An analysis of patient variables that influence intravenous patient-controlled analgesic use of morphine with quantile regression

Abstract

Background: Previous studies using linear regression analysis have shown that age, weight, gender, and the site of operation affect intravenous patient-controlled analgesia (IVPCA) narcotic use. However, there are inconsistent observations in the literature. The authors postulate that patient variables could have different effects at various doses of narcotics. To test this hypothesis, the authors analyzed the effect of patient variables on increasing doses of IVPCA narcotic with quantile regression.

Methods: The authors collected retrospective data from 1,782 patients who received IVPCA for a minimum of 3 days after surgery. The authors used stepwise linear regression model to identify variables that significantly affected the total IVPCA requirements. Quantile regression model was further applied to assess the effects of selected variables on the ascending percentile of IVPCA narcotic use.

Results: Gender, age, body weight, cancer, and surgical site were identified as significant predictors for IVPCA demand. Body weight had the most and cancer had the least significant effects on total IVPCA demands. The results of quantile regression model revealed that the determinants under consideration varied with different percentiles of IVPCA demand. The patient variables correlated with IVPCA narcotic use differently when the dose exceeded the seventieth to eightieth percentiles compared with other percentiles of narcotic use.

Conclusions: The authors' findings highlight the heterogeneous postoperative pain requirements among patients and the consequent complex process of efficiently managing postoperative pain.