2021 consensus statement for preventing and managing low back pain in elite and subelite adult rowers
Bibliographic record
Abstract
PURPOSE: To synthesise evidence on low back pain (LBP) in adult rowers and to create a consensus statement to inform clinical practice. METHODS: There were four synthesis steps that informed the consensus statement. In step one, seven expert clinicians and researchers established the scope of the consensus statement and conducted a survey of experienced and expert clinicians to explore current practice. In step two, working groups examined current evidence relating to key scope questions and summarised key issues. In step three, we synthesised evidence for each group and used a modified Delphi process to aid in the creation of the overall consensus statements. Finally, in step four, we combined information from step three with the findings of the clinician survey (and with athlete and coach input) to produce recommendations for clinical practice. RESULTS: The scope of the consensus statement included epidemiology; biomechanics; management; the athlete's voice and clinical expertise. Prevention and management of LBP in rowers should include education on risk factors, rowing biomechanics and training load. If treatment is needed, non-invasive management, including early unloading from aggravating activities, effective pain control and exercise therapy should be considered. Fitness should be maintained with load management and progression to full training and competition. The role of surgery is unclear. Management should be athlete focused and a culture of openness within the team encouraged. CONCLUSION: Recommendations are based on current evidence and consensus and aligned with international LBP guidelines in non-athletic populations, but with advice aimed specifically at rowers. We recommend that research in relation to all aspects of prevention and management of LBP in rowers be intensified.
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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 | 0.148 | 0.184 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.021 | 0.016 |
| Insufficient payload (model declined to judge) | 0.015 | 0.016 |
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".