{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T03:49:09Z","timestamp":1788839349358,"version":"build-2803163510"},"reference-count":132,"publisher":"National Institute for Health and Care Research","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journalslibrary.nihr.ac.uk"],"crossmark-restriction":false},"short-container-title":["Health Technol Assess"],"abstract":"<jats:sec id=\"abs1-1\"><jats:title>Background<\/jats:title>\n<jats:p>Acute aortic syndrome is a life-threatening condition that requires urgent diagnosis with computed tomographic angiography. Diagnostic technologies, including clinical scores and biomarkers, can be used to select patients presenting with potential symptoms of acute aortic syndrome for computed tomographic angiography.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-2\"><jats:title>Objectives<\/jats:title>\n<jats:p>We aimed to estimate the accuracy of clinical scores and biomarkers for diagnosing acute aortic syndrome, the cost-effectiveness of alternative diagnostic strategies and the expected value of future research.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-3\"><jats:title>Methods<\/jats:title>\n<jats:p>We searched online databases from inception to February 2024, reference lists of included studies and existing systematic reviews. We included cohort studies evaluating the accuracy of clinical scores or biomarkers for diagnosing acute aortic syndrome compared with a reference standard. Two authors independently selected and extracted data. Risk of bias was appraised using the quality assessment of diagnostic accuracy studies-2 tool. Data were synthesised using either a multinomial or a bivariate normal meta-analysis model.<\/jats:p>\n<jats:p>We developed a decision-analytic model to simulate the management of a hypothetical cohort of patients attending hospital with possible acute aortic syndrome. We modelled diagnostic strategies that used the Aortic Dissection Detection Risk Score and D-dimer to select patients for computed tomographic angiography. We used estimates from our meta-analysis, existing literature and clinical experts to model the consequences of diagnostic strategies upon survival, health utility and healthcare costs. We estimated the incremental cost per quality-adjusted life-year gained by each strategy compared to the next most effective alternative on the efficiency frontier, and the expected value of perfect information.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-4\"><jats:title>Results<\/jats:title>\n<jats:p>Primary meta-analysis included 12 studies of Aortic Dissection Detection Risk Score alone, 6 studies of Aortic Dissection Detection Risk Score with D-dimer and 18 studies of D-dimer using the 500\u00a0ng\/ml threshold. Sensitivities and specificities (95% credible intervals) were: Aortic Dissection Detection Risk Score &gt;\u20050 94.6% (90% to 97.5%) and 34.7% (20.7% to 51.2%), Aortic Dissection Detection Risk Score &gt;\u20051 43.4% (31.2% to 57.1%) and 89.3% (80.4% to 94.8%); Aortic Dissection Detection Risk Score &gt;\u20050 or D-dimer &gt;\u2005500\u00a0ng\/ml 99.8% (98.7% to 100%) and 21.8% (12.1% to 32.6%); Aortic Dissection Detection Risk Score &gt;\u20051 or D-dimer &gt;\u2005500\u00a0ng\/ml 98.3% (94.9% to 99.5%) and 51.4% (38.7% to 64.1%); Aortic Dissection Detection Risk Score &gt;\u20051 or Aortic Dissection Detection Risk Score\u2005=\u20051 with D-dimer &gt;\u2005500\u00a0ng\/ml 93.1% (87.1% to 96.3%) and 67.1% (54.4% to 77.7%); and D-dimer alone 96.5% (94.8% to 98%) and 56.2% (48.3% to 63.9%). We identified 11 cohort studies of other biomarkers, but accuracy estimates were limited and inconsistent.<\/jats:p>\n<jats:p>Decision-analytic modelling showed that applying diagnostic strategies to an unselected population (acute aortic syndrome prevalence 0.26%) resulted in high rates of computed tomographic angiography, and only the strategy selecting patients with Aortic Dissection Detection Risk Score &gt;\u20051 for computed tomographic angiography was cost-effective. If clinicians can select a population for investigation with higher acute aortic syndrome prevalence (0.61%), then using a strategy of Aortic Dissection Detection Risk Score &gt;\u20051 or Aortic Dissection Detection Risk Score =\u20051 with D-dimer &gt;\u2005500\u00a0ng\/ml\u00a0or a strategy of Aortic Dissection Detection Risk Score &gt;\u20051 or D-dimer &gt;\u2005500\u00a0ng\/ml to select patients for computed tomographic angiography is cost-effective and deliverable. At a threshold of \u00a320,000\/quality-adjusted life-year, population expected value of perfect information was around \u00a317.75M.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-5\"><jats:title>Limitations<\/jats:title>\n<jats:p>Studies included in the meta-analysis showed substantial heterogeneity in estimates of specificity. In the modelling, there was substantial uncertainty around what constitutes suspected acute aortic syndrome and the effect of delayed diagnosis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-6\"><jats:title>Conclusions<\/jats:title>\n<jats:p>The Aortic Dissection Detection Risk Score and D-dimer provide useful diagnostic information and may offer cost-effective strategies for selecting patients for computed tomographic angiography, but their role depends upon how clinicians identify suspected acute aortic syndrome.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-7\"><jats:title>Future work<\/jats:title>\n<jats:p>Primary research is required to compare different combinations of Aortic Dissection Detection Risk Score with D-dimer in practice, explore how suspected acute aortic syndrome is identified and evaluate alternative biomarkers.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"abs1-8\"><jats:title>Funding<\/jats:title>\n<jats:p>This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR151853.<\/jats:p>\n<\/jats:sec>","DOI":"10.3310\/ggop6363","type":"journal-article","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T05:06:28Z","timestamp":1740719188000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.3310\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":5,"title":["Diagnostic strategies for suspected acute aortic syndrome: systematic review, meta-analysis, decision-analytic modelling and value of information analysis"],"prefix":"10.3310","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0803-8444","authenticated-orcid":true,"given":"Steve","family":"Goodacre","sequence":"first","affiliation":[{"name":"Sheffield Centre for Health and Related Research, University of Sheffield, Sheffield, 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