کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8827042 1610662 2018 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Improving the Prediction of Mortality in the High Model for End-Stage Liver Disease Score Liver Transplant Recipient: A Role for the Left Atrial Volume Index
ترجمه فارسی عنوان
بهبود پیش بینی مرگ و میر در مدل بالا برای نمره بیماری کبد مرحله پایانی گیرنده پیوند کبد: نقش شاخص حجم جلدی چپ
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی عمل جراحی
چکیده انگلیسی
Left atrial volume index (LAVI) is an echocardiographic measurement used in assessing diastolic dysfunction, and is associated with mortality in many populations. In this retrospective cohort study including 254 patients, we investigated whether LAVI is an independent predictor of post-liver transplantation mortality using multivariable Cox regression. We found that elevated LAVI was associated with increased mortality among patients with high Model for End-Stage Liver Disease (MELD) scores, but not among those with lower MELD scores, indicating that recipients with high LAVI values and high MELD scores may represent patients at an increased risk of post-transplantation mortality. Specifically, there was a statistically significant interaction between LAVI and MELD score (P = .006) such that for patients with MELD scores ≥33, LAVI >27 mL/m2 was associated with increased mortality (hazard ratio = 2.3; 95% confidence interval, 1.04-5.20; P = .04.) We further show that the inclusion of LAVI in a multivariable model led to a statistically significant improvement in the ability to predict post-liver transplantation mortality, with an increase in the model's C-statistic from 0.68 to 0.71. The incorporation of LAVI in multivariable risk models may be useful in the selection of transplant recipients with high MELD scores, and may be helpful in decreasing the probability of futile transplantation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transplantation Proceedings - Volume 50, Issue 5, June 2018, Pages 1407-1412
نویسندگان
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