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Cardiovascular Effects Of Metabolic Syndrome After Transplantation: Convergence Of Obesity And Transplant-Related Factors., Kristen Sgambat, Sarah Clauss, Asha Moudgil 2018 George Washington University

Cardiovascular Effects Of Metabolic Syndrome After Transplantation: Convergence Of Obesity And Transplant-Related Factors., Kristen Sgambat, Sarah Clauss, Asha Moudgil

Pediatrics Faculty Publications

Children are at increased risk of developing metabolic syndrome (MS) after kidney transplantation, which contributes to long-term cardiovascular (CV) morbidities and decline in allograft function. While MS in the general population occurs due to excess caloric intake and physical inactivity, additional chronic kidney disease and transplant-related factors contribute to the development of MS in transplant recipients. Despite its significant health consequences, the interplay of the individual components in CV morbidity in pediatric transplant recipients is not well understood. Additionally, the optimal methods to detect early CV dysfunction are not well defined in this unique population. The quest to establish clear ...


Fluid Balance Concepts In Medicine: Principles And Practice., Maria-Eleni Roumelioti, Robert H Glew, Zeid J Khitan, Helbert Rondon-Berrios, Christos P Argyropoulos, Deepak Malhotra, Dominic S Raj, Emmanuel I Agaba, Mark Rohrscheib, Glen H Murata, Joseph I Shapiro, Antonios H Tzamaloukas 2018 George Washington University

Fluid Balance Concepts In Medicine: Principles And Practice., Maria-Eleni Roumelioti, Robert H Glew, Zeid J Khitan, Helbert Rondon-Berrios, Christos P Argyropoulos, Deepak Malhotra, Dominic S Raj, Emmanuel I Agaba, Mark Rohrscheib, Glen H Murata, Joseph I Shapiro, Antonios H Tzamaloukas

Medicine Faculty Publications

The regulation of body fluid balance is a key concern in health and disease and comprises three concepts. The first concept pertains to the relationship between total body water (TBW) and total effective solute and is expressed in terms of the tonicity of the body fluids. Disturbances in tonicity are the main factor responsible for changes in cell volume, which can critically affect brain cell function and survival. Solutes distributed almost exclusively in the extracellular compartment (mainly sodium salts) and in the intracellular compartment (mainly potassium salts) contribute to tonicity, while solutes distributed in TBW have no effect on tonicity ...


Physical Therapy Considerations For Chronic Kidney Disease And Secondary Sarcopenia, Michael O. Harris-Love, Haniel J. Hernandez, Gideon Obamwonyi 2018 George Washington University

Physical Therapy Considerations For Chronic Kidney Disease And Secondary Sarcopenia, Michael O. Harris-Love, Haniel J. Hernandez, Gideon Obamwonyi

Exercise and Nutrition Sciences Faculty Publications

Chronic kidney disease (CKD) is a progressive condition that may negatively affect musculoskeletal health. These comorbidities may include malnutrition, osteoporosis, and decreased lean body mass. Secondary sarcopenia due to CKD may be associated with mobility limitations and elevated fall risk. Physical therapists are well-positioned among the health care team to screen for secondary sarcopenia in those with CKD and for the treatment of musculoskeletal comorbid conditions that may affect functional performance. Given the consequences of both low muscle mass and low bone mineral density, appropriate and timely physical therapy is important for fall risk assessment and intervention to minimize the ...


Percutaneous Externally Assembled Laparoscopic (Peal) Donor Nephrectomy: A Cohort Pain Comparison, Tyler Miskin, Isaac Kelly, Matthew Pierce, Samuel Abourbih, Duane D. Baldwin 2017 Loma Linda University Health Department of Urology

Percutaneous Externally Assembled Laparoscopic (Peal) Donor Nephrectomy: A Cohort Pain Comparison, Tyler Miskin, Isaac Kelly, Matthew Pierce, Samuel Abourbih, Duane D. Baldwin

Loma Linda University Student Journal

Donor nephrectomies can be technically demanding. Donors also may not be fully psychologically prepared for their post-operative pain or cosmetic outcome. A novel Percutaneous Externally Assembled Laparoscopic (PEAL) paradigm was developed to decrease incisional pain and laparoscopic scars. The aim of this study is to compare the post-operative outcomes between donor nephrectomies performed with and without the PEAL instruments.


Effect Of Hyperchloremia On Acute Kidney Injury In Critically Ill Septic Patients: A Retrospective Cohort Study, Lenar Yessayan, Javier A. Neyra, Fabrizio Canepa-Escaro, George Vasquez-Rios, Michael Heung, Jerry Yee, Acute Kidney Injury in Critical Illness Study Group 2017 University of Michigan - Ann Arbor

Effect Of Hyperchloremia On Acute Kidney Injury In Critically Ill Septic Patients: A Retrospective Cohort Study, Lenar Yessayan, Javier A. Neyra, Fabrizio Canepa-Escaro, George Vasquez-Rios, Michael Heung, Jerry Yee, Acute Kidney Injury In Critical Illness Study Group

Internal Medicine Faculty Publications

Background: Hyperchloremia is common in critically ill septic patients. The impact of hyperchloremia on the incidence of acute kidney injury (AKI) is not well studied. We investigated the association between hyperchloremia and AKI within the first 72 h of intensive care unit (ICU) admission.

Methods: 6490 ICU adult patients admitted with severe sepsis or septic shock were screened for eligibility. Exclusion criteria included: AKI on admission, baseline estimated glomerular filtration rate (eGFR) < 15 ml/min/1.73 m2, chronic renal replacement therapy, absent baseline serum creatinine data, and absent serum chloride data on ICU admission.

Results: A total of 1045 patients were available for analysis ...


Idiopathic Nodular Glomerulosclerosis In A Chronic Marijuana User; A Case Report And Review Of The Literature, Mehri Mollaee, Tibor Fülöp, Sohil Abdul Salim, Seyed Mehrdad Hamrahian 2017 Thomas Jefferson University

Idiopathic Nodular Glomerulosclerosis In A Chronic Marijuana User; A Case Report And Review Of The Literature, Mehri Mollaee, Tibor Fülöp, Sohil Abdul Salim, Seyed Mehrdad Hamrahian

Department of Pathology, Anatomy and Cell Biology Faculty Papers

Background: Nodular glomerulosclerosis is a characteristic histological finding of diabetic nephropathy (DN) with thickened glomerular basement membrane (GBM) and hyalinized arterioles. Idiopathic nodular glomerulosclerosis (ING), a rare distinct clinicopathologic entity, is the term used to denote classic DN confirmed by light microscopy, immuno-fluorescence, and electron microscopy in the absence of diabetes mellitus (DM). ING has been linked to heavy tobacco smoking, chronic hypertension, obesity and insulin resistance. Its association with marijuana use is unknown. Case Presentation: We report a case of biopsy-proved ING in the absence of pre-existing history of DM and heavy smoking. This report addresses the possible accentuation ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Prasanna Santhanam

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians. Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set. Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program. Results: We found that using clinical parameters available at entry into the ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Juan R. Sanabria

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians.

Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set.

Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program.

Results: We found that using clinical parameters available at entry into the ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Joseph I Shapiro MD

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians. Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set. Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program. Results: We found that using clinical parameters available at entry into the ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Nader G. Abraham

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians.

Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set.

Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program.

Results: We found that using clinical parameters available at entry into the ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Komal Sodhi

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians.

Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set.

Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program.

Results: We found that using clinical parameters available at entry into the ...


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Zeid J. Khitan

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians. Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set. Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program. Results: We found that using clinical parameters available at entry into the ...


Effect Of Baseline Serum Calcium On Responses To Extended-Release Calcifediol (Erc) In Stage 3 - 4 Ckd, Nelson Kopyt DO, FASN, FACP, Stephen A. Strugnell, Akhtar Ashfaq, Martin Petkovich, Charles W. Bishop 2017 Lehigh Valley Health Network

Effect Of Baseline Serum Calcium On Responses To Extended-Release Calcifediol (Erc) In Stage 3 - 4 Ckd, Nelson Kopyt Do, Fasn, Facp, Stephen A. Strugnell, Akhtar Ashfaq, Martin Petkovich, Charles W. Bishop

Department of Medicine

No abstract provided.


Six Month Av Fistulae Outcomes Following Local Perianastomotic Delivery Of Sirolimuspreliminary Report From A Us Phase 3 Clinical Trial (Access Trial), Sriram Iyer, Nelson Kopyt DO, FASN, FACP, Joseph J. Lee, Osman Khawar, Thomas Wooldridge, Nirav Gandhi, Robert I. Lynn, William Paulson, Maria DeVita 2017 Lehigh Valley Health Network

Six Month Av Fistulae Outcomes Following Local Perianastomotic Delivery Of Sirolimuspreliminary Report From A Us Phase 3 Clinical Trial (Access Trial), Sriram Iyer, Nelson Kopyt Do, Fasn, Facp, Joseph J. Lee, Osman Khawar, Thomas Wooldridge, Nirav Gandhi, Robert I. Lynn, William Paulson, Maria Devita

Department of Medicine

No abstract provided.


Novel Immunotherapy Treatments: The Adverse Effects Of Nivolumab., Angela Magdaleno DO, Wael Hanna MD 2017 Lehigh Valley Health Network

Novel Immunotherapy Treatments: The Adverse Effects Of Nivolumab., Angela Magdaleno Do, Wael Hanna Md

Department of Medicine

No abstract provided.


Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro 2017 Marshall University

Predicting Adverse Outcomes In Chronic Kidney Disease Using Machine Learning Methods: Data From The Modification Of Diet In Renal Disease, Zeid Khitan, Anna P. Shapiro, Preeya T. Shah, Juan R. Sanabria, Prasanna Santhanam, Komal Sodhi, Nader G. Abraham, Joseph I. Shapiro

Marshall Journal of Medicine

Background: Understanding factors which predict progression of renal failure is of great interest to clinicians.

Objectives: We examined machine learning methods to predict the composite outcome of death, dialysis or doubling of serum creatinine using the modification of diet in renal disease (MDRD) data set.

Methods: We specifically evaluated a generalized linear model, a support vector machine, a decision tree, a feed-forward neural network and a random forest evaluated within the context of 10 fold validation using the CARET package available within the open source architecture R program.

Results: We found that using clinical parameters available at entry into the ...


Risk Factors For Bk Virus Infection After Kidney Transplantation, London, Ontario 2016, Seyed M Hosseini-Moghaddam 2017 The University of Western Ontario

Risk Factors For Bk Virus Infection After Kidney Transplantation, London, Ontario 2016, Seyed M Hosseini-Moghaddam

Electronic Thesis and Dissertation Repository

Our objective was to determine the risk factors for BK virus infection in renal allograft recipients in the first year after transplantation. In this cohort, we included all patients who received renal allograft at London Health Sciences Centre (LHSC) between 2012 and 2014. We continued post-transplantation follow-up for one year. Of 175 patients (37% female) with median age (range) of 53 (14-82) years, 40 (22.9%) developed BK viremia (median interval:100 days, range: 35-264). Recipient age, recipient gender, hemodialysis (HD) vs peritoneal dialysis (PD), Human Leukocyte Antigens A1, B35 and Cw4 increased the risk of post-transplant BKV infection. However ...


Higher Mineralized Bone Volume Is Associated With A Lower Plain X-Ray Vascular Calcification Score In Hemodialysis Patients, Teresa Adragao, Anibal Ferreira, Joao M. Frazao, Ana Luisa Papoila, Iola Pinto, Marie-Claude Monier-Faugere, Hartmut H. Malluche 2017 Santa Cruz Hospital, Portugal

Higher Mineralized Bone Volume Is Associated With A Lower Plain X-Ray Vascular Calcification Score In Hemodialysis Patients, Teresa Adragao, Anibal Ferreira, Joao M. Frazao, Ana Luisa Papoila, Iola Pinto, Marie-Claude Monier-Faugere, Hartmut H. Malluche

Internal Medicine Faculty Publications

Background and objectives

In dialysis patients, there is an increasing evidence that altered bone metabolism is associated with cardiovascular calcifications. The main objective of this study was to analyse, in hemodialysis patients, the relationships between bone turnover, mineralization and volume, evaluated in bone biopsies, with a plain X-ray vascular calcification score.

Design, setting, participants and measurements

In a cross-sectional study, bone biopsies and evaluation of vascular calcifications were performed in fifty hemodialysis patients. Cancellous bone volume, mineralized bone volume, osteoid volume, activation frequency, bone formation rate/bone surface, osteoid thickness and mineralization lag time were determined by histomorphometry. Vascular calcifications ...


Managing Renal Cell Carcinoma Associated Paraneoplastic Syndrome With Nephron-Sparing Surgery In A Patient With Von Hippel-Lindau., John M DiBianco, Julie Y An, Sally Tanakchi, Zachary Stanik, Aidan McGowan, Mahir Maruf, Abhinav Sidana, Amit Lodha Jain, Akhil Muthigi, Arvin K George, Christopher Bayne, W Marston Linehan, Shawna L Boyle, Adam R Metwalli 2017 George Washington University

Managing Renal Cell Carcinoma Associated Paraneoplastic Syndrome With Nephron-Sparing Surgery In A Patient With Von Hippel-Lindau., John M Dibianco, Julie Y An, Sally Tanakchi, Zachary Stanik, Aidan Mcgowan, Mahir Maruf, Abhinav Sidana, Amit Lodha Jain, Akhil Muthigi, Arvin K George, Christopher Bayne, W Marston Linehan, Shawna L Boyle, Adam R Metwalli

Urology Faculty Publications

A patient with germline von Hippel-Lindau (VHL) gene alteration and history of multiple tumors present with classical paraneoplastic syndrome (PNS) associated with renal cell carcinoma (RCC). She underwent open nephron sparing surgery with resolution of symptoms. She remained without recurrence of RCC for the initial 2 years of her follow-up. To the best of our knowledge, this case represents the first in which PNS was specifically resolved using a partial nephrectomy in a patient with VHL. This case report provides initial evidence for the potential role of nephron sparing surgery in the management of paraneoplastic symptoms associated with hereditary RCC.


Plk2 Plays An Essential Role In High D-Glucose-Induced Apoptosis, Ros Generation And Inflammation In Podocytes., Hong-Hong Zou, Ping-Ping Yang, Tian-Lun Huang, Xiao-Xu Zheng, Gao-Si Xu 2017 George Washington University

Plk2 Plays An Essential Role In High D-Glucose-Induced Apoptosis, Ros Generation And Inflammation In Podocytes., Hong-Hong Zou, Ping-Ping Yang, Tian-Lun Huang, Xiao-Xu Zheng, Gao-Si Xu

Medicine Faculty Publications

Diabetic kidney disease (DKD) is a serious complication of hyperglycemia. Currently, there is no effective therapeutic intervention for DKD. In this study, we sought to provide a set of gene profile in diabetic kidneys. We identified 338 genes altered in diabetes-induced DKD glomeruli, and PLK2 exhibited the most dramatic change. Gene set enrichment analysis (GSEA) indicated multiple signaling pathways are involved DKD pathogenesis. Here, we investigated whether PLK2 contributes to podocyte dysfunction, a characteristic change in the development of DKD. High D-glucose (HDG) significantly increased PLK2 expression in mouse podocytes. Suppressing PLK2 attenuated HDG-induced apoptosis and inflammatory responses both in ...


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