title: Real time noninvasive estimation of work of breathing using facemask leak-corrected tidal volume during noninvasive pressure support: validation study.
abstract: We describe a real time, noninvasive method of estimating work of breathing (esophageal balloon not required) during noninvasive pressure support (PS) that uses an artificial neural network (ANN) combined with a leak correction (LC) algorithm, programmed to ignore asynchronous breaths, that corrects for differences in inhaled and exhaled tidal volume (VT) from facemask leaks (WOBANN,LC/min). Validation studies of WOBANN,LC/min were performed. Using a dedicated and popular noninvasive ventilation ventilator (V60, Philips), in vitro studies using PS (5 and 10 cm H2O) at various inspiratory flow rate demands were simulated with a lung model. WOBANN,LC/min was compared with the actual work of breathing, determined under conditions of no facemask leaks and estimated using an ANN (WOBANN/min). Using the same ventilator, an in vivo study of healthy adults (n = 8) receiving combinations of PS (3-10 cm H2O) and expiratory positive airway pressure was done. WOBANN,LC/min was compared with physiologic work of breathing/min (WOBPHYS/min), determined from changes in esophageal pressure and VT applied to a Campbell diagram. For the in vitro studies, WOBANN,LC/min and WOBANN/min ranged from 2.4 to 11.9 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBANN/breath, r = 0.99, r(2) = 0.98 (p < 0.01). There were essentially no differences between WOBANN,LC/min and WOBANN/min. For the in vivo study, WOBANN,LC/min and WOBPHYS/min ranged from 3 to 12 J/min and there was an excellent relationship between WOBANN,LC/breath and WOBPHYS/breath, r = 0.93, r(2) = 0.86 (p < 0.01). An ANN combined with a facemask LC algorithm provides noninvasive and valid estimates of work of breathing during noninvasive PS. WOBANN,LC/min, automatically and continuously estimated, may be useful for assessing inspiratory muscle loads and guiding noninvasive PS settings as in a decision support system to appropriately unload inspiratory muscles.
authors.affiliation: Department of Anesthesiology, University of Florida College of Medicine, 1600 SW Archer Road, PO Box 100254, Gainesville, FL, 32610, USA. MBanner@anest.ufl.edu.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Banner
authors.affiliation: Convergent Engineering, 107 SW 140th Terrace, #1, Newberry, FL, 32669, USA.
authors.forename: Carl G
authors.initials: CG
authors.lastname: Tams
authors.affiliation: Convergent Engineering, 107 SW 140th Terrace, #1, Newberry, FL, 32669, USA.
authors.forename: Neil R
authors.initials: NR
authors.lastname: Euliano
authors.affiliation: Santa Fe College, Gainesville, FL, USA.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Stephan
authors.affiliation: Convergent Engineering, 107 SW 140th Terrace, #1, Newberry, FL, 32669, USA.
authors.forename: Trevor J
authors.initials: TJ
authors.lastname: Leavitt
authors.affiliation: Department of Anesthesiology, University of Florida College of Medicine, 1600 SW Archer Road, PO Box 100254, Gainesville, FL, 32610, USA.|Department of Physical Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, 32610, USA.
authors.forename: A Daniel
authors.initials: AD
authors.lastname: Martin
authors.affiliation: Department of Anesthesiology, University of Florida College of Medicine, 1600 SW Archer Road, PO Box 100254, Gainesville, FL, 32610, USA.
authors.forename: Nawar
authors.initials: N
authors.lastname: Al-Rawas
authors.affiliation: Department of Anesthesiology, University of Florida College of Medicine, 1600 SW Archer Road, PO Box 100254, Gainesville, FL, 32610, USA.
authors.forename: Andrea
authors.initials: A
authors.lastname: Gabrielli
mesh_terms: D055371:Acute Lung Injury / Q000503:physiopathology / Q000628:therapy; D000465:Algorithms; D003199:Computer Systems / Q000706:statistics & numerical data; D006801:Humans; D008991:Monitoring, Physiologic / Q000706:statistics & numerical data*; D016571:Neural Networks, Computer; D011312:Pressure; D012121:Respiration, Artificial / Q000295:instrumentation / Q000706:statistics & numerical data; D013990:Tidal Volume / Q000502:physiology; D014939:Work of Breathing / Q000502:physiology
keywords: Facemask; Noninvasive; Real-time corrections; Tidal volume; Work of breathing