Autor: |
Robert Ohle, Sarah McIsaac, Madison Van Drusen, Aaron Regis, Owen Montpellier, Mackenzie Ludgate, Oluwadamilola Bodunde, David W. Savage, Krishan Yadav |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Emergency Medicine International, Vol 2023 (2023) |
Druh dokumentu: |
article |
ISSN: |
2090-2859 |
DOI: |
10.1155/2023/6636800 |
Popis: |
Introduction. Acute aortic syndrome (AAS) is a rare clinical syndrome with a high mortality rate. The Canadian clinical practice guideline for the diagnosis of AAS was developed in order to reduce the frequency of misdiagnoses. As part of the guideline, a clinical decision aid was developed to facilitate clinician decision-making (RIPP score). The aim of this study is to validate the diagnostic accuracy of this tool and assess its performance in comparison to other risk prediction tools that have been developed. Methods. This was a historical case-control study. Consecutive cases and controls were recruited from three academic emergency departments from 2002–2020. Cases were identified through an admission, discharge, or death certificated diagnosis of acute aortic syndrome. Controls were identified through presenting complaint of chest, abdominal, flank, back pain, and/or perfusion deficit. We compared the clinical decision tools’ C statistic and used the DeLong method to test for the significance of these differences and report sensitivity and specificity with 95% confidence intervals. Results. We collected data on 379 cases of acute aortic syndrome and 1340 potential eligible controls; 379 patients were randomly selected from the final population. The RIPP score had a sensitivity of 99.7% (98.54–99.99). This higher sensitivity resulted in a lower specificity (53%) compared to the other clinical decision aids (63–86%). The DeLong comparison of the C statistics found that the RIPP score had a higher C statistic than the ADDRS (−0.0423 (95% confidence interval −0.07–0.02); P |
Databáze: |
Directory of Open Access Journals |
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