Serial Analgesic Consumptions and Predictors of Intravenous Patient-controlled Analgesia with Cluster Analysis

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To elucidate the dynamics of analgesic consumption regarding intravenous patient controlled analgesia (IVPCA) during postoperative period is rather complex partly due to between-patient variation and partly due to within-patient variation. A statistical method was proposed to classify serial analgesic consumption into different classifications that were further taken as the multiple outcomes on which to explore the associated predictors.


We retrospectively included 3284 patients administrated by IVPCA for 3 days after surgery. A repeated measurement design corresponding to serial analgesic consumption variables defined as six-hour total analgesic consumptions was adopted. After determining the numbers of clusters, serial analgesic consumptions were classified into several homogeneous subgroups. Factors associated with new classifications were identified and quantified with a multinominal logistic regression model.


Three distinct analgesic classifications were aggregated, including “high”, ”middle” and “low” level of analgesic consumption of IVPCA. The mean analgesic consumptions on 12 successive analgesic consumptions at 6-hour interval of each classification consistently revealed a decreasing trend. As the trends were almost parallel with time, this suggests the time-invariant proportionality of analgesic consumption between the levels of analgesic consumption of IVPCA. Patient’s characteristics, like age, gender, weight, height, and cancer status, were significant factors associated with analgesic classifications. Surgical sites had great impacts on analgesic classifications.


The serial analgesic consumptions were simplified into 3 analgesic consumptions classifications. The identified predictors are useful to recognize patient’s analgesic classifications before using IVPCA. This study explored a new approach to analysing dynamic changes of postoperative analgesic consumptions.

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