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Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study
Patients with Takotsubo syndrome (TTS) admitted to the intensive care unit (ICU) always confront a higher risk of in-hospital death than those hospitalized in the cardiology unit. The prognosis of the latter was analyzed by a large number of studies. However, there was no utility model to predict th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832151/ https://www.ncbi.nlm.nih.gov/pubmed/36627324 http://dx.doi.org/10.1038/s41598-022-27224-5 |
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author | Chen, Jun Wang, Yimin Shou, Xinyang Liu, Qiang Mei, Ziwei |
author_facet | Chen, Jun Wang, Yimin Shou, Xinyang Liu, Qiang Mei, Ziwei |
author_sort | Chen, Jun |
collection | PubMed |
description | Patients with Takotsubo syndrome (TTS) admitted to the intensive care unit (ICU) always confront a higher risk of in-hospital death than those hospitalized in the cardiology unit. The prognosis of the latter was analyzed by a large number of studies. However, there was no utility model to predict the risk of in-hospital death for patients with TTS in the ICU. This study aimed to establish a model predicting in-hospital death in patients with TTS admitted to ICU. We retrospectively included ICU patients with TTS from the MIMIC-IV database. The outcome of the nomogram was in-hospital death. Least Absolute Shrinkage Selection Operator (LASSO) analysis selected predictors preliminarily. The model was developed by multivariable logistic regression analysis. Calibration, decision curve analysis (DCA), and receiver operating characteristic (ROC) measured the performance of the nomogram on the accuracy, clinical utility, and discrimination, respectively. Eventually, 368 ICU patients with TTS were enrolled in this research. The in-hospital mortality was 13.04%. LASSO regression and multivariate logistic regression analysis verified risk factors significantly associated with in-hospital mortality. They were potassium, prothrombin time (PT), age, myocardial infarction, white cell count (WBC), hematocrit, anion gap, and sequential organ failure assessment (SOFA) score. This nomogram excellently discriminated against patients with a risk of in-hospital death. The area under curve (AUC) was 0.779 (95%CI: 0.732–0.826) in training set and 0.775 (95%CI: 0.711–0.839) in test set. The calibration plot and DCA showed good clinical benefits for this nomogram. We developed a nomogram that predicts the probability of in-hospital death for ICU patients with TTS. This nomogram was able to discriminate patients with a high risk of in-hospital death and performed clinical utility. |
format | Online Article Text |
id | pubmed-9832151 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98321512023-01-12 Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study Chen, Jun Wang, Yimin Shou, Xinyang Liu, Qiang Mei, Ziwei Sci Rep Article Patients with Takotsubo syndrome (TTS) admitted to the intensive care unit (ICU) always confront a higher risk of in-hospital death than those hospitalized in the cardiology unit. The prognosis of the latter was analyzed by a large number of studies. However, there was no utility model to predict the risk of in-hospital death for patients with TTS in the ICU. This study aimed to establish a model predicting in-hospital death in patients with TTS admitted to ICU. We retrospectively included ICU patients with TTS from the MIMIC-IV database. The outcome of the nomogram was in-hospital death. Least Absolute Shrinkage Selection Operator (LASSO) analysis selected predictors preliminarily. The model was developed by multivariable logistic regression analysis. Calibration, decision curve analysis (DCA), and receiver operating characteristic (ROC) measured the performance of the nomogram on the accuracy, clinical utility, and discrimination, respectively. Eventually, 368 ICU patients with TTS were enrolled in this research. The in-hospital mortality was 13.04%. LASSO regression and multivariate logistic regression analysis verified risk factors significantly associated with in-hospital mortality. They were potassium, prothrombin time (PT), age, myocardial infarction, white cell count (WBC), hematocrit, anion gap, and sequential organ failure assessment (SOFA) score. This nomogram excellently discriminated against patients with a risk of in-hospital death. The area under curve (AUC) was 0.779 (95%CI: 0.732–0.826) in training set and 0.775 (95%CI: 0.711–0.839) in test set. The calibration plot and DCA showed good clinical benefits for this nomogram. We developed a nomogram that predicts the probability of in-hospital death for ICU patients with TTS. This nomogram was able to discriminate patients with a high risk of in-hospital death and performed clinical utility. Nature Publishing Group UK 2023-01-10 /pmc/articles/PMC9832151/ /pubmed/36627324 http://dx.doi.org/10.1038/s41598-022-27224-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chen, Jun Wang, Yimin Shou, Xinyang Liu, Qiang Mei, Ziwei Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title | Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title_full | Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title_fullStr | Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title_full_unstemmed | Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title_short | Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
title_sort | development and validation of a prognostic nomogram for takotsubo syndrome patients in the intensive care units: a retrospective cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832151/ https://www.ncbi.nlm.nih.gov/pubmed/36627324 http://dx.doi.org/10.1038/s41598-022-27224-5 |
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