Near infrared spectroscopy of the central nervous system: monitoring oxygenation in the neonatal brain and in the spinal cord following traumatic injury
Bibliographic record
Abstract
Progressive development and innovation have led to a growing number of applications of near infrared spectroscopy (NIRS) becoming clinically relevant. The ability of NIRS technologies to monitor oxygenation and hemodynamic parameters relevant to ensuring that the brain and spinal cord are adequately perfused and oxygenated to meet varying metabolic demands is a key example. Just as the inclusion of pulse oximetry became the standard of care for surgical anesthesia when the importance of the real-time data this new technology provided was recognized 50 years ago, so nowadays cerebral oxygenation monitoring is increasingly widely employed in this context. In parallel, comparable NIRS technologies are now relied on as adjuncts to aid central nervous system monitoring during intensive care of both critically ill patients, and the smallest, most immature premature infants. Such monitoring offers the prospect not only of improving care during critical illness, but also minimizing secondary injury following situations such as intrapartum asphyxia and traumatic spinal cord injury, where the initial neural injury is all too often compounded by secondary damage from intracellular energy failure or ischemia to compromised but potentially recoverable brain cells and neural tissue. The advances that have led to effective NIRS monitoring systems have most often come about because of the willingness of scientists, clinicians and other end-users to collaborate. In this way the most pressing clinical issues are identified and novel solutions generated using the latest physics concepts, newest materials, and increasingly innovative approaches. Key lessons learned in this way, and what several historic advances in biophotonics can teach us are the subject of this review, as they are relevant to the further evolution of NIRS applications in medicine, both to address ongoing complexities of care, and also if we are to take advantage of the opportunities provided by the growing trend for monitoring personal health data as a way to continue to improve health and wellbeing.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".