• J Clin Monit Comput · Oct 2022

    Pressure-flow breath representation eases asynchrony identification in mechanically ventilated patients.

    • Alberto Casagrande, Francesco Quintavalle, Enrico Lena, Francesco Fabris, and Umberto Lucangelo.
    • Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy.
    • J Clin Monit Comput. 2022 Oct 1; 36 (5): 1499-1508.

    AbstractBreathing asynchronies are mismatches between the requests of mechanically ventilated subjects and the support provided by mechanical ventilators. The most widespread technique in identifying these pathological conditions is the visual analysis of the intra-tracheal pressure and flow time-trends. This work considers a recently introduced pressure-flow representation technique and investigates whether it can help nurses in the early detection of anomalies that can represent asynchronies. Twenty subjects-ten Intensive Care Unit (ICU) nurses and ten persons inexperienced in medical practice-were asked to find asynchronies in 200 breaths pre-labeled by three experts. The new representation increases significantly the detection capability of the subjects-average sensitivity soared from 0.622 to 0.905-while decreasing the classification time-from 1107.0 to 567.1 s on average-at the price of a not statistically significant rise in the number of wrong identifications-specificity average descended from 0.589 to 0.52. Moreover, the differences in experience between the nurse group and the inexperienced group do not affect the sensitivity, specificity, or classification times. The pressure-flow diagram significantly increases sensitivity and decreases the response time of early asynchrony detection performed by nurses. Moreover, the data suggest that operator experience does not affect the identification results. This outcome leads us to believe that, in emergency contexts with a shortage of nurses, intensive care nurses can be supplemented, for the sole identification of possible respiratory asynchronies, by inexperienced staff.© 2021. The Author(s), under exclusive licence to Springer Nature B.V.

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