Disturbed Paraspinal Reflex Following Prolonged Flexion-Relaxation and Recovery
Bibliographic record
Abstract
STUDY DESIGN: Repeated measures experimental study of the effect of flexion-relaxation, recovery, and gender on paraspinal reflex dynamics. OBJECTIVE: To determine the effect of prolonged flexion-relaxation and recovery time on reflex behavior in human subjects. SUMMARY OF BACKGROUND DATA: Prolonged spinal flexion has been shown to disturb the paraspinal reflex activity in both animals and human beings. Laxity in passive tissues of the spine from flexion strain may contribute to desensitization of mechanoreceptors. Animal studies indicate that recovery of reflexes may take up to several hours. Little is known about human paraspinal reflex behavior following flexion tasks or the recovery of reflex behavior following the flexion tasks. METHODS: A total of 25 subjects performed static flexion-relaxation tasks. Paraspinal muscle reflexes were recorded before and immediately after flexion-relaxation and after a recovery period. Reflexes were quantified from systems identification analyses of electromyographic response in relation to pseudorandom force disturbances applied to the trunk. RESULTS: Trunk angle measured during flexion-relaxation postures was significantly higher following static flexion-relaxation tasks (P < 0.001), indicating creep deformation of passive supporting structures in the trunk. Reflex response was diminished following flexion-relaxation (P < 0.029) and failed to recover to baseline levels during 16 minutes of recovery. CONCLUSION: Reduced reflex may indicate that the spine is less stable following prolonged flexion-relaxation and, therefore, susceptible to injury. The absence of recovery in reflex after a substantial time indicates that increased low back pain risk from flexion-relaxation may persist after the end of the flexion task.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".