A Novel Patient-Specific Model for Predicting Postoperative SIRS in Elderly Patients: A Retrospective Cohort Study

Abstract Background Postoperative systemic inflammatory response syndrome (SIRS) is common in surgical ICU patients especially in elderly patients, and the geriatric population with SIRS is more susceptible to sepsis, MODS, and death. There have been no reliable and accurate methods to predict SIRS in the elderly. Therefore, we aimed to develop and validate a novel effective model for predicting postoperative SIRS in elderly patients. Methods Data of 16141 patients aged ≥ 65 years who underwent surgery in two centers of Third Affiliated Hospital of Sun Yat-sen University from January 2015 to September 2020 were retrieved and analyzed. We developed a predictive model for postoperative SIRS based on a retrospectively cohort study of 5904 patients spanning from January 2015 to December 2019. The discriminative performance of this model was determined by area under the receiver operating characteristics curve (AUC). We also used the model to validate outcomes in 1105 patients who underwent surgery at the same institutions from January 2020 to September 2020, and to perform a stratified analysis. Results A total of 5904 patients were enrolled in the training cohort and 1105 patients comprised the validation cohort, in which incidence rates of postoperative SIRS were 24.6% and 20.2%, respectively. Patients with SIRS had more postoperative complications and a worse in-hospital survival rate than patients without SIRS. Six feature variables including preoperative fever, preoperative serum albumin level, ASA classification, total intraoperative infusion volume, surgical duration, and postoperative intensive care unit admission were identified as valuable predictors to construct the nomogram, with high AUCs in both the training and validation cohorts (0.800 [0.787, 0.813] and 0.823 [0.791, 0.855], respectively). Conclusions We constructed an effective nomogram using 6 routinely obtained variables to assist clinicians to predict postoperative SIRS in elderly patients.