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

被引:107
作者
Blanch, Lluis [1 ,2 ,3 ]
Sales, Bernat [2 ,3 ]
Montanya, Jaume [3 ]
Lucangelo, Umberto [4 ]
Garcia-Esquirol, Oscar [1 ,3 ]
Villagra, Ana [1 ,2 ]
Chacon, Encarna [1 ]
Estruga, Anna [1 ]
Borelli, Massimo [4 ]
Jose Burgueno, Ma [1 ]
Oliva, Joan C. [3 ]
Fernandez, Rafael [2 ,5 ]
Villar, Jesus [2 ,6 ]
Kacmarek, Robert [7 ,8 ]
Murias, Gaston [9 ]
机构
[1] Univ Autonoma Barcelona, Crit Care Ctr, Hosp Sabadell, Sabadell 08208, Spain
[2] ISCiii, CIBER Enfermedades Respiratorias, Madrid, Spain
[3] Univ Autonoma Barcelona, Fundacio Parc Tauli, Sabadell 08208, Spain
[4] Univ Trieste, Dept Perioperat Med Intens Care & Emergency, Cattinara Hosp, Trieste, Italy
[5] Manresa & Univ Internac Catalunya, Servei Med Intens, Fundacio Althaia, Barcelona, Spain
[6] Hosp Univ Dr Negrin, MODERN, Res Unit, Las Palmas Gran Canaria, Spain
[7] Massachusetts Gen Hosp, Boston, MA 02114 USA
[8] Harvard Univ, Sch Med, Boston, MA USA
[9] Clin Bazterr & Clin Santa Isabel, Buenos Aires, DF, Argentina
关键词
Mechanical ventilation; Patient-ventilator dyssynchronies; Ineffective inspiratory efforts during expiration; Expiratory flow pattern; Expert clinicians analysis; Automatic algorithms; RESPIRATORY-FAILURE; FLOW; ASYNCHRONIES;
D O I
10.1007/s00134-012-2493-4
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
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(A (R))) system that obtains and processes data from intensive care unit (ICU) ventilators in real time. The Better Care(A (R)) 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(A (R)) 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. Optimal sensitivity and specificity were achieved by setting the cutoff point for IEE by Better Care(A (R)) 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%)]. In this pilot, Better Care(A (R)) classified breaths as IEE in close agreement with experts and the EAdi signal.
引用
收藏
页码:772 / 780
页数:9
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