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Artificial Intelligence to StrategiCally Enhance Pulmonary Embolism Response Team Activation (ASCENT)

University Hospitals (UH) logo

University Hospitals (UH)

Status

Withdrawn

Conditions

Pulmonary Embolism Subacute Massive

Treatments

Diagnostic Test: Walking test

Study type

Interventional

Funder types

Other
Industry

Identifiers

NCT06246045
STUDY20220475

Details and patient eligibility

About

Pulmonary embolism (PE) remains a high mortality and morbidity disease state. The investigators have previously shown that use of a Pulmonary Embolism Response Team (PERT) can improve overall readmission, bleeding, and mortality outcomes. Unfortunately, PERT may still be underutilized from a national standpoint and may not be readily available in underserved areas.

The use of artificial intelligence (AI) may help streamline and systematically ensure unbiased mechanism for activation of PERT for discussion of patients with siginficant clot burden and hemodynamic abnormalities. AI algorithms have been FDA approved for use of triage of the PE patient. The institutional PERT program will adapt the use of an AI algorithm for activation as routine care; the efficiency of activation will be compared to our retrospective historical comparison for efficiency and appropriateness of activation.

The active phase of the study is designed to further differentiate between patients who are considered to be intermediate-high risk category but yet do not clearly qualify for invasive therapy (catheter-directed therapy, systemic thrombolysis, or invasive hemodynamic support). These patients will undergo walking test to further understand noninvasive hemodynamic compromise and undergo 2:1 randomization to early-invasive strategy versus mtranditional medical therapy.

Sex

All

Ages

18 to 99 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • Patients obtaining a CT at University Hospitals found to have a pulmonary embolism with evidence of right ventricular strain (RV:LV > 0.9) along with an abnormal vital sign (HR > 110 bpm, RR > 30/min, SBP < 100 mmHg, or O2 saturation < 90%)
  • Patients undergoing PERT discussion as deemed appropriate by the provider

Exclusion criteria

  • Age <18
  • Pregnant patients. Women of childbearing age will be asked if they are pregnant before enrollment. No formal pregnancy test will be performed as a part of this study. If a patient does require invasive intervention, as part of the routine procedure for cardiac catheterization laboratory, women of childbearing age will either undergo pregnancy testing or opt-out per their own discretion
  • Patients unable to perform 6MWT (e.g., lack of one or both legs) will not be included in the randomization. They will be included in the observation for routine treatment

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

0 participants in 2 patient groups

Early-Invasive Strategy
Experimental group
Description:
Patients who do not clearly qualify for early intervention (including catheter-directed therapies, systemic thrombolysis, or invasive hemodynamic support) based on assessment by PERT members, will undergo walk testing on the first day of admission. If the subject meets criteria based on pre-specified hemodynamic changes, then the patient will be randomized in a 2:1 fashion to early invasive strategy with catheter-directed therapies as treatment arm.
Treatment:
Diagnostic Test: Walking test
Traditional Medical Therapy
Active Comparator group
Description:
Patients who do not clearly qualify for early intervention (including catheter-directed therapies, systemic thrombolysis, or invasive hemodynamic support) based on assessment by PERT members, will undergo walk testing on the first day of admission. If the subject meets criteria based on pre-specified hemodynamic changes, then the patient will be randomized (2:1, treatment to control) to traditional routine care with medical therapy.
Treatment:
Diagnostic Test: Walking test

Trial contacts and locations

1

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Central trial contact

Jun Li, MD

Data sourced from clinicaltrials.gov

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