Assessment of a simple artificial neural network for predicting residual neuromuscular block

Postoperative residual curarization (PORC) after surgery is common and its detection has a high error rate. Artificial neural networks are being used increasingly to examine complex data. We hypothesized that a neural network would enhance prediction of PORC. In 40 previously reported patients, neur...

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Veröffentlicht in:British journal of anaesthesia : BJA 2003-01, Vol.90 (1), p.48-52
Hauptverfasser: Laffey, J.G., Tobin, é., Boylan, J.F., McShane, A.J.
Format: Artikel
Sprache:eng
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Zusammenfassung:Postoperative residual curarization (PORC) after surgery is common and its detection has a high error rate. Artificial neural networks are being used increasingly to examine complex data. We hypothesized that a neural network would enhance prediction of PORC. In 40 previously reported patients, neuromuscular function, neuromuscular block/antagonist usage and time intervals were recorded throughout anaesthesia until tracheal extubation by an observer uninvolved in patient care. PORC was defined as significant ‘fade’ (train of four
ISSN:0007-0912
1471-6771
DOI:10.1093/bja/aeg015