• Int. J. Clin. Pract. · Jan 2022

    Observational Study

    Validation of a Prediction Model for Intraoperative Hypothermia in Patients Receiving General Anesthesia.

    • Ziyi Dai, Yuelun Zhang, Jie Yi, and Yuguang Huang.
    • Department of Anesthesiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
    • Int. J. Clin. Pract. 2022 Jan 1; 2022: 6806225.

    ObjectivesThere have been no fully validated tools for the rapid identification of surgical patients at risk of intraoperative hypothermia. The objective of this study was to validate the performance of a previously established prediction model in estimating the risk of intraoperative hypothermia in a prospective cohort.MethodsIn this observational study, consecutive adults scheduled for elective surgery under general anesthesia were enrolled prospectively at a tertiary hospital between September 4, 2020, and December 28, 2020. An intraoperative hypothermia risk score was calculated by a mobile application of the prediction model. A wireless axillary thermometer was used to continuously measure perioperative core temperature as the reference standard. The discrimination and calibration of the model were assessed, using the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and Brier score.ResultsAmong 227 participants, 99 (43.6%) developed intraoperative hypothermia, and 10 (4.6%) received intraoperative active warming with forced-air warming. The model had an AUC of 0.700 (95% confidence interval [CI], 0.632-0.768) in the overall cohort with adequate calibration (Hosmer-Lemeshow χ 2 = 13.8, P=0.087; Brier score = 0.33 [95% CI, 0.29-0.37]). We categorized the risk scores into low-risk, moderate-risk, and high-risk groups, in which the incidence of intraoperative hypothermia was 23.0% (95% CI, 12.4-33.5), 43.4% (95% CI, 33.7-53.2), and 62.7% (95% CI, 51.5-74.3), respectively (P for trend <0.001).ConclusionsThe intraoperative hypothermia prediction model demonstrated possibly helpful discrimination and adequate calibration in our prospective validation. These findings suggest that the risk screening model could facilitate future perioperative temperature management.Copyright © 2022 Ziyi Dai et al.

      Pubmed     Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

Want more great medical articles?

Keep up to date with a free trial of metajournal, personalized for your practice.
1,624,503 articles already indexed!

We guarantee your privacy. Your email address will not be shared.