Assessment of Lumbar Spine Height Following Sustained Lumbar Extension Posture: Comparison Between Musculoskeletal Ultrasonography and Stadiometry
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to correlate sitting height measured by stadiometry with lumbar spine height (LSH) modifications measured by musculoskeletal ultrasonography (MSU). METHODS: Eighteen healthy young adults were recruited for this study (mean age: 21.5 ± 1.5 years). All subjects were tested in the following sequence: (1) lying supine for 10 minutes, (2) sitting under loaded (9.5 kg) and unloaded conditions for 5 minutes each, (3) lying supine for 15 minutes with passive lumbar extension, and (4) sitting unloaded for 5 minutes. Both stadiometry and MSU measurements were taken after each step of the testing sequence. RESULTS: Following the loaded sitting step, sitting height (measured by stadiometry) decreased by 3.4 ± 1.6 mm, whereas following sustained lumbar extension, sitting height increased by 5.4 ± 3.5 mm (P < .05). Following loaded sitting and sustained lumbar extension, LSH decreased by 3.8 ± 1.7 mm and increased by 6.2 ± 4.1 mm, respectively (P < .05). On the basis of the mean differences (between the different steps of the testing sequence), the mean correlation coefficient and the mean coefficient of determination between stadiometry and MSU measurements were calculated at 0.93 ± 0.07 and 0.88 ± 0.13, respectively, and no statistical differences were observed (P > .05). CONCLUSIONS: In vivo measurements of sitting height changes, measured using stadiometry, were strongly correlated with LSH changes, measured using ultrasonography.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".