Delayed decompression exacerbates ischemia-reperfusion injury in cervical compressive myelopathy
Bibliographic record
Abstract
Degenerative cervical myelopathy (DCM) is the most common progressive nontraumatic spinal cord injury. The most common recommended treatment is surgical decompression, although the optimal timing of intervention is an area of ongoing debate. The primary objective of this study was to assess whether a delay in decompression could influence the extent of ischemia-reperfusion injury and alter the trajectory of outcome in DCM. Using a DCM mouse model, we show that decompression acutely led to a 1.5- to 2-fold increase in levels of inflammatory cytokines within the spinal cord. Delayed decompression was associated with exacerbated reperfusion injury, astrogliosis, and poorer neurological recovery. Additionally, delayed decompression was associated with prolonged elevation of inflammatory cytokines and an exacerbated peripheral monocytic inflammatory response (P < 0.01 and 0.001). In contrast, early decompression led to resolution of reperfusion-mediated inflammation, neurological improvement, and reduced hyperalgesia. Similar findings were observed in subjects from the CSM AOSpine North America and International studies, where delayed decompressive surgery resulted in poorer neurological improvement compared with patients with an earlier intervention. Our data demonstrate that delayed surgical decompression for DCM exacerbates reperfusion injury and is associated with ongoing enhanced levels of cytokine expression, microglia activation, and astrogliosis, and paralleled with poorer neurological recovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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".