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dc.contributor.authorKellett, John
dc.contributor.authorRasool, Shahzeb
dc.date.accessioned2012-01-26T11:21:45Z
dc.date.available2012-01-26T11:21:45Z
dc.date.issued2011-08
dc.identifier.citationThe prediction of the in-hospital mortality of acutely ill medical patients by electrocardiogram (ECG) dispersion mapping compared with established risk factors and predictive scores--a pilot study. 2011, 22 (4):394-8 Eur. J. Intern. Med.en
dc.identifier.issn1879-0828
dc.identifier.pmid21767758
dc.identifier.doi10.1016/j.ejim.2011.01.013
dc.identifier.urihttp://hdl.handle.net/10147/205011
dc.description.abstractECG dispersion mapping (ECG-DM) is a novel technique that analyzes low amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI). This study compared the ability of ECG-DM to predict in-hospital mortality with traditional risk factors such as age, vital signs and co-morbid diagnoses, as well as three predictive scores: the Simple Clinical Score (SCS)--based on clinical and ECG findings, and two Medical Admission Risk System scores--one based on vital signs and laboratory data (MARS), and one only on laboratory data (LD).
dc.description.abstractA convenient sample of 455 acutely ill medical patients (mean age 69.7±14.0 years) had their vital signs, mental and functional status recorded and a 12 lead ECG, routine laboratory investigations and ECG-DM performed immediately after admission to hospital. Each patient's in-hospital course and diagnoses at death or discharge were reviewed.
dc.description.abstractOf the vital signs only oxygen saturation and respiratory rate were statistically significant predictors of death. The continuous variables that predicted death the best were: MARS, SCS, LD, white cell count and MMI. The categorical variables that predicted in-hospital mortality with highest Chi-square were: a diagnosis of stroke, SCS>=12, LD>0.10, MARS>0.09 and MMI>36%.
dc.description.abstractECG-DM may be a clinically useful predictor of in-hospital mortality. ECG-DM is inexpensive, only takes a few seconds to perform and requires no skill to interpret.
dc.language.isoenen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S0953620511000185en
dc.subject.meshAcute Disease
dc.subject.meshAge Factors
dc.subject.meshAged
dc.subject.meshBody Surface Potential Mapping
dc.subject.meshFemale
dc.subject.meshFollow-Up Studies
dc.subject.meshHospital Mortality
dc.subject.meshHumans
dc.subject.meshIreland
dc.subject.meshMale
dc.subject.meshPilot Projects
dc.subject.meshPredictive Value of Tests
dc.subject.meshPrognosis
dc.subject.meshRetrospective Studies
dc.subject.meshRisk Factors
dc.subject.meshSeverity of Illness Index
dc.titleThe prediction of the in-hospital mortality of acutely ill medical patients by electrocardiogram (ECG) dispersion mapping compared with established risk factors and predictive scores--a pilot study.en
dc.typeArticleen
dc.contributor.departmentDepartment of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.neten
dc.identifier.journalEuropean journal of internal medicineen
dc.description.provinceMunster
html.description.abstractECG dispersion mapping (ECG-DM) is a novel technique that analyzes low amplitude ECG oscillations and reports them as the myocardial micro-alternation index (MMI). This study compared the ability of ECG-DM to predict in-hospital mortality with traditional risk factors such as age, vital signs and co-morbid diagnoses, as well as three predictive scores: the Simple Clinical Score (SCS)--based on clinical and ECG findings, and two Medical Admission Risk System scores--one based on vital signs and laboratory data (MARS), and one only on laboratory data (LD).
html.description.abstractA convenient sample of 455 acutely ill medical patients (mean age 69.7±14.0 years) had their vital signs, mental and functional status recorded and a 12 lead ECG, routine laboratory investigations and ECG-DM performed immediately after admission to hospital. Each patient's in-hospital course and diagnoses at death or discharge were reviewed.
html.description.abstractOf the vital signs only oxygen saturation and respiratory rate were statistically significant predictors of death. The continuous variables that predicted death the best were: MARS, SCS, LD, white cell count and MMI. The categorical variables that predicted in-hospital mortality with highest Chi-square were: a diagnosis of stroke, SCS>=12, LD>0.10, MARS>0.09 and MMI>36%.
html.description.abstractECG-DM may be a clinically useful predictor of in-hospital mortality. ECG-DM is inexpensive, only takes a few seconds to perform and requires no skill to interpret.


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