Patients on weaning trials classified with support vector machines
Por:
Garde, A, Schroeder, R, Voss, A, Caminal, P, Benito, S, Giraldo, BF
Publicada:
1 jul 2010
Resumen:
The process of discontinuing mechanical ventilation is called weaning and is one of the most challenging problems in intensive care. An unnecessary delay in the discontinuation process and an early weaning trial are undesirable. This study aims to characterize the respiratory pattern through features that permit the identification of patients' conditions in weaning trials. Three groups of patients have been considered: 94 patients with successful weaning trials, who couldmaintain spontaneous breathing after 48 h (GSucc); 39 patients who failed the weaning trial (GFail) and 21 patients who had successful weaning trials, but required reintubation in less than 48 h (GRein). Patients are characterized by their cardiorespiratory interactions, which are described by joint symbolic dynamics (JSD) applied to the cardiac interbeat and breath durations. The most discriminating features in the classification of the different groups of patients (GSucc, GFail and GRein) are identified by support vector machines (SVMs). The SVM-based feature selection algorithm has an accuracy of 81% in classifying GSucc versus the rest of the patients, 83% in classifying GRein versus GSucc patients and 81% in classifying GRein versus the rest of the patients. Moreover, a good balance between sensitivity and specificity is achieved in all classifications.
Filiaciones:
Garde, A:
Univ Politecn Cataluna, Dept ESAII, Inst Bioengn Catalonia, Barcelona, Spain
Networking Ctr Biomed Res Bioengn Biomat & Nanome, Barcelona, Spain
Schroeder, R:
Univ Appl Sci Jena, Dept Med Engn & Biotechnol, Jena, Germany
Voss, A:
Univ Appl Sci Jena, Dept Med Engn & Biotechnol, Jena, Germany
Caminal, P:
Univ Politecn Cataluna, Dept ESAII, Inst Bioengn Catalonia, Barcelona, Spain
Networking Ctr Biomed Res Bioengn Biomat & Nanome, Barcelona, Spain
Benito, S:
Hosp Santa Creu & Sant Pau, Dept Intens Care Med, Barcelona, Spain
Giraldo, BF:
Univ Politecn Cataluna, Dept ESAII, Inst Bioengn Catalonia, Barcelona, Spain
Networking Ctr Biomed Res Bioengn Biomat & Nanome, Barcelona, Spain
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