Detecting Pain in Traumatic Brain-injured Patients With Different Levels of Consciousness During Common Procedures in the ICU
Bibliographic record
Abstract
PURPOSE: Pain behaviors such as grimacing and muscle rigidity are recommended for pain assessment in nonverbal populations. However, these behaviors may not be appropriate for critically ill patients with a traumatic brain injury (TBI) depending on their level of consciousness (LOC). This study aimed to validate the use of behaviors for assessing pain of critically ill TBI adults with different LOC. METHODS: Using a repeated measure within subject design, participants (N=45) were observed for 1 minute before (baseline), during, and 15 minutes after 2 procedures: (1) noninvasive blood pressure: NIBP (non-nociceptive); and (2) turning (nociceptive). A behavioral checklist combining 50 items from existing pain assessment tools and video recording were used to describe participants' behaviors. Intrarater and interrater agreements of observed behaviors were also examined. RESULTS: Overall, pain behaviors were observed more frequently during turning (median=4; T=-5.336; P≤0.001) than at baseline (median=1), or during noninvasive blood pressure (median=0). TBI patients' pain behaviors were mostly "atypical" and included uncommon responses such as flushing, sudden eye opening, eye weeping, and flexion of limbs. These behaviors were observed in ≥25.0% of TBI participants during turning independent of their LOC, and in 22.2% to 66.7% of conscious participants who reported the presence of pain. Agreements were >92% among and between the 2 raters. CONCLUSIONS: This study support previous findings that critically ill TBI patients could exhibit atypical behaviors when exposed to nociceptive procedures. As such, use of current recommended pain behaviors as part of standardized scales may not be optimal for assessing the analgesic needs of this vulnerable group.
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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 | 0.022 | 0.025 |
| 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".