5 Frontal plane femoral adduction during single-leg landing and low back pain in young athletes: a prospective profits cohort study
Bibliographic record
Abstract
Introduction Prospective studies investigating risk factors for low back pain (LBP) in young athletes are limited. The aim of this prospective cohort study was to investigate the association between LBP and selected biomechanical factors and postural stability during dynamic movement tasks in young athletes. Materials and methods 396 young floorball and basketball players (mean age 15.8±1.9) were included and followed prospectively for 1–3 years (2011–2014). In the beginning of every study year the players were tested. The physical tests included single-leg squat (SLS), single-leg vertical drop jump (SLVDJ), vertical drop jump (VDJ) and Star Reach Excursion Balance Test (SEBT). Individual exposure time and LBP resulting in time-loss were recorded prospectively. Cox’s proportional hazard models with mixed effects and time-varying risk factors were used. Results In SLVDJ landing with non-dominant leg, the risk for general LBP and non-traumatic LBP in specific, was significantly higher with increased femoral adduction (HR 1.10, 95% CI 1.02–1.19 and HR 1.12, 95% CI 1.03–1.22, respectively) and significantly lower with increased in femur-pelvic angle (FPA; angle-between pelvis and femur) (HR 0.93, 95% CI 0.88–0.99 and HR 0.92, 95% CI 0.86–0.99, respectively). However, the ROC analysis revealed poor combined sensitivity and specificity for femoral adduction and for FPA. Conclusions Increased femoral adduction and decreased FPA during SLVDJ landing are associated with risk of LBP in young team ball players. However, the identified risk factors do not discriminate players with or without future LBP well enough and therefore further studies on effect of neuromuscular training on lumbo-pelvic control and LBP incidence are warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".