Lumbar Multifidus Characteristics in University Level Athletes May be Predictors of Low Back Pain and Lower Limb Injury
Bibliographic record
Abstract
Introduction: Low back pain (LBP) is highly prevalent in athletes, with decreased lumbar multifidus (LM) crosssectional area (CSA) reported in athletes with LBP and lower limb injury (LLI) as well as decreased LM thickness in athletes with LLI. Previous research has only investigated connections between LM, LBP, and LLI in small samples of athletes in a single sport at a time. This study aimed to (1) examine LM morphology and function across a general sample of male and female university level varsity athletes; (2) investigate whether LM characteristics were predictors of LBP and LLI. Methods: Ultrasound images of LM at L5 were acquired in prone and standing. Body composition was assessed with DEXA and a self-reported questionnaire provided demographics and history of injury. Paired t-tests and independent t-tests compared LM measurements between the sides and sex, respectively. Univariate and multivariate logistic regression analyses were used to assess possible LM characteristic predictors of LBP and LLI. Results: 134 university varsity athletes were evaluated. LM CSA was larger on the non-dominant side in prone. Increased LM thickness was associated with decreased odds of LBP in the previous 4-week (OR=0.49 [0.27, 0.88], p=0.02) and 3-month (OR=0.43 [0.21, 0.89], p=0.02) in the multivariable model, while a greater number of years playing at the university level was associated with increased odds of LBP (OR=1.29 [1.01, 1.65], p=0.04). Greater LM CSA asymmetry (OR=1.14 [1.01, 1.28], p=0.03) and sport (OR=1.44 [1.04, 1.96], p=0.02) were significant predictors of LLI in the previous 12 months. Conclusion: Leg dominance may play a role in unilateral differences. LM thickness and LM CSA asymmetry were predictors of injury. Preseason screening of LM morphology and function could help identify athletes at risk of LBP and LLI, allowing coaches, medical staff, and training staff to target these individuals and provide specific injury prevention programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.004 | 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".