Objective: To determine work of breathing per minute or power of breathing noninvasively (POB(N)) by using an artificial neural network (ANN) without the need for an esophageal catheter in patients with respiratory failure.
Design: Prospective study comparing the relationship between POB(N) and invasively measured power of breathing (POB(I)).
Setting: Intensive care unit of a university hospital.
Patients: Forty-five intubated adults (age, 51 +/- 11 yrs; weight, 71 +/- 18 kg; 28 males and 17 females) receiving pressure support ventilation (PSV).
Interventions: Data from an esophageal catheter and airway pressure/flow sensor were used to measure POB(I). A pretrained ANN provided real time calculation of POB(N). POB(I) and POB(N) were measured at various levels of PSV, ranging from 5 to 25 cm H(2)O.
Measurements and main results: POB(N) was highly correlated with POB(I) (r = 0.91; p < .002), and because POB(N) explained or predicted 83% of the variance in POB(I), it was considered a very good predictor (r(2) = 0.83; p < .002). Bias was negligible (0.00) and precision was clinically acceptable (2.2 J/min).
Conclusions: POB can be calculated noninvasively with reasonable clinical accuracy for patients receiving ventilatory support by using an ANN. This method obviates the need for inserting an esophageal catheter and thus greatly simplifies measurement of POB. POB(N) may be a clinically useful tool for consideration when setting PSV to unload the respiratory muscles. Before considering its use in clinical practice, POB(N) would need to be incorporated within the context of load tolerance and shown to improve outcomes.