Brief Article
Copyright ©2013 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Cardiol. Jun 26, 2013; 5(6): 196-206
Published online Jun 26, 2013. doi: 10.4330/wjc.v5.i6.196
BLEED-Myocardial Infarction Score: Predicting mid-term post-discharge bleeding events
Sérgio Barra, Rui Providência, Francisca Caetano, Inês Almeida, Luís Paiva, Paulo Dinis, António Leitão Marques
Sérgio Barra, Rui Providência, Francisca Caetano, Inês Almeida, Luís Paiva, Paulo Dinis, António Leitão Marques, Cardiology Department, Coimbra’s Hospital and University Centre-General Hospital, 3041-801 S. Martinho do Bispo, Coimbra, Portugal
Rui Providência, Faculty of Medicine, University of Coimbra, 3046-853 Coimbra, Portugal
Author contributions: Barra S designed the study; Barra S and Providência R wrote the draft version of the article; Leitão Marques A co-ordinated the development of the manuscript; all authors contributed to the collection of data, reviewed the draft version, gave advice for improving the manuscript and read and approved the final version.
Correspondence to: Dr. Sérgio Barra, Cardiology Department, Coimbra’s Hospital and University Centre-General Hospital, Quinta dos Vales, 3041-801 S. Martinho do Bispo, Coimbra, Portugal. sergioncbarra@gmail.com
Telephone: +351-916-685716 Fax: +351-239-445737
Received: February 21, 2013
Revised: April 23, 2013
Accepted: May 16, 2013
Published online: June 26, 2013
Processing time: 127 Days and 13.2 Hours
Abstract

AIM: To derive and validate a score for the prediction of mid-term bleeding events following discharge for myocardial infarction (MI).

METHODS: One thousand and fifty patients admitted for MI and followed for 19.9 ± 6.7 mo were assigned to a derivation cohort. A new risk model, called BLEED-MI, was developed for predicting clinically significant bleeding events during follow-up (primary endpoint) and a composite endpoint of significant hemorrhage plus all-cause mortality (secondary endpoint), incorporating the following variables: age, diabetes mellitus, arterial hypertension, smoking habits, blood urea nitrogen, glomerular filtration rate and hemoglobin at admission, history of stroke, bleeding during hospitalization or previous major bleeding, heart failure during hospitalization and anti-thrombotic therapies prescribed at discharge. The BLEED-MI model was tested for calibration, accuracy and discrimination in the derivation sample and in a new, independent, validation cohort comprising 852 patients admitted at a later date.

RESULTS: The BLEED-MI score showed good calibration in both derivation and validation samples (Hosmer-Lemeshow test P value 0.371 and 0.444, respectively) and high accuracy within each individual patient (Brier score 0.061 and 0.067, respectively). Its discriminative performance in predicting the primary outcome was relatively high (c-statistic of 0.753 ± 0.032 in the derivation cohort and 0.718 ± 0.033 in the validation sample). Incidence of primary/secondary endpoints increased progressively with increasing BLEED-MI scores. In the validation sample, a BLEED-MI score below 2 had a negative predictive value of 98.7% (152/154) for the occurrence of a clinically significant hemorrhagic episode during follow-up and for the composite endpoint of post-discharge hemorrhage plus all-cause mortality. An accurate prediction of bleeding events was shown independently of mortality, as BLEED-MI predicted bleeding with similar efficacy in patients who did not die during follow-up: Area Under the Curve 0.703, Hosmer-Lemeshow test P value 0.547, Brier score 0.060; low-risk (BLEED-MI score 0-3) event rate: 1.2%; intermediate risk (score 4-6) event rate: 5.6%; high risk (score ≥ 7) event rate: 12.5%.

CONCLUSION: A new bedside prediction-scoring model for post-discharge mid-term bleeding has been derived and preliminarily validated. This is the first score designed to predict mid- term hemorrhagic risk in patients discharged following admission for acute MI. This model should be externally validated in larger cohorts of patients before its potential implementation.

Keywords: Myocardial infarction; Bleeding; Prediction model; Risk stratification

Core tip: Prediction of mid- to long-term clinically significant bleeding following discharge for a myocardial infarction has received scarce attention from the scientific community. The BLEED-myocardial infarction (MI) prediction model is the first score designed to predict mid-term hemorrhagic risk in these patients. Easy to use and comprising clinical and analytical items that can be collected in a few minutes, BLEED-MI showed good calibration, accuracy and discriminative performance for predicting post-discharge hemorrhagic episodes and a composite endpoint of bleeding events plus all-cause mortality. Importantly, an accurate prediction of bleeding events was shown independently of mortality. Furthermore, a progressively increasing risk of the primary and secondary endpoints was seen with increasing BLEED-MI scores and our results suggested a very high capability of the BLEED-MI rule in identifying low-risk patients. Depending on its potential external validation in larger cohorts of patients, the BLEED-MI score may eventually help tailor therapeutic decisions