Trial reportJournal of translational medicine2019
Predictive model for acute respiratory distress syndrome events in ICU patients in China using machine learning algorithms: a secondary analysis of a cohort study.
Trial report in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07328997 (Exploration of Diagnosis and Treatment Strategies and Prognostic Prediction Models for Acute Respiratory Distress Syndrome Based on Radiographic Evaluations Assessed by Artificial Intelligence), which is not on this map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Exploration of Diagnosis and Treatment Strategies and Prognostic Prediction Models for Acute Respiratory Distress Syndrome Based on Radiographic Evaluations Assessed by Artificial Intelligence
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of machine learning models for management, prediction and classification of ARDS.Respiratory research · 2024Pooled it
- Development and validation of a clinical risk model to predict the hospital mortality in ventilated patients with acute respiratory distress syndrome: a population-based study.BMC pulmonary medicine · 2022Trial
- Trial
- Deep knowledge-driven multi-modal fusion for diagnosis and prognosis of SI-ARDS.Communications medicine · 2026Article
- RMS: a ML-based system for ICU respiratory monitoring and resource planning.NPJ digital medicine · 2025Article
- Development and validation of a predictive model for postoperative acute respiratory distress syndrome in patients with type A aortic dissection based on the 2023 updated definition.Respiratory research · 2025Article
- Predicting Outcome and Duration of Mechanical Ventilation in Acute Hypoxemic Respiratory Failure: The PREMIER Study.Journal of clinical medicine · 2025Article
- Comparison of artificial intelligence and logistic regression models for mortality prediction in acute respiratory distress syndrome: a systematic review and meta-analysis.Intensive care medicine experimental · 2025Review
- Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit.Scientific reports · 2024Article
- Predicting the Length of Mechanical Ventilation in Acute Respiratory Disease Syndrome Using Machine Learning: The PIONEER Study.Journal of clinical medicine · 2024Article
- Long short-term memory model identifies ARDS and in-hospital mortality in both non-COVID-19 and COVID-19 cohort.BMJ health & care informatics · 2023Article
- Understanding clinical and biological heterogeneity to advance precision medicine in paediatric acute respiratory distress syndrome.The Lancet. Respiratory medicine · 2023Review
- A narrative review of progress in the application of artificial intelligence in acute respiratory distress syndrome: subtypes and predictive models.Annals of translational medicine · 2023Review
- Discriminating Acute Respiratory Distress Syndrome from other forms of respiratory failure via iterative machine learning.Intelligence-based medicine · 2023Article
- Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm.Frontiers in endocrinology · 2023Article
- Risk of Acute Respiratory Distress Syndrome in Community-Acquired Pneumonia Patients: Use of an Artificial Neural Network Model.Emergency medicine international · 2023Article
- Identifying and evaluating barriers for the implementation of machine learning in the intensive care unit.Communications medicine · 2022Article
- Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry.ACR open rheumatology · 2022Article
- Hypotension Prediction Index with non-invasive continuous arterial pressure waveforms (ClearSight): clinical performance in Gynaecologic Oncologic Surgery.Journal of clinical monitoring and computing · 2022Article
- Multi-Modal Data Analysis for Pneumonia Status Prediction Using Deep Learning (MDA-PSP).Diagnostics (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo develop a machine learning model for predicting acute respiratory distress syndrome (ARDS) events through commonly available parameters, including baseline characteristics and clinical and laboratory parameters.
methodsA secondary analysis of a multi-centre prospective observational cohort study from five hospitals in Beijing, China, was conducted from January 1, 2011, to August 31, 2014. A total of 296 patients at risk for developing ARDS admitted to medical intensive care units (ICUs) were included. We applied a random forest approach to identify the best set of predictors out of 42 variables measured on day 1 of admission.
resultsAll patients were randomly divided into training (80%) and testing (20%) sets. Additionally, these patients were followed daily and assessed according to the Berlin definition. The model obtained an average area under the receiver operating characteristic (ROC) curve (AUC) of 0.82 and yielded a predictive accuracy of 83%. For the first time, four new biomarkers were included in the model: decreased minimum haematocrit, glucose, and sodium and increased minimum white blood cell (WBC) count.
conclusionsThis newly established machine learning-based model shows good predictive ability in Chinese patients with ARDS. External validation studies are necessary to confirm the generalisability of our approach across populations and treatment practices.
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