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Related Concept Videos

Acute Respiratory Failure-I01:21

Acute Respiratory Failure-I

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Acute respiratory failure is a condition characterized by the inability of the lungs to perform their primary function: gas exchange. This failure leads to insufficient oxygen levels (hypoxemia) in the blood, elevated carbon dioxide levels (hypercapnia), or both, causing critical impairment in organ function.
Definition: It is defined by specific criteria based on blood gas measurements. Hypoxemia happens when the partial pressure of oxygen (PaO2) falls below 60 mmHg. At the same time,...
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Acute Respiratory Failure-II01:21

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Type I Respiratory Failure, or hypoxemic respiratory failure, occurs when the partial pressure of oxygen (PaO2) in arterial blood falls below 60 mmHg while breathing room air without a corresponding increase in arterial carbon dioxide levels (PaCO2). This condition highlights a significant impairment in the lungs' capacity to oxygenate the blood.
The underlying physiological abnormalities that contribute to hypoxemic respiratory failure include:
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Acute Respiratory Failure-IV01:23

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Respiratory failure can manifest suddenly or gradually, characterized by a rapid decline in PaO2 and a rapid rise in PaCO2. This situation indicates a severe respiratory problem that may quickly become a life-threatening emergency. One of the early signs of hypoxemic Acute Respiratory Failure (ARF) is a change in mental status due to the brain's sensitivity to oxygen levels and changes in acid-base balance. Symptoms such as restlessness, confusion, and agitation suggest inadequate oxygen...
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Acute Respiratory Failure-III01:30

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Hypercapnic respiratory failure, also known as Type 2 or ventilatory respiratory failure, is a severe condition characterized by the body's inability to effectively remove carbon dioxide (CO2) from the bloodstream. It leads to an arterial CO2 pressure (PaCO2) exceeding 45 mmHg and a blood pH above 7.35. This situation indicates that the body's ventilatory demand, or the ventilation needed to maintain normal PaCO2 levels, surpasses its supply or the maximum gas flow achievable without...
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Acute Respiratory Failure-V01:29

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The treatment for acute respiratory failure varies based on factors like the underlying cause, overall health, and severity. A collaborative healthcare team is essential for early detection, often through arterial blood gas analysis. Identifying the cause is the primary goal, with treatment strategies adjusted for ventilation/perfusion (V/Q) mismatch, shunting, or diffusion impairment.
Ensure that patients are monitored continuously for their response to therapy, including changes in...
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Methods of Documentation VII: EMR01:30

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Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
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Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
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Identification of Acute Respiratory Failure Phenotypes With Electronic Health Record Data.

Charles R Terry1, Daniel L Brinton2, Katie G Kirchoff3

  • 1Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Medical University of South Carolina, Charleston, SC.

CHEST Critical Care
|November 27, 2025
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Summary

Electronic health records (EHRs) can identify two distinct subphenotypes of acute respiratory failure in ventilator-dependent patients. These subphenotypes show differences in physiology and organ function, with one linked to higher mortality.

Keywords:
artificial intelligencecluster analysismechanicalrespiratory insufficiencyventilators

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Surfactant Depletion Combined with Injurious Ventilation Results in a Reproducible Model of the Acute Respiratory Distress Syndrome ARDS
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Area of Science:

  • Critical Care Medicine
  • Pulmonology
  • Health Informatics

Background:

  • Previous studies identified acute respiratory failure subphenotypes using clinical trial and observational data.
  • Subphenotypes have not been previously characterized using real-world electronic health record (EHR) data.

Purpose of the Study:

  • To determine if subphenotypes of acute ventilator-dependent respiratory failure are identifiable using readily available EHR data.

Main Methods:

  • A multicenter retrospective cohort study utilized EHR data from two institutions (n=4,233 and n=8,313).
  • K-means clustering models were trained and validated using multiply imputed data at 24 and 48 hours post-intubation.

Main Results:

  • Two stable clusters were consistently identified at 24 and 48 hours, differentiating patients based on pulmonary physiology, perfusion, organ dysfunction, and metabolic status.
  • Cluster 2 exhibited higher 90-day mortality and increased ventilator days compared to Cluster 1, even after multivariable adjustment.
  • A crossover from the higher-acuity Cluster 2 to the lower-acuity Cluster 1 was observed by 48 hours post-intubation.

Conclusions:

  • Acute ventilator-dependent respiratory failure presents with two discernible subphenotypes identifiable through EHR data.
  • These subphenotypes differ in key physiologic features and organ dysfunction markers.
  • This finding supports the development of EHR tools for early identification of high-risk patients.