Evidence map›Paper›PMID 41222893›Full record

ArticleCJEM2025

Evaluation of probability-adjusted D-dimer algorithms among patients imaged for pulmonary embolism in three Canadian emergency departments.

Logan Haynes, Travis Black, Philip J Davis, Taofiq Olusegun Oyedokun, Sachin V Trivedi

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in CJEM, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Logan HaynesDepartment of Emergency Medicine, University of Saskatchewan, Royal University Hospital, Saskatoon, SK, Canada. logan.haynes@usask.ca.ORCID 0009-0004-4591-8891
Travis BlackCollege of Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
Philip J DavisDepartment of Emergency Medicine, University of Saskatchewan, Royal University Hospital, Saskatoon, SK, Canada.
Taofiq Olusegun OyedokunDepartment of Emergency Medicine, University of Saskatchewan, Royal University Hospital, Saskatoon, SK, Canada.
Sachin V TrivediDepartment of Emergency Medicine, University of Saskatchewan, Royal University Hospital, Saskatoon, SK, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesD-dimer testing can reduce imaging utilization in the workup of pulmonary embolism, but the optimal cutoff remains unclear. The conventional D-dimer cutoff is < 500 µg/L Fibrinogen Equivalent Units, while the age-adjusted cutoff in patients over 50 is age × 10. Newer probability-adjusted strategies-the YEARS criteria and PEGeD algorithm-allow a higher threshold (D-dimer < 1000 µg/L) for select low-risk patients. We aimed to retrospectively compare the diagnostic accuracy of four evidence-based pathways to exclude pulmonary embolism without imaging among our emergency department patients who were imaged.

methodsA historical patient cohort was generated including all adults who received computed tomography pulmonary angiography or ventilation-perfusion scans after D-dimer testing in three emergency departments in a large urban Canadian center. Electronic medical records were reviewed to retrospectively compare the test performance of four D-dimer pathways: (i) conventional, (ii) age-adjusted, (iii) YEARS, and (iv) PEGeD.

resultsOf 1092 patients, 129 had pulmonary embolism. Conventional and age-adjusted cutoffs were both 100% sensitive (95% CI, 97.1-100.0), with specificities of 3.5% (2.5-4.9) and 6.4% (5.1-8.2). YEARS was 93.8% sensitive (88.2-96.8) and 30.4% specific (27.6-33.4), with PPV of 15.3% (13.0-18.0) and NPV of 97.3% (94.8-98.6). PEGeD was the least sensitive (92.2%, 86.3-95.7), but most specific (39.1%, 36.1-42.3), with PPV of 16.9% (14.3-19.8) and NPV of 97.4% (95.3-98.6). PEGeD would have resulted in the most patients managed without imaging (35.4%), followed by YEARS (27.6%), age-adjusted (5.7%), and the conventional cutoff (3.1%).

conclusionWhile implementation of a probability-adjusted D-dimer pathway, such as YEARS or PEGeD, would have substantially reduced imaging utilization, these strategies may miss some cases of pulmonary embolism detectable by both age-adjusted and conventional cutoffs. We add to the heterogeneity of safety data, suggesting that adjustment of D-dimer to clinical probability represents a trade-off between sensitivity and imaging utilization.

Indexed as

AlgorithmsEmergency Service, HospitalFibrin Fibrinogen Degradation ProductsPulmonary EmbolismAdultAgedBiomarkersCanadaComputed Tomography AngiographyFemaleHumansMaleMiddle AgedProbabilityRetrospective StudiesVentilation-Perfusion ScanBiomarkersFibrin Fibrinogen Degradation Productsfibrin fragment DClinical decision rulesEmergency medicinePulmonary embolism

Identifiers

PMID41222893

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.