Neurally adjusted ventilatory assist in ventilated very preterm infants: A crossover study.

OBJECTIVE: To assess the effects of neurally adjusted ventilatory assist (NAVA) ventilation on oxygenation and respiratory parameters in preterm infants. STUDY DESIGN: An observational crossover study with a convenience sample of 19 infants born before 30 gestational weeks. Study parameters were recorded during 3-h periods of both NAVA and conventional ventilation. The proportion of time peripheral oxygen saturation (SpO2 ) and cerebral regional oxygen saturation (cRSO2 ) were within their target ranges, plus the number and severity of desaturation episodes were analyzed. In addition, electrical activity of the diaphragm (Edi), neural respiratory rates, and peak inspiratory pressures (PIPs) were recorded. RESULTS: Infants were born at a median age of 264/7 gestational weeks (range: 230/7 -293/7 ); the study was performed at a median age of 20 days (range: 1-82). The proportion of time SpO2 was within the target range, the number of peripheral desaturations or cRSO2 did not differ between the modes. However, the desaturation severity index was lower (131 vs. 152; p = .03) and fewer manual supplemental oxygen adjustments (1.3 vs. 2.2/h; p = .006) were needed during the period of NAVA ventilation following conventional ventilation. The mean Edi (8.1 vs. 11.4 µV; p < .006) and PIP values (14.9 vs. 19.1; p < .001) were lower during the NAVA mode. CONCLUSIONS: Although NAVA ventilation did not increase the proportion of time with optimal saturation, it was associated with decreased diaphragmatic activity, lower PIPs, less severe hypoxemic events, and fewer manual oxygen adjustments in very preterm infants.

Nasal high-flow therapy decreased electrical activity of the diaphragm in preterm infants during the weaning phase.

AIM: We evaluated whether nasal high-flow therapy was better than no respiratory support during the weaning phase in preterm infants. METHODS: The study was conducted in the neonatal intensive care unit of the Turku University Hospital between September 2014 and August 2015. Preterm infants who were alternating between nasal high-flow therapy and unassisted breathing were enrolled. Electrical activity of the diaphragm (EAdi) was recorded and compared during three-hour time periods for each option. RESULTS: We studied eight infants at a median gestational age of 31 weeks. The EAdi peak was lower during nasal high-flow therapy when compared to no respiratory support (6.1 µV vs 7.1 µV, p = 0.02), but the EAdi minimum was similar with and without respiratory support. Neural respiratory rate (62 vs 68 per minute, p = 0.02) and the frequency of sighs (27.8 vs 37.9 per hour, p = 0.03) were lower during nasal high-flow therapy than no respiratory support. CONCLUSION: Nasal high-flow therapy reduced diaphragm activation in our cohort when compared to no respiratory support, as indicated by the lower Edi peak. An increase in the respiratory rate and the sigh frequency without respiratory support also suggests that nasal high-flow therapy provided support during the weaning phase.

Authoring and verification of clinical guidelines: a model driven approach.

OBJECTIVES: The goal of this research is to provide a framework to enable authoring and verification of clinical guidelines. The framework is part of a larger research project aimed at improving the representation, quality and application of clinical guidelines in daily clinical practice. METHODS: The verification process of a guideline is based on (1) model checking techniques to verify guidelines against semantic errors and inconsistencies in their definition, (2) combined with Model Driven Development (MDD) techniques, which enable us to automatically process manually created guideline specifications and temporal-logic statements to be checked and verified regarding these specifications, making the verification process faster and cost-effective. Particularly, we use UML statecharts to represent the dynamics of guidelines and, based on this manually defined guideline specifications, we use a MDD-based tool chain to automatically process them to generate the input model of a model checker. The model checker takes the resulted model together with the specific guideline requirements, and verifies whether the guideline fulfils such properties. RESULTS: The overall framework has been implemented as an Eclipse plug-in named GBDSSGenerator which, particularly, starting from the UML statechart representing a guideline, allows the verification of the guideline against specific requirements. Additionally, we have established a pattern-based approach for defining commonly occurring types of requirements in guidelines. We have successfully validated our overall approach by verifying properties in different clinical guidelines resulting in the detection of some inconsistencies in their definition. CONCLUSIONS: The proposed framework allows (1) the authoring and (2) the verification of clinical guidelines against specific requirements defined based on a set of property specification patterns, enabling non-experts to easily write formal specifications and thus easing the verification process.