The flow-pressure plot: a new look on the patient-ventilator interaction in neonatal care

Visual function scale for identification of infants with low respiratory compliance

AIM

Precise estimation of respiratory function is essential to optimise neonatal respiratory care. However, current clinical scores have not been validated with quantitative measures of respiratory function. The aim of this study was to develop a physiological scoring system to predict low respiratory dynamic compliance of <0.6 ml/cmH₂O/kg.

METHODS

Forty-four newborn infants were studied before (dynamic compliance) and shortly after scheduled extubation (physiological signs). A novel scoring system was developed based on the association between physiological signs and dynamic compliance.

RESULTS

The respiratory rate was identified as the primary independent variable for dynamic compliance in the univariate analysis. The prediction score for low dynamic compliance comprised the presence of nasal flaring, see-saw respiration, suprasternal/intercostal retraction, and the respiratory rate ranks (0-3). The area under the receiver-operating characteristics curve of the composite score had discriminatory capability of 0.86 (95% confidence interval: 0.75-0.97) to predict low dynamic compliance with the optimal cut-off value of ≥3 (sensitivity, 0.882; specificity, 0.667).

CONCLUSION

Our novel scoring system might help predict newborn infants with low dynamic compliance, who may require escalation of respiratory support, or transfer to higher level units.

Automated respiratory cycles selection is highly specific and improves respiratory mechanics analysis

OBJECTIVE

Selected optimal respiratory cycles should allow calculation of respiratory mechanic parameters focusing on patient-ventilator interaction. New computer software automatically selecting optimal breaths and respiratory mechanics derived from those cycles are evaluated.

DESIGN

Retrospective study.

SETTING

University level III neonatal intensive care unit.

SUBJECTS

Ten mins synchronized intermittent mandatory ventilation and assist/control ventilation recordings from ten newborns.

INTERVENTION

The ventilator provided respiratory mechanic data (ventilator respiratory cycles) every 10 secs. Pressure, flow, and volume waves and pressure-volume, pressure-flow, and volume-flow loops were reconstructed from continuous pressure-volume recordings. Visual assessment determined assisted leak-free optimal respiratory cycles (selected respiratory cycles). New software graded the quality of cycles (automated respiratory cycles). Respiratory mechanic values were derived from both sets of optimal cycles. We evaluated quality selection and compared mean values and their variability according to ventilatory mode and respiratory mechanic provenance. To assess discriminating power, all 45 "t" values obtained from interpatient comparisons were compared for each respiratory mechanic parameter.

MEASUREMENTS AND MAIN RESULTS

A total of 11,724 breaths are evaluated. Automated respiratory cycle/selected respiratory cycle selections agreement is high: 88% of maximal κ with linear weighting. Specificity and positive predictive values are 0.98 and 0.96, respectively. Averaged values are similar between automated respiratory cycle and ventilator respiratory cycle. C20/C alone is markedly decreased in automated respiratory cycle (1.27 ± 0.37 vs. 1.81 ± 0.67). Tidal volume apparent similarity disappears in assist/control: automated respiratory cycle tidal volume (4.8 ± 1.0 mL/kg) is significantly lower than for ventilator respiratory cycle (5.6 ± 1.8 mL/kg). Coefficients of variation decrease for all automated respiratory cycle parameters in all infants. "t" values from ventilator respiratory cycle data are two to three times higher than ventilator respiratory cycles.

CONCLUSIONS

Automated selection is highly specific. Automated respiratory cycle reflects most the interaction of both ventilator and patient. Improving discriminating power of ventilator monitoring will likely help in assessing disease status and following trends. Averaged parameters derived from automated respiratory cycles are more precise and could be displayed by ventilators to improve real-time fine tuning of ventilator settings.

Case-control study of respiratory dynamic compliance in mechanically ventilated near-term newborns in a pre-hospital setting

PURPOSE

To determine the threshold value between normal or decreased dynamic compliance (Cdyn) in ventilated near-term newborns.

METHODS

A case control study was performed during pediatric transport. Controls were newborns without pulmonary disease (group 1; n = 30) and cases were newborns with respiratory distress syndrome, the paradigm of decreased Cdyn (group 2; n = 30). All consecutive newborns of more than 34 weeks' gestation and less than 5 days of life, intubated and ventilated with Babylog 8,000 plus (Dräger, Lübeck, Germany) were included from February 2008 to June 2010. Newborns were assigned to groups 1, 2, or 3 (other patients with disease where the compliance is not easily predictable) by two physicians, using predefined criteria. Cdyn was as measured by the ventilator in spontaneous mandatory ventilation mode with less than 15% leaks.

RESULTS

One hundred and twelve newborns were included in the study. In the multivariate analysis, the groups of diseases and height were statistically associated with Cdyn (p < 0.001). The receiver operating characteristic curve of Cdyn corrected for height constructed with group 1 and 2 newborns yielded a cutoff value of 2.02 mL/mbar/m with a sensitivity of 100% (95% confidence interval [100-100%]) and a specificity of 96% (95% confidence interval [90-100%]) to differentiate between group 1 and 2 newborns.

CONCLUSION

Ventilator-measured dynamic compliance can differentiate normal and decreased compliance in near-term newborns of more than 34 weeks' gestation in the clinical setting.

Experimental evaluation of errors in the measurement of respiratory parameters of the newborn performed by a continuous flow neonatal ventilator

Pulmonary ventilators for intensive care provide information on, among many other patient respiratory parameters, patient resistance, compliance and 'work of breathing' values calculated from pressure and flow data patterns according to a widely utilized algorithm. The effects induced by the breathing circuit and analogue filtering of the ventilator measuring system are experimentally investigated during controlled ventilation. Three main phenomena are observed: (a) errors in calculation of resistance and compliance due to filtering of pressure and flow waveforms; (b) the presence of pressure oscillations at the beginning of inspiration and expiration phases; and (c) the phase shift between pressure and flow waveforms. The experimental evaluation of the measuring system of a neonatal ventilator is then conducted and: (a) a delay in pressure and flow measurement synchronization equal to 22 +/- 2 ms is evaluated; moreover, (b) a difference between the values provided by the ventilator and those measured by the reference experimental setup on respiratory parameters such as the compliance, resistance and work of breathing that lies in the range of 7-16% of reading is observed.