Temporal changes in cortical sensory processing during the transition from acute to chronic low back pain
Bibliographic record
Abstract
Abstract Introduction: Sensory cortex activity differs between acute and chronic low back pain (LBP) with decreased activity in acute LBP but increased activity in chronic LBP. However, it is unknown how and when sensory cortex activity changes during the transition from acute to chronic LBP and whether fluctuations in sensory cortex activity are associated with pain sensitivity. Objectives: To examine (1) the trajectory of changes in sensory cortex activity over a period of six months from the onset of acute LBP; (2) the assoication between sesnory cortex activity and pain pain sensitivity. Methods: In a prospective cohort study (N = 120), sensory evoked potentials (SEPs) were recorded using electroencephalography within 6 weeks of LBP onset (baseline) and at 3- and 6-month follow-up. Pain sensitivity was assessed using quantitative sensory testing (QST). Results: At baseline, individuals who developed chronic pain at 6-month follow-up exhibited less nonnoxious sensory processing (smaller area of N80, N150, and P260 SEP components) compared with those who recovered. In individuals who recovered, SEP measures did not change over time. In individuals who developed chronic pain, N80 and N150 SEP area increased between baseline and 3 months, while P260 SEP area increased between baseline and 6 months, reaching values consistent with those of recovered individuals. Sensory evoked potential measures showed no relationship with QST, except for a larger P260 SEP area correlating with higher 6-month heat pain threshold at the site of LBP. Conclusions: Nonnoxious sensory processing in acute LBP was less in those who developed chronic pain than those who recovered. Nonnoxious sensory processing increased over time in those who developed chronic pain but was unchanged in those who recovered. In the transition from acute to chronic LBP, nonnoxious sensory processing in the sensory cortex was not associated with pain sensitivity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".