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Record W2317899863 · doi:10.1097/brs.0000000000001042

The Influence of Spine Surgeons’ Experience on the Classification and Intraobserver Reliability of the Novel AOSpine Thoracolumbar Spine Injury Classification System

2015· article· en· W2317899863 on OpenAlexaff
Said Sadiqi, F. Cumhur Öner, Marcel F. Dvorak, Bizhan Aarabi, Gregory D. Schroeder, Alexander R. Vaccaro

Bibliographic record

VenueSpine · 2015
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsUniversity of British Columbia
FundersAOSpine
KeywordsMedicineKappaReliability (semiconductor)Grading (engineering)Cohen's kappaOrthopedic surgerySurgeryPhysical therapyStatistics

Abstract

fetched live from OpenAlex

STUDY DESIGN: International validation study. OBJECTIVE: To investigate the influence of the spine surgeons' level of experience on the intraobserver reliability of the novel AOSpine Thoracolumbar Spine Injury Classification system, and the appropriate classification according to this system. SUMMARY OF BACKGROUND DATA: Wide variability has been demonstrated for intraobserver reliability of the AOSpine classification system. The spine surgeons' level of experience may play a crucial role in the appropriate classification of thoracolumbar fractures, and the degree of reproducibility of the same observer on separate occasions. However, this has not been previously investigated. METHODS: After a training on the classification system, high quality CT images together with clinical data from 25 patients with thoracolumbar fractures were independently assessed by 100 spine surgeons from across the world on 2 different occasions, 1 month apart from each other. The spine surgeons were allocated to a subgroup, according to their years of experience. Intraobserver reliability was calculated for each individual surgeon and for each subgroup, using the Kappa statistics (κ). Descriptive statistics was used to describe any differences between the subgroups. Analysis of any misclassifications was performed by calculating sensitivity and specificity estimates. RESULTS: Almost all surgeons demonstrated at least moderate intraobserver reliability. All surgeon subgroups demonstrated substantial reliability (κ = 0.67-0.69) for fracture subtype grading, and almost all subgroups demonstrated excellent reliability (κ = 0.79-0.83) for fracture morphology type regardless of subtype identified. In general, the fractures were most frequently misclassified by the most experienced surgeons. No major differences were observed among the subgroups when comparing the sensitivity and specificity rates. CONCLUSION: This international study demonstrated that the spine surgeons' level of experience does not substantially influence the classification and intraobserver reliability of the recently described AOSpine Thoracolumbar Spine Injury Classification System. LEVEL OF EVIDENCE: 4.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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

Citations31
Published2015
Admission routes1
Has abstractyes

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