The original and simplified Wells rules and age‐adjusted D‐dimer testing to rule out pulmonary embolism: an individual patient data meta‐analysis
暂无分享,去创建一个
P. Bossuyt | H. Büller | F. Klok | M. Huisman | P. D. den Exter | N. Es | N. Kraaijpoel | I. Mos | J. Galipienzo | P. L. Exter | P. Bossuyt
[1] P. Bossuyt,et al. Wells Rule and d-Dimer Testing to Rule Out Pulmonary Embolism , 2016, Annals of Internal Medicine.
[2] A. Hoes,et al. Diagnostic prediction models for suspected pulmonary embolism: systematic review and independent external validation in primary care , 2015, BMJ : British Medical Journal.
[3] Jose Luis Zamorano,et al. The Task Force for the Diagnosis and Management of Acute Pulmonary Embolism of the European Society of Cardiology (ESC) Endorsed by the European Respiratory Society (ERS) , 2014 .
[4] H. Büller,et al. Diagnostic outcome management study in patients with clinically suspected recurrent acute pulmonary embolism with a structured algorithm. , 2014, Thrombosis research.
[5] O. Rutschmann,et al. Age-adjusted D-dimer cutoff levels to rule out pulmonary embolism: the ADJUST-PE study. , 2014, JAMA.
[6] Jeroen J. Bax,et al. ESC Guidelines on the diagnosis and management of acute pulmonary embolism , 2014 .
[7] Hendrik Koffijberg,et al. Individual Participant Data Meta-Analysis for a Binary Outcome: One-Stage or Two-Stage? , 2013, PloS one.
[8] Martha Sajatovic,et al. Clinical Prediction Models , 2013 .
[9] J. Galipienzo,et al. Effectiveness of a diagnostic algorithm combining clinical probability, D-dimer testing, and computed tomography in patients with suspected pulmonary embolism in an emergency department. , 2012, Romanian journal of internal medicine = Revue roumaine de medecine interne.
[10] H. Büller,et al. The combination of four different clinical decision rules and an age-adjusted D-dimer cut-off increases the number of patients in whom acute pulmonary embolism can safely be excluded , 2011, Thrombosis and Haemostasis.
[11] Pieter W Kamphuisen,et al. Performance of 4 Clinical Decision Rules in the Diagnostic Management of Acute Pulmonary Embolism , 2011, Annals of Internal Medicine.
[12] Lisa Moores,et al. Simplification of the pulmonary embolism severity index for prognostication in patients with acute symptomatic pulmonary embolism. , 2010, Archives of internal medicine.
[13] H. Büller,et al. Validity and clinical utility of the simplified Wells rule for assessing clinical probability for the exclusion of pulmonary embolism , 2008, Thrombosis and Haemostasis.
[14] Arnaud Perrier,et al. Simplification of the revised Geneva score for assessing clinical probability of pulmonary embolism. , 2008, Archives of internal medicine.
[15] Piotr Pruszczyk,et al. Guidelines on the Diagnosis and Management of Acute Pulmonary Embolism , 2008 .
[16] Patrick M Bossuyt,et al. Further validation and simplification of the Wells clinical decision rule in pulmonary embolism , 2007, Thrombosis and Haemostasis.
[17] R. W. Niessen,et al. Simple and safe exclusion of pulmonary embolism in outpatients using quantitative D-dimer and Wells’ simplified decision rule , 2006, Thrombosis and Haemostasis.
[18] T. Stijnen,et al. Review: a gentle introduction to imputation of missing values. , 2006, Journal of clinical epidemiology.
[19] Pieter W Kamphuisen,et al. Effectiveness of managing suspected pulmonary embolism using an algorithm combining clinical probability, D-dimer testing, and computed tomography. , 2006, JAMA.
[20] Gerd Gigerenzer,et al. Fast and frugal heuristics in medical decision making , 2005 .
[21] M Gent,et al. Derivation of a Simple Clinical Model to Categorize Patients Probability of Pulmonary Embolism: Increasing the Models Utility with the SimpliRED D-dimer , 2000, Thrombosis and Haemostasis.
[22] S. le Cessie,et al. Predictive value of statistical models. , 1990, Statistics in medicine.
[23] E. DeLong,et al. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.
[24] R. Dawes. Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .
[25] D. Rubin. INFERENCE AND MISSING DATA , 1975 .