Quantifying neonatal pulmonary mechanics in mechanical ventilation. (July 2019)
- Record Type:
- Journal Article
- Title:
- Quantifying neonatal pulmonary mechanics in mechanical ventilation. (July 2019)
- Main Title:
- Quantifying neonatal pulmonary mechanics in mechanical ventilation
- Authors:
- Kim, Kyeong Tae
Knopp, Jennifer
Dixon, Bronwyn
Chase, Geoff - Abstract:
- Highlights: NICU ventilation data set of 535, 428 breaths from 9 invasively ventilated NICU patients on conventional ventilation. A single compartment model successfully captures all observed dynamics and mechanics. NICU infants had 21% asynchrony rate, which was partly ventilation mode dependent. There were significant differences in elastance between difference weight groups, and those receiving surfactant therapy. Abstract: Background: Mechanical Ventilation (MV) is an important intensive care therapy. It is often used in neonatal intensive care units (NICUs) to treat respiratory distress syndrome. This paper uses model-based methods in a first in-depth attempt to quantify the underlying lung mechanics in NICU patients. Methods: Up to 24 h of airway flow and pressure data were recorded in 10 mechanically ventilated patients. A single compartment model with added term for the pressure drop across the endotracheal tube is used to identify breath-specific elastance and resistance. Result: The model was fitted to 422, 475 (79%) breaths of 535, 428, with the remainder comprising a range of asynchronies. Elastance was median 1.62 [IQR: 0.85–2.25] cmH2 O/ml and resistance 5.22 [0.00–33.85] cmH2 O.s/ml. Patients treated with surfactant therapy had significantly lower specific elastance (adjusting for weight) than those without (p ≤ 0.01). A decrease in elastance with increasing weight was also noted. Conclusion: The single compartment model was successfully fit with low error.Highlights: NICU ventilation data set of 535, 428 breaths from 9 invasively ventilated NICU patients on conventional ventilation. A single compartment model successfully captures all observed dynamics and mechanics. NICU infants had 21% asynchrony rate, which was partly ventilation mode dependent. There were significant differences in elastance between difference weight groups, and those receiving surfactant therapy. Abstract: Background: Mechanical Ventilation (MV) is an important intensive care therapy. It is often used in neonatal intensive care units (NICUs) to treat respiratory distress syndrome. This paper uses model-based methods in a first in-depth attempt to quantify the underlying lung mechanics in NICU patients. Methods: Up to 24 h of airway flow and pressure data were recorded in 10 mechanically ventilated patients. A single compartment model with added term for the pressure drop across the endotracheal tube is used to identify breath-specific elastance and resistance. Result: The model was fitted to 422, 475 (79%) breaths of 535, 428, with the remainder comprising a range of asynchronies. Elastance was median 1.62 [IQR: 0.85–2.25] cmH2 O/ml and resistance 5.22 [0.00–33.85] cmH2 O.s/ml. Patients treated with surfactant therapy had significantly lower specific elastance (adjusting for weight) than those without (p ≤ 0.01). A decrease in elastance with increasing weight was also noted. Conclusion: The single compartment model was successfully fit with low error. The subgroup cohorts showed expected trends and further validates the identified model values. There was significant breath-to-breath variability in elastance within and between patients. … (more)
- Is Part Of:
- Biomedical signal processing and control. Volume 52(2019)
- Journal:
- Biomedical signal processing and control
- Issue:
- Volume 52(2019)
- Issue Display:
- Volume 52, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 52
- Issue:
- 2019
- Issue Sort Value:
- 2019-0052-2019-0000
- Page Start:
- 206
- Page End:
- 217
- Publication Date:
- 2019-07
- Subjects:
- NICU -- Elastance -- Pulmonary mechanics -- Neonatal -- Respiratory
Signal processing -- Periodicals
Biomedical engineering -- Periodicals
Signal Processing, Computer-Assisted -- Periodicals
Image Processing, Computer-Assisted -- Periodicals
Biomedical Engineering -- Periodicals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/17468094 ↗
http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%2329675%232006%23999989998%23626449%23FLA%23&_cdi=29675&_pubType=J&_auth=y&_acct=C000045259&_version=1&_urlVersion=0&_userid=836873&md5=664b5cf9a57fc91971a17faf20c32ec1 ↗ - DOI:
- 10.1016/j.bspc.2019.04.015 ↗
- Languages:
- English
- ISSNs:
- 1746-8094
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 2087.880400
British Library DSC - BLDSS-3PM
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