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Comparing the Predictive Power of Preoperative Risk Assessment Tools to Best Predict Major Adverse Cardiac Events in Kidney Transplant Patients
المؤلفون المشاركون
Greenstein, Stuart
Dunn, Colin P.
Emeasoba, Emmanuel U.
Holtzman, Ari J.
Hung, Michael
Kaminetsky, Joshua
Alani, Omar
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-6، 6ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-03-20
دولة النشر
مصر
عدد الصفحات
6
التخصصات الرئيسية
الملخص EN
Background.
Patients undergoing kidney transplantation have increased risk of adverse cardiovascular events due to histories of hypertension, end-stage renal disease, and dialysis.
As such, they are especially in need of accurate preoperative risk assessment.
Methods.
We compared three different risk assessment models for their ability to predict major adverse cardiac events at 30 days and 1 year after transplant.
These were the PORT model, the RCRI model, and the Gupta model.
We used a method based on generalized U-statistics to determine statistically significant improvements in the area under the receiver operator curve (AUC), based on a common major adverse cardiac event (MACE) definition.
For the top-performing model, we added new covariates into multivariable logistic regression in an attempt to create further improvement in the AUC.
Results.
The AUCs for MACE at 30 days and 1 year were 0.645 and 0.650 (PORT), 0.633 and 0.661 (RCRI), and finally 0.489 and 0.557 (Gupta), respectively.
The PORT model performed significantly better than the Gupta model at 1 year (p=0.039).
When the sensitivity was set to 95%, PORT had a significantly higher specificity of 0.227 compared to RCRI’s 0.071 (p=0.009) and Gupta’s 0.08 (p=0.017).
Our additional covariates increased the receiver operator curve from 0.664 to 0.703, but this did not reach statistical significance (p=0.278).
Conclusions.
Of the three calculators, PORT performed best when the sensitivity was set at a clinically relevant level.
This is likely due to the unique variables the PORT model uses, which are specific to transplant patients.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Dunn, Colin P.& Emeasoba, Emmanuel U.& Holtzman, Ari J.& Hung, Michael& Kaminetsky, Joshua& Alani, Omar…[et al.]. 2019. Comparing the Predictive Power of Preoperative Risk Assessment Tools to Best Predict Major Adverse Cardiac Events in Kidney Transplant Patients. Surgery Research and Practice،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1210783
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Dunn, Colin P.…[et al.]. Comparing the Predictive Power of Preoperative Risk Assessment Tools to Best Predict Major Adverse Cardiac Events in Kidney Transplant Patients. Surgery Research and Practice No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1210783
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Dunn, Colin P.& Emeasoba, Emmanuel U.& Holtzman, Ari J.& Hung, Michael& Kaminetsky, Joshua& Alani, Omar…[et al.]. Comparing the Predictive Power of Preoperative Risk Assessment Tools to Best Predict Major Adverse Cardiac Events in Kidney Transplant Patients. Surgery Research and Practice. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1210783
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1210783
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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