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

Recruitingn/aAges 25 Weeks - 33 WeeksAllYork University
NCT05579496 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

To address the current limitations related to infant pain assessment in the NICU, our international team of knowledge users and health/natural science/engineering/social science researchers have come together to build a machine learning algorithm that will learn how to discriminate invasive and non-invasive distress. Furthermore, to improve the use of current pain management practices, our team seeks to better understand the developmental mechanisms underlying skin-to-skin contact over time and factors that may influence its efficacy in mitigating pain responses in preterm infants. This is an ongoing naturalistic observational study.

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📋 Eligibility rules (as published)
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
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What it tests

  • Not listed
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Where

2 sites
Mount Sinai Hospital
Toronto, Canada
University College London Hospital
London, United Kingdom
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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