Preterm Infant
Conditions
Keywords
Bubble CPAP, Airflow, Neonatal Intensive Care, Respiratory acoustics, Acoustic monitoring, Airway pressure monitoring, Bubbling sounds
Brief summary
This is an observational, proof-of-concept, feasibility study where 30 preterm infants on bubble CPAP with gestational age \< 32+0 weeks will be recruited from the neonatal intensive care unit (NICU) at the Montreal Children's Hospital. The study's main goals are: 1. To determine the relationship between ambient bubbling sounds and delivered pressures in preterm infants on bCPAP. 2. To determine the relationship between transmitted bubbling sounds and airway pressures transmitted to the lungs of preterm infants on bCPAP. 3. To develop models to predict delivered and transmitted bCPAP pressures from the acoustic properties of bubbling sounds.
Detailed description
Continuous positive airway pressure (CPAP) is an essential, non-invasive therapy for treating various respiratory conditions in the Neonatal Intensive Care Units (NICU). CPAP is an effective treatment for respiratory distress syndrome, apneas, or after extubation, exerting its physiological benefits by maintaining upper airway patency and functional residual capacity. Bubble CPAP (bCPAP) is the most widely used CPAP due to its low cost and ease of use. It consists of an inspiratory tube carrying heated and humidified air, a nasal interface, and an expiratory tube immersed in a water chamber. The generation of bubbles in the water chamber by exhaled gas creates low amplitude and high-frequency pressure oscillations that are transmitted back to the chest. Successful CPAP requires constant transmission of the pressure via an unobstructed circuit. However, this is difficult to achieve in practice due to inadequate interface, leaks from an open mouth, and obstructed airway. As a result, bCPAP requires frequent manual checks by nurses and respiratory therapists to ensure that the circuit is secure and unobstructed. As a proposed solution, bCPAP sounds heard in the patient room or upon auscultation are routinely used to assess the effectiveness of CPAP therapy. This sound can be heard both from the water tank creating the vibrations and during auscultation with a stethoscope, as the sound vibration is transmitted to the neonatal lungs. In the current era of digital technology, acoustic sounds can be converted to electronic signals for further processing and analysis. We hypothesize that continuous recording and analysis of bCPAP sounds could be used as a proxy for real-time objective monitoring of the pressure transmitted to infants' lungs.
Interventions
DEVICEExternal pressure transducer
The delivered CPAP pressure will be measured using an ultra-thin, multi-use catheter pressure transducer inserted into a port in the expiratory limb of the bubble CPAP circuit.
DEVICEStandard microphone
The bubble sound of the water tank will be collected with a standard condenser microphone directly affixed to the pole holding the water tank, with a secure clip.
DEVICEWireless acoustic sensor
The wireless acoustic sensor contains a dual microphone capable of capturing target sounds as well as ambient noise. The frequencies associated with ambient noise will be subtracted to maximize the signal-to-noise ratio of the bubble sound waveform. The wireless sensor will be placed on the suprasternal notch of the infant for monitoring the bubble sounds transmitted to the lungs and secured using a silicone-based tape approved for use in neonates. Data will be transmitted in real-time to a research-dedicated tablet using the Bluetooth Communication Controller and stored for future analysis.
DEVICEInternal pressure transducer
The transmitted CPAP pressure will be measured using an ultra-thin, single-use catheter pressure transducer inserted through the mouth to the level of the infant's nasopharynx. The data will be acquired with a sampling rate of 10kHz and stored for later analysis.
Sponsors
McGill University Health Centre/Research Institute of the McGill University Health Centre
Northwestern University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
28 Weeks to 32 Weeks
Healthy volunteers
No
Inclusion criteria
* Infants on bCPAP with gestational age \< 32+0 weeks * Postmenstrual age between 28+0 and 36+6 weeks at the time of the study * Postnatal age greater than 168 hours (7 days) at the time of the study * On the bubble CPAP device with binasal prongs at the time of the study * Receiving bubble CPAP levels of 5 to 7 cm H2O with gas flows between 6L/min and 10L/min at the time of the study
Exclusion criteria
* Infants with known major congenital anomalies * Infants with known congenital heart disorders * Infants with known neuromuscular disease * Infants receiving ventilator-derived CPAP at the time of the study * Infants receiving CPAP via a nasal mask interface at the time of the study * Infants receiving inotropes, narcotics or sedative agents at the time of the study * Infants deemed clinically unstable for the study by the attending neonatologist
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Pressure | 3 hours | The mean pressure and the standard deviation of the pressure will be computed for each segment. |
| External bubble CPAP sounds | 3 hours | Two metrics will be computed: 1. The root mean square (RMS) 2. The power contained between a pre-determined range within each segment; We will determine the range that contains 80% of the signal power, in order to minimize other noises from bubble CPAP signal. |
| Internal bubble CPAP sounds | 3 hours | 1. We will apply biomedical signal processing methods to separate the bubbling sounds from breathing sounds. Then, RMS and power will be computed. 2. We will use the Pearson correlation coefficient to compute the relationship between bubbling sound and pressure metrics. We will evaluate the linear regression models to identify the combination of sound metrics and covariates with the highest predictive accuracy. |
Countries
Canada
Contacts
CONTACTWissam Shalish, MD, PhD
PRINCIPAL_INVESTIGATORWissam Shalish, MD PhD
McGill University Health Centre/Research Institute of the McGill University Health Centre
Outcome results
None listed