Original research
Population-based studies suggest the mean annual incidence of AD ranges from 6 4 to 7.2 5 per 100 000 person-years, while a US study which included all AAS (AD, IMH and PAU) found an incidence of 7.7 per 100 000 person-years. 6 The misdiagnosis rate is estimated to be 33.8%, 7 with diagnostic delay of up to 24 hours for 25% of cases, 2 and mortality follows a linear increase of 0.5% per hour in the first 48 hours. 8 Chest pain is the most common presenting symptom of AAS (80%) although back and abdominal pain are not uncommon. 9 Chest pain is responsible for 7.6 million annual visits to EDs in the USA 10 and collectively, chest, back and abdominal pain accounts for over 2 million ED attendances annually in England 11 and are overwhelmingly due to causes other than AAS. The esti- mated incidence of AAS is one in every 980 ED atraumatic chest pain attendances, 12 thus creating a substantial diagnostic chal- lenge. Too low a threshold for performing a CT aorta angiogram (CTA), the gold standard for diagnosis, would result in low diag- nostic yields, 13 14 significant costs and risks of ionising radiation. Clinicians therefore need to use CTA selectively, yet there is no validated clinical decision tool (CDT) for this scenario. Several CDTs have been proposed. 15–17 However, they have been tested in patients undergoing CTA. Additionally, D-dimer has been suggested as a rule-out biomarker in low pre-test prob- ability patients (95–98% sensitivity) 18 19 and has been incorpo- rated into the Aortic Dissection Detection Risk Score (ADD-RS) CDT. No CDT has previously been studied in truly undifferen- tiated ED populations. It is important to test possible CDTs and biomarkers in undifferentiated ED patients, because ED clini- cians are likely to apply them to all patients with possible AAS rather than just those selected for CTA. It is currently unclear whether any AAS CDTs have sufficient sensitivity to be accept- able to clinicians, which is the most accurate, and whether they are likely to lead to CTA and D-dimer over-investigation. Assess- ment of CTA rate versus CTA positivity has not previously been studied in the clinically relevant population. With these challenges in mind, we aimed to describe the char- acteristics of ED attendances with possible AAS and to assess existing CDTs and use of CTA in an ‘all-comer’ cohort of patients. METHODS This was a multicentre observational cohort study of ED patients with symptoms potentially attributable to AAS. The primary objective was to establish the characteristics and performance of existing clinical decision tools, including ADD-RS, 15 Canadian guideline, 16 AORTAs 17 and Sheffield (Ben Loryman, personal communication, 30 September 2021), in this cohort of patients. Secondary objectives were to establish patient characteristics, CTA rates and patient enrolment at participating sites. This study was conducted in 27 EDs in England, Scotland and Wales. A pragmatic approach to maximise recruitment was taken, with each ED including eligible patients for a consecutive period of between 2 and 40days in autumn 2022. Data from each patient’s attendance was entered onto a standard Case Report Form (CRF)online supplemental appendix 1, with subse- quent 30-day outcome data captured from the Electronic Patient Record (EPR). People aged 16 years or over, attending the ED with new- onset symptoms of possible AAS were eligible for inclusion. New onset was defined as starting within the past 7 days; and possible AAS symptoms included chest, back or abdominal pain, syncope or symptoms related to malperfusion. The only exclusion was the absence of any potential AAS symptoms. Patients transferred
from other centres were included. Patients were either identi- fied prospectively by the treating clinician, prospectively by the local study team reviewing real-time ED attendance data to identify presentations of chest, back or abdominal pain, syncope or symptoms related to malperfusion, or retrospectively by the local study team, where local legal and ethical consent processes allowed. Data was collected by either the treating clinicians or the local study team. Where patients were identified prospec- tively, either the treating clinician commenced the CRF or was approached by the study team as soon after the consultation as possible, to establish their clinical suspicion of AAS before any confirmatory testing took place. Retrospective patient identifi- cation was done from daily searches of the EPR using an ED presenting problems of chest, back or abdominal pain, syncope or symptoms related to malperfusion and radiology records of ED-requested CTAs during the study period. This enabled collec- tion of an accurate picture of the epidemiology and management of patients attending the ED with symptoms of AAS, including at weekends and out of hours when research staffing was often reduced relative to daytime hours. For patients identified prospectively, the treating clinician was also asked about their clinical suspicion of AAS (Yes/No), with likelihood from 0 to 10, and whether they thought AAS was the most likely diagnosis (Yes/No). If the treating clinician thought that there was a negligible likelihood of AAS, the patient was still enrolled to allow us to assess what proportion of presenta- tions with symptoms possibly associated with AAS had no clin- ical concern for AAS. Clinician impression was recorded by the treating clinician at the time of reviewing the patient to ensure they were not influenced by any laboratory or radiological results. There was no change to usual clinical care and no study specific interventions for participants. Anonymised patient data was uploaded to an electronic CRF (eCRF) (online supplemental appendix 1), sited on an online secure database (Research Electronic Data Capture (REDCap); http://www.project-redcap.org) on a University of Edinburgh server. 20 21 No participant identifiable data was entered onto the eCRF, left the local hospital or was viewed outside of the clinical care team. After eCRFs were completed, hospital/study number linkage was destroyed. Data was recorded for patient demographics (age, sex), attendance date and time and for all characteristics of the clinical decision tools being evaluated. Clinical data included time of onset and features of any pain, relevant medical or family history, examination findings, results from investigations and suspected diagnosis. Diagnoses and data were not adjudicated. Data was not validated but was cleaned by the central analysis team with any data queries being addressed where possible by the site study teams. Study endpoints ► The proportion of patients in whom the ED clinician thought AAS was a possible differential diagnosis, and most likely diagnosis, who had confirmed AAS. ► The proportion of patients in whom the ED clinician thought AAS was not a possible differential diagnosis but had confirmed AAS ► Test characteristics of clinical acumen, ADD-RS, AORTAs, Canadian and Sheffield AAS clinical decision tools and D-dimer (separately and in combination). ► CT/CTA ordering and positivity rate. ► Proportion of alternative diagnoses found on CT/CTA and final hospital diagnosis. ► Median time from hospital presentation to imaging diagnosis.
McLatchie R, et al . Emerg Med J 2024; 41 :136–144. doi:10.1136/emermed-2023-213266
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