{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/61574"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/61574","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Association of adverse cardiovascular outcomes with weighted morphologic variability following non-ST-elevation acute coronary syndromes","abstract":"Patients who have had an acute coronary syndrome (ACS) are at a relatively high risk of having subsequent adverse cardiac events. Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes.","abstract_html":"Patients who have had an acute coronary syndrome (ACS) are at a relatively high risk of having subsequent adverse cardiac events. Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes.","abstract_has_math":false,"creators":["Sarker, Joyatee Mudra"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Collin M. Stultz."],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-22T22:21:55Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/61574","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Collin M. Stultz."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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Several electrocardiographic (ECG) measures such as heart rate variability, heart rate turbulence, deceleration capacity, T-wave altemans, and morphologic variability have been used to identify patients at an increased risk of recurrent myocardial infarctions and cardiovascular death. In this work, we develop a new ECG-based measure for patient risk stratification called weighted morphologic variability. This measure is based on assessment of beat-to-beat changes in the morphology of consecutive beats. Weighted morphologic variability identifies patients who are at more than four-fold risk for cardiovascular death, which is an improvement in ECG-based risk stratification. The body of this work suggests that prognosticating patients based on electrocardiographic measures is an effective way of identifying those at risk of adverse cardiovascular outcomes."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["Association of adverse cardiovascular outcomes with weighted morphologic variability following non-ST-elevation acute coronary syndromes"]}]}],"canonical_facts":{"dc:contributor.advisor":["Collin M. Stultz."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:creator":["Sarker, Joyatee Mudra"],"dc:date.accessioned":["2011-03-07T15:17:23Z"],"dc:date.available":["2011-03-07T15:17:23Z"],"dc:date.issued":["2010"],"dc:description":["Thesis (M. 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