Acute aortic syndrome (AAS) is a life-threatening emergency condition affecting the upper aorta affecting \~4000 people in the (United Kingdom; UK) a year with an ED misdiagnosis rate as high as 38%. Previous research has identified several strategies combining clinical probability scoring with blood tests (D-Dimer) to rule out the condition but when applied to a large population (ED) with relatively low numbers of actual cases, these result in a high rate of computed tomographic angiography (CTA) scanning. Current guidelines reflect the uncertainty of existing evidence. This study, the first phase of three, aims to describe the characteristics of ED attendances with possible AAS, to determine the service implications of using different diagnostic strategies and inform future research. The investigators plan to recruit all ED attendances with possible AAS over a 1-4 week period. The investigators plan a prospective and retrospective approach to data collection adopting a waived-consent strategy with endpoint measures describing the characteristics of patients presenting with possible AAS.
AAS is a life-threatening emergency condition which presents to the ED. Around 4,000 people suffer per year in the UK \[1\], many not receiving timely diagnosis and treatment. 25% of patients are not diagnosed until 24 hours after arriving in the ED due to the varied nature of presentation \[2\]. Chest pain is the most common presenting symptom of AAS (80%) although back pain (40%) and abdominal pain are not uncommon \[1\]. These symptoms account for over 2 million ED attendances per year in England \[National Health Service; NHS Digital A\&E 2021\] and are overwhelmingly due to causes other than AAS. The estimated incidence of AAS is 1 in every 980 ED attendances with atraumatic chest pain \[3\], thus creating a substantial diagnostic challenge. Prognosis is best when patients are treated early, and mortality increases 2% per hour of delay. \[4\] The misdiagnosis rate during the initial ED visit for AAS is estimated to be between 1 in 3 to 1 in 7 AASs \[5\], leading to worse outcomes \[6,7\] whilst CTA over testing leads to diagnostic yields as low as 2-3%. \[2,8\]. CTA scanning of the aorta has high sensitivity and specificity for diagnosing AAS, but an unrestricted CT strategy will incur significant costs, has ionising radiation risks, resource implications, CT delays for non-AAS patients and the burden of 'incidentalomas'. Clinicians therefore need to use CTA selectively but there is no validated scoring system to help this decision. Several have been proposed \[1, 9-14\] including the ADD-RS score, the Canadian clinical practice guideline Clinical Decision Aid \[13\], the AORTAs score \[14\] and the Sheffield score \[unpublished\]. D-Dimer has been suggested as a rule-out biomarker in low pre-test probability patients (95-98% sensitivity) \[15,16\] and has been incorporated into the Aortic Dissection Detection-Risk Stratification (ADD-RS) score to reduce CTA rate in low pre-test probability patients. None have been studied in truly undifferentiated ED populations, or in the UK where CTA threshold is different compared to North America. It is currently unclear whether any have sufficient sensitivity to be acceptable to clinicians, which is the most accurate, and whether they are likely to lead to CTA and D-Dimer over testing. Assessment of CTA rate and CT positivity has also not previously been studied. The Royal College of Emergency Medicine has recently released a national guideline advocating any patient with an ADD-RS score of \>=1 (no D-dimer incorporated) should have a CT aorta performed (unless other cause for symptoms identified and evidenced). The recommendation is not based on UK-validated clinical evidence, however, and clinical impacts of the recommendation are yet to be seen. In view of these diagnostic challenges, the investigators aim in our programme of work to ultimately to assess which of the four aforementioned clinical decision tools is most effective, assess external validity, and assess clinical impact. This study (Phase 1; DAShED) will involve prospective data collection on all characteristics of four different risk scores, in addition to evaluation of patient characteristics, potential CT aorta rates with different strategies, and enrolment rates at participating sites. This will inform Phase 2, which will involve full interventional external validation study of the decision aid(s) selected in Phase 1 (including biomarker collection); the main objective being to select the score to subject to assessment of clinical impact (intervention step-wedge trial) in Phase 3. This is an observational cohort study of all people attending the ED with symptoms of possible AAS, including new-onset chest, back or abdominal pain, syncope or symptoms related to malperfusion.
Study Type
OBSERVATIONAL
Enrollment
5,548
All patients will have a focussed Electronic Case Report Form completed collecting information around Presenting complaint, Past Medical History, Family History, Physical Examination findings, and Investigations.
Royal United Hospital
Bath, United Kingdom
Bristol Royal Infirmary
Bristol, United Kingdom
North Bristol NHS Trust
Bristol, United Kingdom
Addenbrookes hospital
Cambridge, United Kingdom
Royal Infirmary of Edinburgh
Edinburgh, United Kingdom
St Johns Hospital
Edinburgh, United Kingdom
Frimley Health
Frimley, United Kingdom
Queen Elizabeth University Hospital
Glasgow, United Kingdom
Royal Alexandra Hospital
Glasgow, United Kingdom
James Paget University Hospital
Great Yarmouth, United Kingdom
...and 15 more locations
Enrolment rate at each participating site
Number of participants during study period enrolled
Time frame: 30 days
Proportion of patients in whom the ED clinician thinks Acute Aortic Syndrome (AAS) is a possible differential who have confirmed AAS
Proportion of patients in whom the ED clinician thinks Acute Aortic Syndrome (AAS) is a possible differential who have confirmed AAS
Time frame: 30 days
Proportion of patients in whom ED clinician considers AAS NOT a possible differential who had confirmed AAS
Proportion of patients in whom ED clinician considers AAS NOT a possible differential who had confirmed AAS
Time frame: 30 days
Number of AAS patients not enrolled due to lack of clinical/research support
Number of AAS patients not enrolled due to lack of clinical/research support
Time frame: 30 days
CT angiogram (CTA) ordering and positivity rate
Number of CT angiograms ordered and the proportion that are positive scans
Time frame: 30 days
Test characteristics of clinical acumen
Test characteristics of clinical acumen (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Test characteristics of ADD-RS (Aortic Dissection Detection-Risk Score)
Test characteristics of Aortic Dissection Detection-Risk Score (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Test characteristics Aorta score
Test characteristics of Aorta score (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Test characteristics of Canadian guideline score
Test characteristics of Canadian guideline score (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Test characteristics of Sheffield AAS decision rule
Test characteristics of Sheffield AAS decision rule (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Test characteristics of D-dimer
Test characteristics of D-dimer (i.e. sensitivity, specificity, positive predictive value, negative predictive value)
Time frame: 30 days
Median time from hospital presentation to imaging diagnosis and median time from symptom onset to hospital presentation (hours)
Median time from hospital presentation to imaging diagnosis and median time from symptom onset to hospital presentation (hours)
Time frame: 30 days
30-day mortality in proven AAS
30-day mortality in proven AAS
Time frame: 30 days
Proportion of alternative diagnoses found on CTA and final hospital diagnosis
Proportion of alternative diagnoses found on CTA and final hospital diagnosis
Time frame: 30 days
Number of patients not able to be enrolled with reason why not enrolled
Number of patients not able to be enrolled with reason why not enrolled
Time frame: 30 days
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