Motor Recovery Depends on Timing of Surgery in Patients With Lumbar Disk Herniation
Bibliographic record
Abstract
BACKGROUND: Although approximately half of the patients undergoing lumbar disk surgery present with motor deficits, timing of surgery for radicular weakness is largely unclear. OBJECTIVE: To evaluate the impact of surgical timing on motor recovery in patients with lumbar disk herniation (LDH) and to identify an ideal time window for intervention. METHODS: In a single-center observational trial, 390 patients with LDH-associated motor deficits were prospectively followed for a minimum of 12 months after nonelective microscopic disk surgery. The duration of motor deficit before surgery was documented. Motor function was graded according to the Medical Research Council (MRC) scale. Statistical analysis of motor recovery applied unbiased recursive partitioning conditional inference tree to determine cutoff times for optimal surgical intervention. The slope of recovery calculated as the change of the MRC grade over time served as the primary outcome. RESULTS: A preoperative motor deficit of MRC ≤2/5 and the duration of paresis were identified as the most important predictors of recovery ( P < .001). Surgery within 3 days was associated with a better recovery for both severe and moderate/mild deficits ( P = .017 for MRC ≤ 2/5; P < .001 for MRC > 2/5; number needed to treat [NNT] <2). A sensitivity analysis in mild motor deficits indicated a cutoff of 8 days. CONCLUSION: Timing of surgery is crucial for motor recovery in LDH-associated deficits. Immediate diagnosis, imaging, and referral should be aimed for to allow disk surgery within 3 days in patients with severe and moderate radicular weakness. If functionally disabling, even mild deficits may warrant decompression within a week.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".