Acute PainBabyAIBabyCalmNCT05579496
Rebooting Infant Pain Care: Using Machine Learning and Skin-to-Skin Contact to Exponentially Improve Neonatal Intensive Care Unit Practice
An observational study of Acute Pain, run by York University at 2 sites in 2 countries.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 25 to 33 weeks
- Conditions the study is for
- Acute Pain
- How many people
- 400 participants
- Where
- 2 sitesin 2 countries
- Study dates
- 1 Nov 2020to Mar 2031
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 25 to 33 weeks
- All sexes
- No healthy volunteers
- Child
Study population: Preterm infants
Who may be able to join
- Parents of a child currently in the NICU or
- Health professionals currently working in the NICU.
- 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
Who cannot join
- Participants who cannot communicate fluently in English
- QUANTITITATIVE DATA CAPTURE (video, eeg, ecg, RR, SPo2)
- 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 locations and contacts
2 sites in 2 countries. Contact the study team or a site near you to ask about taking part.
2 sites in 2 countries
Canada1 site, 1 recruiting
- Recruiting
Mount Sinai Hospital
Toronto, Ontario, M5G 1X5
Vibhuti Shah, MD, 4165864816, Vibhuti.Shah@sinaihealth.ca
Carol Cheng, MSc, carol.cheng@sinaihealth.ca
United Kingdom1 site, 1 recruiting
- Recruiting
University College London Hospital
London, No Province, N1 2EP
Lorenzo Fabrizi, PhD, 02031081888 ext. Ext. 51888, l.fabrizi@ucl.ac.uk
Judith Meek, MD, 020 3447 8094, judith.meek@nhs.net
About this study
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.
Read the detailed description
Unmanaged pain in hospitalized infants has serious long-term complications. Existing infant pain assessment approaches demonstrate several key flaws (e.g., dependent on human cognitive capacity to simply combine data from multiple indicators into a total pain score, none have passed a critical discriminant validity test, bias introduced from human caregivers). Thus, the complexity of preterm pain assessment necessitates a machine learning approach. 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, better understanding how skin-to-skin contact works in caregiver-infant dyads and factors that influence the effectiveness of this pain management strategy is a critical step in improving infant pain care in NICUs. Relatedly, the design and sample of our current study (acute pain paradigm while infant is either in skin-to-skin contact with the birthing parent or in the cot) allows us to not only test the influence of skin-to-skin contact vs. cot on preterm newborn pain responding, but also interrogate potential mechanisms underlying the effectiveness of skin-to-skin contact (i.e., cardiac regulation attunement between caregivers and their infants during the procedure; influence of birthing parent perceived stress given the particularly elevated stress levels of NICU parents). A sample of 400 preterm infants (300 from Mount Sinai Hospital and 100 from University College London Hospital [UCLH]) and their birthing parents (if available) will be followed during a routine painful procedure (heel lance). Pain indicators (facial grimacing [behavioural indicators], heart rate, respiration rate, oxygen saturation levels [physiologic indicators], brain electrical activity) during the painful procedure will be used to train the algorithm to discriminate between different types of distress (pain-related and non-pain related). Heart rate and respiration rate, as well as maternal-reported perceived stress levels, will be collected from the birthing parent to examine factors impacting the effectiveness of skin-to-skin contact.
- Conditions
- Acute Pain
- Keywords
- NICU (Neonatal Intensive Care Unit), Artificial Intelligence, Pain Assessment, Skin-to-Skin Contact, Parent Stress, Pain Management
- Medical subject headings
- Acute Pain, Agnosia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Infants Hospitalized in the NICU | Infants born between 25 0/7 weeks 32 6/7 weeks gestational age, who are within 8 weeks postnatal age, and their caregiver (if available) and/or health professional will be recruited for qualitative interview. Infants will participate in the study either in skin-to-skin contact with the birthing parent or in the cot if the parent is unable to participate. If the baby participates in a skin-to-skin study, they will be transferred from the cot to skin-to-skin following EEG electrode placement and a 10-minute cot baseline recording. Babies will be then exposed to a sham lance and a real lance while in skin-to-skin. For cot studies, babies are kept in the cot for the whole study duration, and thus the sham lance and real lance will be conducted while they are in the cot receiving standard care. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Behavioural Correlate of Distress
To be analyzed using machine learning via bedside videography: Facial Grimacing using Neonatal Facial Coding System (NFCS-P subset; Bucsea et al., 2022, 10.1097/j.pain.0000000000002798)
Measured: NFCS-P coded in 1-5 minute epochs, over 2 hour surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
Cortical Correlate of Distress
To be analyzed using machine learning via bedside monitoring: Continuous EEG data capture
Measured: For 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
Cardiac Correlates of Distress
To be analyzed using machine learning via bedside monitoring: Heart Rate, Heart Rate Variability
Measured: Over 2 hours surrounding painful procedure (time locked to heel lance)
Oxygen Saturation Correlate of Distress
To be analyzed using machine learning via bedside monitoring: amount of oxygen-carrying hemoglobin in the blood relative to the amount of hemoglobin not carrying oxygen
Measured: Over 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
Respiration Rate Correlate of Distress
To be analyzed using machine learning via bedside monitoring: Respiratory patterns
Measured: [Time Frame: Over 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)]
Secondary outcomes (6)
Birthing Parent Heart Rate and Respiration Rate
We will measure parent cardiac stress in order to control for the effect of the parent context on infant pain processing. We will collect ECG data with 3 leads and a thin belt for respiration from the CNS monitor.
Measured: [Time Frame: Over 1.5 hours surrounding painful procedure (time locked to heel lance)]
Chart review of general health indicators and other NICU experiences (control as potential confounders), such as:
- Gestational age at birth, post menstrual age at study, and postnatal age
- Birthweight
- Current weight
- Sex
- Birth order
- Type of delivery and any resuscitation required
- Appearance, Pulse, Grimace, Activity, and Respiration (APGAR) scores at birth (1 and 5 minutes)
- SNAP II scores
- Ventilation requirements
- Type and time of last feed
- What indwelling devices are present during the study
- Area or location of study
- Diagnoses (active problems in the last 72h and any diagnosis that have now resolved [>72h])
- Antenatal history
- Brain imaging (cranial ultrasound)
- Acute procedure history (type, per day, number of attempts)
- Amount of skin to skin per day
- Hours since last skin-breaking procedure \& number of skin-breaking procedures in the 48-hours preceding the heel lance
- Total doses of sucrose \& sucrose at time of study
- Drug classes at time of heel lance
Measured: Extracted from participants' medical charts following study completion
Chart Review of Cumulative Painful Procedures
We will collect data on the cumulative exposure of painful and/or invasive procedures that the infant experienced since birth. A published tool will be used to calculate total pain burden during their NICU stay (Laudiano-Dray et al., 2020; 10.1097/j.pain.0000000000001814).
Measured: Extracted from participants' medical charts following study completion
Parent Self-Report Questionnaires
Four questionnaires will be completed to understand the perspectives and experiences of birthing parents at time of study:
- Participant Information Sheet (PIS) - quantifies socio-economic status, ethnic background, and familial characteristics of the sample.
- Parental Stress Scale: NICU (PSS:NICU) - measures NICU specific stress
- Experiences in Close Relationships Scale (ECR) - measures adult attachment patterns
- Perceived Stress Scale (PSS) - measures general stress levels
Measured: Completed at the beginning of the study while EEG electrodes are being applied to the baby
Detailed documentation of noxious and sham stimulation details: (Control for their influence on infant responses)
- Time of lance/sham
- Stimulation site
- Infant position
- Exact monitoring measurements taken or failed
- Sleep/wake states
- Any cuts visible on the heels (including the other heel not lanced)
- Maternal position
- Degree of skin contact
- Blood test required for the lance and volume
- Whether heel was squeezed during lance and duration (if applicable)
Measured: Documented following the study completion
Semi-Structured Interview
Health Professionals and Caregivers will be asked about their thoughts on using AI for infant pain assessment
Measured: These interviews are occurring at the beginning of the study and will be qualitatively analyzed. They are not linked to infants whose data we are collecting primary outcomes.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Oct 2022
- Study start1 Nov 2020
- Primary completionMar 2030 (estimated)
- Study completionMar 2031 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute PainStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- York University
- Sponsor type
- University, hospital or other
- Collaborators
- MOUNT SINAI HOSPITAL, University College, London, University College London Hospitals
- Responsible party
- Principal investigator, Rebecca Pillai Riddell, York University
- Investigators
- Rebecca Pillai Riddell, PhD, Principal investigator, York University/Mount Sinai Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05579496
- Sponsor's protocol ID
- 19-0252-A
- Acronym
- BabyAIBabyCalm
- Status last verified
- Jul 2026
- First submitted
- 24 Dec 2020
- Last updated
- 13 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Rebooting Infant Pain Care: Using Machine Learning and Skin-to-Skin Contact to Exponentially Improve Neonatal Intensive Care Unit Practice
- ClinicalTrials.gov ID
- NCT05579496
- Acronym / sponsor ID
- BabyAIBabyCalm / 19-0252-A
- Conditions
- Acute Pain
- Keywords
- NICU (Neonatal Intensive Care Unit), Artificial Intelligence, Pain Assessment, Skin-to-Skin Contact, Parent Stress, Pain Management
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- York UniversityUniversity, hospital or other
- Collaborators
- MOUNT SINAI HOSPITAL, University College, London, University College London Hospitals
- Study start
- 1 Nov 2020 (actual)
- Primary completion
- Mar 2030 (estimated)
- Study completion
- Mar 2031 (estimated)
- First posted
- 13 Oct 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Unmanaged pain in hospitalized infants has serious long-term complications. Existing infant pain assessment approaches demonstrate several key flaws (e.g., dependent on human cognitive capacity to simply combine data from multiple indicators into a total pain score, none have passed a critical discriminant validity test, bias introduced from human caregivers). Thus, the complexity of preterm pain assessment necessitates a machine learning approach. 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, better understanding how skin-to-skin contact works in caregiver-infant dyads and factors that influence the effectiveness of this pain management strategy is a critical step in improving infant pain care in NICUs. Relatedly, the design and sample of our current study (acute pain paradigm while infant is either in skin-to-skin contact with the birthing parent or in the cot) allows us to not only test the influence of skin-to-skin contact vs. cot on preterm newborn pain responding, but also interrogate potential mechanisms underlying the effectiveness of skin-to-skin contact (i.e., cardiac regulation attunement between caregivers and their infants during the procedure; influence of birthing parent perceived stress given the particularly elevated stress levels of NICU parents). A sample of 400 preterm infants (300 from Mount Sinai Hospital and 100 from University College London Hospital [UCLH]) and their birthing parents (if available) will be followed during a routine painful procedure (heel lance). Pain indicators (facial grimacing [behavioural indicators], heart rate, respiration rate, oxygen saturation levels [physiologic indicators], brain electrical activity) during the painful procedure will be used to train the algorithm to discriminate between different types of distress (pain-related and non-pain related). Heart rate and respiration rate, as well as maternal-reported perceived stress levels, will be collected from the birthing parent to examine factors impacting the effectiveness of skin-to-skin contact.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Infants Hospitalized in the NICU | – | –Infants born between 25 0/7 weeks 32 6/7 weeks gestational age, who are within 8 weeks postnatal age, and their caregiver (if available) and/or health professional will be recruited for qualitative interview. Infants will participate in the study either in skin-to-skin contact with the birthing parent or in the cot if the parent is unable to participate. If the baby participates in a skin-to-skin study, they will be transferred from the cot to skin-to-skin following EEG electrode placement and a 10-minute cot baseline recording. Babies will be then exposed to a sham lance and a real lance while in skin-to-skin. For cot studies, babies are kept in the cot for the whole study duration, and thus the sham lance and real lance will be conducted while they are in the cot receiving standard care. |
Who may qualify
- Ages
- 25 to 33 weeks
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
- Study population
- Preterm infants
Key inclusion criteria (5 listed)
- Parents of a child currently in the NICU or
- Health professionals currently working in the NICU.
- 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
Key exclusion criteria (7 listed)
- Participants who cannot communicate fluently in English
- QUANTITITATIVE DATA CAPTURE (video, eeg, ecg, RR, SPo2)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Behavioural Correlate of Distress
Time frame: NFCS-P coded in 1-5 minute epochs, over 2 hour surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
To be analyzed using machine learning via bedside videography: Facial Grimacing using Neonatal Facial Coding System (NFCS-P subset; Bucsea et al., 2022, 10.1097/j.pain.0000000000002798)
Cortical Correlate of Distress
Time frame: For 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
To be analyzed using machine learning via bedside monitoring: Continuous EEG data capture
Cardiac Correlates of Distress
Time frame: Over 2 hours surrounding painful procedure (time locked to heel lance)
To be analyzed using machine learning via bedside monitoring: Heart Rate, Heart Rate Variability
Oxygen Saturation Correlate of Distress
Time frame: Over 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)
To be analyzed using machine learning via bedside monitoring: amount of oxygen-carrying hemoglobin in the blood relative to the amount of hemoglobin not carrying oxygen
Respiration Rate Correlate of Distress
Time frame: [Time Frame: Over 2 hours surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)]
To be analyzed using machine learning via bedside monitoring: Respiratory patterns
6 secondary outcomes
Birthing Parent Heart Rate and Respiration Rate
Time frame: [Time Frame: Over 1.5 hours surrounding painful procedure (time locked to heel lance)]
Chart review of general health indicators and other NICU experiences (control as potential confounders), such as:
Time frame: Extracted from participants' medical charts following study completion
Chart Review of Cumulative Painful Procedures
Time frame: Extracted from participants' medical charts following study completion
Parent Self-Report Questionnaires
Time frame: Completed at the beginning of the study while EEG electrodes are being applied to the baby
Detailed documentation of noxious and sham stimulation details: (Control for their influence on infant responses)
Time frame: Documented following the study completion
Semi-Structured Interview
Time frame: These interviews are occurring at the beginning of the study and will be qualitatively analyzed. They are not linked to infants whose data we are collecting primary outcomes.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jul 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Rebecca Pillai Riddell, PhD principal investigator
York University/Mount Sinai Hospital
2 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Pain, run by York University at 2 sites in 2 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 13 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Canada, United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Rebecca Pillai Riddell, PhD (4167362100 ext. ext. 20177, rpr@yorku.ca), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Behavioural Correlate of Distress (time frame: NFCS-P coded in 1-5 minute epochs, over 2 hour surrounding painful procedure (time locked to heel lance; approximately 1 hour before to 1 hour after heel lance)). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Jul 2026.