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Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy

BACKGROUND: Currently, there is no gold standard for monitoring patients’ intraoperative stress levels under general anesthesia, while excessive stress may affect their postoperative outcomes. This prospective cohort study developed a prediction model using patients’ hemodynamic parameters to predic...

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Autores principales: Guan, Yu, Tang, Jie, Yu, Jiali, Zhu, Yiqi, Li, Ailun, Fang, Fang, Cang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279793/
https://www.ncbi.nlm.nih.gov/pubmed/35845526
http://dx.doi.org/10.21037/atm-22-2276
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author Guan, Yu
Tang, Jie
Yu, Jiali
Zhu, Yiqi
Li, Ailun
Fang, Fang
Cang, Jing
author_facet Guan, Yu
Tang, Jie
Yu, Jiali
Zhu, Yiqi
Li, Ailun
Fang, Fang
Cang, Jing
author_sort Guan, Yu
collection PubMed
description BACKGROUND: Currently, there is no gold standard for monitoring patients’ intraoperative stress levels under general anesthesia, while excessive stress may affect their postoperative outcomes. This prospective cohort study developed a prediction model using patients’ hemodynamic parameters to predict the change in adrenocorticotropic hormone (ACTH) concentrations, one of the stress hormones, under surgical stimuli to evaluate intraoperative stress levels. METHODS: A total of 205 patients undergoing scheduled open hepatectomy were enrolled in this study to investigate the correlations between ACTH levels and hemodynamic parameters. The ACTH concentration was assessed before surgery (baseline) and 10 minutes after skin incision. Blood pressure (BP) and heart rate (HR) were obtained at baseline and again at 1-minute intervals for 10 minutes after the skin incision. A logistic regression model was built to predict intraoperative stress level based on ACTH fluctuations, using the bootstrapped sampling approach. The model was validated using the internal sample. RESULTS: Three essential variables were used in the prediction model, including two significant variables, namely, baseline ACTH and mean arterial pressure (MAP), and one variable that was close to achieving significance, that is, HR. This model was able to detect 74.9% of patients with predefined unacceptable ACTH changes. The model had an average of area under the curve (AUC) of 0.723 [95% confidence interval (CI): 0.657–0.791]. CONCLUSIONS: The model developed herein may be a potential practical method for predicting intraoperative stress levels. This prediction model may be a preliminary step to building a real-time stress model based on routine monitoring during general anesthesia, needing further validations in an external sample.
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spelling pubmed-92797932022-07-15 Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy Guan, Yu Tang, Jie Yu, Jiali Zhu, Yiqi Li, Ailun Fang, Fang Cang, Jing Ann Transl Med Original Article BACKGROUND: Currently, there is no gold standard for monitoring patients’ intraoperative stress levels under general anesthesia, while excessive stress may affect their postoperative outcomes. This prospective cohort study developed a prediction model using patients’ hemodynamic parameters to predict the change in adrenocorticotropic hormone (ACTH) concentrations, one of the stress hormones, under surgical stimuli to evaluate intraoperative stress levels. METHODS: A total of 205 patients undergoing scheduled open hepatectomy were enrolled in this study to investigate the correlations between ACTH levels and hemodynamic parameters. The ACTH concentration was assessed before surgery (baseline) and 10 minutes after skin incision. Blood pressure (BP) and heart rate (HR) were obtained at baseline and again at 1-minute intervals for 10 minutes after the skin incision. A logistic regression model was built to predict intraoperative stress level based on ACTH fluctuations, using the bootstrapped sampling approach. The model was validated using the internal sample. RESULTS: Three essential variables were used in the prediction model, including two significant variables, namely, baseline ACTH and mean arterial pressure (MAP), and one variable that was close to achieving significance, that is, HR. This model was able to detect 74.9% of patients with predefined unacceptable ACTH changes. The model had an average of area under the curve (AUC) of 0.723 [95% confidence interval (CI): 0.657–0.791]. CONCLUSIONS: The model developed herein may be a potential practical method for predicting intraoperative stress levels. This prediction model may be a preliminary step to building a real-time stress model based on routine monitoring during general anesthesia, needing further validations in an external sample. AME Publishing Company 2022-06 /pmc/articles/PMC9279793/ /pubmed/35845526 http://dx.doi.org/10.21037/atm-22-2276 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Guan, Yu
Tang, Jie
Yu, Jiali
Zhu, Yiqi
Li, Ailun
Fang, Fang
Cang, Jing
Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title_full Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title_fullStr Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title_full_unstemmed Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title_short Developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
title_sort developing a prediction model for estimating adrenocorticotropic hormone changes in patients undergoing scheduled open hepatectomy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279793/
https://www.ncbi.nlm.nih.gov/pubmed/35845526
http://dx.doi.org/10.21037/atm-22-2276
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