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A Noninvasive Anthropometric Technique for Measuring Kyphosis and Lordosis

2000· article· en· W1981530806 on OpenAlexaff
Michel Leroux, Karl Zabjek, Geneviève Simard, J. Badeaux, Christine Coillard, Charles H. Rivard

Bibliographic record

VenueSpine · 2000
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineKyphosisSagittal planeLordosisOrthodonticsScoliosisSpinal CurvaturesIntraclass correlationRadiographyAnthropometryCobb angleAnatomySurgeryInternal medicine

Abstract

fetched live from OpenAlex

STUDY DESIGN: Cross-sectional measurement of the sagittal geometry of adolescent idiopathic scoliosis patients. OBJECTIVES: To evaluate the accuracy of a noninvasive anthropometric approach for the measurement of kyphosis and lordosis. SUMMARY OF BACKGROUND DATA: Noninvasive approaches were developed to estimate the sagittal curvatures of the spine. However, the magnitude of the estimation error could be high for an important proportion of patients, which leads to a difficult clinical application. METHODS: The group was composed of 124 female patients with a mean age of 13.5 years (SD 2. 7 years) with Cobb angles ranging from 4 degrees to 66 degrees. Kyphosis and lordosis were measured on the lateral radiograph. The spine sagittal curvature of the same patients was also estimated using the spatial localization of skin markers placed overlying the spinous processes. These coordinates served as input into a simple trigonometric model. Data were collected by means of a stereovideographic technique (Motion Analysis Corp., Santa Rosa, CA). RESULTS: The intraclass correlation coefficient between both approaches was 0.94 for kyphosis and 0.91 for lordosis; the mean absolute differences were 5 degrees (SD 4 degrees ) and 6 degrees (SD 6 degrees ), respectively. The difference was less than 10 degrees in 91% of the patients for kyphosis, and in 79% for lordosis. CONCLUSIONS: The proposed technique appears to give more representative results than those presented in the literature. It has the advantage of being part of a global noninvasive postural evaluation. Using this approach in a systematic manner could help reduce radiograph exposure while keeping track of the spine sagittal curvatures.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.305
Teacher spread0.269 · 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 designBench or experimental
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

Citations125
Published2000
Admission routes1
Has abstractyes

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