The Treatment of Perioperative Spinal Cord Injury With Hyperbaric Oxygen Therapy
Bibliographic record
Abstract
STUDY DESIGN: Case report (level IV evidence). OBJECTIVE: To describe a potential novel application of hyperbaric oxygen therapy (HBOT) in the successful treatment of a postoperative spinal cord injury. SUMMARY OF BACKGROUND DATA: A 68-year-old man presented with an acute spinal cord injury (ASIA impairment scale D), on the background of degenerative lower thoracic and lumbar canal stenosis. He underwent emergent decompression and instrumented fusion (T9-L5), with an uncomplicated intraoperative course and no electrophysiological changes. Immediate postoperative assessment demonstrated profound bilateral limb weakness (1/5 on the Medical Research Council [MRC] grading scale, ASIA impairment scale B), without radiological abnormality. METHODS: Conventional medical management (hypertension, level 2 care) was instigated with the addition of Riluzole, with no effect after 30 hours. At 36 hours 100% oxygen at 2.8 atmospheres was applied for 90 minutes, and repeated after 8 hours, with a further three treatments over 48 hours. RESULTS: The patient demonstrated near-immediate improvement in lower limb function to anti-gravity (MRC grading 3/5) after one treatment. Motor improvement continued over the following treatments, and after 2 weeks the patient was ambulatory. At 4 months, the patient demonstrated normal motor function with no sphincteric disturbance. CONCLUSION: The application of HBOT contributed to the immediate and sustained improvement (ASIA B to ASIA E) in motor recovery after postoperative spinal cord injury. HBOT may represent a new avenue of therapy for spinal cord injury, and requires further prospective investigation. LEVEL OF EVIDENCE: 4.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".