Systematic review of imaging comparisons of spinal alignment among standing positions in healthy adolescents or adolescents with idiopathic scoliosis: SOSORT 2023 award winner
Bibliographic record
Abstract
PURPOSE: Clinicians detect scoliosis worsening over time using frequent radiographs during growth. Arms must be elevated when capturing sagittal radiographs to visualize the vertebrae, and this may affect the sagittal angles. The aim was to systematically review the published evidence of the effect of arm positions used during radiography on spinal alignment parameters in healthy participants and those with AIS. METHODS: Design was registered in PROSPERO (CRD42022347494). A search strategy was run in Medline, Embase, CINAHL, and Web of Science. Healthy participants ≥ 10 years old and participants with AIS between 10 and 18 years old, with Cobb angles > 10° were included. Study quality was assessed using the Appraisal tool for Cross-Sectional Studies (AXIS). Meta-analysis was performed where possible. RESULTS: Overall, 1332 abstracts and 33 full texts were screened. Data was extracted from 7 included studies. The most common positions were habitual standing, fists on clavicle, and active (arms raised unsupported). Kyphosis, lordosis, and sagittal vertical axis (SVA) were most measured. Meta-analysis showed significantly decreased kyphosis (SMD = 0.78, 95%CI 0.48, 1.09) and increased lordosis (SMD = - 1.21, 95%CI - 1.58, - 0.85) when clavicle was compared to standing. Significant posterior shifts in SVA were shown in clavicle compared to standing (MD = 30.59 mm, 95%CI 23.91, 37.27) and active compared to clavicle (MD = - 2.01 mm, 95%CI - 3.38, - 0.64). Cobb angles and rotation were rarely studied (1 study). CONCLUSION: Meta-analysis evidence showed elevated arm positions modify sagittal measurements compared to standing. Most studies did not report on all relevant parameters. It is unclear which position best represent habitual standing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".