Development and initial validation of a simple clinical decision tool to predict the presence of heart failure in primary care: the MICE (Male, Infarction, Crepitations, Edema) rule

Abstract

Aims: Diagnosis of heart failure in primary care is often inaccurate, and access to and use of echocardiography is suboptimal. This study aimed to develop and provisionally validate a clinical prediction rule to optimize referral for echocardiography of people identified in primary care with suspected heart failure.

Methods and results: A systematic review identified studies of diagnosis of heart failure set in primary care. The individual patient data for five of these studies were obtained. Logistic regression models to predict heart failure were developed on one of the data sets and validated on the others using area under the receiver operating characteristic curve (AUROC), and goodness-of-fit calibration plots. A model based upon four simple clinical features (Male, history of myocardial Infarction, Crepitations, Edema: MICE) and natriuretic peptide had good validity when applied to other data sets, with AUROCs between 0.84 and 0.93, and reasonable calibration. The rule performed well across the data sets, with sensitivity between 81% and 96% and specificity between 57% and 74%.

Conclusions: A simple clinical rule based upon gender, history of myocardial infarction, presence of ankle oedema, and presence of basal lung crepitations can discriminate between people with suspected heart failure who should be referred straight for echocardiography and people for whom referral should depend upon the result of a natriuretic peptide test. Prospective validation and an implementation evaluation of the rule is now warranted.