Yaping (Lucy) Zhang

Bio: Yaping (Lucy) Zhang is an academic researcher from Tufts University. The author has contributed to research in topics: Renal function & Creatinine. The author has an hindex of 5, co-authored 5 publications receiving 20607 citations. Previous affiliations of Yaping (Lucy) Zhang include Tufts Medical Center.

A New Equation to Estimate Glomerular Filtration Rate

Abstract: The Modification of Diet in Renal Disease (MDRD) Study equation underestimates glomerular filtration rate (GFR) in patients with mild kidney disease. Levey and associates therefore developed and va...

Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate.

Abstract: Using standardized creatinine assays, the authors remeasured serum creatinine levels in 1628 patients whose glomerular filtration rate (GFR) had been measured by urinary clearance of 125I-isothalam...

Evaluating the performance of equations for estimating glomerular filtration rate.

Abstract: Glomerular filtration rate (GFR) is an important indicator of kidney function, critical for detection, evaluation and management of chronic kidney disease (CKD). GFR cannot be practically measured in most clinical or research settings; therefore, estimating equations are used as a primary measure of kidney function. A considerable body of literature now evaluates the performance of GFR estimating equations. The results of these studies are often not comparable, because of variation in GFR measurement methods, endogenous filtration marker assays and tools by which the equations were evaluated. In this article, methods for the evaluation of GFR estimating equations are discussed. Topics addressed include statistical methods used in development and validation of equations; explanation of measures of performance used for evaluation, with focus on distinction between bias, precision and accuracy, and with reference to examples of published evaluations of creatinine- and cystatin C-based equations; explanation of errors in GFR estimates; and challenges and questions in reporting performance of GFR estimating equations.

A New Equation to Estimate Glomerular Filtration Rate

Abstract: The Modification of Diet in Renal Disease (MDRD) Study equation underestimates glomerular filtration rate (GFR) in patients with mild kidney disease. Levey and associates therefore developed and va...

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

KDIGO clinical practice guidelines for acute kidney injury.

Abstract: tion’, implying that most patients ‘should’ receive a particular action. In contrast, level 2 guidelines are essentially ‘suggestions’ and are deemed to be ‘weak’ or discretionary, recognising that management decisions may vary in different clinical contexts. Each recommendation was further graded from A to D by the quality of evidence underpinning them, with grade A referring to a high quality of evidence whilst grade D recognised a ‘very low’ evidence base. The overall strength and quality of the supporting evidence is summarised in table 1 . The guidelines focused on 4 key domains: (1) AKI definition, (2) prevention and treatment of AKI, (3) contrastinduced AKI (CI-AKI) and (4) dialysis interventions for the treatment of AKI. The full summary of clinical practice statements is available at www.kdigo.org, but a few key recommendation statements will be highlighted here.

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

Abstract: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee