Dataset for Group-Based Trajectory Modeling of Postoperative Temperature Recovery in Urological Surgery Patients
Description
This dataset contains postoperative temperature recovery data for adult patients undergoing urological surgery, collected during the first hour after admission to the post-anesthesia care unit (PACU). A total of 12 temperature measurements were recorded at 5-minute intervals. The dataset also includes patient demographic information, surgical and anesthesia details, as well as the last preoperative and the first postoperative venous blood test results. Included variables (but not limited to): Gender, age, and body mass index (BMI) Duration of tracheal extubation and surgical procedure Length of hospital stay and PACU stay Intraoperative medication use (e.g., tramadol, atropine) Temperature at PACU admission and discharge Postoperative length of stay History of comorbidities (e.g., hypertension, diabetes, heart disease)
Files
Steps to reproduce
Basic demographic information and relevant laboratory and examination results were extracted from the surgical anesthesia information system. Upon transfer to the PACU, tympanic temperature was measured using an ear thermometer. After connection to the monitor, axillary temperature was automatically collected via a temperature probe. Missing data were addressed using multiple imputation in R. Continuous temperature measurements were modeled using the “gbtm” package in R to identify trajectory patterns, followed by regression analysis for further investigation.
Institutions
- Sun Yat-Sen University Second University Hospital