Pupil Light Reflex for the Assessment of Analgesia in Critically Ill Sedated Patients With Traumatic Brain Injury: A Preliminary Study
Bibliographic record
Abstract
ABSTRACT: BACKGROUND: Analgesia monitoring is essential to preserve comfort in critically ill sedated patients with traumatic brain injury (TBI). Although pupil dilation (PD) and pain behaviors can be used to assess analgesia, these indicators require application of noxious stimulations for elicitation. Recently, the pupillary light reflex (PLR) has emerged as a nonnoxious parameter that may be used to predict analgesia requirements in non-brain-injured patients. Here, we explored whether PLR can be used for the purpose of analgesia monitoring in critically ill sedated TBI patients. METHODS: Fifteen mechanically ventilated TBI patients (11 men; 54 ± 20 years) under continuous analgesia and sedation infusions were assessed at predefined time within 72 hours of intensive care unit admission. Data collection was performed using video-pupillometry and the Behavioral Pain Scale. At each assessment, pupil size and PLR at rest were recorded followed immediately by the documentation of PD and pain behaviors elicited by a calibrated noxious stimulus. Blood concentrations of analgesics/sedatives were monitored. RESULTS: One hundred three assessments were completed. PLR resulted in an average decrease of 19% in pupil diameter, and PD resulted in an average increase of 10% in pupil diameter. Variations in PLR and PD were more pronounced in subjects who showed a Behavioral Pain Scale score greater than 3 (a recognized sign of subanalgesia) compared with those with no behavioral reaction. Multiple regression analyses suggest a significant overlap between fluctuations in pupillary reflexes and blood levels of fentanyl, not propofol. CONCLUSION: In our sample, percentages of variation in PLR and PD were found to be directly representative of TBI patients' fentanyl blood concentration. Considering information about blood drug concentration is generally not available at bedside, PLR could be used as a proxy to assess analgesia requirements before a nociceptive procedure in critically ill sedated TBI patients who are vulnerable to stress.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".