Cerebral hemodynamic response to a therapeutic bed for procedural pain management in preterm infants in the NICU: a randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: We developed a novel device, Calmer, that mimics key components of skin-to-skin holding to reduce stress in preterm infants. Our feasibility trial showed that Calmer worked 50% better than no treatment and no differently from our standard of care, facilitated tucking (FT), for reducing pain scores during a heel lance in preterm infants in the neonatal intensive care unit. OBJECTIVE: We compared the effects of Calmer on regional cerebral hemodynamic activity during a noxious stimulation to FT. METHODS: During a clinically required heel lance, we measured frontal cortex tissue oxygenation in a subsample of 29 preterm infants (27-33 weeks gestational age) from our larger randomized controlled trial. Infants were randomized to either FT (n = 16) or Calmer treatment (n = 12). The outcome measure, obtained using near-infrared spectroscopy, was a change in the tissue oxygenation index (TSI) across study phases (Baseline, Heel Lance, Recovery; median duration 517 seconds [421-906 seconds]). RESULTS: No statistically significant differences were found between groups in the median TSI during any of the study phases. In response to the heel lance, 7 infants (27.6%) had a TSI that dipped below the 60% threshold (3 in the Calmer group 25% and 4 in the FT group 25%); none below 50%. CONCLUSIONS: Infants on Calmer maintained normal regional cerebral oxygen levels (55%-85%) no differently from infants receiving a human touch intervention during blood collection. Parental skin-to-skin holding is one of the most effective strategies to relieve procedural pain in preterm infants. When parents or FT are not available, Calmer shows potential for filling this gap in care.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".