Management of procedural pain in preterm infants through olfactive stimulation with mothers’ milk: A pilot study
Bibliographic record
Abstract
Introduction: Repeated and untreated pain can lead to long-term consequences in preterm infants, such as pain hypersensitivity and impaired motor and intellectual development. Studies on pharmacological and non-pharmacological interventions for pain management in preterm infants are limited. Thus, we piloted an intervention based on olfactive stimulation with mothers’ milk. Objective: To assess the feasibility, acceptability, and preliminary effects of an olfactive stimulation intervention with mothers’ milk for procedural pain in preterm infants. Methods: A pilot study was conducted with mothers, nurses, and preterm infants. Twelve preterm infants were familiarized to the odor of their mother’s milk 9 hours before heel prick. During heel prick, mothers’ milk odor was combined with standard care by placing a pad saturated with mothers’ milk beneath the infant’s nose. Pain was measured using Preterm Infant Pain Profile-Revised tool. Mothers (n=11) and nurses (n=20) completed questionnaires regarding feasibility and acceptability. Results: More than 80% of mothers and nurses reported that the olfactive stimulation intervention was feasible and acceptable. Time taken for preterm infants’ heart rate and oxygen saturation to return to the baseline was reduced and pain scores were lower when the mothers’ milk pad was placed at 1 millimeter(mm) of the infant’s nose. Discussion and conclusion: The olfactive stimulation intervention is feasible and acceptable for nurses and mothers. The observed preliminary effects suggest that a pad saturated in mother’s milk placed 1 mm from the preterm infants’ nose could reduce the pain response. A randomized clinical trial should be conducted to assess the effectiveness of this intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".