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significant predictors in all clusters, and included age (Group 2, likelihood estimate (LE) -0.030, p<0.001, Group 3, LE -0.027, p<0.001 and Group 4, LE -0.034, p<0.001; reference Group 1) and BMI (Group 2, LE 0.034, p<0.001, Group 3, LE 0.063, p<0.001 and Group 4, LE 0.71, p<0.001; reference Group 1). Conclusions: Patients display different temperature trajectories following elective knee arthroplasty. Further work is needed to determine whether different trajectories indicate different likelihoods of an adverse event occurring. Group based trajectory modeling may allow for personalizing the interpretation of a temperature in the postoperative setting.

What is a Normal Postoperative Temperature? Group Based Trajectory Modeling in Postoperative Knee Arthroplasty Patients in a Large Health System