The Validity of Vital Signs for Pain Assessment in Critically Ill Adults: A Narrative Review
Bibliographic record
Abstract
OBJECTIVES: Pain assessment in the intensive care unit (ICU) is challenging because many patients are unable to self-report or exhibit pain-related behaviors. In such situations, vital signs (VS) through continuous monitoring are alternative cues for pain assessment. This review aimed to describe the reliability and validity of VS for ICU pain assessment. DESIGN: Narrative review of the literature. DATA SOURCES: Medline, Embase, CINAHL, Cochrane. REVIEW/ANALYSIS METHODS: A narrative review was conducted with a comprehensive search in four databases. Search terms included VS, pain assessment, and ICU. RESULTS: Out of 1,359 results, 30 studies from 17 countries were included. Heart rate, blood pressure, and respiratory rate were most used for ICU pain assessment. Assessments were performed at rest before procedures, during nociceptive and non-nociceptive procedures, and after procedures. Increases in respiratory rate were clinically significant by more than 25% during nociceptive procedures (e.g., endotracheal suctioning, turning) compared with rest/pre-procedures in five studies. Correlations of VS with self-reported pain (reference standard measure) and behavioral pain scores (alternative measure) were absent or weak. CONCLUSIONS: VS are not valid indicators for ICU pain assessment. Increases of respiratory rate may be a cue for the detection of pain. However, fluctuations in respiratory rate can be influenced by opioids or controlled ventilation mode. Our results dissuade the use of VS for pain assessment because of the lack of association with ICU pain reference standards. Other physiologic measures of pain in critically ill adults should be explored.
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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 | 0.010 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".