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Up–down sequential allocation and regional anaesthesia

IN the September issue of Acta Anaesthesiologica Scandinavica was an example of the use of up– down sequential allocation. Ortner et al. measured the impact of a dose of sufentanil on how much local anaesthetic is required in an intrathecal cocktail or recipe for pain relief in labour. Sequential allocation, the ‘up and down’ method, is the term given to a sensitivity experiment that was developed for studying the sensitivity of explosives to sudden impact. The model for this involves dropping a weight from a height onto the explosive or dropping an explosive from varying heights. The height at which the experiment is begun is arbitrarily chosen, but thereafter depends on the result of the previous test. If, as the result of the first test, an explosion occurs, the height is reduced by a predetermined amount for the second test. If an explosion does not occur, the height is increased by one increment for the next test, and so on. As the experiment progresses, an up and down oscillation is obtained containing the two different kinds of outcomes around a median height. The two outcomes represent successes and failures as defined by the experiment and the measure of central tendency represents the median effective value, EV50. Studies of this nature have long been used in anaesthesia for comparisons of volatile agents, [minimum alveolar concentration (MAC)], and intravenous agents (minimum infusion rate). The application of the technique to epidural pain relief in labour was in response to the poor quality of studies comparing different analgesic cocktails. The nature of the cocktails under test was decided by the researcher, who, in a desire for efficacy, almost invariably chose cocktails that were effective at producing analgesia. From time to time, a group was selected that performed poorly and it was considered acceptable to exclude it from the study. This approach more or less guaranteed that the comparisons were conducted on the flat upper part of the dose–response curve, beyond the EV95. Consequently, it was inevitable that researchers were unable to show differences. One useful example of this had six groups. Group 1 received 8 ml bupivacaine 0.125% wt/vol, and was excluded because of failures. Among the remaining groups, no differences were found between bupivacaine 0.125% wt/vol with fentanyl, and bupivacaine 0.25% wt/vol with fentanyl, between plain bupivacaine and bupivacaine with fentanyl, or between 50 and 100mg fentanyl. Some researchers would compound their errors by concluding that the cocktails under test were of equal efficacy. Sequential allocation offers some solution to these problems. With the traditional approach, the researchers’ choice of the cocktails under test determined the part of the dose–response on which the study was to be conducted, and this in turn predicted the result. The design of sequential allocation allows the researcher to choose the starting dose, but thereafter, the results dictate subsequent doses. The effective and ineffective outcomes of sequential allocation oscillate on either side of the median value; the study takes place around the steep, linear middle part of the dose–response curve. A major advantage of this, which works well for MAC, is that standardisation allows comparison of the potency of different agents. Another advantage is that, for a given accuracy, fewer subjects are needed. An oscillation with little variability can provide an EV50 with as few as 15 subjects, while greater variability might require as many as 40. The ability to research with a smaller sample also has both ethical and economic advantages. Since the data plot reverts to around the 50th centile, the researcher’s choice of the cocktail to