Romain Chopard1, Gregory Piazza2, Nicolas Falvo3, Fiona Ecarnot4, Mathieu Besutti5, Gilles Capellier6, François Schiele4, Marc Badoz4, Nicolas Meneveau7. 1. Department of Cardiology, University Hospital Jean Minjoz, Besançon, France; EA3920, University of Burgundy Franche-Comté, Besançon, France; F-CRIN, INNOVTE network, France. Electronic address: chopardromain@yahoo.fr. 2. Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. 3. Department of Internal Medicine, University Hospital Dijon-Bourgogne, Dijon, France. 4. Department of Cardiology, University Hospital Jean Minjoz, Besançon, France; EA3920, University of Burgundy Franche-Comté, Besançon, France. 5. Department of Cardiology, University Hospital Jean Minjoz, Besançon, France. 6. EA3920, University of Burgundy Franche-Comté, Besançon, France; Medical Intensive Care Unit, University Hospital Jean Minjoz, Besançon, France. 7. Department of Cardiology, University Hospital Jean Minjoz, Besançon, France; EA3920, University of Burgundy Franche-Comté, Besançon, France; F-CRIN, INNOVTE network, France.
Abstract
BACKGROUND: Improved prediction of the risk of early major bleeding in pulmonary embolism (PE) is needed to optimize acute management. RESEARCH QUESTION: Does a simple scoring system predict early major bleeding in acute PE patients, identifying patients with either high or low probability of early major bleeding? STUDY DESIGN AND METHODS: From a multicenter prospective registry including 2,754 patients, we performed post hoc multivariable logistic regression analysis to build a risk score to predict early (up to hospital discharge) major bleeding events. We validated the endpoint model internally, using bootstrapping in the derivation dataset by sampling with replacement for 500 iterations. Performances of this novel score were compared with that of the VTE-BLEED (Venous Thrombo-Embolism Bleed), RIETE (Registro informatizado de la enfermedad tromboembólica en España; Computerized Registry of Patients with Venous Thromboembolism), and BACS (Bleeding, Age, Cancer, and Syncope) models. RESULTS: Multivariable regression identified three predictors for the occurrence of 82 major bleeds (3.0%; 95% CI, 2.39%-3.72%): Syncope (+1.5); Anemia, defined as hemoglobin <12 g/dL (+2.5); and Renal Dysfunction, defined as glomerular filtration rate <60 mL/min (+1 point) (SARD). The PE-SARD bleeding score was calculated by summing all the components. Overall, 52.2% (95% CI, 50.29%-54.11%) of patients were classified as low bleeding-risk (score, 0 point), 35.2% (95% CI, 33.39%-37.04%) intermediate-risk (score, 1-2.5 points), and 12.6% (95% CI, 9.30%-16.56%) high-risk (score >2.5 points). Observed bleeding rates increased with increasing risk group, from 0.97% (95% CI, 0.53%-1.62%) in the low-risk to 8.93% (95% CI, 6.15%-12.44%) in the high-risk group. C-index was 0.74 (95% CI, 0.73-0.76) and Brier score 0.028 in the derivation cohort. Similar values were calculated from internal bootstrapping. Performance of the PE-SARD score was better than that observed with the VTE-BLEED, RIETE, and BACS scores, leading to a high proportion of bleeding-risk reclassification in patients who bled and those who did not. INTERPRETATION: The PE-SARD bleeding risk score is an original, user-friendly score to estimate risk of early major bleeding in patients with acute PE.
BACKGROUND: Improved prediction of the risk of early major bleeding in pulmonary embolism (PE) is needed to optimize acute management. RESEARCH QUESTION: Does a simple scoring system predict early major bleeding in acute PE patients, identifying patients with either high or low probability of early major bleeding? STUDY DESIGN AND METHODS: From a multicenter prospective registry including 2,754 patients, we performed post hoc multivariable logistic regression analysis to build a risk score to predict early (up to hospital discharge) major bleeding events. We validated the endpoint model internally, using bootstrapping in the derivation dataset by sampling with replacement for 500 iterations. Performances of this novel score were compared with that of the VTE-BLEED (Venous Thrombo-Embolism Bleed), RIETE (Registro informatizado de la enfermedad tromboembólica en España; Computerized Registry of Patients with Venous Thromboembolism), and BACS (Bleeding, Age, Cancer, and Syncope) models. RESULTS: Multivariable regression identified three predictors for the occurrence of 82 major bleeds (3.0%; 95% CI, 2.39%-3.72%): Syncope (+1.5); Anemia, defined as hemoglobin <12 g/dL (+2.5); and Renal Dysfunction, defined as glomerular filtration rate <60 mL/min (+1 point) (SARD). The PE-SARD bleeding score was calculated by summing all the components. Overall, 52.2% (95% CI, 50.29%-54.11%) of patients were classified as low bleeding-risk (score, 0 point), 35.2% (95% CI, 33.39%-37.04%) intermediate-risk (score, 1-2.5 points), and 12.6% (95% CI, 9.30%-16.56%) high-risk (score >2.5 points). Observed bleeding rates increased with increasing risk group, from 0.97% (95% CI, 0.53%-1.62%) in the low-risk to 8.93% (95% CI, 6.15%-12.44%) in the high-risk group. C-index was 0.74 (95% CI, 0.73-0.76) and Brier score 0.028 in the derivation cohort. Similar values were calculated from internal bootstrapping. Performance of the PE-SARD score was better than that observed with the VTE-BLEED, RIETE, and BACS scores, leading to a high proportion of bleeding-risk reclassification in patients who bled and those who did not. INTERPRETATION: The PE-SARD bleeding risk score is an original, user-friendly score to estimate risk of early major bleeding in patients with acute PE.
Authors: Paul L den Exter; Scott C Woller; Helia Robert-Ebadi; Camila Masias; Pierre-Emmanuel Morange; David Castelli; John-Bjarne Hansen; Geert-Jan Geersing; Deborah M Siegal; Kerstin de Wit; Frederikus A Klok Journal: J Thromb Haemost Date: 2022-06-23 Impact factor: 16.036