Development and validation of nomograms to predict preoperative anxiety and postoperative pain in patients undergoing gynecological surgery: An observational analysis

Background: Perioperative anxiety and pain are associated with patient dissatisfaction, postoperative complica-tions, and prolonged hospital stay. Early identification of high-risk patients with preoperative anxiety and postoperative pain will be useful for the implementation of preventive management.Methods: Patients, who underwent gynecological surgery in our hospital between March 2022 and September 2022, were consecutively enrolled. Perioperative anxiety and pain were evaluated with the Visual Analogue Scale of Anxiety (VAA) and Visual Analogue Scale of Pain (VAS), respectively. Step Akaike Information Criterion analysis was performed to identify risk factors and logistic regression was used to establish nomograms, followed by discrimination, calibration, and clinical utility evaluation.Results: A total of 197 patients were included for analysis, including 116 and 81 patients who were randomized to training and test groups, respectively. The prediction model of preoperative moderate to severe anxiety identified four preoperative relevant factors: age, sleep duration, preoperative pain, and regular exercise before gyneco-logical surgery. The model had an area under the receiver operating characteristics curve of 0.808 (0.729, 0.887) and 0.754 (0.634, 0.875) in the training and test groups, respectively. The prediction model of postoperative moderate to severe pain identified four relevant factors: preoperative pain, surgery type, VAA before anesthesia, and patient-controlled analgesia. The model had an area under the receiver operating characteristics curve of 0.867 (0.798, 0.935) and 0.852 (0.761, 0.943) in the training and test groups, respectively.Conclusions: The established nomograms accurately identified high-risk patients with preoperative anxiety and postoperative pain before gynecological surgery. Clinical registration at: www.chictr.org.cn (ChiCTR2200057757).