Ultrasonography of Lumbar Multifidus Muscle in University American Football Players
Bibliographic record
Abstract
PURPOSE: The primary objective of this study was to examine and compare lumbar multifidus (LM) muscle size, asymmetry, and function in university football players with and without low back pain (LBP). A secondary objective was to examine the relationship between LM characteristics and body composition in football players. METHODS: Ultrasound assessments of the LM muscle were performed in 41 university football players during the preseason. LM muscle cross-sectional area, echo intensity (e.g., indicator of fatty infiltration and connective tissue), thickness at rest, and thickness during submaximal contraction (e.g., contralateral arm lift) measurements in prone and standing positions were obtained bilaterally at the L5-S1 level. Body composition measures were acquired using dual-energy x-ray absorptiometry. A self-administered questionnaire was used to obtain LBP history data. RESULTS: The LM muscle thickness at rest in prone and in standing was significantly smaller in football players who reported the presence of LBP in the previous 3 months. The LM cross-sectional area in prone was significantly and positively correlated with weight, height, lean body mass, total fat mass, and total percent body fat. LM echo intensity was strongly correlated with total percent body fat and total fat mass and negatively correlated with the percent thickness change during contraction. CONCLUSION: The results of this study provide novel information on LM muscle morphology and activation in football players in prone and standing and suggest that players with LBP in the previous 3 months had smaller LM muscle thickness. LM morphology was strongly correlated with body composition measurements.
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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 | 0.001 |
| 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".