BACKGROUND: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low risk of short-term mortality and who could be safely discharged early or treated entirely in an outpatient setting. OBJECTIVES: To externally validate the clinical prognostic algorithm in an independent patient sample. METHODS: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age > or = 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse > or = 110 min(-1), systolic blood pressure < 100 mmHg, oxygen saturation < 90%, and altered mental status) at baseline were defined as being at low risk. We compared 30-day overall mortality among low-risk patients, on the basis of the algorithm, between the validation sample and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. RESULTS: Overall, the algorithm classified 16.3% of patients with PE as being at low risk. Mortality at 30 days was 1.9% among low-risk patients, and did not differ between the validation sample and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. CONCLUSIONS: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low risk of short-term mortality. Patients who are at low risk according to our algorithm are potential candidates for less costly outpatient treatment.
BACKGROUND: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low risk of short-term mortality and who could be safely discharged early or treated entirely in an outpatient setting. OBJECTIVES: To externally validate the clinical prognostic algorithm in an independent patient sample. METHODS: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age > or = 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse > or = 110 min(-1), systolic blood pressure < 100 mmHg, oxygen saturation < 90%, and altered mental status) at baseline were defined as being at low risk. We compared 30-day overall mortality among low-risk patients, on the basis of the algorithm, between the validation sample and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. RESULTS: Overall, the algorithm classified 16.3% of patients with PE as being at low risk. Mortality at 30 days was 1.9% among low-risk patients, and did not differ between the validation sample and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. CONCLUSIONS: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low risk of short-term mortality. Patients who are at low risk according to our algorithm are potential candidates for less costly outpatient treatment.
Authors: Clive Kearon; Elie A Akl; Anthony J Comerota; Paolo Prandoni; Henri Bounameaux; Samuel Z Goldhaber; Michael E Nelson; Philip S Wells; Michael K Gould; Francesco Dentali; Mark Crowther; Susan R Kahn Journal: Chest Date: 2012-02 Impact factor: 9.410
Authors: Waltraud Leiss; Marie Méan; Andreas Limacher; Marc Righini; Kurt Jaeger; Hans-Jürg Beer; Joseph Osterwalder; Beat Frauchiger; Christian M Matter; Nils Kucher; Anne Angelillo-Scherrer; Jacques Cornuz; Martin Banyai; Bernhard Lämmle; Marc Husmann; Michael Egloff; Markus Aschwanden; Nicolas Rodondi; Drahomir Aujesky Journal: J Gen Intern Med Date: 2014-08-21 Impact factor: 5.128
Authors: Marie Méan; Marc Righini; Kurt Jaeger; Hans-Jürg Beer; Beat Frauchiger; Joseph Osterwalder; Nils Kucher; Bernhard Lämmle; Jacques Cornuz; Anne Angelillo-Scherrer; Nicolas Rodondi; Andreas Limacher; Sven Trelle; Christian M Matter; Marc Husmann; Martin Banyai; Markus Aschwanden; Michael Egloff; Lucia Mazzolai; Olivier Hugli; Henri Bounameaux; Drahomir Aujesky Journal: J Thromb Thrombolysis Date: 2013-11 Impact factor: 2.300
Authors: Eveline Hofmann; Nicolas Faller; Andreas Limacher; Marie Méan; Tobias Tritschler; Nicolas Rodondi; Drahomir Aujesky Journal: PLoS One Date: 2016-09-08 Impact factor: 3.240
Authors: Alexandra Mathis; Lukas Villiger; Martin F Reiner; Michael Egloff; Hans Ruedi Schmid; Simona Stivala; Andreas Limacher; Marie Mean; Drahomir Aujesky; Nicolas Rodondi; Anna Angelillo-Scherrer; Marc Righini; Daniel Staub; Markus Aschwanden; Beat Frauchiger; Joseph Osterwalder; Nils Kucher; Christian M Matter; Martin Banyai; Oliver Hugli; Juerg H Beer Journal: Sci Rep Date: 2020-02-12 Impact factor: 4.379