Effectiveness of postsurgical rehabilitation following lumbar disc herniation surgery: A systematic review
Bibliographic record
Abstract
Introduction: The effectiveness of post-surgical rehabilitation following lumbar disc herniation (LDH) surgery is unclear. Research question: To investigate the effectiveness and safety of rehabilitation interventions initiated within three months post-surgery for adults treated surgically for LDH. Material and methods: This systematic review searched seven databases from inception to November 2023. Independent reviewers screened studies, assessed and extracted data, and rated the certainty of the evidence using the GRADE approach. Results: This systematic review retrieved 20,531 citations and included 25 randomized controlled trials. The high certainty evidence suggests that adding Pilates exercise to routine care and cognitive behavioral therapy may improve function immediately post-intervention (1 RCT), and that adding whole-body magnetic therapy to exercise, pharmacological and aquatic therapy may reduce low back pain intensity (1 RCT) immediately post-intervention. Compared to placebo, pregabalin did not reduce low back pain or leg pain intensity (1 RCT) (moderate to high certainty evidence). We found no differences between: 1) behavioral graded activity vs. physiotherapy (1 RCT); 2) exercise and education vs. neck massage or watchful waiting (1 RCT); 3) exercise, education, and in-hospital usual care vs. in-hospital usual care (1 RCT); 4) functional or staged exercise vs. usual post-surgical care including exercise (2 RCTs); and 5) supervised exercise with education vs. education (1 RCT). No studies assessed adverse events. Discussion and conclusion: Evidence on effective and safe post-surgical rehabilitation interventions is sparse. This review identified two interventions with potential short-term benefits (Pilates exercises, whole-body magnetic therapy) but safety is unclear, and one with an iatrogenic effect (pregabalin).
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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 | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| 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) | 0.005 | 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".