Jumping into recovery: A systematic review and meta‐analysis of discriminatory and responsive force plate parameters in individuals following anterior cruciate ligament reconstruction during countermovement and drop jumps
Bibliographic record
Abstract
Comprehensive understanding of force plate parameters distinguishing individuals postprimary anterior cruciate ligament reconstruction (ACLR) from healthy controls during countermovement jumps (CMJ) and/or drop jumps (DJ) is lacking. This review addresses this gap by identifying discriminative force plate parameters and examining changes over time in individuals post-ACLR during CMJ and/or DJ.We conducted a systematic review and meta analyses following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. Nine databases were searched from inception to March 2022. We included cross-sectional papers comparing post-ACLR with healthy controls or longitudinal studies of individuals at least 6 months postprimary ACLR while performing CMJ and/or DJ on force plates. The methodological quality was appraised using the Modified Downs and Black Checklist.Thirty-three studies including 1185 (50.38%) participants post-ACLR, and 1167 (49.62%) healthy controls, were included. Data were categorised into single-leg CMJ, double-leg CMJ, single-leg DJ, and double-leg DJ. Jump height was reduced in both single (mean difference [MD] = -3.13; p < 0.01; 95% confidence interval [CI]: [-4.12, -2.15]) and double-leg (MD = -4.24; p < 0.01; 95% CI: [-5.14, -3.34]) CMJs amongst individuals with ACLR. Similarly, concentric impulse and eccentric/concentric impulse asymmetry could distinguish between ACLR (MD = 3.42; p < 0.01; 95% CI: [2.19, 4.64]) and non-ACLR (MD = 5.82; p < 0.01; 95% CI: [4.80, 6.80]) individuals. In double-leg DJs, peak vertical ground reaction forces were lower in the involved side (MD = -0.10; p = 0.03; 95% CI: [-0.18, -0.01]) but higher in the uninvolved side (MD = 0.15; p < 0.01; 95% CI: [0.10, 0.20]) when compared to controls and demonstrated significant changes between 6 months and 3 years post-ACLR.This study identified discriminative kinetic parameters when comparing individuals with and without ACLR and also monitored neuromuscular function post-ACLR. Due to heterogeneity, a combination of parameters may be required to better identify functional deficits post-ACLR.Level III.
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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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".