Indicators of pain in neonates at risk for neurological impairment
Bibliographic record
Abstract
AIM: This paper is a report of a study to compare the importance and usefulness ratings of physiological and behavioural indicators of pain in neonates at risk for neurological impairment by nurse clinicians and pain researchers. BACKGROUND: Neonates at risk for neurological impairment have not been systematically included in neonatal pain measure development and how clinicians and researchers view pain indicators in these infants is unknown. METHODS: Data triangulation was undertaken in three Canadian Neonatal Intensive Care Units using data from: (a) 149 neonates at high, moderate and low risk for neurological impairment, (b) 95 nurse clinicians from the three units where infant data were collected and (c) 14 international pain researchers. Thirteen indicators were assessed following heel lance in neonates and 39 indicators generated from nurse clinicians and pain researchers were assessed for importance and accuracy. Data were collected between 2004 and 2005. RESULTS: Across risk groups, indicators with the highest accuracy for discriminating 'pain' among neonates were: brow bulge (77-83%), eye squeeze (75-84%), nasolabial furrow (79-81%), and total facial expression (78-83%). Correlations between nurse ratings and neonatal accuracy scores ranged from moderate to none (mild risk r = 0.52, P = 0.07; moderate r = 0.43, P = 0.15; high r = -0.12, P = 0.69). Researchers demonstrated a better understanding of the importance of pain indicators (mild risk, r = 0.91, P < 0.001; moderate 0.85, P < 0.001; 0.0002; high r = 0.64, P = 0.019) than nurse clinicians. CONCLUSION/DISCUSSION: Facial actions were rated as the most important indicators of neonatal pain. However, as neurological impairment risk increased, physiological indicators were rated more important by nurse clinicians and pain researchers, opposite to pain indicators demonstrated by neonates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".