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Table 1 Comparison of some automated methods for patient-ventilator asynchrony detection

From: Patient-ventilator asynchronies during mechanical ventilation: current knowledge and research priorities

 Type of PVAAlgorithmPerformance
Gholami et al. (2018) [69]Cycling asynchrony (premature and delayed cycling)ML: Random forest and k-fold cross validation
Pressure and airflow signals
N = 11 patients (1377 breaths)
Se 89–97%, Sp 93–99%, Kappa index 0.9
ventMAP platform
Adams et al. (2017) [70]
Double-trigger and breath stackingRule-based algorithm
Pressure and airflow signals
Derivation cohort, N = 16 patients (5075 breaths); validation cohort, N = 17 patients (4644 breaths)
Se 94–96.7%, Sp 92–98%, Acc 92.2–97.7%
(on the validation cohort)
NeuroSync index
Sinderby et al. (2013) [71]
Patient-ventilator interaction classification (asynchronous, dyssynchronous or synchronous)Rule-based timings algorithm
EAdi and pressure signals
N = 24 patients
ICC 0.95 vs. Colombo et al. (2011) [5]
Better Care® system
Blanch et al. (2012) [37]
Ineffective efforts during expirationRule-based combining digital signal processing techniques and ROC curves
Airflow signal
Cohort 1: N = 8 patients (1024 breaths)
Cohort 2: N = 8 patients (9600 breaths) with EAdi signal as reference
Se 91.5%, Sp 91.7%, PPV 80.3%, NPV 96.7%, Kappa index 0.797
(vs. the expert’s classification)
Se 65.2%, Sp 99.3%, PPV 90.8%, NPV 96.5%, Kappa index 0.739
(vs. EAdi signal)
Gutierrez et al. (2011) [72]Index for asynchronous/no asynchronous breathsTime-frequency analysis
Airflow signals
N = 110 patients
Se 83%, Sp 83% when index < 43% for AI > 10%
Mulqueeny et al. (2007) [73]Ineffective triggering and double triggeringRule-based and digital signal processing methods
Airflow and pressure signals
N = 20 patients (3343 breaths)
Se 91%, Sp 97%
PVI monitor
Younes et al. (2007) [74]
Ineffective effortsRule-based
Equation of motion from pressure, airflow, and Peso signals
N = 21 patients
Se 79.7%
  1. Abbreviations: ML machine learning, Se sensitivity, Sp specificity, ICC intraclass correlation coefficient, Acc overall accuracy, Peso esophageal pressure, PPV positive predictive value, NPV negative predictive value, ROC receiver operating characteristics, AI asynchrony index according to the definition from Thille et al. [7]