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Omar H. Dabbous

Researcher at University of Massachusetts Medical School

Publications -  54
Citations -  10252

Omar H. Dabbous is an academic researcher from University of Massachusetts Medical School. The author has contributed to research in topics: Myocardial infarction & Acute coronary syndrome. The author has an hindex of 28, co-authored 46 publications receiving 9456 citations.

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Predictors of hospital mortality in the global registry of acute coronary events.

TL;DR: Across the entire spectrum of ACS and in general clinical practice, this model provides excellent ability to assess the risk for death and can be used as a simple nomogram to estimate risk in individual patients.
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A validated prediction model for all forms of acute coronary syndrome:estimating the risk of 6-month postdischarge death in an international registry

TL;DR: The GRACE 6-month postdischarge prediction model is a simple, robust tool for predicting mortality in patients with ACS and Clinicians may find it simple to use and applicable to clinical practice.
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Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE)

TL;DR: This risk prediction tool uses readily identifiable variables to provide robust prediction of the cumulative six month risk of death or myocardial infarction and can guide patient triage and management across the spectrum of patients with acute coronary syndrome.

Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome

TL;DR: In this article, the authors developed a clinical risk prediction tool for estimating the cumulative six month risk of death and death or myocardial infarction to facilitate triage and management of patients with acute coronary syndrome.
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Management of acute coronary syndromes. Variations in practice and outcome. Findings from the Global Registry of Acute Coronary Events (GRACE)

TL;DR: The GRACE study reveals substantial differences in the management of patients based on hospital type and geographical location and will determine whether such variations translate into differences in longer term outcomes.