Document Detail


Electrocardiogram characteristics prior to in-hospital cardiac arrest.
MedLine Citation:
PMID:  25236259     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Survival after in-hospital cardiac arrest (I-HCA) remains < 30 %. There is very limited literature exploring the electrocardiogram changes prior to I-HCA. The purpose of the study was to determine demographics and electrocardiographic predictors prior to I-HCA. A retrospective study was conducted among 39 cardiovascular subjects who had cardiopulmonary resuscitation from I-HCA with initial rhythms of pulseless electrical activity (PEA) and asystole. Demographics including medical history, ejection fraction, laboratory values, and medications were examined. Electrocardiogram (ECG) parameters from telemetry were studied to identify changes in heart rate, QRS duration and morphology, and time of occurrence and location of ST segment changes prior to I-HCA. Increased age was significantly associated with failure to survive to discharge (p < 0.05). Significant change was observed in heart rate including a downtrend of heart rate within 15 min prior to I-HCA (p < 0.05). There was a significant difference in heart rate and QRS duration during the last hour prior to I-HCA compared to the previous hours (p < 0.05). Inferior ECG leads showed the most significant changes in QRS morphology and ST segments prior to I-HCA (p < 0.05). Subjects with an initial rhythm of asystole demonstrated significantly greater ECG changes including QRS morphology and ST segment changes compared to the subjects with initial rhythms of PEA (p < 0.05). Diagnostic ECG trends can be identified prior to I-HCA due to PEA and asystole and can be further utilized for training a predictive machine learning model for I-HCA.
Authors:
Mina Attin; Gregory Feld; Hector Lemus; Kayvan Najarian; Sharad Shandilya; Lu Wang; Pouya Sabouriazad; Chii-Dean Lin
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-9-19
Journal Detail:
Title:  Journal of clinical monitoring and computing     Volume:  -     ISSN:  1573-2614     ISO Abbreviation:  J Clin Monit Comput     Publication Date:  2014 Sep 
Date Detail:
Created Date:  2014-9-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9806357     Medline TA:  J Clin Monit Comput     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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