Systemic Inflammatory and Th17 Immune Activation among Patients Treated for Lumbar Radiculopathy Exceeds that of Patients Treated for Persistent Postoperative Neuropathic Pain
Bibliographic record
Abstract
BACKGROUND: The pathophysiology of lumbar radiculopathy includes both mechanical compression and biochemical irritation of apposed neural elements. Inflammatory and immune cytokines have been implicated, induced by systemic exposure of immune-privileged intervertebral disc tissue. Surgical intervention provides improved symptoms and quality of life, but persistent postoperative neuropathic pain (PPNP) afflicts a significant fraction of patients. OBJECTIVE: To compare the inflammatory and immune phenotypes among patients undergoing structural surgery for lumbar radiculopathy and spinal cord stimulation for neuropathic pain. METHODS: Consecutive patients undergoing surgical intervention for lumbar radiculopathy or neuropathic pain were studied. Demographic data included age, gender, and VAS and neuropathic pain scores. Serum was evaluated for cytokine levels (IL-6, Il-17, TNF-α) and cellular content [white blood cell (WBC)/differential, lymphocyte subtypes]. The primary analysis differentiated molecular and cellular profiles between radiculopathy and neuropathic pain patients. Subgroup analysis within the surgical radiculopathy population compared those patients achieving relief of symptoms and those with PPNP. RESULTS: Heightened IL-6, Il-17, and TNF-α levels were observed for the lumbar radiculopathy group compared with the neuropathic pain group. This was complemented by higher WBC count and a greater fraction of Th17 lymphocytes among radiculopathy patients. In the lumbar discectomy subgroup, pain relief was seen among patients with preoperatively elevated IL-17 levels. Those patients with PPNP refractory to surgical discectomy exhibited normal cytokine levels. CONCLUSION: Differences in Th17 immune activation are seen among radiculopathy and neuropathic pain patients. These cellular and molecular profiles may be translated into biomarkers to improve patient selection for structural spine surgery.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".