Successful treatment of neurologic injury after complex spinal surgery with hyperbaric oxygen therapy: a case report
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Neurologic injury is relatively common in the context of spinal surgery, and is often treated with physiotherapy, pharmacotherapy, or surgical intervention. Emerging evidence supports a possible role for hyperbaric oxygen therapy (HBOT) in the treatment of peripheral and spinal nerve injuries. We describe the successful use of HBOT in improving neurologic recovery after complex spine surgery with new-onset postoperative unilateral foot drop. Case Description: A 50-year-old woman was found to have new right-sided foot drop and L2-S1 motor deficits following complex thoracolumbar revision spinal surgery. She received standard conservative management for a provisional diagnosis of acute traumatic nerve ischemia, but demonstrated no neurologic improvement. On postoperative day four, after other avenues of treatment were exhausted, she was referred for HBOT. The patient received a total of twelve sessions of HBOT at 2.0 absolute atmospheres (ATA) of pressure, for 90 minutes (including two air breaks) per session, before transfer to a rehabilitation facility. Conclusions: The patient displayed marked neurologic improvement after the first hyperbaric session, and further recovery thereafter. She concluded therapy with a significantly improved range of motion and lower limb power, ability to ambulate, and pain control. HBOT was associated with a rapid, sustained improvement when applied in this case as a salvage therapy for persistent postoperative neurologic deficit. Mounting evidence supports the consideration of hyperbaric therapy as a standard adjunct treatment for traumatic neurologic injury.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it