Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data
Abstract Background In 2023, the European Society of Intensive Care Medicine (ESICM) recommended updated criteria for acute respiratory distress syndrome (ARDS). In 2024, Matthay et al. updated the global ARDS definition in AJRCCM, titled “A New Global Definition of Acute Respiratory Distress Syndro...
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BMC
2025-01-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02289-w |
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| author | Duanhong Song Qingquan Chen Shangbin Huang Shengxun Qiu Zeshun Chen Yuanhang Cai Yifu Zeng Xiaoyang Chen Yixiang Zhang |
| author_facet | Duanhong Song Qingquan Chen Shangbin Huang Shengxun Qiu Zeshun Chen Yuanhang Cai Yifu Zeng Xiaoyang Chen Yixiang Zhang |
| author_sort | Duanhong Song |
| collection | DOAJ |
| description | Abstract Background In 2023, the European Society of Intensive Care Medicine (ESICM) recommended updated criteria for acute respiratory distress syndrome (ARDS). In 2024, Matthay et al. updated the global ARDS definition in AJRCCM, titled “A New Global Definition of Acute Respiratory Distress Syndrome.” However, the impact of this new definition on ARDS treatments is currently unknown. Objective This study aims to determine the effect of the new ARDS definition on patients with hypoxemic respiratory failure and study the heterogeneity of patients in the new definition to guide treatment. Methods Clinical consultation data from the Medical Information Mart for Intensive Care IV database were extracted using Structured Query Language based on the PostgreSQL tool (version 10.0). Data were analyzed using Python (version 3.9) and the deep learning framework Pytorch. Kaplan–Meier survival analysis was used to compare survival between the old and new definitions. A hierarchical clustering approach was applied to identify potential ARDS clinical subtypes. Results The new definition diagnosed ARDS earlier and included individuals with lower mortality rates compared with the Berlin definition. Patients meeting the new definition but not the Berlin criteria exhibited a favorable response to non-invasive ventilation strategies (p = 0.009). The XGBoost classifier, trained to predict subphenotypes, achieved an AUC of 0.88 ± 0.02 on the training set. Additionally, mortality was significantly associated with patients with hypoxemia compared with survivors, particularly regarding respiratory parameters. Easily accessible metrics, such as respiratory rate and urea nitrogen (BUN), can help diagnose ARDS in high-risk populations in resource-limited settings. Conclusions The new ARDS definition offers advantages in earlier detection, more accurate grading, and more precise diagnosis in resource-limited settings compared with the Berlin definition. This study also established a robust prediction model for early ARDS identification, improving the patient prognosis and reducing the mortality rate. |
| format | Article |
| id | doaj-art-22c05c0efa794156b48008ac499120fa |
| institution | Kabale University |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | European Journal of Medical Research |
| spelling | doaj-art-22c05c0efa794156b48008ac499120fa2025-01-26T12:21:49ZengBMCEuropean Journal of Medical Research2047-783X2025-01-0130111210.1186/s40001-025-02289-wEvaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort dataDuanhong Song0Qingquan Chen1Shangbin Huang2Shengxun Qiu3Zeshun Chen4Yuanhang Cai5Yifu Zeng6Xiaoyang Chen7Yixiang Zhang8The Second Affiliated Hospital of Fujian Medical UniversityThe Second Affiliated Hospital of Fujian Medical UniversityThe School of Medical Imaging, Fujian Medical UniversityThe School of Clinical Medicine, Fujian Medical UniversityThe School of Clinical Medicine, Fujian Medical UniversityThe School of Medical Imaging, Fujian Medical UniversityCyberspace Institute of Advanced Technology, Guangzhou UniversityThe Second Affiliated Hospital of Fujian Medical UniversityThe Second Affiliated Hospital of Fujian Medical UniversityAbstract Background In 2023, the European Society of Intensive Care Medicine (ESICM) recommended updated criteria for acute respiratory distress syndrome (ARDS). In 2024, Matthay et al. updated the global ARDS definition in AJRCCM, titled “A New Global Definition of Acute Respiratory Distress Syndrome.” However, the impact of this new definition on ARDS treatments is currently unknown. Objective This study aims to determine the effect of the new ARDS definition on patients with hypoxemic respiratory failure and study the heterogeneity of patients in the new definition to guide treatment. Methods Clinical consultation data from the Medical Information Mart for Intensive Care IV database were extracted using Structured Query Language based on the PostgreSQL tool (version 10.0). Data were analyzed using Python (version 3.9) and the deep learning framework Pytorch. Kaplan–Meier survival analysis was used to compare survival between the old and new definitions. A hierarchical clustering approach was applied to identify potential ARDS clinical subtypes. Results The new definition diagnosed ARDS earlier and included individuals with lower mortality rates compared with the Berlin definition. Patients meeting the new definition but not the Berlin criteria exhibited a favorable response to non-invasive ventilation strategies (p = 0.009). The XGBoost classifier, trained to predict subphenotypes, achieved an AUC of 0.88 ± 0.02 on the training set. Additionally, mortality was significantly associated with patients with hypoxemia compared with survivors, particularly regarding respiratory parameters. Easily accessible metrics, such as respiratory rate and urea nitrogen (BUN), can help diagnose ARDS in high-risk populations in resource-limited settings. Conclusions The new ARDS definition offers advantages in earlier detection, more accurate grading, and more precise diagnosis in resource-limited settings compared with the Berlin definition. This study also established a robust prediction model for early ARDS identification, improving the patient prognosis and reducing the mortality rate.https://doi.org/10.1186/s40001-025-02289-wAcute respiratory distress syndromeEuropean Society of Intensive Care MedicineMIMIC-IVPrediction modelPrognosis |
| spellingShingle | Duanhong Song Qingquan Chen Shangbin Huang Shengxun Qiu Zeshun Chen Yuanhang Cai Yifu Zeng Xiaoyang Chen Yixiang Zhang Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data European Journal of Medical Research Acute respiratory distress syndrome European Society of Intensive Care Medicine MIMIC-IV Prediction model Prognosis |
| title | Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data |
| title_full | Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data |
| title_fullStr | Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data |
| title_full_unstemmed | Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data |
| title_short | Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data |
| title_sort | evaluating the impact of esicm 2023 guidelines and the new global definition of ards on clinical outcomes insights from mimic iv cohort data |
| topic | Acute respiratory distress syndrome European Society of Intensive Care Medicine MIMIC-IV Prediction model Prognosis |
| url | https://doi.org/10.1186/s40001-025-02289-w |
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