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    The 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.

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    Authors
    Kellett, John
    Rasool, Shahzeb
    Affiliation
    Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland. jgkellett@eircom.net
    Issue Date
    2011-08
    MeSH
    Acute Disease
    Age Factors
    Aged
    Body Surface Potential Mapping
    Female
    Follow-Up Studies
    Hospital Mortality
    Humans
    Ireland
    Male
    Pilot Projects
    Predictive Value of Tests
    Prognosis
    Retrospective Studies
    Risk Factors
    Severity of Illness Index
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    Citation
    The 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.
    Journal
    European journal of internal medicine
    URI
    http://hdl.handle.net/10147/205011
    DOI
    10.1016/j.ejim.2011.01.013
    PubMed ID
    21767758
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0953620511000185
    Abstract
    ECG 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).
    A 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.
    Of 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%.
    ECG-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.
    Item Type
    Article
    Language
    en
    ISSN
    1879-0828
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ejim.2011.01.013
    Scopus Count
    Collections
    Nenagh General Hospital

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