• Medicina clinica · May 2020

    Usefulness of predictive models of pulmonary embolism.

    • Luis Carlos García-Gómez, Luis Castilla-Guerra, Juan de la Vega-Sánchez, Francisco Jesús Olmo-Montes, and Miguel Ángel Colmenero-Camacho.
    • Servicio de Medicina Interna, Hospital Universitario Virgen Macarena, Sevilla, España. Electronic address: luiscarlosgarciagomez@hotmail.com.
    • Med Clin (Barc). 2020 May 8; 154 (9): 338-343.

    BackgroundFaced with the suspicion of pulmonary embolism (PE), the guidelines recommend the use of clinical probability scales, measurement of D-dimer and, in certain cases, confirmation by pulmonary angiography by computed tomography (CTPA) or scintigraphy. Recently, it has been proposed to adjust the D-dimer according to age or use simpler scales (YEARS algorithm) for a better selection of patients.ObjectiveTo define the degree of application of the guidelines in our population and compare sensitivity, specificity and positive and negative predictive values of the different diagnostic models: Standard model (Wells 2 categories+D-dimer), Model adjusted for age (Wells 2 categories+D-dimer adjusted for age), YEARS algorithm.Material And MethodsA retrospective study of all patients who underwent APTC at our centre for the diagnosis of PE over one year.ResultsOf 618 cases (85.4% of initial APTC), 544 patients were included. A total of 113 EPs were diagnosed (20.8%). The degree of application of the standard model was very high (90.1%) and proved to have the best sensitivity and negative predictive value ratio (sensitivity=1.0, negative predictive value=1.0). The new models could reduce the number of scans (17, 3.2% model adjusted for age and 48, 8.8% model YEARS) with a risk of false negatives (2 PE [1.8%] undiagnosed respectively).ConclusionsThe current diagnostic models for PE lead to a large number of unnecessary explorations. The new models could reduce the number of APTC although with a minimum risk of false negatives.Copyright © 2019 Elsevier España, S.L.U. All rights reserved.

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