AIMC Topic: Respiratory Distress Syndrome

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The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

BMC anesthesiology
OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalization, poses a significant challenge to recovery and long-term outcomes. The aim of this study was to characterize long-term muscle wasting trajectories...

Early Prediction of Mortality Risk in Acute Respiratory Distress Syndrome: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a life-threatening condition associated with high mortality rates. Despite advancements in critical care, reliable early prediction methods for ARDS-related mortality remain elusive. Accurate ...

[Acute respiratory distress syndrome-quo vadis : Innovative and individualized treatment approaches].

Medizinische Klinik, Intensivmedizin und Notfallmedizin
Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome characterized by variable pathophysiology and different therapeutic approaches. Recent guidelines emphasize the importance of prone positioning and venovenous extracorpor...

A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.

BMC infectious diseases
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Scientific reports
Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic. Accurate prediction of in-hospital mortality of patients is crucial to optimize treatment and improve prognosis under the new global definition of AR...

Subphenotyping prone position responders with machine learning.

Critical care (London, England)
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a heterogeneous condition with varying response to prone positioning. We aimed to identify subphenotypes of ARDS patients undergoing prone positioning using machine learning and assess their a...

Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...

RespBERT: A Multi-Site Validation of a Natural Language Processing Algorithm, of Radiology Notes to Identify Acute Respiratory Distress Syndrome (ARDS).

IEEE journal of biomedical and health informatics
Acute respiratory distress syndrome (ARDS) is a severe organ dysfunction associated with significant mortality and morbidity among critically ill patients admitted to the Intensive Care Unit (ICU). The etiology related to ARDS can be highly heterogen...

Accuracy of artificial intelligence algorithms in predicting acute respiratory distress syndrome: a systematic review and meta-analysis.

BMC medical informatics and decision making
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a serious threat to human life. Hence, early and accurate diagnosis and treatment are crucial for patient survival. This meta-analysis evaluates the accuracy of artificial intelligence in the ...

Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like ...