OBJECTIVE: To identify patients with a low short-term risk of complications following acute pulmonary thromboembolism. PATIENTS AND METHODS: A prospective multicenter study was conducted in 8 Spanish hospitals; 681 consecutive outpatients diagnosed with pulmonary thromboembolism were enrolled. Clinically significant variables were weighted using coefficients derived from a logistic regression model in order to optimize the diagnostic performance of a clinical prediction rule to predict the following complications within 10 days of acute pulmonary thromboembolism: death, recurrent thromboembolism, and major or minor bleeding. RESULTS: Forty-three patients (6.3%) had 51 complications. These included 33 deaths, 12 major bleeding episodes, and 6 minor bleeding episodes. The clinical variables used in the prediction rule were assigned the following scores: recent major bleeding episode and cancer with metastasis, 4 points each; creatinine levels of over 2 mg/dL, 3 points; cancer without metastasis and immobility due to a recent medical condition, 2 points each; and absence of surgery in the past 2 months and an age of over 60 years, 1 point each. A risk score of 2 or less, obtained by 47.8% of patients, indicated a low short-term risk of developing complications following pulmonary thromboembolism. The area under the receiver operating characteristic curve for the prediction rule was 0.75 (95% confidence interval [CI], 0.67-0.83). For this cutoff point, sensitivity was 82.9% (95% CI, 68.7-91.5) and the likelihood ratios for a positive and negative test result were 1.63 (95% CI, 1.39-1.92), and 0.35 (95% CI, 0.18-0.69), respectively. CONCLUSIONS: Our clinical prediction rule could be useful for identifying patients with a low risk of complications in the 10 days following acute pulmonary thromboembolism. Those patients would be eligible for consideration for outpatient treatment.
OBJECTIVE: To identify patients with a low short-term risk of complications following acute pulmonary thromboembolism. PATIENTS AND METHODS: A prospective multicenter study was conducted in 8 Spanish hospitals; 681 consecutive outpatients diagnosed with pulmonary thromboembolism were enrolled. Clinically significant variables were weighted using coefficients derived from a logistic regression model in order to optimize the diagnostic performance of a clinical prediction rule to predict the following complications within 10 days of acute pulmonary thromboembolism: death, recurrent thromboembolism, and major or minor bleeding. RESULTS: Forty-three patients (6.3%) had 51 complications. These included 33 deaths, 12 major bleeding episodes, and 6 minor bleeding episodes. The clinical variables used in the prediction rule were assigned the following scores: recent major bleeding episode and cancer with metastasis, 4 points each; creatinine levels of over 2 mg/dL, 3 points; cancer without metastasis and immobility due to a recent medical condition, 2 points each; and absence of surgery in the past 2 months and an age of over 60 years, 1 point each. A risk score of 2 or less, obtained by 47.8% of patients, indicated a low short-term risk of developing complications following pulmonary thromboembolism. The area under the receiver operating characteristic curve for the prediction rule was 0.75 (95% confidence interval [CI], 0.67-0.83). For this cutoff point, sensitivity was 82.9% (95% CI, 68.7-91.5) and the likelihood ratios for a positive and negative test result were 1.63 (95% CI, 1.39-1.92), and 0.35 (95% CI, 0.18-0.69), respectively. CONCLUSIONS: Our clinical prediction rule could be useful for identifying patients with a low risk of complications in the 10 days following acute pulmonary thromboembolism. Those patients would be eligible for consideration for 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: A Carmona-Bayonas; M Sánchez-Cánovas; J M Plasencia; A Custodio; E Martínez de Castro; J A Virizuela; F Ayala de la Peña; P Jiménez-Fonseca Journal: Clin Transl Oncol Date: 2017-06-07 Impact factor: 3.405
Authors: Jean-Pierre Iskandar; Essa Hariri; Christopher Kanaan; Nicholas Kassis; Hayaan Kamran; Denise Sese; Colin Wright; Mark Marinescu; Scott J Cameron Journal: J Thromb Thrombolysis Date: 2021-09-29 Impact factor: 2.300
Authors: Fahad M Al-Hameed; Hasan M Al-Dorzi; Abdulkarim M Al-Momen; Farjah H Algahtani; Hazzaa A Al-Zahrani; Khalid A Al-Saleh; Mohammed A Al-Sheef; Tarek M Owaidah; Waleed Alhazzani; Ignacio Neumann; Wojtek Wiercioch; Jan Brozek; Holger Schunemann; Elie A Akl Journal: Saudi Med J Date: 2015-08 Impact factor: 1.484