Presence of Tumor Necrosis Factor-Alpha in Urine Samples of Patients With Chronic Low Back Pain Undergoing Chiropractic Care: Preliminary Findings From a Prospective Cohort Study
Bibliographic record
Abstract
Background and aims Low back pain is the leading cause of years lived with disability worldwide. Chiropractors employ different interventions to treat low back pain, including spinal manipulative therapy, although the mechanisms through which chiropractic care improves low back pain are still unclear. Clinical research and animal models suggest that spinal manipulation might modulate plasma levels of inflammatory cytokines, which have been involved in different stages of low back pain. More specifically, serum levels of Tumor Necrosis Factor-alpha (TNF-α) have been found to be elevated in patients with chronic low back pain. We aimed to investigate whether urine from chronic low back pain patients could be an appropriate medium to measure concentrations of TNF-α and to examine possible changes in its levels associated to chiropractic care. Methods Urine samples were collected from 24 patients with chronic low back pain and TNF-α levels were analyzed by ELISA before and after 4–6 weeks of care compared to a reference value obtained from 5 healthy control subjects, by means of a Welch’s t -test. Simultaneously, pain intensity and disability were also evaluated before and after care. Paired t -tests were used to compare mean pre and post urinary concentrations of TNF-α and clinical outcomes. Results Significantly higher baseline levels of urinary TNF-α were observed in chronic low back pain patients when compared to our reference value ( p < 0.001), which were significantly lower after the period of chiropractic treatment ( p = 0.03). Moreover, these changes were accompanied by a significant reduction in pain and disability (both p < 0.001). However, levels of urinary TNF-α were not correlated with pain intensity nor disability. Conclusion These results suggest that urine could be a good milieu to assess TNF-α changes, with potential clinical implications for the management of chronic low back pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".