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A model for predicting emergency physician opinion of electrocardiogram tracing data quality.
Goebel, Mat; Busico, Luke; Snow, Greg; Bledsoe, Joseph.
Afiliación
  • Goebel M; UC San Diego School of Medicine, San Diego, CA, United States. Electronic address: mrgoebel@ucsd.edu.
  • Busico L; Intermountain Medical Center, EKG Department, Murray, UT, United States.
  • Snow G; Intermountain Office of Research, Murray, UT, United States.
  • Bledsoe J; Intermountain Medical Center, Emergency Department, Murray, UT, United States.
J Electrocardiol ; 51(4): 683-686, 2018.
Article en En | MEDLINE | ID: mdl-29997013
BACKGROUND: Limited work has established an objective measure of ECG quality that correlates with physician opinion of the study. We seek to establish a threshold of acceptable ECG data quality for the purpose of ruling out STEMI derived from emergency physician opinion. METHODS: A panel of three emergency physicians rated 240 12-Lead ECGs as being acceptable or unacceptable data quality. Each lead of the ECG had the following measurements recorded: baseline wander, QRS signal amplitude, and artifact amplitude. A lasso regression technique was used to create the model. RESULTS: The area under the curve for the model using all 36 elements is 1.0, indicating a perfect fit. A simplified model using 22 terms has an area under the curve of 0.994. CONCLUSIONS: This study demonstrated that emergency physician opinion of ECG quality for the purpose of ruling out STEMI can be predicted through a regression model.
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Médicos / Actitud del Personal de Salud / Modelos Logísticos / Electrocardiografía / Medicina de Emergencia / Exactitud de los Datos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Electrocardiol Año: 2018 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Médicos / Actitud del Personal de Salud / Modelos Logísticos / Electrocardiografía / Medicina de Emergencia / Exactitud de los Datos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: J Electrocardiol Año: 2018 Tipo del documento: Article