Improving the Diagnosis of Acute Heart Failure Using a Validated Prediction Model

被引:56
作者
Steinhart, Brian [1 ,4 ]
Thorpe, Kevin E. [3 ,9 ]
Bayoumi, Ahmed M. [1 ,3 ,5 ,10 ]
Moe, Gordon [1 ,3 ,6 ]
Januzzi, James L., Jr. [11 ,12 ]
Mazer, C. David [2 ,3 ,7 ,8 ]
机构
[1] St Michaels Hosp, Dept Med, Toronto, ON M5B 1W8, Canada
[2] St Michaels Hosp, Dept Anesthesia & Crit Care Med, Toronto, ON M5B 1W8, Canada
[3] St Michaels Hosp, Keenan Res Ctr, Li Ka Shing Knowledge Inst, Toronto, ON M5B 1W8, Canada
[4] Univ Toronto, Dept Med, Div Emergency Med, Toronto, ON, Canada
[5] Univ Toronto, Div Gen Med, Toronto, ON, Canada
[6] Univ Toronto, Div Cardiol, Toronto, ON, Canada
[7] Univ Toronto, Fac Med, Dept Anesthesia, Toronto, ON, Canada
[8] Univ Toronto, Fac Med, Dept Physiol, Toronto, ON, Canada
[9] Univ Toronto, Fac Med, Dalla Lana Sch Publ Hlth, Toronto, ON, Canada
[10] Univ Toronto, Fac Med, Dept Hlth Policy Management & Evaluat, Toronto, ON, Canada
[11] Harvard Univ, Sch Med, Dept Med, Boston, MA USA
[12] Massachusetts Gen Hosp, Dept Med, Boston, MA 02114 USA
关键词
acute heart failure; diagnosis; natriuretic peptide; prediction model; Bayesian theorem; PULMONARY-EMBOLISM; NATRIURETIC PEPTIDE; EMERGENCY DIAGNOSIS; MEDICAL LITERATURE; BIOCHEMICAL SCORE; USERS GUIDES; DYSPNEA; BNP; GUIDELINES; DERIVATION;
D O I
10.1016/j.jacc.2009.05.065
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives We sought to derive and validate a prediction model by using N-terminal pro-B-type natriuretic peptide (NT-proBNP) and clinical variables to improve the diagnosis of acute heart failure (AHF). Background The optimal way of using natriuretic peptides to enhance the diagnosis of AHF remains uncertain. Methods Physician estimates of probability of AHF in 500 patients treated in the emergency department from the multicenter IMPROVE CHF (Improved Management of Patients With Congestive Heart Failure) trial recruited between December 2004 and December 2005 were classified into low (0% to 20%), intermediate (21% to 79%), or high (80% to 100%) probability for AHF and then compared with the blinded adjudicated AHF diagnosis. Likelihood ratios were calculated and multiple logistic regression incorporated covariates into an AHF prediction model that was validated internally by the use of bootstrapping and externally by applying the model to another 573 patients from the separate PRIDE (N-Terminal Pro-BNP Investigation of Dyspnea in the Emergency Department) study of the use of NT-proBNP in patients with dyspnea. Results Likelihood ratios for AHF with NT-proBNP were 0.11 (95% confidence interval [CI]: 0.06 to 0.19) for cut- point values < 300 pg/ml; increasing to 3.43 (95% CI: 2.34 to 5.03) for values 2,700 to 8,099 pg/ml, and 12.80 (95% CI: 5.21 to 31.45) for values >= 8,100 pg/ml. Variables used to predict AHF were age, pre-test probability, and log NT-proBNP. When applied to the external data by use of its adjudicated final diagnosis as the gold standard, the model appropriately reclassified 44% of patients by intermediate clinical probability to either low or high probability of AHF with negligible (< 2%) inappropriate redirection. Conclusions A diagnostic prediction model for AHF that incorporates both clinical assessment and NT-proBNP has been derived and validated and has excellent diagnostic accuracy, especially in cases with indeterminate likelihood for AHF. (J Am Coll Cardiol 2009; 54: 1515-21) (C) 2009 by the American College of Cardiology Foundation
引用
收藏
页码:1515 / 1521
页数:7
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