Diagnosis of acute aortic syndromes with ultrasound and d-dimer: the PROFUNDUS study.
Aorta
Diagnosis
Dissection
Probability
Score
Ultrasound
d-dimer
Journal
European journal of internal medicine
ISSN: 1879-0828
Titre abrégé: Eur J Intern Med
Pays: Netherlands
ID NLM: 9003220
Informations de publication
Date de publication:
12 Jun 2024
12 Jun 2024
Historique:
received:
12
04
2024
revised:
10
05
2024
accepted:
22
05
2024
medline:
14
6
2024
pubmed:
14
6
2024
entrez:
13
6
2024
Statut:
aheadofprint
Résumé
In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting. We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI. This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes. Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0-0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46-50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4-9 %, vs standard cutoff). The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency. Clinicaltrials.gov, NCT04430400.
Sections du résumé
BACKGROUND
BACKGROUND
In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting.
OBJECTIVES
OBJECTIVE
We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI.
METHODS
METHODS
This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes.
RESULTS
RESULTS
Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0-0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46-50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4-9 %, vs standard cutoff).
CONCLUSIONS
CONCLUSIONS
The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency.
CLINICAL TRIAL REGISTRATION
BACKGROUND
Clinicaltrials.gov, NCT04430400.
Identifiants
pubmed: 38871565
pii: S0953-6205(24)00234-6
doi: 10.1016/j.ejim.2024.05.029
pii:
doi:
Banques de données
ClinicalTrials.gov
['NCT04430400']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Investigateurs
Arianna Ardito
(A)
Alice Bartalucci
(A)
Gilberto Calzolari
(G)
Francesca Giachino
(F)
Dario Leone
(D)
Stefania Locatelli
(S)
Virginia Scategni
(V)
Maria Tizzani
(M)
Francesca Rubiolo
(F)
Alessandro Becucci
(A)
Ernesta Bondi
(E)
Gabriele Cavallaro
(G)
Cosimo Caviglioli
(C)
Stefania Guerrini
(S)
Eriola Haxhiraj
(E)
Barbara Paladini
(B)
Alessio Prota
(A)
Mattia Ronchetti
(M)
Federica Guerra
(F)
Múcio Tavares de Oliveira
(M)
Paulo Rogério Soares
(PR)
Margerita Malacarne
(M)
Massimo Santini
(M)
Mattia Bonzi
(M)
Paola Bartalucci
(P)
Alessandro Coppa
(A)
Christian Mueller
(C)
Chan Pei Fong
(CP)
Francesco Franceschi
(F)
Gianluca Tullo
(G)
Ludovica Ceschi
(L)
Michael Schwameis
(M)
Informations de copyright
Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.