Measuring “pain load” during general anesthesia
Bibliographic record
Abstract
Introduction: Functional near-infrared spectroscopy (fNIRS) allows for ongoing measures of brain functions during surgery. The ability to evaluate cumulative effects of painful/nociceptive events under general anesthesia remains a challenge. Through observing signal differences and setting boundaries for when observed events are known to produce pain/nociception, a program can trigger when the concentration of oxygenated hemoglobin goes beyond ±0.3 mM from 25 s after standardization. Method: fNIRS signals were retrieved from patients undergoing knee surgery for anterior cruciate ligament repair under general anesthesia. Continuous fNIRS measures were measured from the primary somatosensory cortex (S1), which is known to be involved in evaluation of nociception, and the medial polar frontal cortex (mPFC), which are both involved in higher cortical functions (viz. cognition and emotion). Results: A ±0.3 mM threshold for painful/nociceptive events was observed during surgical incisions at least twice, forming a basis for a potential near-real-time recording of pain/nociceptive events. Evidence through observed true positives in S1 and true negatives in mPFC are linked through statistically significant correlations and this threshold. Conclusion: Our results show that standardizing and observing concentrations over 25 s using the ±0.3 mM threshold can be an arbiter of the continuous number of incisions performed on a patient, contributing to a potential intraoperative pain load index that correlates with post-operative levels of pain and potential pain chronification.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".