Two Methods of Forward Head Posture Assessment: Radiography vs. Posture and Their Clinical Comparison
Bibliographic record
Abstract
Background: Forward head posture (FHP) and altered cervical lordotic curvatures are common spine displacements often associated with neck pain and disability. Two primary categories for determining FHP exist: radiographic and postural measurements. Methods: This study investigated the correlation between the craniovertebral angle (CVA), the radiographically measured C2–C7 sagittal vertical axis (SVA), and cervical lordosis (absolute rotation angle: ARA C2–C7) in a sample of participants with chronic myofascial pain (CMP). In 120 participants, we performed both a postural measurement of the CVA and a lateral cervical radiograph, where the C2–C7 SVA and ARA C2–C7 were measured. A linear-regression R2 value to assess the correlation between the CVA, C2–C7 SVA, and ARA C2–C7 was sought. Results: A statistically significant weak linear fit was identified (Spearman’s r = 0.549; R2 = 0.30, p < 0.001) between the CVA and C2–C7 SVA, having considerable variation between the two measures. A statistically significant linear fit (very weak) was identified for the lordosis ARA C2–C7 and the CVA: Spearman’s r = 0.524; R2 = 0.275; p < 0.001. A value of 50° for the CVA corresponded to a value of 20 mm for the C2–C7 SVA on an X-ray. Conclusion: While the CVA and radiographic C2–C7 SVA are weakly correlated in an individual, they seem to represent different aspects of sagittal cervical balance. The CVA cannot replace radiographically measured cervical lordosis. We recommend that more emphasis be given to radiographic measures of sagittal cervical alignment than the CVA when considering patient interventions.
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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 | 0.022 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".