Article

The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making

Cardiovascular Division, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, USA.
JAMA The Journal of the American Medical Association (Impact Factor: 30.39). 08/2000; 284(7):835-42.
Source: PubMed

ABSTRACT Patients with unstable angina/non-ST-segment elevation myocardial infarction (MI) (UA/NSTEMI) present with a wide spectrum of risk for death and cardiac ischemic events.
To develop a simple risk score that has broad applicability, is easily calculated at patient presentation, does not require a computer, and identifies patients with different responses to treatments for UA/NSTEMI.
Two phase 3, international, randomized, double-blind trials (the Thrombolysis in Myocardial Infarction [TIMI] 11B trial [August 1996-March 1998] and the Efficacy and Safety of Subcutaneous Enoxaparin in Unstable Angina and Non-Q-Wave MI trial [ESSENCE; October 1994-May 1996]). A total of 1957 patients with UA/NSTEMI were assigned to receive unfractionated heparin (test cohort) and 1953 to receive enoxaparin in TIMI 11B; 1564 and 1607 were assigned respectively in ESSENCE. The 3 validation cohorts were the unfractionated heparin group from ESSENCE and both enoxaparin groups.
The TIMI risk score was derived in the test cohort by selection of independent prognostic variables using multivariate logistic regression, assignment of value of 1 when a factor was present and 0 when it was absent, and summing the number of factors present to categorize patients into risk strata. Relative differences in response to therapeutic interventions were determined by comparing the slopes of the rates of events with increasing score in treatment groups and by testing for an interaction between risk score and treatment. Outcomes were TIMI risk score for developing at least 1 component of the primary end point (all-cause mortality, new or recurrent MI, or severe recurrent ischemia requiring urgent revascularization) through 14 days after randomization.
The 7 TIMI risk score predictor variables were age 65 years or older, at least 3 risk factors for coronary artery disease, prior coronary stenosis of 50% or more, ST-segment deviation on electrocardiogram at presentation, at least 2 anginal events in prior 24 hours, use of aspirin in prior 7 days, and elevated serum cardiac markers. Event rates increased significantly as the TIMI risk score increased in the test cohort in TIMI 11B: 4.7% for a score of 0/1; 8.3% for 2; 13. 2% for 3; 19.9% for 4; 26.2% for 5; and 40.9% for 6/7 (P<.001 by chi(2) for trend). The pattern of increasing event rates with increasing TIMI risk score was confirmed in all 3 validation groups (P<.001). The slope of the increase in event rates with increasing numbers of risk factors was significantly lower in the enoxaparin groups in both TIMI 11B (P =.01) and ESSENCE (P =.03) and there was a significant interaction between TIMI risk score and treatment (P =. 02).
In patients with UA/NSTEMI, the TIMI risk score is a simple prognostication scheme that categorizes a patient's risk of death and ischemic events and provides a basis for therapeutic decision making. JAMA. 2000;284:835-842

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    • "Rapid and accurate risk stratification of chest pain patients in the emergency department (ED) plays an important role in guiding appropriate disposition and early intervention so as to rapidly identify those with high risk of adverse coronary events. A conventional risk score for potential acute coronary syndromes (ACS) is the thrombolysis in myocardial infarction (TIMI) score [1]. The TIMI score was suggested to be a useful tool in the ED setting [2] [3]. "
    International Journal of Cardiology 12/2014; 177(3):1095–1097. DOI:10.1016/j.ijcard.2014.09.199 · 6.18 Impact Factor
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    • "In this observational cohort study of ED patients with chest pain, the 12-lead ECG combined with HRV and vital signs were found to strongly associate with acute cardiac complications within 72 h. A novel scoring method ESS has been proposed to integrate multiple sources of predictors for risk stratification, which showed superior performance compared with several existing methods such as TIMI [5], MEWS [6], and an intelligent scoring method DIST [14]. As illustrated in Fig. 5, ESS was the best performer in accurately identifying both high risk patients and low risk patients. "
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    ABSTRACT: Fast and accurate risk stratification is essential in the emergency department (ED) as it allows clinicians to identify chest pain patients who are at high risk of cardiac complications and require intensive monitoring and early intervention. In this paper, we present a novel intelligent scoring system using heart rate variability, 12-lead electrocardiogram (ECG), and vital signs where a hybrid sampling-based ensemble learning strategy is proposed to handle data imbalance. The experiments were conducted on a dataset consisting of 564 chest pain patients recruited at the ED of a tertiary hospital. The proposed ensemble-based scoring system was compared with established scoring methods such as the modified early warning score and the thrombolysis in myocardial infarction score, and showed its effectiveness in predicting acute cardiac complications within 72 h in terms of the receiver operation characteristic analysis.
    IEEE Journal of Biomedical and Health Informatics 11/2014; 18(6):1894-1902. DOI:10.1109/JBHI.2014.2303481 · 1.98 Impact Factor
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    • "Various systems exist for stratifying the risk of acute coronary syndromes (ACS) [4-6]. The thrombolysis in myocardial infarction (TIMI) [5] score and the Global Registry of Acute Coronary Events (GRACE) [6] score were developed to predict the risk of death, reinfarction and revascularization. TIMI and GRACE scores have been validated on an unselected population of chest pain patients at the ED for predicting adverse events. "
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    ABSTRACT: Background The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE) using clinical signs and heart rate variability. Methods A total of 702 chest pain patients at the Emergency Department (ED) of a tertiary hospital in Singapore were included in this study. The recruited patients were at least 30 years of age and who presented to the ED with a primary complaint of non-traumatic chest pain. The primary outcome was a composite of MACE such as death and cardiac arrest within 72 h of arrival at the ED. For each patient, eight clinical signs such as blood pressure and temperature were measured, and a 5-min ECG was recorded to derive heart rate variability parameters. A random forest-based novel method was developed to select the most relevant variables. A geometric distance-based machine learning scoring system was then implemented to derive a risk score from 0 to 100. Results Out of 702 patients, 29 (4.1%) met the primary outcome. We selected the 3 most relevant variables for predicting MACE, which were systolic blood pressure, the mean RR interval and the mean instantaneous heart rate. The scoring system with these 3 variables produced an area under the curve (AUC) of 0.812, and a cutoff score of 43 gave a sensitivity of 82.8% and specificity of 63.4%, while the scoring system with all the 23 variables had an AUC of 0.736, and a cutoff score of 49 gave a sensitivity of 72.4% and specificity of 63.0%. Conventional thrombolysis in myocardial infarction score and the modified early warning score achieved AUC values of 0.637 and 0.622, respectively. Conclusions It is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h. We conclude that more predictors do not necessarily guarantee better prediction results. Furthermore, machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.
    BMC Medical Informatics and Decision Making 08/2014; 14(1):75. DOI:10.1186/1472-6947-14-75 · 1.50 Impact Factor
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