Return to Play After Symptomatic Lumbar Disc Herniation in Elite Athletes: A Systematic Review and Meta-analysis of Operative Versus Nonoperative Treatment
Bibliographic record
Abstract
Context: The prevalence of symptomatic lumbar disc herniation (LDH) in athletes can be as high as 75%. For elite athletes diagnosed with LDH, return to play (RTP) is a major concern, and thus comparing surgical with nonoperative care is essential to guide practitioners and athletes, not just in terms of recovery rates but also speed of recovery. Objective: The purpose of this systematic review is to provide an update on RTP outcomes for elite athletes after lumbar discectomy versus nonoperative treatment of LDHs. Data Sources: A search of the literature was conducted using 3 online databases (MEDLINE, EMBASE, and PubMed) to identify pertinent studies. Study Selection: Yielded studies were screened according to the inclusion criteria. Study Design: Systematic review with meta-analysis. Level of Evidence: Level 4. Data Extraction: Relevant data were extracted. A meta-analysis was performed comparing RTP rate for all comparative studies. Results: Twenty studies met the inclusion criteria and were included in this review. Overall, 663 out of 799 patients (83.0%) returned to play in the surgical group and 251 out of 308 patients (81.5%) returned to play in the nonoperative group. No statistically significant difference for RTP rate was found (odds ratio, 1.39; 95% CI, 0.58-3.34; P = 0.46; I2, 71%). The mean time to RTP for patients undergoing lumbar discectomy was 5.19 months (range 1.00-8.70 months), and 4.11 months (range 3.60-5.70 months) for those treated conservatively. Conclusion: There was no significant difference in RTP rate between athletes treated with operative or nonoperative management of LDHs, nor did operative management have a faster time to RTP. Athletes should consider the lack of difference in RTP rate in addition to the potential risks associated with spinal surgery when choosing a treatment option. Future randomized controlled trials are needed on this topic to allow for high-powered conclusions.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".