Continuous Optical Monitoring of Spinal Cord Oxygenation and Hemodynamics during the First Seven Days Post-Injury in a Porcine Model of Acute Spinal Cord Injury
Bibliographic record
Abstract
One of the only currently available treatment options to potentially improve neurological recovery after acute spinal cord injury (SCI) is augmentation of mean arterial blood pressure (MAP) to promote blood flow and oxygen delivery to the injured cord. However, to optimize such hemodynamic management, clinicians require a method to monitor the physiological effects of these MAP alterations within the injured cord. Therefore, we investigated the feasibility and effectiveness of using a novel optical sensor, based on near-infrared spectroscopy (NIRS), to monitor real-time spinal cord oxygenation and hemodynamics during the first 7 days post-injury in a porcine model of acute SCI. Six Yucatan miniature pigs underwent a T10 vertebral level contusion-compression injury. Spinal cord oxygenation and hemodynamics were continuously monitored by a minimally invasive custom-made NIRS sensor, and by invasive intraparenchymal (IP) probes to validate the NIRS measures. Episodes of MAP alteration and hypoxia were performed acutely after injury, and at 2 and 7 days post-injury to simulate the types of hemodynamic changes SCI patients experience after injury. The NIRS sensor demonstrated the ability to provide oxygenation and hemodynamic measurements over the 7-day post-SCI period. NIRS measures showed statistically significant correlations with each of the invasive IP measures and MAP changes during episodes of MAP alteration and hypoxia throughout the first week post-injury ( p < 0.05). These results indicate that this novel NIRS system can monitor real-time changes in spinal cord oxygenation and hemodynamics over the first 7 days post-injury, and has the ability to detect local tissue changes that are reflective of systemic hemodynamic changes.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".