Salivary Biomarkers of Inflammation in Patients With Chronic Non-Specific Low Back Pain
Bibliographic record
Abstract
Background: Chronic non-specific low back pain (CNSLBP) is a debilitating condition with unclear underlying mechanisms. The presence of systemic biomarkers associated with inflammation in nonspecific low back pain (NSLBP) has been inconsistently reported primarily through invasive blood sampling. Objective: This study evaluates the use of saliva as an alternative medium for assessing inflammatory biomarker levels in patients with CNSLBP. Design: Prospective cross-sectional pilot study. Methods: Twenty-five patients with CNSLBP and 25 age and sex matched asymptomatic participants were selected according to specific inclusion and exclusion criteria. The primary outcome was determination of the levels of inflammatory biomarkers in unstimulated saliva samples of CNSLBP patients relative to controls using Luminex™ 200 technology. Secondary outcomes were pain, disability and anxiety/stress levels of participants. Results: In CNSLBP patients, 9 biomarkers interferon γ (IFNγ), interleukin-2 (IL-2), IL-4, IL-5, IL-10, IL-13, IL-12p40, IL-12p70, and tumor necrosis factor α (TNFα) were comparable to controls ( P = .25-.94). However, 4 pro-inflammatory mediators were significantly elevated, exhibiting medium to large effect sizes: IL-1β ( P = .028, Cohen’s d = 1.62), IL-6 ( P = .001, d = 1.0), IL-8 ( P = .002, d = 0.86), and MCP-1 ( P = .001, d = 0.77). Additionally, IL-1Ra levels were significantly higher, though with a small effect size ( P = .03, d = 0.43). A significant correlation ( P = .02) was observed between VAS pain scores and MCP-1 levels. Conclusion: Saliva represents a viable medium for assessing key inflammatory biomarkers in patients with chronic non-specific low back pain (CNSLBP). Elevated levels of proinflammatory cytokines, IL-1, IL-6, IL-8, and the nociceptive chemokine MCP-1 were observed in comparison to asymptomatic controls, with MCP-1 showing a positive correlation with self-reported pain intensity. Future studies utilizing unstimulated saliva samples may further investigate changes in inflammatory biomarker levels to monitor treatment outcomes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".