LAUSR

In this edition of JCMCI, two related papers have been published respectively exploring the feasibility [1] and the acceptability [2] of a new algorithm for the optimization of intravenous propofol titration in combination with remifentanil and fentanyl. Based on the demographic data of the patient and the timing and magnitude of the doses administered, the time course of the effect-site concentration has been calculated for each drug administered. These effect-site concentrations than serve as input for response surface druginteraction models that are elegant mathematical solutions to quantify the nature of drug interactions between drugs. Many clinical effects evoked by combinations of propofol and opioids have been studied this way, such as the probability of responsiveness to a verbal, tactile or noxious stimulation; or endpoints related to respiratory function; or residual analgesic effect [3–5]. By combining the predictions of models, the authors developed an advisory system for clinicians, that proposes dose adjustments in 20-min intervals to target an optimization of the recovery conditions for the patient. The proof of concept of this new algorithm is provided by demonstrating a theoretical advantage, being a prolongation of the time between end of surgery and the first need for additional analgesia, without causing excessive delays in respiratory function recovery. The authors confirm that the algorithm could be tweaked successfully to reach these predefined goals. In a second paper, the acceptability of the proposed dose adjustments by the new algorithm was tested in major spine surgery cases in a population of adolescent patients [2]. Thams et al. found a very high acceptance rate, suggesting that the algorithm proposes dose adjustments that are within normal clinical ranges, as perceived by experienced anesthesiologists. This primary endpoint is not sufficiently objective to confirm adequate performance of the algorithm, but it shows the willingness of clinicians to guide drug titration by means of theoretical models. The authors confirm that several methodological issues may have contributed to this positive result, and therefore the conclusion needs to be put in perspective. The methodology used for developing the algorithm may also include a degree of positive bias, especially if the algorithm will be dependent on human interaction when used in “real life” clinical practice. First, a computer simulation uses input of drug administration rates with a 100% accuracy for dosing and timing, which will lead to the lowest possible prediction-errors in the estimation of the corresponding effect-site concentration and subsequently the most accurate prediction of the interaction effect from combined drugs. However, in clinical practice, the input of data might be diminished by human performance, as humans are notoriously less consistent in task performance due to fatigue, distraction or lack of concentration compared to computers. A higher prediction error may also originate from the 20 min interval between dose adjustments as currently advised by the algorithm, compared to the higher resolution of dose adjustments (1-s intervals) using existing technology, such as target controlled infusion (TCI) pumps. As the initiative for this study was taken by a USA based research center, the reason for not using TCI technology is probably related to the disturbing reality that nowadays no commercialized version of effect-site controlled TCI is approved by FDA in the US [6]. The reasons for the non-approval in the USA of a widespread and safe technology has a complex history and would lead me too far in this editorial [7–9]. But the worldwide acceptance of TCI technology does provide reassurance though, that effect-site controlled TCI pumps are easily applicable devices for targeting and maintaining predefined effect-site concentrations over time for many commonly used anesthetic drugs. The higher resolution of the dose adaptation of effect-site controlled TCI pumps * Hugo E. M. Vereecke [email protected]; [email protected]