Metalloproteinase-2 in failed back surgery syndrome caused by epidural fibrosis: can it play a role in persistent pain?
Bibliographic record
Abstract
Purpose Failed Back Surgery Syndrome (FBSS) occurs in 10–40% of patients treated surgically due to disk herniation (DH). There are several factors that can cause a predisposition to FBSS, but the exact pathomechanism has not been elucidated. The aim of this study was to investigate Metalloproteinase-2 (MMP-2) and Tissue Inhibitor of Metalloproteinase-2 (TIMP-2) activities in a homogeneous group of FBSS patients with epidural fibrosis in comparison to its activity in patients with surgically treated DH. Methods DH, FBSS, and control (CG) groups consisted of 30 subjects. The patients were assessed clinically by the Numerical Rating Scale (NRS), McGill Pain Questionnaire (SF -MPQ), Oswestry Disability Index (ODI), and Beck Depression Inventory (BDI). Serum concentrations of MMP-2 and TIMP-2 were measured by using the immunoenzymatic method. Results There was a significantly higher MMP-2 expression (medians: 4797.49 vs. 2656.65; p < 0.0001) and TIMP-2 concentration (medians: 166.40 vs. 109.60; p < 0.0001) in the DH compared to the CG. Significantly higher MMP-2 expression (4219.95 vs. 2656.65; p < 0.0001) and TIMP-2 concentration (medians: 150.17 vs. 109.60; p = 0.0003) were also found in the FBSS compared to the CG. The activity of MMP-2, measured as MMP-2/TIMP-2, did not significantly change between the DH, FBSS, and CG. MMP2 expression (p < 0.0001) and TIMP-2 concentration (p < 0.0001) were significantly higher in the DH than FBSS. Conclusion Results indicate the presence of a contribution of MMP-2 and TIMP-2 in DH and FBSS. Unchanged activity of MMP-2 can indicate an insufficiency in the MMP-2 repair system in both diseases. Lower MMP-2 expression and TIMP-2 concentration in the FBSS group can reflect the chronicity of the process.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".