OBJECTIVE: This study investigated whether the bispectral index (BIS monitor) corresponded with the clinical assessment of anaesthetic depth in dogs.
STUDY DESIGN: Prospective clinical study.
ANIMALS: Sixty-five dogs undergoing anaesthesia for surgery.
METHODS: Dogs were assigned to one of three different anaesthetic techniques. A three point scale was devised to determine the clinical depth of anaesthesia (CDA); CDA 1 represented light, CDA 2 surgical and CDA 3 excessive depth of anaesthesia. BIS values were recorded and CDA assessed at specific times and points throughout surgery. Data were statistically analysed using mixed model regression.
RESULTS: Clinical depth of anaesthesia was assessed as CDA 1 on 68, 2 on 748 and 3 on four occasions. The BIS recorded for CDA 1 differed significantly from that for CDA 2 (p<0.001). However, individual BIS values measured at light and surgical levels of anaesthesia overlapped considerably. The sensitivities and specificities calculated for BIS to diagnose CDA 1 compared to CDA 2 in the three anaesthetic protocols were 28-86% and 55-85%. The accompanying positive predictive value was 0.08-0.29 and the negative predictive value was 0.95-0.97. End-tidal isoflurane concentrations (anaesthetic techniques 1 and 3) and propofol infusion (technique 2) at CDA 1 was significantly lower than those at CDA 2 (p=0.001).
CONCLUSIONS: Although BIS values overall distinguished between CDA scores, the calculated specificities, sensitivities and predictive values were low, and there were anomalous results in individual cases.
CLINICAL RELEVANCE: The use of the BIS as the sole method to determine anaesthetic depth in dogs is imprudent.
Bibliographical note© 2011 The Authors. Veterinary Anaesthesia and Analgesia. © 2011 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesiologists.
- Anesthesia, General
- Anesthetics, Inhalation
- Anesthetics, Intravenous
- Consciousness Monitors
- Monitoring, Intraoperative
- Predictive Value of Tests
- Prospective Studies
- Regression Analysis
- Sensitivity and Specificity