| Objective To establish risk warning model for intraoperative hypothermia in patients undergoing laparoscopic myomectomy based on the nomogram model. Methods 127 patients undergoing laparoscopic myomectomy were divided into non-hypothermia group (86 cases) and hypothermia group (41 cases) according to whether intraoperative hypothermia occurred. Multivariate Logistic regression was used to analyze the influencing factors of intraoperative hypothermia in patients, and Nomogram prediction model was constructed and verified according to the influencing factors. Results The intraoperative irrigation volume and intravenous input volume in the hypothermia group were higher than those in the non-hypothermia group, the basal body temperature at admission, intraoperative infusion temperature, and the proportion of intraoperative warmth were lower than those in the non-hypothermia group, the operation time and anesthesia time were longer than that in the non-hypothermia group (all P<0.05). Multivariate logistic regression analysis showed that, excessive intraoperative irrigation volume, low basal body temperature and excessive intravenous input volume were risk factors for intraoperative hypothermia in patients undergoing laparoscopic myomectomy (P<0.05), while intraoperative warmth was protective factor (P<0.05). A nomogram prediction model was constructed based on influencing factors, and it was verified that the model had good discrimination (area under the curve was 0.881, P<0.05), calibration degree (C-index=0.852, mean absolute error=0.002) and clinical applicability. Conclusion Intraoperative irrigation volume, basal body temperature, intravenous input volume, and intraoperative warmth are the influence factors that intraoperative hypothermia in patients undergoing laparoscopic myomectomy, this Nomogram model based on these factors has a good predictive efficacy and clinical value for the prediction of intraoperative hypothermia in patients undergoing laparoscopic myomectomy. |
