Respiratory arrest after cadaveric renal transplant
European Journal of Anaesthesiology (Impact Factor: 3.01). 06/2009; 26(5):435-6. DOI: 10.1097/EJA.0b013e32831dccf4
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ABSTRACT: Integrating opioid risk and benefit into a single function may give a useful single measure of the opioid's positive and negative effects. An explorative study on the effects of fentanyl on antinociception and respiratory depression was performed to construct fentanyl risk-benefit (utility) functions. Twelve volunteers received a 3.5-μg/kg fentanyl intravenous injection on 2 separate study days. On one occasion, ventilation at a clamped increased carbon dioxide concentration was measured and on another the pain tolerance to electrical stimulation. In both sessions, arterial plasma samples were obtained. The data were analyzed with a population pharmacokinetic-pharmacodynamic model. A simulation study was performed, using the model parameter estimates and their variances, in which simulated subjects received 3.5 μg/kg of fentanyl. The resultant distributions were used to calculate the utility functions, defined as the probability of at least 50% analgesia (an increase in pain tolerance by ≥50%) minus the probability of at least 50% respiratory depression (a reduction in ventilation by ≥50%). Utility functions were constructed in concentration and time domains. Fentanyl produced significant respiratory depression and analgesia. The pharmacokinetic and pharmacodynamic models adequately described the data. The constructed utility functions were negative at effect-site concentrations of greater than 0.5 ng/ml in the first 90 min after the 3.5 μg/kg bolus infusion. Utility functions based on fentanyl's experimental effects on respiration and pain relief were successfully constructed. These functions are useful in multiple effect comparisons among experimental drugs. Further studies are required to assess whether this risk-benefit analysis is valuable in clinical practice.Anesthesiology 09/2013; 119(3):663-74. DOI:10.1097/ALN.0b013e31829ce4cb · 6.17 Impact Factor
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