• S Bignall, P Dixon, C Quinn, and R Kitney.
• Department of Paediatrics, Imperial College of Medicine at St. Mary's, London, UK.
• Crit. Care Med. 1997 Mar 1;25(3):545-53.

ObjectivesTo determine the value of a new bedside monitor in assessing the interactions between spontaneous respiratory activity and ventilator inflations in preterm infants; and to monitor continuously the degree of patient-ventilator synchrony and the stability of spontaneous respiratory effort during different modes of ventilation and in response to care procedures.DesignA prospective, observational study of physiologic variables recorded by a computerized monitoring system.SettingA neonatal intensive care unit in a teaching hospital.PatientsThirty-one neonates (median gestational age of 28 wks [range 24 to 36]; median birth weight of 942 g [range 624 to 2940]) were monitored during conventional mandatory ventilation at rates ranging from 47 to 108 inflations/min, and 22 infants (median gestational age of 27.5 wks [range 25 to 40]; median birth weight of 1345 g [range 510 to 3490]) were monitored during patient-triggered ventilation. All infants were sedated as part of the routine care policy.InterventionsSpontaneous respiration (abdominal pressure capsule) and ventilator inflations (airway pressure) were recorded continuously for periods of up to 3 days in mechanically ventilated preterm infants.Measurements And Main ResultsThe monitoring system uses the Frequency Tracking Locus method to derive the interaction Score, which quantifies the degree of entrainment of the spontaneous respiratory pattern by the ventilator. This analysis was applied to airway pressure and abdominal capsule signals. A perfect 1:1 interaction between spontaneous inspirations and mechanical inflations returns an interaction Score of 1.00, and irregular interactions return a score of > 1.5. During conventional mandatory ventilation, a total of 53,074 16-sec epochs (representing 782,811 spontaneous breaths) were studied in 31 preterm infants: 27.4% of epochs showed a 1:1 interaction, 60.5% a non 1:1 interaction, and 12.1% indicated a passive (i.e., infant apneic) response by the infant, despite excluding periods when paralyzing agents were used. The median interaction Score value during 1:1 interactions was 1.2, whereas for non 1:1 interactions the interaction Score was 2.2. One to one entrainment occurred at conventional mandatory ventilation rates between 50 and 85 inflations/min: for many infants, such entrainment was achievable over a range of conventional mandatory ventilation rates, while in some infants respiration was unstable at all rates of conventional mandatory ventilation. During passive ventilation, the median Interaction Score was 1.0. During patient-triggered mechanical ventilation, approximately 67,150 spontaneous respiratory cycles, represented by 3,592 16-sec epochs, were studied in 22 infants. Overall, 19.5% (702) of epochs showed the criteria for ideal triggering by spontaneous inspiration and 19.6% (703) showed autotriggering. In 60.9% (2187) of epochs, a non 1:1 interaction was noted. During ideal patient-triggered mechanical ventilation, the median interaction Score was 1.14; during passive (autotriggered) ventilation, the median Interaction Score was 1.05; and during non 1:1 ventilation, the median score was 1.74. "Autotriggering" was found frequently in infants of < or = 28 wks gestation. The monitor was able to distinguish between stable and unstable interactions and apnea during conventional mandatory ventilation and patient-triggered mechanical ventilation by reference to the Interaction Score value.ConclusionsWe describe a new kind of bedside monitor for the Interpretation of respiratory data. Unlike other methods, it is able to give the clinician a continuous measure of patient-ventilator interaction which is easy to interpret. It appears to have wide-spread application in neonatal intensive care nurseries where the babies' own breathing efforts can affect the efficiency of respiration and cause unwanted physiologic instability. The monitor can be used to determine the optimal ventilatory settings to

22 keywords...

hide…