Clinical Trials Monitor/
RecruitingNCT05579496

Rebooting Infant Pain Care: Using Machine Learning and Skin-to-Skin Contact to Exponentially Improve Neonatal Intensive Care Unit Practice

Sponsor: York University

Trial Details

ConditionAcute Pain
StatusRecruiting
Participants400
Est. Completion1 Mar 2030
Last Updated13 July 2026

Primary Outcome

Behavioural Correlate of Distress; Cortical Correlate of Distress; Cardiac Correlates of Distress; Oxygen Saturation Correlate of Distress; Respiration Rate Correlate of Distress

Eligibility Criteria

Inclusion Criteria

QUALITATIVE INTERVIEWS Inclusion Criteria: * Parents of a child currently in the NICU or * Health professionals currently working in the NICU. Exclusion Criteria: \*Participants who cannot communicate fluently in English QUANTITITATIVE DATA CAPTURE (video, eeg, ecg, RR, SPo2) Inclusion Criteria: * Infants born between 25 0/7 weeks 32 6/7 weeks gestational age * Infants who are within 8 weeks postnatal age * Infants who are undergoing a routine heel lance Exclusion Criteria: * Infants with congenital malformations * Infants receiving analgesics or sedatives at the time of study (aside from sucrose) * Infants with history of perinatal hypoxia/ischemia at the time of study * Infants with diaper rash or excoriated buttocks * Parents who are not fluent in English

Trial Sites

Countries

CanadaUnited Kingdom
View Registry Entry

Related Analysis

NICU Pain Assessment Reimagined: International Trial Deploys Machine Learning and Skin-to-Skin Contact to Transform Preterm Infant Pain Care

A York University-led international observational trial is deploying multimodal physiological monitoring and machine learning to build an objective neonatal pain detection algorithm, while simultaneously investigating the developmental mechanisms of skin-to-skin contact analgesia in preterm infants. With 400 participants targeted across Canadian and UK NICUs and a completion date of March 2030, the study could fundamentally reshape how acute pain is assessed and managed in the world's most vulnerable patients.

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