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Aim: To construct and validate a postoperative hypothermia prediction model for patients undergoing joint replacement surgery. Background: Postoperative hypothermia is one of the harmful perioperative complications in patients undergoing joint replacement surgery. The previous studies mainly focused on intraoperative hypothermia prediction models. The prediction model for postoperative hypothermia in patients with joint replacement surgery was understudied. Design: Cohort study. Methods: We collected data from 503 participants undergoing joint replacement surgery in a tertiary hospital from January 2019 to December 2021. Of those, 404 cases were assigned to the modelling and 99 to the validation groups. Logistic regression was used to construct the model. The AUC was used to test the predictive effect of the model. Finally, 99 cases were used to verify the application effect of the model. A TRIPOD checklist was used to guide the reporting of this study. Results: The factors entered into the prediction model were age, intraoperative hypothermia, BMI, heat preservation measures and platelet (PLT). The model was constructed as follows: Logit (P) =.537 + 3.669 × 1 (intraoperative hypothermia) +.030 × age −.289 × BMI + 2.857 × 1 (intraoperative insulation measures) +.003 × PLT. Hosmer–Lemeshow test, p =.608, the area under the receiver operating characteristic curve (AUC) was.861. The Youden index was.530, the sensitivity was.599 and the specificity was.93. The incidence of postoperative hypothermia in the modelling group was 42.93% (173/404), and that in the verification group was 43.43% (43/99), χ2 =.012, p =.912. The correct practical application rate was 87.88%. This model has a good application effect. Conclusion: The current prediction model provided a reference for clinical screening of patients with high‐risk hypothermia after joint replacement surgery. Relevance to clinical practice: Clinical nurses can use the developed prediction model to predict the occurrence of postoperative hypothermia and provide a reference for the preventive measure. [ABSTRACT FROM AUTHOR]

Background: Hypothermia is a common clinical issue during the perioperative period. The patients with perioperative inadvertent hypothermia are associated with higher risk of postoperative complications and higher hospitalisation costs. Aims: The aim of this study is to explore the prevalence of and predictors for hypothermia in patients entering postanaesthesia care unit. Design: Retrospective cohort study. Methods: A rigorous retrospective cohort study was conducted according to the STROBE reporting checklist. A total of 7216 patients were enrolled in this study. The perioperative variables potentially related to hypothermia were collected. Univariate analysis and multivariate logistic regression analysis were performed to investigate the contributing factors. Results: The overall prevalence of inadvertent hypothermia in postanaesthesia care unit was 21.3% (n = 1505). The multivariate logistic regression analysis showed that age >65 (OR = 1.561, 95% CI 1.371–1.778, p <.001), non‐supine position [lateral decubitus position (OR = 1.341, 95% CI 1.133–1.586, p =.001), lithotomy position (OR = 1.639, 95% CI 1.295–2.075, p <.001)], non‐superficial surgery (OR = 2.195, 95% CI 1.566–3.077, p <.001), non‐open surgery [laparoscopic surgery (OR = 1.205, 95% CI 1.020–1.423, p =.029), endoscopic surgery (OR = 1.430, 95%CI 1.084–1.887, p =.011)], the volume of intravenous infusion fluid >1000 ml (OR = 1.814, 95% CI 1.500–2.194, p <.001), blood transfusion (OR = 1.552, 95% CI 1.159–2.078, p =.003), operation performed in the summer or fall (OR = 1.874, 95%CI 1.656–2.122, p <.001) and use of dexmedetomidine (OR = 1.147, 95%CI 1.015–1.296, p =.028) were associated with increased risk of hypothermia. In contrast, our finding showed that body mass index ≥25 kg/m2 (OR = 0.556, 95%CI 0.491–0.630, p <.001), higher baseline body temperature (OR = 0.641, 95%CI 0.541–0.761, p <.001) and duration of fasting ≥18 h (OR = 0.487, 95%CI 0.345–0.689, p <.001) were associated with decreased risk of hypothermia. Compared with non‐hypothermic patients, patients with hypothermia were associated with prolonged length of hospital days (5 vs. 4 days, p <.001). Conclusion: For patients admitted to postanaesthesia care unit after elective procedures, old age, non‐supine position, non‐open surgery, non‐superficial surgery, large volume of intravenous infusion fluid, dexmedetomidine, blood transfusion and Summer or Fall operative season were associated with increased risk of hypothermia, whereas high body mass index, high baseline body temperature and long fasting duration were associated with decreased risk of hypothermia. Relevance to clinical practice: The outcomes of this study will raise the concerns of perioperative care team on hypothermia in surgical patients. Measures should be taken to improve perioperative hypothermia and clinical outcome. [ABSTRACT FROM AUTHOR]