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A Porcine Model of Acute Autologous Pulmonary Embolism
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Radiology-Led Pulmonary Embolism Response Team (PERT) Activation: Initial Experience.

Kamil Tomaszek1, Dustin Gulizia1, Abhaya Trivedi1

  • 1Rush University Medical Center, Chicago, IL, United States.

European Journal of Radiology
|March 1, 2025
PubMed
Summary
This summary is machine-generated.

A new Pulmonary Embolism Response Team (PERT) activated by radiology diagnosis streamlines care. This approach improves pulmonary embolism (PE) detection, risk stratification, and coordination for better patient outcomes.

Keywords:
Interventional radiology (IR)Multidisciplinary carePERTPulmonary embolus (PE)

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Area of Science:

  • Pulmonary Medicine
  • Radiology
  • Emergency Medicine

Background:

  • Pulmonary embolism (PE) diagnosis requires timely and accurate risk stratification.
  • Existing protocols may lack integrated, rapid response mechanisms.
  • Multidisciplinary collaboration is crucial for effective PE management.

Purpose of the Study:

  • To implement and evaluate a Pulmonary Embolism Response Team (PERT) activated by diagnostic radiology.
  • To assess the effectiveness of a novel clinical algorithm for PE severity stratification.
  • To identify benefits and challenges of a radiology-activated PERT.

Main Methods:

  • Development of a multidisciplinary clinical algorithm for PERT activation.
  • Activation of PERT upon radiologic diagnosis of PE.
  • Clinical stratification of PE severity using the developed algorithm.
  • Data collection on 524 PE diagnoses from August 2021 to March 2023.

Main Results:

  • The PERT was activated for 524 pulmonary embolism diagnoses.
  • Clinical stratification revealed: 34% low risk, 35% intermediate-low risk, 27% intermediate-high risk, and 3% high risk.
  • Implementation demonstrated streamlined stratification, improved detection, and enhanced care coordination.

Conclusions:

  • A radiology-activated PERT offers significant benefits in managing pulmonary embolism.
  • The novel algorithm facilitates efficient clinical stratification and care coordination.
  • Further research on clinical outcomes and AI comparisons is recommended.