- ICH GCP
- Registro degli studi clinici negli Stati Uniti
- Sperimentazione clinica NCT07794007
Automated Apnoea Detection in Preterms on Non-invasive Ventilation
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.
Panoramica dello studio
Stato
Condizioni
Intervento / Trattamento
Descrizione dettagliata
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.
Tipo di studio
Iscrizione (Stimato)
Contatti e Sedi
Contatto studio
- Nome: Ourania Kaltsogianni, MD (Res)
- Numero di telefono: 38494 0044+02032999000
- Email: ourania.kaltsogianni@nhs.net
Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
- Bambino
Accetta volontari sani
Metodo di campionamento
Popolazione di studio
Descrizione
Inclusion Criteria:
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.
Exclusion Criteria:
- Infants born above 32 weeks of gestation.
- Infants with known major congenital abnormalities.
- Infants above 36 weeks postmenstrual age (PMA).
- Non-English speakers.
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Lasso di tempo |
|---|---|
|
Number of apnoeic episodes correctly identified by the automated machine learning model
Lasso di tempo: From enrollment to the end of monitoring at eight hours
|
From enrollment to the end of monitoring at eight hours
|
Misure di risultato secondarie
Misura del risultato |
Lasso di tempo |
|---|---|
|
The proportion of apnoeas correctly classified as central or obstructive by the automated machine learning model
Lasso di tempo: From enrollment to the end of monitoring at eight hours
|
From enrollment to the end of monitoring at eight hours
|
Collaboratori e investigatori
Investigatori
- Investigatore principale: Anne Greenough, Professor, King's College Hospital NHS Trust
Studiare le date dei record
Studia le date principali
Inizio studio (Stimato)
Completamento primario (Stimato)
Completamento dello studio (Stimato)
Date di iscrizione allo studio
Primo inviato
Primo inviato che soddisfa i criteri di controllo qualità
Primo Inserito (Effettivo)
Aggiornamenti dei record di studio
Ultimo aggiornamento pubblicato (Effettivo)
Ultimo aggiornamento inviato che soddisfa i criteri QC
Ultimo verificato
Maggiori informazioni
Termini relativi a questo studio
Parole chiave
Termini MeSH pertinenti aggiuntivi
- Malattie urogenitali
- Malattie del sistema nervoso
- Malattie urogenitali femminili e complicanze della gravidanza
- Travaglio ostetrico, prematuro
- Complicanze ostetriche del lavoro
- Complicazioni della gravidanza
- Malattie delle vie respiratorie
- Disturbi respiratori
- Disturbi del sonno e della veglia
- Segni e sintomi, respiratori
- Disturbi del sonno, intrinseci
- Dissonnie
- Sindromi da apnee notturne
- Condizioni patologiche, segni e sintomi
- Segni e sintomi
- Nascita prematura
- Apnea
- Apnea notturna, centrale
Altri numeri di identificazione dello studio
- 371040
Piano per i dati dei singoli partecipanti (IPD)
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