Search Results - "Savvidaki, E"

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  1. 1

    Gastrointestinal Disorders After Renal Transplantation by Savvidaki, E, Papachristou, E, Kazakopoulos, P, Papasotiriou, M, Vardoulaki, M, Goumenos, D.S

    Published in Transplantation proceedings (01-11-2014)
    “…Abstract Background Gastrointestinal disorders (GDs) are common in renal transplant recipients. The main cause of GDs seems to be the use of immunosuppressive…”
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    Journal Article
  2. 2

    Parameters Influencing Blood Erythropoietin Levels of Renal Transplant Recipients During the Early Post-transplantation Period by Kalantzi, M, Kalliakmani, P, Papachristou, E, Papasotiriou, M, Savvidaki, E, Zavvos, V, Karavias, D, Goumenos, D.S, Vlachojannis, J.G

    Published in Transplantation proceedings (01-11-2014)
    “…Abstract Aim Renal transplantation is accompanied by restoration of renal function and endogenous erythropoietin production. The purpose of this study was to…”
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    Journal Article
  3. 3

    Outcome of Transplantation in Renal Allograft Recipients From Cadaveric Donors With Standard and Expanded Criteria: A Single-Center Experience by Papachristou, E, Provatopoulou, S, Savvidaki, E, Kaplanis, N, Kalliakmani, P, Papasotiriou, M, Fyssa, L, Tsamantas, A, Fokaefs, E, Marangos, M, Mira, N, Maroulis, I, Karavias, D, Goumenos, D.S, Vlachogajannis, J

    Published in Transplantation proceedings (01-11-2014)
    “…Abstract Introduction The increasing number of patients requiring kidney transplantation and the lack of available organs has led to the utilization of kidneys…”
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    Journal Article
  4. 4

    Ezetimibe is effective in the treatment of persistent hyperlipidemia of renal allograft recipients by Savvidaki, E, Koukoulaki, M, Benou, A, Roumeliotou, M, Fourtounas, C, Kalliakmani, P, Papachristou, E, Vlachojannis, J G, Goumenos, D

    Published in Clinical nephrology (01-02-2011)
    “…Ezetimibe is a hypolipidemic agent acting via inhibition of cholesterol absorption from the small intestine. The effectiveness and safety of long-term…”
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    Journal Article
  5. 5

    Pollen Grain Classification using Geometrical and Textural Features by Manikis, G. C., Marias, K., Alissandrakis, E., Perrotto, L., Savvidaki, E., Vidakis, N.

    “…This study presents an image analysis framework coupled with machine learning algorithms for the classification of microscopy pollen grain images. Pollen grain…”
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    Conference Proceeding
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