Analysis of the Sagittal Balance of the Spine and Pelvis Using Shape and Orientation Parameters
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to introduce a method to analyze and characterize the global sagittal balance of the human trunk using indexes derived from the shape and orientation of the pelvis and cervical, thoracic, and lumbar spine. METHODS: Standing lateral x-rays of a cohort of 160 asymptomatic young adult volunteers were obtained. On each radiograph, a simplified model of the spine and pelvis was created using a dedicated computer software, and the following shape and orientation variables were calculated at each anatomic level: pelvic incidence, pelvic tilt, sacral slope, cervical curvature and tilt, thoracic curvature and tilt, and lumbar curvature and tilt. RESULTS: Significant linear correlations were found between each single adjacent shape parameter as well as between each single adjacent orientation parameter at all anatomic levels. Significant correlations were also found between some shape and orientation parameters at the same anatomic level as well as between adjacent anatomic areas. In general, the linear correlations were stronger between shape and orientation variables at the pelvic, lumbar, and cervical areas and weaker at the thoracic level and between the thoracic and lumbar areas. CONCLUSIONS: These results confirm that the pelvis and spine in the sagittal plane can be considered as a linear chain linking the head to the pelvis where the shape and orientation of each anatomic segment are closely related and influence the adjacent segment to maintain a stable posture with a minimum of energy expenditure. Changes in shape or orientation at one level will have a direct influence on the adjacent segment. Knowledge of these normal relationships is of prime importance for the comprehension of sagittal balance in normal and pathologic conditions of the spine and pelvis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".