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Record W1543111258 · doi:10.3171/2014.7.peds13591

Estimation of normal computed tomography measurements for the upper cervical spine in the pediatric age group

2014· article· en· W1543111258 on OpenAlexaff
Shobhan Vachhrajani, Anish N. Sen, Krishna B. Satyan, Abhaya V. Kulkarni, Sherri Birchansky, Andrew Jea

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineSagittal planeCoronal planeCervical spineConfidence intervalNuclear medicineCervical vertebraeSoft tissueRadiologySurgery

Abstract

fetched live from OpenAlex

OBJECT: Upper cervical spine injuries in the pediatric age group have been recognized as extremely unstable from ligamentous disruption and as potentially lethal. Few measurement norms have been published for the pediatric upper cervical spine to help diagnose this pathological state. Instead, adult measurement techniques and results are usually applied inappropriately to children. The authors propose using high-resolution reconstructed CT scans to define a range of normal for a collection of selected upper cervical spine measurements in the pediatric age group. METHODS: Sagittal and coronal reformatted images were obtained from thin axial CT scans obtained in 42 children (< 18 years) in a 2-month period. There were 25 boys and 17 girls. The mean age was 100.9 months (range 1-214 months). Six CT scans were obtained for nontrauma indications, and 36 were obtained as part of a trauma protocol and later cleared for cervical spine injury. Six straightforward and direct linear distances-basion-dental interval (BDI); atlantodental interval (ADI); posterior atlantodental interval (PADI); right and left lateral mass interval (LMI); right and left craniocervical interval (CCI); and prevertebral soft-tissue thickness at C-2-that minimized logistical and technical distortions were measured and recorded. Statistical analysis including interobserver agreement, age stratification, and sex differences was performed for each of the 6 measurements. RESULTS: The mean ADI was 2.25 ± 0.24 mm (± SD), the mean PADI was 18.3 ± 0.07 mm, the mean BDI was 7.28 ± 0.10 mm, and the mean prevertebral soft tissue width at C-2 was 4.45 ± 0.43 mm. The overall mean CCI was 2.38 ± 0.44 mm, and the overall mean LMI was 2.91 ± 0.49 mm. Linear regression analysis demonstrated statistically significant age effects for PADI (increased 0.02 mm/month), BDI (decreased 0.02 mm/month), and CCI (decreased 0.01 mm/month). Similarly significant effects were found for sex; females demonstrated on average a smaller CCI by 0.26 mm and a smaller PADI by 2.12 mm. Moderate to high interrater reliability was demonstrated across all parameters. CONCLUSIONS: Age-dependent and age-independent normal CT measurements of the upper cervical spine will help to differentiate physiological and pathological states in children. The BDI appears to change significantly with age but not sex; on the other hand, the LMI and ADI appear to be age-independent measures. This preliminary study suggests acceptable levels of interrater reliability, and further expanded study will aim to validate these measurements to produce a profile of normal upper cervical spine measurements in children.

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.033
GPT teacher head0.289
Teacher spread0.256 · 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 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

Citations32
Published2014
Admission routes1
Has abstractyes

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