NIRS monitoring of brain and spinal cord — detection of adverse intraoperative events
Bibliographic record
Abstract
Near infrared spectroscopy (NIRS) monitors changes in oxygenated haemoglobin (HbO2), and redox status of cytochromeaa3 (cyt) continuously and non‐invasively in living tissue. We present examples where clinically relevant changes in HbO2 and/or cyt were detected in real time, allowing intervention to avert potentially harmful hypoxic‐ischaemic damage to the brain and/or spinal cord. Brain monitoring: In children undergoing surgery on cardiopulmonary bypass, observations include that: atrial fibrillation (cardiac arrhythmia) lowered cerebral HbO2 concentration; concealed haemorrhage decreased cerebral HbO2 concentration; inadequate level of anaesthetic resulted in spikes of changes in volume with interventions such as suturing; circulatory arrest reduced brain HbO2 and cyt redox status; and bypass pump problems compromised cerebral blood flow. Spinal cord monitoring: In the experimental animal, we observed that NIRS detected ischaemic change immediately following aortic compression, spinal column distraction (instrumentation to separate the vertebrae), and hypoxia. In an infant requiring release of a congenitally tethered spinal cord, we observed that traction on the spinal cord of the infant resulted in decreased total haemoglobin concentration. Summary: NIRS brain monitoring probably represents the “standard of care” during cardiac surgery because adverse events can be detected and quantified. Similarly, spinal cord monitoring could reduce ischaemic spinal cord damage in spinal cord surgery and aortic aneurysm repair.
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 | 0.001 |
| 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 | 0.001 | 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".