Systemic pro- and anti-inflammatory profiles in acute non-specific low back pain: An exploratory longitudinal study of the relationship to six-month outcome
Bibliographic record
Abstract
OBJECTIVES: Pro-inflammatory molecules are thought to underpin the development of chronic low back pain (LBP). Although research has begun to explore the association between pro-inflammatory molecules in acute LBP and long-term outcome, no study has explored the role of anti-inflammatory molecules. We aimed to explore whether levels of systemic pro- and anti-inflammatory molecules 1) changed over a period of six months from the onset of acute LBP; 2) differed between people who were recovered (N = 11) and unrecovered (N = 24) from their episode of LBP at six months; 3) baseline psychological factors were related to inflammatory molecule serum concentrations at baseline, three and six months. METHODS: We retrospectively included participants with acute LBP included from a larger prospective trial and examined blood samples for the measurement of pro- and anti-inflammatory molecules and measures of pain, disability, and psychological factors at baseline, three and six months. RESULTS: The serum concentrations of pro- and anti-inflammatory molecules did not differ over time when compared between participants who recovered and those who did not recover at six-month follow-up. At three months, the unrecovered group had higher interleukin (IL)-8 and IL-10 serum concentrations than the recovered group. Baseline psychological factors were not related to inflammatory molecules at any time point. DISCUSSION: This exploratory study showed that levels of systemic inflammatory molecules did not change over the course of LBP, irrespective of whether people were recovered or unrecovered at six months. There was no relationship between acute-stage psychological factors and systemic inflammatory molecules. Further investigation is needed to elucidate the contribution of pro- and anti-inflammatory molecules to long-term LBP outcome.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".