Validation of the Critical-Care Pain Observation Tool in Adult Patients
Bibliographic record
Abstract
BACKGROUND: Little research has been conducted to validate pain assessment tools in critical care, especially for patients who cannot communicate verbally. OBJECTIVE: To validate the Critical-Care Pain Observation Tool. METHODS: A total of 105 cardiac surgery patients in the intensive care unit, recruited in a cardiology health center in Quebec, Canada, participated in the study. Following surgery, 33 of the 105 were evaluated while unconscious and intubated and 99 while conscious and intubated; all 105 were evaluated after extubation. For each of the 3 testing periods, patients were evaluated by using the Critical-Care Pain Observation Tool at rest, during a nociceptive procedure (positioning), and 20 minutes after the procedure, for a total of 9 assessments. Each patient's self-report of pain was obtained while the patient was conscious and intubated and after extubation. RESULTS: The reliability and validity of the Critical-Care Pain Observation Tool were acceptable. Interrater reliability was supported by moderate to high weighted kappa coefficients. For criterion validity, significant associations were found between the patients' self-reports of pain and the scores on the Critical-Care Pain Observation Tool. Discriminant validity was supported by higher scores during positioning (a nociceptive procedure) versus at rest. CONCLUSIONS: The Critical-Care Pain Observation Tool showed that no matter their level of consciousness, critically ill adult patients react to a noxious stimulus by expressing different behaviors that may be associated with pain. Therefore, the tool could be used to assess the effect of various measures for the management of pain.
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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 | 0.017 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".