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Construction and application of inadvertent perioperative hypothermia prediction model for patients under general anesthesia based on deep learning / 中华急诊医学杂志
Chinese Journal of Emergency Medicine ; (12): 1116-1120, 2022.
Artigo em Chinês | WPRIM | ID: wpr-954537
ABSTRACT

Objective:

To construct a prediction model of inadvertent perioperative hypothermia in patients under general anesthesia , and to apply to clinic to verify its performance.

Methods:

The data of 19 068 surgical patients in a Grade Ⅲ Class A hospital in Zhejiang Province from January 2016 to September 2020 were included. The model was constructed by using artificial intelligence technology based on deep learning, and the prediction effect of the model was tested by using the area under the subject operating characteristic curve and decision curve. Totally 2 157 surgical patients were included from October 2020 to March 2021 to test the prediction accuracy of the model.

Results:

The incidence of hypothermia was 13.89% (2 649/19 068) in the modeling group and 14.18% (306/2 157) in the validation group. The area under the subject operating characteristic curve of the prediction model was 0.724 (95% CI 0.707-0.741), the sensitivity was 0.516, the specificity was 0.823, the cut-off value was 0.175, and the accuracy of practical application was 79.54%.

Conclusions:

This model can stably predict the incidence of perioperative inadvertent hypothermia in patients under general anesthesia, and provide reference for clinical prevention of inadvertent perioperative hypothermia.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Emergency Medicine Ano de publicação: 2022 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Emergency Medicine Ano de publicação: 2022 Tipo de documento: Artigo