ApnoeaNCT07794007
Automated Apnoea Detection in Preterms on Non-invasive Ventilation
An observational study of Apnoea and Prematurity, run by King's College Hospital NHS Trust.
Trial summary
The aim of this study is to monitor the frequency of apnoeas (pauses in breathing) on various methods of non-invasive respiratory support that are detected by an automated machine-learning (ML) model based on diaphragmatic electromyography (dEMG), in infants born at less than 32 weeks of gestation. Read more about this study
- Who is it for?
- Ages Up to 36 weeks
- Conditions the study is for
- Apnoea, Prematurity
- What is being tested?
- Diaphragmatic electromyography
- How many people
- 30 participants
- Where
- No sites listed yet
- Study dates
- 7 Sep 2026to 27 Jul 2027
- 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 Up to 36 weeks
- All sexes
- No healthy volunteers
- Child
Study population: Infants admitted and cared for at the Neonatal Intensive Care Unit at King's College Hospital
Who may be able to join
- Preterm infants <32 weeks of gestation at birth and up to 36 weeks postmenstrual age, on non-invasive respiratory support including:
- non-invasive positive pressure ventilation (NIPPV)
- nasal continuous positive airway pressure (CPAP)
- heated humidified high flow nasal cannula (HHFNC) oxygen, either as primary or post extubation respiratory support.
Who cannot join
- Infants born above 32 weeks of gestation.
- Infants with known major congenital abnormalities.
- Infants above 36 weeks postmenstrual age (PMA).
- Non-English speakers.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Prospective Observational Study of Automated Apnoea Detection in Preterm Infants Receiving Non-invasive Respiratory Support
The aim of this study is to monitor the frequency of apnoeas (pauses in breathing) on various methods of non-invasive respiratory support that are detected by an automated machine-learning (ML) model based on diaphragmatic electromyography (dEMG), in infants born at less than 32 weeks of gestation.
Our hypothesis is that the ML algorithm will improve identification of apnoeic episodes and their classification to central or obstructive.
The study will measure outcomes including the number of apnoeic episodes during the monitoring period, their classification to central and obstructive apnoeas and the predictive ability of the machine-learning algorithm to correctly identify and classify these episodes compared to those documented in nursing charts. Correct classification of apnoeic episodes may help identify underlying causes that require specific intervention.
Read the detailed description
When the clinical team identifies an infant is eligible for enrolment to the study and following verbal assent of the attending neonatal consultant, a member of clinical staff will initially approach the parents/ legal guardians of eligible infants and if they agree, a researcher. The parents will be provided with an information sheet about the study. The researchers will answer questions and respond to any concerns in a face-to-face meeting. Written informed consent will be obtained.
Electrical activity of the diaphragm, airway pressure, flow and peripheral oxygen saturation levels will be recorded for a duration of eight hours. Transcutaneous diaphragm EMG (sEMG) will be monitored using three surface electrodes (3M Red Dot Foam monitoring electrode 2228, 3M, United Kingdom) that are placed on the infant's abdomen and sternum. The electrodes are connected to a small battery-operated measuring device (SERA, DEMCON; Makawi Medical Systems, the Netherlands) that amplifies and pre-processes the signals received from the electrodes. The pre-processed signals are sent via a Bluetooth connection to a receiving unit that performs higher level processing to derive the EMG signal and other measurements. These results are communicated via a wired connection to a bedside computer running SERA Graphical User Interface (GUI) software.
Airway pressure and flow signals will be measured by a flow sensor and pressure tube (Sensirion AG, Stäfa, Switzerland) that will be placed between the exit of the SLE6000/ SLE6000N ventilators (Inspiration Healthcare, Croydon, UK) and the tubing that is attached to the patient. This will ensure pressure and flow data are recorded simultaneously with the sEMG signal. These data will also be fed to the SERA measuring device.
An SpO2 cable (SLE uSpO2, Inspiration Healthcare, Croydon, UK) will be connected to the patient and the ventilator for continuous (second by second) recording of SpO2 levels. These data will be time synced using post processing.
Participants will also be connected to the standard bedside monitor (Phillips Intellivue MX750) for the whole duration of the study.
Surface EMG, pressure, flow and SpO2 data will be synchronised. Two researchers will identify all apnoeic episodes and classify them as central, obstructive or noise.
The ML algorithm will also be used to identify and classify apnoeic episodes that occurred during the study duration.
Comparisons will be made between the apnoeic episodes identified the researchers, the ML algorithm and the nursing staff electronic patient records. These records include classification of an episode as apnoea or desaturation or bradycardia, its duration and any actions taken.
- Conditions
- Apnoea, Prematurity
- Being tested
- Diaphragmatic electromyography
- Keywords
- apnoea detection, apnoea classification, obstructive apnoea, central apnoea, preterm infant
- Medical subject headings
- Apnea, Premature Birth, Sleep Apnea, Central
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Diaphragmatic electromyographyDiagnostic test
Also called Airway pressure and flow measurements, Recording of peripheral oxygen saturation levels
Electrical activity of the diaphragm, airway pressure, flow and peripheral oxygen saturation levels will be recorded for a duration of eight hours. Transcutaneous diaphragm EMG (sEMG) will be monitored using three surface electrodes (3M Red Dot Foam monitoring electrode 2228, 3M, United Kingdom) that are placed on the infant's abdomen and sternum. The electrodes are connected to a small battery-operated measuring device (SERA, DEMCON; Makawi Medical Systems, the Netherlands) that amplifies and pre-processes the signals received from the electrodes. The pre-processed signals are sent via a Bluetooth connection to a receiving unit that performs higher level processing to derive the EMG signal and other measurements. These results are communicated via a wired connection to a bedside computer running SERA Graphical User Interface (GUI) software.
Airway pressure and flow signals will be measured by a flow sensor and pressure tube (Sensirion AG, Stäfa, Switzerland) that will be placed betwe
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of apnoeic episodes correctly identified by the automated machine learning model
Measured: From enrollment to the end of monitoring at eight hours
Secondary outcomes (1)
The proportion of apnoeas correctly classified as central or obstructive by the automated machine learning model
Measured: From enrollment to the end of monitoring at eight hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Aug 2026
- Study start7 Sep 2026 (estimated)
- Primary completion27 Jul 2027 (estimated)
- Study completion27 Jul 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ApnoeaStudies of the same condition, open and under way.
- More trials run by King's College Hospital NHS TrustThe sponsor's other registered studies.
- 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
- 30 participants (estimated)
Sponsor and investigators
- Lead sponsor
- King's College Hospital NHS Trust
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Anne Greenough, Professor, Principal investigator, King's College Hospital NHS Trust
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07794007
- Sponsor's protocol ID
- 371040
- Status last verified
- Aug 2026
- First submitted
- 25 Aug 2026
- Last updated
- 31 Aug 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 31 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Observational Study of Automated Apnoea Detection in Preterm Infants Receiving Non-invasive Respiratory Support
- ClinicalTrials.gov ID
- NCT07794007
- Acronym / sponsor ID
- 371040
- Conditions
- Apnoea, Prematurity
- Keywords
- apnoea detection, apnoea classification, obstructive apnoea, central apnoea, preterm infant
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 30 participants (estimated)
- Lead sponsor
- King's College Hospital NHS TrustUniversity, hospital or other
- Study start
- 7 Sep 2026 (estimated)
- Primary completion
- 27 Jul 2027 (estimated)
- Study completion
- 27 Jul 2027 (estimated)
- First posted
- 31 Aug 2026 (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.
The aim of this study is to monitor the frequency of apnoeas (pauses in breathing) on various methods of non-invasive respiratory support that are detected by an automated machine-learning (ML) model based on diaphragmatic electromyography (dEMG), in infants born at less than 32 weeks of gestation.
Our hypothesis is that the ML algorithm will improve identification of apnoeic episodes and their classification to central or obstructive.
The study will measure outcomes including the number of apnoeic episodes during the monitoring period, their classification to central and obstructive apnoeas and the predictive ability of the machine-learning algorithm to correctly identify and classify these episodes compared to those documented in nursing charts. Correct classification of apnoeic episodes may help identify underlying causes that require specific intervention.
Detailed description
When the clinical team identifies an infant is eligible for enrolment to the study and following verbal assent of the attending neonatal consultant, a member of clinical staff will initially approach the parents/ legal guardians of eligible infants and if they agree, a researcher. The parents will be provided with an information sheet about the study. The researchers will answer questions and respond to any concerns in a face-to-face meeting. Written informed consent will be obtained.
Electrical activity of the diaphragm, airway pressure, flow and peripheral oxygen saturation levels will be recorded for a duration of eight hours. Transcutaneous diaphragm EMG (sEMG) will be monitored using three surface electrodes (3M Red Dot Foam monitoring electrode 2228, 3M, United Kingdom) that are placed on the infant's abdomen and sternum. The electrodes are connected to a small battery-operated measuring device (SERA, DEMCON; Makawi Medical Systems, the Netherlands) that amplifies and pre-processes the signals received from the electrodes. The pre-processed signals are sent via a Bluetooth connection to a receiving unit that performs higher level processing to derive the EMG signal and other measurements. These results are communicated via a wired connection to a bedside computer running SERA Graphical User Interface (GUI) software.
Airway pressure and flow signals will be measured by a flow sensor and pressure tube (Sensirion AG, Stäfa, Switzerland) that will be placed between the exit of the SLE6000/ SLE6000N ventilators (Inspiration Healthcare, Croydon, UK) and the tubing that is attached to the patient. This will ensure pressure and flow data are recorded simultaneously with the sEMG signal. These data will also be fed to the SERA measuring device.
An SpO2 cable (SLE uSpO2, Inspiration Healthcare, Croydon, UK) will be connected to the patient and the ventilator for continuous (second by second) recording of SpO2 levels. These data will be time synced using post processing.
Participants will also be connected to the standard bedside monitor (Phillips Intellivue MX750) for the whole duration of the study.
Surface EMG, pressure, flow and SpO2 data will be synchronised. Two researchers will identify all apnoeic episodes and classify them as central, obstructive or noise.
The ML algorithm will also be used to identify and classify apnoeic episodes that occurred during the study duration.
Comparisons will be made between the apnoeic episodes identified the researchers, the ML algorithm and the nursing staff electronic patient records. These records include classification of an episode as apnoea or desaturation or bradycardia, its duration and any actions taken.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- Up to 36 weeks
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
- Study population
- Infants admitted and cared for at the Neonatal Intensive Care Unit at King's College Hospital
Key inclusion criteria (4 listed)
- Preterm infants <32 weeks of gestation at birth and up to 36 weeks postmenstrual age, on non-invasive respiratory support including:
- non-invasive positive pressure ventilation (NIPPV)
- nasal continuous positive airway pressure (CPAP)
- heated humidified high flow nasal cannula (HHFNC) oxygen, either as primary or post extubation respiratory support.
Key exclusion criteria (4 listed)
- Infants born above 32 weeks of gestation.
- Infants with known major congenital abnormalities.
- Infants above 36 weeks postmenstrual age (PMA).
- Non-English speakers.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Diaphragmatic electromyographyAlso: Airway pressure and flow measurements, Recording of peripheral oxygen saturation levelsElectrical activity of the diaphragm, airway pressure, flow and peripheral oxygen saturation levels will be recorded for a duration of eight hours. Transcutaneous diaphragm EMG (sEMG) will be monitored using three surface electrodes (3M Red Dot Foam monitoring electrode 2228, 3M, United Kingdom) that are placed on the infant's abdomen and sternum. The electrodes are connected to a small battery-operated measuring device (SERA, DEMCON; Makawi Medical Systems, the Netherlands) that amplifies and pre-processes the signals received from the electrodes. The pre-processed signals are sent via a Bluetooth connection to a receiving unit that performs higher level processing to derive the EMG signal and other measurements. These results are communicated via a wired connection to a bedside computer running SERA Graphical User Interface (GUI) software. Airway pressure and flow signals will be measured by a flow sensor and pressure tube (Sensirion AG, Stäfa, Switzerland) that will be placed betwe | Diagnostic test | – |
Primary outcome
Number of apnoeic episodes correctly identified by the automated machine learning model
Time frame: From enrollment to the end of monitoring at eight hours
1 secondary outcome
The proportion of apnoeas correctly classified as central or obstructive by the automated machine learning model
Time frame: From enrollment to the end of monitoring at eight hours
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 31 Aug 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.
Anne Greenough, Professor principal investigator
King's College Hospital NHS Trust
Questions about this trial
What is this clinical trial studying?
An observational study of Apnoea and Prematurity, run by King's College Hospital NHS Trust.
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 4 inclusion and 4 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: opening soon, as of the sponsor's last update on 31 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
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 Ourania Kaltsogianni, MD (Res) (0044+02032999000 ext. 38494, ourania.kaltsogianni@nhs.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of apnoeic episodes correctly identified by the automated machine learning model (time frame: From enrollment to the end of monitoring at eight hours). 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 31 Aug 2026.