2.50
Hdl Handle:
http://hdl.handle.net/10755/166248
Category:
Abstract
Type:
Presentation
Title:
Mortality Probability Model in Patients with Acute Myocardial Infarction
Author(s):
Rosenow, Doris
Author Details:
Doris Rosenow, PhD, Assistant Professor, University of Texas Medical Branch-Galveston School of Nursing, Galveston, Texas, USA, (updated February 2015) email: drosenow1@alamo.edu
Abstract:
Specific Aims: Among the elderly, cardiovascular disease now ranks as the leading cause of disability and death. Patients who suffer an acute myocardial infarction (AMI) are a very heterogeneous group whose prognosis after an AMI differs widely. Studies have shown that approxiinately 10% to 29% of hospitalized patients after AMI will not live to be discharged. Therefore, the specific aims of this study were to: (1) determine factors predictive of hospital mortality in patients with AMI; and (2) examine the usefulness of three severity of illness indices. Research Question: What are the predictive factors of hospital mortality in patients with acute myocardial infarction? Methodology: Data was collected by a retrospective chart review. A pilot study of 110 charts of men and women diagnosed with AMI who had expired in a Southwestern University Medical were reviewed. The three severity of illness indices that were used for data collection were: (1) Funk & Pooley-Richards (1994) Coronary Prognostic Indices which included five variables [history of AMI, older age, lower LVEF, and a higher number of occluded coronary vessels]; (2) Dubois, Pierard, Albert, et al., (1988) Prognostic Index which included three subgroups of patients [high risk, intermediate risk, and good prognosis]; and (3) Gustafson, Fryback, Rose, et al., (1986) Ischemic Heart Disease Index (IHDI) which included 10 categones; time from onset of symptoms, duration of pain, age, previous heart disease, preexisting second organ disease, family and social history, electrical instability, amount of myocardial damage, presence of acute MI, and electrical complications. Data Analysis: A logistic regression analysis will be used to determine the results of the study. At present, the data analysis is not completed. Therefore, the findings will be presented at the conference, which will include a mortality probability model for patients at high risk for mortality after an AMI. Implications: Clinical assessment of those patients for high risk mortality after an AMI should lead to closer monitoring, selective and more focused intervention regimes which would provide more timely management decisions.
Repository Posting Date:
27-Oct-2011
Date of Publication:
27-Oct-2011
Conference Date:
Feb 29 - Mar 2, 1996
Conference Host:
Southern Nursing Research Society
Note:
This is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.

Full metadata record

DC FieldValue Language
dc.type.categoryAbstracten_US
dc.typePresentationen_GB
dc.titleMortality Probability Model in Patients with Acute Myocardial Infarctionen_GB
dc.contributor.authorRosenow, Dorisen_US
dc.author.detailsDoris Rosenow, PhD, Assistant Professor, University of Texas Medical Branch-Galveston School of Nursing, Galveston, Texas, USA, (updated February 2015) email: drosenow1@alamo.eduen_US
dc.identifier.urihttp://hdl.handle.net/10755/166248-
dc.description.abstractSpecific Aims: Among the elderly, cardiovascular disease now ranks as the leading cause of disability and death. Patients who suffer an acute myocardial infarction (AMI) are a very heterogeneous group whose prognosis after an AMI differs widely. Studies have shown that approxiinately 10% to 29% of hospitalized patients after AMI will not live to be discharged. Therefore, the specific aims of this study were to: (1) determine factors predictive of hospital mortality in patients with AMI; and (2) examine the usefulness of three severity of illness indices. Research Question: What are the predictive factors of hospital mortality in patients with acute myocardial infarction? Methodology: Data was collected by a retrospective chart review. A pilot study of 110 charts of men and women diagnosed with AMI who had expired in a Southwestern University Medical were reviewed. The three severity of illness indices that were used for data collection were: (1) Funk & Pooley-Richards (1994) Coronary Prognostic Indices which included five variables [history of AMI, older age, lower LVEF, and a higher number of occluded coronary vessels]; (2) Dubois, Pierard, Albert, et al., (1988) Prognostic Index which included three subgroups of patients [high risk, intermediate risk, and good prognosis]; and (3) Gustafson, Fryback, Rose, et al., (1986) Ischemic Heart Disease Index (IHDI) which included 10 categones; time from onset of symptoms, duration of pain, age, previous heart disease, preexisting second organ disease, family and social history, electrical instability, amount of myocardial damage, presence of acute MI, and electrical complications. Data Analysis: A logistic regression analysis will be used to determine the results of the study. At present, the data analysis is not completed. Therefore, the findings will be presented at the conference, which will include a mortality probability model for patients at high risk for mortality after an AMI. Implications: Clinical assessment of those patients for high risk mortality after an AMI should lead to closer monitoring, selective and more focused intervention regimes which would provide more timely management decisions.en_GB
dc.date.available2011-10-27T14:43:17Z-
dc.date.issued2011-10-27en_GB
dc.date.accessioned2011-10-27T14:43:17Z-
dc.conference.dateFeb 29 - Mar 2, 1996en_US
dc.conference.hostSouthern Nursing Research Societyen_US
dc.description.noteThis is an abstract-only submission. If the author has submitted a full-text item based on this abstract, you may find it by browsing the Virginia Henderson Global Nursing e-Repository by author. If author contact information is available in this abstract, please feel free to contact him or her with your queries regarding this submission. Alternatively, please contact the conference host, journal, or publisher (according to the circumstance) for further details regarding this item. If a citation is listed in this record, the item has been published and is available via open-access avenues or a journal/database subscription. Contact your library for assistance in obtaining the as-published article.-
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