Predictors of In-Hospital Mortality Among Acute Myocardial Infarction Patients in a Large Health Care System
dc.contributor.advisor | Karan Singh | |
dc.contributor.committeeMember | Antonio Rene | |
dc.contributor.committeeMember | Sally Blakley | |
dc.creator | Zhang, Huiling | |
dc.date.accessioned | 2019-08-22T21:52:10Z | |
dc.date.available | 2019-08-22T21:52:10Z | |
dc.date.issued | 2001-07-01 | |
dc.date.submitted | 2014-05-01T06:48:05-07:00 | |
dc.description.abstract | Zhang, Huiling. Predictors of In-hospital Mortality Among Acute Myocardial Infarction Patients in a Large Health Care System. Master of Public Health, July 2000, 29 pp., 4 tables, 29 references. Background---There is increasing interest in the identification of risk predictors for in-hospital mortality due to acute myocardial infarction (AMI). To date, there has been no AMI in-hospital mortality prediction models developed using clinical database. Methods and Results---The study population consists of 4,167 AMI cases admitted to 36 hospitals in 3 states. Thirty variables were selected as candidate predictors, and 19 showed significant bivariate association with AMI in-hospital mortality. By applying multiple logistic regression and stepwise selection, 10 variables were selected for inclusion in the final prediction model: age, arrive from cardiac rehabilitation center, CPR on arrival, Killip class, AMI with comorbidities, AMI with complications, PCTA performed, beta-blockers given, ACE inhibitors given, Plavix given. Conclusion---A ten-variable in-hospital mortality prediction model for AMI patients, which includes both risk factors and beneficial treatment procedures, was developed. Chi-square goodness of fit test suggested a very good fit for the model. | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | https://hdl.handle.net/20.500.12503/29641 | |
dc.language.iso | en | |
dc.provenance.legacyDownloads | 0 | |
dc.subject | Clinical Epidemiology | |
dc.subject | Health and Medical Administration | |
dc.subject | Health Services Administration | |
dc.subject | Health Services Research | |
dc.subject | Medicine and Health Sciences | |
dc.subject | Other Public Health | |
dc.subject | Public Health | |
dc.subject | In-hospital mortality | |
dc.subject | acute myocardial infarction | |
dc.subject | patients | |
dc.subject | large health care system | |
dc.subject | AMI | |
dc.subject | mortality | |
dc.subject | prediction models | |
dc.subject | clinical database | |
dc.subject | prediction model | |
dc.subject | variables | |
dc.title | Predictors of In-Hospital Mortality Among Acute Myocardial Infarction Patients in a Large Health Care System | |
dc.type | Thesis | |
dc.type.material | text | |
thesis.degree.department | School of Public Health | |
thesis.degree.grantor | University of North Texas Health Science Center at Fort Worth | |
thesis.degree.name | Master of Public Health |