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Record W1998149144 · doi:10.1097/brs.0b013e3181ac0045

Classification of Congenital Scoliosis and Kyphosis

2009· review· en· W1998149144 on OpenAlexfundno aff
Noriaki Kawakami, Taichi Tsuji, Shiro Imagama, Lawrence G. Lenke, Rolando M. Puno, Timothy R. Kuklo

Bibliographic record

VenueSpine · 2009
Typereview
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsnot available
FundersMcMaster University
KeywordsMedicineScoliosisKyphosisRachisPhysical medicine and rehabilitationPhysical therapySurgeryRadiography

Abstract

fetched live from OpenAlex

STUDY DESIGN: We reviewed three-dimensional (3D) computed tomography (CT) images of congenital spinal deformities and proposed a new classification based on the information obtained. OBJECTIVES: The purposes of this article were to clearly illustrate the limitations of two-dimensional classification, to summarize the clinical significance of 3D analysis of congenital vertebral anomalies, and to propose a new 3D classification of congenital vertebral anomalies. SUMMARY OF BACKGROUND DATA: The classification of congenital scoliosis or kyphosis were based on radiographic findings of plain radiograph images of congenital vertebral anomalies, it is sometimes difficult in classifying the large variety of anomalous vertebrae or severely twisted 3D curves. METHODS: Three-dimensional CT images of more than 150 patients with congenital spinal deformities were analyzed and compared with plain radiograph images. By developing the algorithm for the evaluation of malformed vertebrae in terms of numbers of abnormal vertebrae, type of formation failure, and type of segmentation failure in separate steps, we attempted to revise the classification of congenital spinal deformities. RESULTS: The images of plain radiograph cannot demonstrate the spatial relationship of each structure of the vertebrae. Three-dimensional findings in congenital-deformed vertebrae included several types of laminae and clearer definitions of each type of anomalous vertebrae. By developing an algorithm for the evaluation of congenital spinal deformity, congenital spinal deformity could be mainly classified into 4 types of congenital vertebral abnormalities: Type 1: solitary simple, Type 2: multiple simple, Type 3: complex, Type 4: segmentation failure. CONCLUSION: The large volume of information that can be obtained by evaluating 3D CT images of congenitally deformed vertebrae can be a great help in developing a strategy for surgical treatment. We need to develop a new classification of congenital scoliosis based on the perspective of 3D imaging to understand the etiology and embryology, as well as to determine an operative strategy.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.091
GPT teacher head0.385
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2009
Admission routes1
Has abstractyes

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