Accuracy of combined EEG parameters in prediction the depth of anesthesia
المؤلفون المشاركون
Arefian, Nur Muhammad
Seddighi, Amir Saied
Seddighi, Afsoun
Zali, Ali Reza
المصدر
Iranian Red Crescent Medical Journal
العدد
المجلد 14، العدد 12 (31 ديسمبر/كانون الأول 2012)16ص.
الناشر
تاريخ النشر
2012-12-31
دولة النشر
الإمارات العربية المتحدة
عدد الصفحات
16
التخصصات الرئيسية
الموضوعات
الملخص EN
Background : The importance of proper qualitative evaluation of EEG parameters during surgery has been recognized since many years.
Although none of the characteristics based on the frequency, entropy, and Bi spectral characteristics have been regarded as a good predictor for detection of the depth of anesthesia alone.
So it seems necessary to study multiple characteristics together. Objectives : In this study we tried to introduce the best combination of the mentioned characteristics. Materials and Methods : EEG data of 64 patients undergoing general anesthesia with the same anesthesia protocol (total intravenous anesthesia) were recorded in all anesthetic stages in Shohada Tajrish Hospital.
Quantitative EEG characteristics are classified into 4 categories : time, frequency, bi spectral and entropy based characteristics.
Their sensitivity, specificity and accuracy in determination of the depth of anesthesia are yielded by comparison with recorded reference signal in awake, light anesthesia, deep anesthesia and brain death patients.
Then, with combining 2, 3, 4 and 5 of characteristics and using coded algorithm we determined the error degree and introduced the combination yielding the least error. Results : Fifteen vectors (of dimension two to five) which yielded the best results were introduced.
Vectors combined of entropy based characteristics obtained 100% specificity and sensitivity during all 4 stages. Conclusions : The combination entropy based characteristics had high accuracy in predicting the depth of anesthesia.
Reevaluation of classic indices cortical status index and BIS seems necessary.
The next step is to find a system to simplify the evaluation of this information for technicians.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Arefian, Nur Muhammad& Seddighi, Amir Saied& Seddighi, Afsoun& Zali, Ali Reza. 2012. Accuracy of combined EEG parameters in prediction the depth of anesthesia. Iranian Red Crescent Medical Journal،Vol. 14, no. 12.
https://search.emarefa.net/detail/BIM-310925
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Arefian, Nur Muhammad…[et al.]. Accuracy of combined EEG parameters in prediction the depth of anesthesia. Iranian Red Crescent Medical Journal Vol. 14, no. 12 (Dec. 2012).
https://search.emarefa.net/detail/BIM-310925
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Arefian, Nur Muhammad& Seddighi, Amir Saied& Seddighi, Afsoun& Zali, Ali Reza. Accuracy of combined EEG parameters in prediction the depth of anesthesia. Iranian Red Crescent Medical Journal. 2012. Vol. 14, no. 12.
https://search.emarefa.net/detail/BIM-310925
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references.
رقم السجل
BIM-310925
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر