < 0.4). For radiographs, inclination showed poor reliability (ICC = 0.09) and the screw percentage in bone showed fair reliability (ICC = 0.54). Version was not measured with plain radiographs. For 2D CT slice measurements, inclination showed poor reliability (ICC = 0.02), version showed excellent reliability (ICC = 0.81), and the screw percentage in bone showed poor reliability (ICC = 0.28). CONCLUSION: The new 3D CT-based method for evaluating RSA glenoid implant positioning and screw volume in bone showed excellent reliability and overcame the metal-artifact limitation of postoperative CT and 3D CT reconstruction.

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)0.001
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 score0.097
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.105
GPT teacher head0.473
Teacher spread0.367 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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