Observational cohort study to validate SEARCH, a novel hierarchical algorithm to define long-term outcomes after pulmonary embolism

Author:

Morris Timothy AORCID,Fernandes Timothy M,Chung Jina,Vintch Janine R E,McGuire W Cameron,Thapamagar SumanORCID,Alotaibi Mona,Aries Savannah,Dakaeva Khadizhat

Abstract

BackgroundChronic dyspnoea and exercise impairment are common after acute pulmonary embolism (PE) but are not defined and quantified sufficiently to serve as outcomes in clinical trials. The planned project will clinically validate a novel method to determine discrete, clinically meaningful diagnoses after acute PE. The method uses an algorithm entitled SEARCH, forsymptom screen,exercise testing,arterial perfusion,resting echocardiography,confirmatory imaging andhaemodynamic measurements. SEARCH is a stepwise algorithm that sorts patients by a hierarchical series of dichotomous tests into discreet categories of long-term outcomes after PE: asymptomatic, post-PE deconditioning, symptoms from other causes, chronic thromboembolism with ventilatory inefficiency, chronic thromboembolism with small stroke volume augmentation, chronic thromboembolic disease and chronic thromboembolic pulmonary hypertension.MethodsThe project will test the inter-rater reliability of the SEARCH algorithm by determining whether it will yield concordant post-PE diagnoses when six independent reviewers review the same diagnostic data on 150 patients evaluated at two time points after PE. The project will also determine whether the post-PE diagnoses are stable, according to the SEARCH algorithm, between the first evaluation and the subsequent one 6 months later.ImplicationsValidation of the SEARCH algorithm would offer clinicians a straightforward method to diagnose post-PE conditions that are rarely distinguished clinically. Their categorisation and definition will allow post-PE conditions to be used as endpoints in clinical trials of acute PE treatment.Trial registration numberNCT05568927.

Funder

Inari Health

Publisher

BMJ

Subject

General Medicine

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