No associations between C-reactive protein and spinal pain trajectories in children and adolescents (CHAMPS study-DK)
Bibliographic record
Abstract
Preliminary evidence points to a link between C-reactive protein (CRP) and spinal pain in adults. However, there is a paucity of research in younger populations. Therefore, we aimed to determine associations between CRP and spinal pain in childhood and adolescence. We identified trajectories of spinal pain from childhood to adolescence and investigated the associations between CRP and trajectory subgroups. Six- to 11-year-old children from 13 primary schools, were followed from October 2008 and until 2014. High-sensitivity CRP collected at baseline (2008) was measured using serum samples. The outcome was the number of weeks with non-traumatic spinal pain between November 2008 and June 2014. We constructed a trajectory model to identify different spinal pain trajectory subgroups. The associations between CRP and spinal pain trajectory subgroups were modelled using mixed-effects multinominal logistic regression. Data from 1556 participants (52% female), with a mean age of 8.4 years at baseline, identified five spinal pain trajectory subgroups: "no pain" (55.3%), "rare" (23.7%), "rare, increasing" (13.6%), "moderate, increasing" (6.1%), and "early onset, decreasing" (1.3%). There were no differences in baseline high-sensitivity CRP levels between spinal pain trajectory subgroups. Thus, the heterogeneous courses of spinal pain experienced were not defined by differences in CRP at baseline.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".