Effect of acute low back pain on the risk of chronicity, functional disability and flexibility of the lumbar spine in CrossFit practitioners: Cross-sectional study
Bibliographic record
Abstract
BACKGROUND:Nonspecific low back pain can become chronic over time. However, monitoring the chronicity of low back pain symptoms can be a major challenge for health professionals. AIM:To verify the effect of acute low back pain on the risk of chronicity and on clinical-functional changes in the lumbar spine in CrossFit practitioners. METHOD:A total of Sixty CrossFit practitioners were divided into two groups: the low back pain group–GL (n=30) and the control group–CG (n=30). The pain was assessed using the VAS and lumbar spine flexibility was assessed using the Schober and Stibor tests. The risk of chronic low back pain was assessed using the Start Back Screening Tool (SBST) questionnaire. The functionality of the lumbar spine was assessed using the Roland-Morris Disability Index questionnaire and the Quebec Back Pain Disability Questionnaire (QBPQ). An independent t-test was used to compare the measurements of the dependent variables between the groups. RESULTS:CrossFit practitioners with low back pain (LBP) showed elevated scores on the Start Back Screening Tool (SBST), indicating a greater risk of chronicity compared to the pain-free control group. Functional disability assessments also revealed significant differences, with the LBP group scoring higher on the Rolland Morris and Quebec questionnaires, indicating greater disability. Both groups demonstrated similar thoracic and lumbar spine mobility and flexibility. CONCLUSION:CrossFit practitioners with acute low back pain had a higher risk of chronicity and decreased functional disability when compared to the control group. Despite these differences, both groups demonstrated similar mobility and flexibility of the thoracic and lumbar spine.
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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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".