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అందరికి ప్రవేశం

నైరూప్య

Gentamicin Monitoring Practices in Teaching Hospitals – Time to Undertake the Necessary Randomised Controlled Trial

Jennifer Martin, Michael Barras, Nicholas Ah Yui, Carl Kirkpatrick, Paul Kubler and Ross Norris

Objective: To compare the clinical appropriateness of the prescribing and monitoring of gentamicin. Method: A retrospective study was undertaken at two tertiary teaching hospitals in Australia. 161 adult patients administered gentamicin and who had at least one serum concentration taken whilst an inpatient were eligible for analysis. The main outcome measures were adherence to local and national guidelines for dosing and monitoring of gentamicin, and percentage of the recommended measure of adequate gentamicin exposure (Area-Under the concentration-time Curve (AUC)) using a nomogram and a Bayesian calculation. Results: Results were similar in both hospitals. Initial dosing: Adherence to local and national dosing guidelines was poor - approximately 50% of initial doses using less than local and 88% less than national recommendations. Monitoring: Approximately 20% of all gentamicin concentrations were collected outside the required sampling window. Sampling was particularly problematic after the initial dose. Here up with to half of the samples were taken outside the recommended time frame for sampling, therefore making interpretation of the nomogram difficult. Dose adjustment: 15% of doses were adjusted without monitoring and approximately half of all dose adjustments were based on inadequate information or inaccurate nomogram interpretation. Dose evaluation: Approximately half of the AUCs were below the therapeutic range. Conclusion: A large number of issues around appropriate use and monitoring of gentamicin were seen. This is particularly concerning considering both hospitals are large tertiary hospitals with expert clinical pharmacy support. We believe it is time for a randomised controlled trial to be undertaken, comparing Bayesian modelling techniques with standard nomogram, powered for clinical endpoints