Evaluation of the multiple linear regression method to monitor respiratory mechanics in ventilated neonates and young children

A potentially useful method to monitor respiratory mechanics in artificially ventilated patients consists of analyzing the relationship between tracheal pressure (P), lung volume (V), and gas flow ($ \mathop {\rm V}\limits^. $) by multiple linear regression (MLR) using a suitable model. Contrary to other methods, it does not require any particular flow waveform and, therefore, may be used with any ventilator. This approach was evaluated in three neonates and seven young children admitted into an intensive care unit for respiratory disorders of various etiologies. P and V were measured and digitized at a sampling rate of 40 Hz for periods of 20–48 s. After correction of P for the non‐linear resistance of the endotracheal tube, the data were first analyzed with the usual linear monoalveolar model: P = PO + E.V + R.$ \mathop {\rm V}\limits^. $ where E and R are total respiratory elastance and resistance, and PO is the static recoil pressure at end‐expiration. A good fit of the model to the data was seen in five of ten children. PO, E, and R were reproducible within cycles, and consistent with the patient's age and condition; the data obtained with two ventilatory modes were highly correlated. In the five instances in which the simple model did not fit the data well, they were reanalyzed with more sophisticated models allowing for mechanical non‐homogeneity or for non‐linearity of R or E. While several models substantially improved the fit, physiologically meaningful results were only obtained when R was allowed to change with lung volume. We conclude that the MLR method is adequate to monitor respiratory mechanics, even when the usual model is inadequate.