Purpose Ineffective respiratory efforts during expiration (IEE) are a problem during mechanical ventilation (MV). The goal of this study is to validate mathematical algorithms that automatically detect IEE in a computerized (Better Care®) system that obtains and processes data from intensive care unit (ICU) ventilators in real time. Methods The Better Care® system, integrated with ICU health information systems, synchronizes and processes data from bedside technology. Algorithms were developed to analyze airflow waveforms during expiration to determine IEE. Data from 2,608,800 breaths from eight patients were recorded. From these breaths 1,024 were randomly selected. Five experts independently analyzed the selected breaths and classified them as IEE or not IEE. Better Care® evaluated the same 1,024 breaths and assigned a score to each one. The IEE score cutoff point was determined based on the experts’ analysis. The IEE algorithm was subsequently validated using the electrical activity of the diaphragm (EAdi) signal to analyze 9,600 breaths in eight additional patients. Results Optimal sensitivity and specificity were achieved by setting the cutoff point for IEE by Better Care® at 42%. A score >42% was classified as an IEE with 91.5% sensitivity, 91.7% specificity, 80.3% positive predictive value (PPV), 96.7% negative predictive value (NPV), and 79.7% Kappa index [confidence interval (CI) (95%) = (75.6%; 83.8%)]. Compared with the EAdi, the IEE algorithm had 65.2% sensitivity, 99.3% specificity, 90.8% PPV, 96.5% NPV, and 73.9% Kappa index [CI (95%) = (71.3%; 76.3%)]. Conclusions In this pilot, Better Care® classified breaths as IEE in close agreement with experts and the EAdi signal.

Validation of the Better Care® system to detect ineffective efforts during expiration in mechanically ventilated patients: a pilot study

LUCANGELO, UMBERTO;BORELLI, MASSIMO;
2012-01-01

Abstract

Purpose Ineffective respiratory efforts during expiration (IEE) are a problem during mechanical ventilation (MV). The goal of this study is to validate mathematical algorithms that automatically detect IEE in a computerized (Better Care®) system that obtains and processes data from intensive care unit (ICU) ventilators in real time. Methods The Better Care® system, integrated with ICU health information systems, synchronizes and processes data from bedside technology. Algorithms were developed to analyze airflow waveforms during expiration to determine IEE. Data from 2,608,800 breaths from eight patients were recorded. From these breaths 1,024 were randomly selected. Five experts independently analyzed the selected breaths and classified them as IEE or not IEE. Better Care® evaluated the same 1,024 breaths and assigned a score to each one. The IEE score cutoff point was determined based on the experts’ analysis. The IEE algorithm was subsequently validated using the electrical activity of the diaphragm (EAdi) signal to analyze 9,600 breaths in eight additional patients. Results Optimal sensitivity and specificity were achieved by setting the cutoff point for IEE by Better Care® at 42%. A score >42% was classified as an IEE with 91.5% sensitivity, 91.7% specificity, 80.3% positive predictive value (PPV), 96.7% negative predictive value (NPV), and 79.7% Kappa index [confidence interval (CI) (95%) = (75.6%; 83.8%)]. Compared with the EAdi, the IEE algorithm had 65.2% sensitivity, 99.3% specificity, 90.8% PPV, 96.5% NPV, and 73.9% Kappa index [CI (95%) = (71.3%; 76.3%)]. Conclusions In this pilot, Better Care® classified breaths as IEE in close agreement with experts and the EAdi signal.
2012
http://www.springerlink.com/content/87p11477j13857k2/
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2614028
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