Nerve Root Sedimentation Sign: Can It Predict the Success for Surgical Intervention in Patients With Symptomatic Lumbar Spinal Stenosis?
Bibliographic record
Abstract
INTRODUCTION: The use of interspinous process devices are less invasive surgical methods designed to manage mild to moderate lumbar spinal stenosis symptoms. Symptomatic relief may not be seen in all patients undergoing this procedure. Magnetic resonance imaging (MRI) parameters have been used to predict the success of clinical outcomes in patients with symptomatic lumbar spinal stenosis for decompressive surgeries. The purpose of this study was to determine the feasibility of using nerve root sedimentation sign to predict mid- to long-term clinical outcomes of patients treated with interspinous spacers for lumbar spinal stenosis. METHODS: This was a retrospective study using prospective multicenter Food and Drug Administration Investigational Device Exemption (FDA IDE) trial (Superion™ and X-STOP®) data. Inclusion criteria were patients treated with interspinous spacers, aged 45 or older with lumbar spinal stenosis at one or more contiguous levels from L1 to L5 and symptoms of neurogenic claudication. Preoperative axial T2 weighted MRI images were used to determine nerve root sedimentation sign. Preoperative, six-week, one- and two-year postoperative clinical outcomes were measured using Oswestry Disability Index (ODI) scores. Clinical outcomes were compared between positive and negative nerve root sedimentation sign groups; p ≤0.05 was considered significant. RESULTS: This study included n=374 patients; 40 excluded; 334 included (113=positive nerve root sedimentation sign (NRSS) (34%) and 221=negative NRSS (66%)). At six weeks, significant postoperative ODI correction was noted in both groups (p<0.001). No significant differences in ODI scores were identified between groups. A subgroup analysis with MRI image quality grade 3 and certainty determination grade 5, six-week postoperative ODI correction was significant in both groups. Six-week, one- and two-year postoperative ODI scores were greater by 6 points in the positive nerve root sedimentation sign group compared to the negative nerve root sedimentation sign group. CONCLUSIONS: Although satisfactory postoperative improvement occurred in both groups, there were statistically significant differences noted in certain sub-categories. The subgroup analysis indicated MRI image quality and nerve root sedimentation sign certainty of determination may be factors that may aid with planning the surgical management of lumbar spinal stenosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".