Articles: respiratory-distress-syndrome.
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Critical care medicine · Jan 2024
Multicenter StudyThe Predictive Validity of the Berlin Definition of Acute Respiratory Distress Syndrome for Patients With COVID-19-Related Respiratory Failure Treated With High-Flow Nasal Oxygen: A Multicenter, Prospective Cohort Study.
The Berlin definition of acute respiratory distress syndrome (ARDS) was constructed for patients receiving invasive mechanical ventilation (IMV) with consideration given to issues related to reliability, feasibility, and validity. Notwithstanding, patients with acute respiratory failure (ARF) may be treated with high-flow nasal oxygen (HFNO) and may not fall within the scope of the original definition. We aimed to evaluate the predictive validity of the Berlin definition in HFNO-treated patients with COVID-19-related respiratory failure who otherwise met ARDS criteria. ⋯ The predictive validity of the Berlin ARDS definition was similar for HFNO-treated patients as compared with the original population of invasively ventilated patients. Our findings support the extension of the Berlin definition to HFNO-treated patients with ARDS.
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Critical care medicine · Jan 2024
Observational StudyPrevalence and Risk Factors for Weaning Failure From Venovenous Extracorporeal Membrane Oxygenation in Patients With Severe Acute Respiratory Insufficiency.
Analysis of the prevalence and risk factors for weaning failure from venovenous extracorporeal membrane oxygenation (VV-ECMO) in patients with severe acute respiratory insufficiency. ⋯ Seventy-nine percent of patients were successfully decannulated with only 4% needing prolonged ECMO weaning. Before EWT only parameters of impaired ventilation (insufficient decarboxylation, higher respiratory rate) but not of oxygenation were predictive for weaning failure, whereas during EWT-impaired oxygenation was associated with weaning failure.
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Anasthesiol Intensivmed Notfallmed Schmerzther · Jan 2024
[Potential of AI for the Treatment of Acute Respiratory Distress Syndrome (ARDS)].
Acute respiratory distress syndrome (ARDS) is still associated with high mortality rates and poses a significant, vital threat to ICU patients because this syndrome is often detected too late (or not at all), and timely therapy and the fastest possible elimination of the underlying causes thus fail to materialize. Artificial Intelligence (AI) solutions can enable clinicians to make every minute in the ICU work for the patient by processing and analyzing all relevant data, thus supporting early diagnosis, adhering to clinical guidelines, and even providing a prognosis for the course of the ICU. This article shows what is already possible and where further challenges lie in this field of digital medicine.