A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study

Background Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock. Met...

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Main Authors: Zhijun Xu, Man Huang
Format: Article
Language:English
Published: PeerJ Inc. 2024-01-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/16723.pdf
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author Zhijun Xu
Man Huang
author_facet Zhijun Xu
Man Huang
author_sort Zhijun Xu
collection DOAJ
description Background Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock. Methods This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients’ clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems. Results A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II. Conclusion The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.
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spelling doaj.art-ab9c9a5efd7045059092b115fa24387a2024-01-25T15:05:10ZengPeerJ Inc.PeerJ2167-83592024-01-0112e1672310.7717/peerj.16723A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort studyZhijun XuMan HuangBackground Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock. Methods This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients’ clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems. Results A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II. Conclusion The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.https://peerj.com/articles/16723.pdfPrediction model28-day mortalitySeptic shock
spellingShingle Zhijun Xu
Man Huang
A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
PeerJ
Prediction model
28-day mortality
Septic shock
title A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
title_full A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
title_fullStr A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
title_full_unstemmed A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
title_short A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study
title_sort dynamic nomogram for predicting 28 day mortality in septic shock a chinese retrospective cohort study
topic Prediction model
28-day mortality
Septic shock
url https://peerj.com/articles/16723.pdf
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