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1. Performance of large language models in numerical vs. semantic medical knowledge: Benchmarking on evidence-based Q&As

Author

Avnat, Eden, Levy, Michal, Herstain, Daniel, Yanko, Elia, Joya, Daniel Ben, Katz, Michal Tzuchman, Eshel, Dafna, Laros, Sahar, Dagan, Yael, Barami, Shahar, Mermelstein, Joseph, Ovadia, Shahar, Shomron, Noam, Shalev, Varda, and Abdulnour, Raja-Elie E.

Subjects
Computer Science - Computation and Language
Abstract

Clinical problem-solving requires processing of semantic medical knowledge such as illness scripts and numerical medical knowledge of diagnostic tests for evidence-based decision-making. As large language models (LLMs) show promising results in many aspects of language-based clinical practice, their ability to generate non-language evidence-based answers to clinical questions is inherently limited by tokenization. Therefore, we evaluated LLMs' performance on two question types: numeric (correlating findings) and semantic (differentiating entities) while examining differences within and between LLMs in medical aspects and comparing their performance to humans. To generate straightforward multi-choice questions and answers (QAs) based on evidence-based medicine (EBM), we used a comprehensive medical knowledge graph (encompassed data from more than 50,00 peer-reviewed articles) and created the "EBMQA". EBMQA contains 105,000 QAs labeled with medical and non-medical topics and classified into numerical or semantic questions. We benchmarked this dataset using more than 24,500 QAs on two state-of-the-art LLMs: Chat-GPT4 and Claude3-Opus. We evaluated the LLMs accuracy on semantic and numerical question types and according to sub-labeled topics. For validation, six medical experts were tested on 100 numerical EBMQA questions. We found that both LLMs excelled more in semantic than numerical QAs, with Claude3 surpassing GPT4 in numerical QAs. However, both LLMs showed inter and intra gaps in different medical aspects and remained inferior to humans. Thus, their medical advice should be addressed carefully.

Published
2024

2. What Factors Increase the Risk of Complications in SARS-CoV-2–Infected Patients? A Cohort Study in a Nationwide Israeli Health Organization

Author

Yanover, Chen, Mizrahi, Barak, Kalkstein, Nir, Marcus, Karni, Akiva, Pinchas, Barer, Yael, Shalev, Varda, and Chodick, Gabriel

Subjects
Public aspects of medicine, RA1-1270
Abstract

BackgroundReliably identifying patients at increased risk for coronavirus disease (COVID-19) complications could guide clinical decisions, public health policies, and preparedness efforts. Multiple studies have attempted to characterize at-risk patients, using various data sources and methodologies. Most of these studies, however, explored condition-specific patient cohorts (eg, hospitalized patients) or had limited access to patients’ medical history, thus, investigating related questions and, potentially, obtaining biased results. ObjectiveThis study aimed to identify factors associated with COVID-19 complications from the complete medical records of a nationally representative cohort of patients, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MethodsWe studied a cohort of all SARS-CoV-2–positive individuals, confirmed by polymerase chain reaction testing of either nasopharyngeal or saliva samples, in a nationwide health organization (covering 2.3 million individuals) and identified those who suffered from serious complications (ie, experienced moderate or severe symptoms of COVID-19, admitted to the intensive care unit, or died). We then compared the prevalence of pre-existing conditions, extracted from electronic health records, between complicated and noncomplicated COVID-19 patient cohorts to identify the conditions that significantly increase the risk of disease complications, in various age and sex strata. ResultsOf the 4353 SARS-CoV-2–positive individuals, 173 (4%) patients suffered from COVID-19 complications (all age ≥18 years). Our analysis suggests that cardiovascular and kidney diseases, obesity, and hypertension are significant risk factors for COVID-19 complications. It also indicates that depression (eg, males ≥65 years: odds ratio [OR] 2.94, 95% CI 1.55-5.58; P=.01) as well as cognitive and neurological disorders (eg, individuals ≥65 years old: OR 2.65, 95% CI 1.69-4.17; P

Published
2020
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5. Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP.

Author

Matsushita, Kunihiro, Kaptoge, Stephen, Hageman, Steven, Sang, Yingying, Ballew, Shoshana, Grams, Morgan, Surapaneni, Aditya, Sun, Luanluan, Arnlov, Johan, Bozic, Milica, Brenner, Hermann, Brunskill, Nigel, Chang, Alex, Chinnadurai, Rajkumar, Cirillo, Massimo, Correa, Adolfo, Ebert, Natalie, Eckardt, Kai-Uwe, Gansevoort, Ron, Gutierrez, Orlando, Hadaegh, Farzad, He, Jiang, Hwang, Shih-Jen, Jafar, Tazeen, Jassal, Simerjot, Kayama, Takamasa, Kovesdy, Csaba, Landman, Gijs, Levey, Andrew, Lloyd-Jones, Donald, Major, Rupert, Miura, Katsuyuki, Muntner, Paul, Nadkarni, Girish, Nowak, Christoph, Ohkubo, Takayoshi, Pena, Michelle, Polkinghorne, Kevan, Sairenchi, Toshimi, Schaeffner, Elke, Schneider, Markus, Shalev, Varda, Shlipak, Michael, Solbu, Marit, Stempniewicz, Nikita, Tollitt, James, Valdivielso, José, van der Leeuw, Joep, Wang, Angela, Wen, Chi-Pang, Woodward, Mark, Yamagishi, Kazumasa, Yatsuya, Hiroshi, Zhang, Luxia, Dorresteijn, Jannick, Di Angelantonio, Emanuele, Visseren, Frank, Pennells, Lisa, and Coresh, Josef

Subjects
Cardiovascular disease, Chronic kidney disease, Meta-analysis, Risk prediction, Humans, Aged, Aged, 80 and over, Cardiovascular Diseases, Risk Factors, Creatinine, Renal Insufficiency, Chronic, Albuminuria, Glomerular Filtration Rate, Heart Disease Risk Factors
Abstract

AIMS: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an Add-on to incorporate CKD measures into these algorithms, using a validated approach. METHODS: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets. RESULTS: In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline. CONCLUSION: Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD.

Published
2023

9. Development of Risk Prediction Equations for Incident Chronic Kidney Disease

Author

Nelson, Robert G, Grams, Morgan E, Ballew, Shoshana H, Sang, Yingying, Azizi, Fereidoun, Chadban, Steven J, Chaker, Layal, Dunning, Stephan C, Fox, Caroline, Hirakawa, Yoshihisa, Iseki, Kunitoshi, Ix, Joachim, Jafar, Tazeen H, Köttgen, Anna, Naimark, David MJ, Ohkubo, Takayoshi, Prescott, Gordon J, Rebholz, Casey M, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schöttker, Ben, Shibagaki, Yugo, Tonelli, Marcello, Zhang, Luxia, Gansevoort, Ron T, Matsushita, Kunihiro, Woodward, Mark, Coresh, Josef, and Shalev, Varda

Subjects
Clinical Research, Kidney Disease, Patient Safety, Prevention, Renal and urogenital, Good Health and Well Being, Aged, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Models, Theoretical, Renal Insufficiency, Chronic, Risk Assessment, Risk Factors, CKD Prognosis Consortium, Medical and Health Sciences, General & Internal Medicine
Abstract

ImportanceEarly identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.ObjectiveTo develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).Design, setting, and participantsIndividual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).ExposuresDemographic and clinical factors.Main outcomes and measuresIncident eGFR of less than 60 mL/min/1.73 m2.ResultsAmong 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.Conclusions and relevanceEquations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.

Published
2019

13. Adiposity and risk of decline in glomerular filtration rate: meta-analysis of individual participant data in a global consortium

Author

Chang, Alex R, Grams, Morgan E, Ballew, Shoshana H, Bilo, Henk, Correa, Adolfo, Evans, Marie, Gutierrez, Orlando M, Hosseinpanah, Farhad, Iseki, Kunitoshi, Kenealy, Timothy, Klein, Barbara, Kronenberg, Florian, Lee, Brian J, Li, Yuanying, Miura, Katsuyuki, Navaneethan, Sankar D, Roderick, Paul J, Valdivielso, Jose M, Visseren, Frank LJ, Zhang, Luxia, Gansevoort, Ron T, Hallan, Stein I, Levey, Andrew S, Matsushita, Kunihiro, Shalev, Varda, Woodward, Mark, Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Yatsuya, Hiroshi, Tamakoshi, Koji, Hirakawa, Yoshihisa, Coresh, Josef, Sang, Yingying, Polkinghorne, Kevan, Chadban, Steven, Atkins, Robert, Levin, Adeera, Djurdjev, Ognjenka, Klein, Ron, Lee, Kristine, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Tang, Mila, Heine, Gunnar, Emrich, Insa, Zawada, Adam, Bauer, Lucie, Nally, Joseph, Schold, Jesse, Shlipak, Michael, Sarnak, Mark, Katz, Ronit, Hiramoto, Jade, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hamano, Takayuki, Hasegawa, Takeshi, Fujii, Naohiko, Jafar, Tazeen, Hatcher, Juanita, Poulter, Neil, Chaturvedi, Nish, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Brenner, Hermann, Schöttker, Ben, Saum, Kai-Uwe, Rothenbacher, Dietrich, Fox, Caroline, Hwang, Shih-Jen, Köttgen, Anna, Schneider, Markus P, Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, Ito, Sadayoshi, Miyazaki, Mariko, Nakayama, Masaaki, Yamada, Cirillo, Massimo, Romundstad, Solfrid, Øvrehus, Marius, Langlo, Knut Asbjørn, Irie, Fujiko, Sairenchi, Toshimi, Rebholz, Casey M, and Young, Bessie

Subjects
Epidemiology, Health Sciences, Obesity, Kidney Disease, Cardiovascular, Aging, Prevention, Nutrition, Clinical Research, Good Health and Well Being, Adiposity, Adult, Aged, Aged, 80 and over, Body Height, Body Mass Index, Cohort Studies, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Mortality, Risk Factors, Waist Circumference, CKD Prognosis Consortium, Clinical Sciences, Public Health and Health Services, General & Internal Medicine, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

ObjectiveTo evaluate the associations between adiposity measures (body mass index, waist circumference, and waist-to-height ratio) with decline in glomerular filtration rate (GFR) and with all cause mortality.DesignIndividual participant data meta-analysis.SettingCohorts from 40 countries with data collected between 1970 and 2017.ParticipantsAdults in 39 general population cohorts (n=5 459 014), of which 21 (n=594 496) had data on waist circumference; six cohorts with high cardiovascular risk (n=84 417); and 18 cohorts with chronic kidney disease (n=91 607).Main outcome measuresGFR decline (estimated GFR decline ≥40%, initiation of kidney replacement therapy or estimated GFR

Published
2019

14. Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442–1451

Author

Astor, Brad, Appel, Lawrence J, Levin, Adeera, Tang, Mila, Djurdjev, Ognjenka, Navaneethan, Sankar D, Jolly, Stacey E, Schold, Jesse D, Nally, Joseph V, Wheeler, David C, Emberson, Jonathan, Townend, John, Landray, Martin, Feldman, Harold I, Hsu, Chi-yuan, Lash, James P, Kalra, Philip A, Ritchie, James P, Maharajan, Raman, Middleton, Rachel J, O’Donoghue, Donal J, Eckardt, Kai-Uwe, Schneider, Markus P, Köttgen, Anna, Kronenberg, Florian, Bärthlein, Barbara, Chang, Alex R, Green, Jamie A, Kirchner, H Lester, Ho, Kevin, Marks, Angharad, Black, Corri, Prescott, Gordon J, Fluck, Nick, Nakayama, Masaaki, Miyazaki, Mariko, Yamamoto, Tae, Yamada, Wang, Angela Yee-Moon, Cheung, Sharon, Wong, Sharon, Chu, Jessie, Wu, Henry, Garg, Amit X, McArthur, Eric, Nash, Danielle M, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Wetzels, Jack FM, van Zuilen, Arjan D, van den Brand, Jan A, Levey, Andrew S, Inker, Lesley A, Sarnak, Mark J, Tighiouart, Hocine, Zhang, Haitao, Stengel, Benedicte, Metzger, Marie, Flamant, Martin, Houillier, Pascal, Haymann, Jean-Philippe, Rios, Pablo G, Mazzuchi, Nelson, Gadola, Liliana, Lamadrid, Verónica, Sola, Laura, Collins, John F, Elley, C Raina, Kenealy, Timothy, Moranne, Olivier, Couchoud, Cecile, Vigneau, Cecile, Brunskill, Nigel J, Major, Rupert W, Shepherd, David, Medcalf, James F, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, Molnar, Miklos Z, Sumida, Keiichi, Potukuchi, Praveen K, Heerspink, Hiddo JL, de Zeeuw, Dick, Brenner, Barry, Carrero, Juan Jesus, Gasparini, Alessandro, Qureshi, Abdul Rashid, Elinder, Carl-Gustaf, Visseren, Frank LJ, van der Graaf, Yolanda, Evans, Marie, Stendahl, Maria, Schön, Staffan, Segelmark, Mårten, Prütz, Karl-Göran, Naimark, David M, Tangri, Navdeep, and Mark, Patrick B

Subjects
Renal and urogenital, Chronic Kidney Disease Prognosis Consortium, Clinical Sciences, Urology & Nephrology
Abstract

The Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: • African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr.; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Rachel J. Middleton, Donal J. O'Donoghue; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Köttgen, Florian Kronenberg, Barbara Bärthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Ontario Institute for Clinical Evaluative Sciences, Provincial Kidney, Dialysis and Transplantation program (ICES KDT): Amit X. Garg, Eric McArthur, Danielle M. Nash; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study (NephroTest): Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, Verónica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agées (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Alessandro Gasparini, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schön, Mårten Segelmark, Karl-Göran Prütz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.• CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.• CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).• Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director).

Published
2018

15. Evans M, Grams ME, Sang Y, et al., for the Chronic Kidney Disease Prognosis Consortium. Risk factors for prognosis in patients with severely decreased GFR. Kidney Int Rep. 2018;3:625–637

Author

Astor, Brad, Appel, Lawrence J, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Navaneethan, Sankar D, Jolly, Stacey E, Schold, Jesse D, Nally, Joseph V, Wheeler, David C, Emberson, Jonathan, Townend, John, Landray, Martin, Feldman, Harold I, Hsu, Chi-yuan, Lash, James P, Kalra, Philip A, Ritchie, James P, Maharajan, Raman, Alderson, Helen, Lane, Beverly, Eckardt, Kai-Uwe, Schneider, Markus P, Köttgen, Anna, Kronenberg, Florian, Bärthlein, Barbara, Chang, Alex R, Green, Jamie A, Kirchner, H Lester, Ho, Kevin, Marks, Angharad, Black, Corri, Prescott, Gordon J, Fluck, Nick, Nakayama, Masaaki, Miyazaki, Mariko, Yamamoto, Tae, Yamada, Wang, Angela Yee-Moon, Cheung, Sharon, Wong, Sharon, Chu, Jessie, Wu, Henry, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Wetzels, Jack FM, van Zuilen, Arjan D, van den Brand, Jan A, Levey, Andrew S, Inker, Lesley A, Sarnak, Mark J, Tighiouart, Hocine, Zhang, Haitao, Stengel, Benedicte, Rios, Pablo G, Mazzuchi, Nelson, Gadola, Liliana, Lamadrid, Verónica, Sola, Laura, Collins, John F, Elley, C Raina, Kenealy, Timothy, Moranne, Olivier, Couchoud, Cecile, Vigneau, Cecile, Brunskill, Nigel J, Major, Rupert W, Shepherd, David, Medcalf, James F, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, Molnar, Miklos Z, Sumida, Keiichi, Potukuchi, Praveen K, Heerspink, Hiddo JL, de Zeeuw, Dick, Brenner, Barry, Carrero, Juan Jesus, Barany, Peter, Qureshi, Abdul Rashid, Elinder, Carl-Gustaf, Visseren, Frank LJ, van der Graaf, Yolanda, Evans, Marie, Stendahl, Maria, Schön, Staffan, Segelmark, Mårten, Prütz, Karl-Göran, Naimark, David M, Tangri, Navdeep, Mark, Patrick B, Traynor, Jamie P, Geddes, Colin C, Thomson, Peter C, and Coresh, Josef

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Renal and urogenital, Good Health and Well Being, Chronic Kidney Disease Prognosis Consortium, Biomedical and clinical sciences, Health sciences
Abstract

[This corrects the article DOI: 10.1016/j.ekir.2018.01.002.].

Published
2018

16. Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis.

Author

Kovesdy, Csaba P, Matsushita, Kunihiro, Sang, Yingying, Brunskill, Nigel J, Carrero, Juan J, Chodick, Gabriel, Hasegawa, Takeshi, Heerspink, Hiddo L, Hirayama, Atsushi, Landman, Gijs WD, Levin, Adeera, Nitsch, Dorothea, Wheeler, David C, Coresh, Josef, Hallan, Stein I, Shalev, Varda, Grams, Morgan E, Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Woodward, Mark, Arima, Hisatomi, Perkovic, Vlado, Djurdjev, Ognjenka, Zhang, Luxia, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Tang, Mila, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hamano, Takayuki, Fujii, Naohiko, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Green, Jamie, Kirchner, H Lester, Chang, Alex R, Cirillo, Massimo, Jee, Sun Ha, Kimm, Heejin, Mok, Yejin, Wetzels, Jack FM, Blankestijn, Peter J, van Zuilen, Arjan D, Bots, M, Sarnak, Mark, Inker, Lesley, Roderick, Paul, Fletcher, Astrid, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen B, Nadukuru, Rajiv, Brunskill, Nigel, Major, Rupert, Shepherd, David, Medcalf, James, Gansevoort, Ron T, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, Jassal, Simerjot K, Bergstrom, Jaclyn, Ix, Joachim H, Barrett-Connor, Elizabeth, Kovesdy, Csaba, Kalantar-Zadeh, Kamyar, de Zeeuw, Dick, Brenner, Barry, Gasparini, Alessandro, Elinder, Carl-Gustaf, Barany, Peter, Evans, Marie, Segelmark, Mårten, Stendahl, Maria, Schön, Staffan, Tangri, Navdeep, Sud, Maneesh, Naimark, David, Wen, Chi-Pang, and Tsao, Chwen-Keng

Subjects
Kidney Disease, Prevention, Clinical Research, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Renal and urogenital, Cardiovascular, Good Health and Well Being, Adult, Aged, Albuminuria, Cardiovascular Diseases, Cause of Death, Comorbidity, Glomerular Filtration Rate, Humans, Hyperkalemia, Hypokalemia, Kidney Failure, Chronic, Middle Aged, Prognosis, Renal Insufficiency, Chronic, Risk Factors, Potassium, Estimated glomerular filtration rate, End-stage renal disease, Mortality, CKD Prognosis Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

AimsBoth hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium.Methods and resultsWe performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 ± 16 years, average eGFR was 83 ± 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 ± 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts.ConclusionsOutpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria.

Published
2018

19. Measures of chronic kidney disease and risk of incident peripheral artery disease: a collaborative meta-analysis of individual participant data

Author

Matsushita, Kunihiro, Ballew, Shoshana H, Coresh, Josef, Arima, Hisatomi, Ärnlöv, Johan, Cirillo, Massimo, Ebert, Natalie, Hiramoto, Jade S, Kimm, Heejin, Shlipak, Michael G, Visseren, Frank LJ, Gansevoort, Ron T, Kovesdy, Csaba P, Shalev, Varda, Woodward, Mark, Kronenberg, Florian, Chalmers, John, Perkovic, Vlado, Grams, Morgan E, Sang, Yingying, Schaeffner, Elke, Martus, Peter, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Heine, Gunnar, Seiler, Sarah, Zawada, Adam, Emrich, Insa, Sarnak, Mark, Katz, Ronit, Brenner, Hermann, Schöttker, Ben, Rothenbacher, Dietrich, Saum, Kai-Uwe, Köttgen, Anna, Schneider, Markus, Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, Chang, Alex R, Black, Corri, Marks, Angharad, Prescott, Gordon, Clark, Laura, Fluck, Nick, Jee, Sun Ha, Mok, Yejin, Chodick, Gabriel, Wetzels, Jack FM, Blankestijn, Peter J, van Zuilen, Arjan D, Bots, M, Peralta, Carmen, Hiromoto, Jade, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen B, Nadukuru, Rajiv, Kenealy, Timothy, Elley, C Raina, Collins, John F, Drury, Paul L, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, Jassal, Simerjot K, Bergstrom, Jaclyn, Ix, Joachim H, Barrett-Connor, Elizabeth, Kalantar-Zadeh, Kamyar, Carrero, Juan J, Gasparini, Alessandro, Qureshi, Abdul Rashid, Barany, Peter, Algra, Ale, van der Graaf, Yolanda, Evans, Marie, Segelmark, Mårten, Stendahl, Maria, Schön, Staffan, Tangri, Navdeep, Sud, Maneesh, Naimark, David, Lannfelt, Lars, Larsson, Anders, Hallan, Stein, Levey, Andrew S, Chen, Jingsha, and Kwak, Lucia

Subjects
Clinical Research, Kidney Disease, Prevention, Renal and urogenital, Good Health and Well Being, Adult, Aged, Albuminuria, Creatinine, Databases, Factual, Female, Glomerular Filtration Rate, Humans, Incidence, Male, Middle Aged, Peripheral Arterial Disease, Renal Insufficiency, Chronic, Risk Factors, Chronic Kidney Disease Prognosis Consortium, Medical Biochemistry and Metabolomics, Clinical Sciences, Public Health and Health Services
Abstract

BackgroundSome evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease.MethodsIn this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics.FindingsWe analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7·4 years [IQR 5·7-8·9], range 2·0-15·8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1·73 m2, adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1·22 (95% CI 1·14-1·30) at an eGFR of 45 mL/min per 1·73 m2 and 2·06 (1·70-2·48) at an eGFR of 15 mL/min per 1·73 m2. Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1·50 (1·41-1·59) at an ACR of 30 mg/g and 2·28 (2·12-2·44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3·68 (95% CI 3·00-4·52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5·76 [4·90-6·77] for incident peripheral artery disease and 10·61 [5·70-19·77] for amputation in eGFR

Published
2017

20. A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys

Author

Shoer, Saar, Karady, Tal, Keshet, Ayya, Shilo, Smadar, Rossman, Hagai, Gavrieli, Amir, Meir, Tomer, Lavon, Amit, Kolobkov, Dmitry, Kalka, Iris, Godneva, Anastasia, Cohen, Ori, Kariv, Adam, Hoch, Ori, Zer-Aviv, Mushon, Castel, Noam, Sudre, Carole, Zohar, Anat Ekka, Irony, Angela, Spector, Tim, Geiger, Benjamin, Hizi, Dorit, Shalev, Varda, Balicer, Ran, and Segal, Eran

Published
2021
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22. The Case of Missed Cancers: Applying AI as a Radiologist’s Safety Net

Author

Chorev, Michal, Shoshan, Yoel, Akselrod-Ballin, Ayelet, Spiro, Adam, Naor, Shaked, Hazan, Alon, Barros, Vesna, Weinstein, Iuliana, Herzel, Esma, Shalev, Varda, Guindy, Michal, Rosen-Zvi, Michal, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Martel, Anne L., editor, Abolmaesumi, Purang, editor, Stoyanov, Danail, editor, Mateus, Diana, editor, Zuluaga, Maria A., editor, Zhou, S. Kevin, editor, Racoceanu, Daniel, editor, and Joskowicz, Leo, editor

Published
2020
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23. All-Cause Mortality Prediction in T2D Patients

Author

Novitski, Pavel, Cohen, Cheli Melzer, Karasik, Avraham, Shalev, Varda, Hodik, Gabriel, Moskovitch, Robert, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Michalowski, Martin, editor, and Moskovitch, Robert, editor

Published
2020
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25. Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Author

Matsushita, Kunihiro, Jassal, Simerjot K, Sang, Yingying, Ballew, Shoshana H, Grams, Morgan E, Surapaneni, Aditya, Arnlov, Johan, Bansal, Nisha, Bozic, Milica, Brenner, Hermann, Brunskill, Nigel J, Chang, Alex R, Chinnadurai, Rajkumar, Cirillo, Massimo, Correa, Adolfo, Ebert, Natalie, Eckardt, Kai-Uwe, Gansevoort, Ron T, Gutierrez, Orlando, Hadaegh, Farzad, He, Jiang, Hwang, Shih-Jen, Jafar, Tazeen H, Kayama, Takamasa, Kovesdy, Csaba P, Landman, Gijs W, Levey, Andrew S, Lloyd-Jones, Donald M, Major, Rupert W., Miura, Katsuyuki, Muntner, Paul, Nadkarni, Girish N, Naimark, David MJ, Nowak, Christoph, Ohkubo, Takayoshi, Pena, Michelle J, Polkinghorne, Kevan R, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schneider, Markus P, Shalev, Varda, Shlipak, Michael, Solbu, Marit D, Stempniewicz, Nikita, Tollitt, James, Valdivielso, José M, van der Leeuw, Joep, Wang, Angela Yee-Moon, Wen, Chi-Pang, Woodward, Mark, Yamagishi, Kazumasa, Yatsuya, Hiroshi, Zhang, Luxia, Schaeffner, Elke, and Coresh, Josef

Published
2020
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30. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury

Author

James, Matthew T, Grams, Morgan E, Woodward, Mark, Elley, C Raina, Green, Jamie A, Wheeler, David C, de Jong, Paul, Gansevoort, Ron T, Levey, Andrew S, Warnock, David G, Sarnak, Mark J, Tonelli, Marcello, Hemmelgarn, Brenda R, Turin, Tanvir Chowdhury, Coresh, Josef, Matsushita, Kunihiro, Grams, Morgan, Sang, Yingying, Shlipak, Michael, Katz, Ronit, Emberson, Jonathan, Landray, Martin J, Townend, Jonathan N, Green, Jamie, Kirchner, H Les, Perkins, Robert, Chang, Alex R, Romundstad, Solfrid, Aasarød, Knut, Øien, Cecilia M, Hallan, Stein, Smith, David H, Thorp, Micah L, Johnson, Eric S, Chodick, Gabriel, Herzel, Esma, Katz, Rachel, Shalev, Varda, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, van der Harst, Pim, Jee, Sun Ha, Kimm, Heejin, Mok, Yejin, Tangri, Navdeep, Naimark, David, Ärnlöv, Johan, Larsson, Anders, Lannfelt, Lars, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, de Jong, Paul E, Iseki, Kunitoshi, Stengel, Benedicte, Warnock, David, and Ballew, Shoshana H

Subjects
Nutrition, Kidney Disease, Clinical Research, Diabetes, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Metabolic and endocrine, Renal and urogenital, Acute Kidney Injury, Adult, Aged, Comorbidity, Diabetes Mellitus, Disease Progression, Female, Glomerular Filtration Rate, Humans, Hypertension, Incidence, Kidney Failure, Chronic, Male, Middle Aged, Prognosis, Renal Insufficiency, Chronic, Estimated glomerular filtration rate, renal function, albuminuria, albumin-creatine ratio, diabetes, hypertension, acute kidney injury, acute renal failure, Chronic Kidney Disease Prognosis Consortium, meta-analysis, CKD Prognosis Consortium, Clinical Sciences, Public Health and Health Services, Urology & Nephrology
Abstract

BackgroundDiabetes mellitus and hypertension are risk factors for acute kidney injury (AKI). Whether estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (ACR) remain risk factors for AKI in the presence and absence of these conditions is uncertain.Study designMeta-analysis of cohort studies.Setting & population8 general-population (1,285,045 participants) and 5 chronic kidney disease (CKD; 79,519 participants) cohorts.Selection criteria for studiesCohorts participating in the CKD Prognosis Consortium.PredictorsDiabetes and hypertension status, eGFR by the 2009 CKD Epidemiology Collaboration creatinine equation, urine ACR, and interactions.OutcomeHospitalization with AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results.ResultsDuring a mean follow-up of 4 years, there were 16,480 episodes of AKI in the general-population and 2,087 episodes in the CKD cohorts. Low eGFRs and high ACRs were associated with higher risks of AKI in individuals with or without diabetes and with or without hypertension. When compared to a common reference of eGFR of 80mL/min/1.73m(2) in nondiabetic patients, HRs for AKI were generally higher in diabetic patients at any level of eGFR. The same was true for diabetic patients at all levels of ACR compared with nondiabetic patients. The risk gradient for AKI with lower eGFRs was greater in those without diabetes than with diabetes, but similar with higher ACRs in those without versus with diabetes. Those with hypertension had a higher risk of AKI at eGFRs>60mL/min/1.73m(2) than those without hypertension. However, risk gradients for AKI with both lower eGFRs and higher ACRs were greater for those without than with hypertension.LimitationsAKI identified by diagnostic code.ConclusionsLower eGFRs and higher ACRs are associated with higher risks of AKI among individuals with or without either diabetes or hypertension.

Published
2015

31. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Age, Race, and Sex With Acute Kidney Injury

Author

Grams, Morgan E, Sang, Yingying, Ballew, Shoshana H, Gansevoort, Ron T, Kimm, Heejin, Kovesdy, Csaba P, Naimark, David, Oien, Cecilia, Smith, David H, Coresh, Josef, Sarnak, Mark J, Stengel, Benedicte, Tonelli, Marcello, Hemmelgarn, Brenda R, James, Matthew T, Turin, Tanvir Chowdhury, Matsushita, Kunihiro, Grams, Morgan, Shlipak, Michael, Katz, Ronit, Wheeler, David C, Emberson, Jonathan, Landray, Martin J, Townend, Jonathan N, Green, Jamie, Kirchner, H Les, Perkins, Robert, Chang, Alex R, Romundstad, Solfrid, Aasarød, Knut, Øien, Cecilia M, Hallan, Stein, Thorp, Micah L, Johnson, Eric S, Chodick, Gabriel, Herzel, Esma, Katz, Rachel, Shalev, Varda, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, van der Harst, Pim, Jee, Sun Ha, Mok, Yejin, Tangri, Navdeep, Ärnlöv, Johan, Larsson, Anders, Lannfelt, Lars, Kalantar-Zadeh, Kamyar, de Jong, Paul E, Iseki, Kunitoshi, Levey, Andrew S, Warnock, David, and Woodward, Mark

Subjects
Clinical Research, Prevention, Kidney Disease, Renal and urogenital, Acute Kidney Injury, Adolescent, Adult, African Americans, Age Distribution, Aged, Albuminuria, Female, Glomerular Filtration Rate, Humans, Incidence, Male, Middle Aged, Predictive Value of Tests, Prognosis, Racial Groups, Severity of Illness Index, Sex Distribution, Whites, Young Adult, Estimated glomerular filtration rate, renal function, albuminuria, albumin-creatinine ratio, proteinuria, age, race/ethnicity, sex, acute kidney injury, acute renal failure, Chronic Kidney Disease Prognosis Consortium, meta-analysis, CKD Prognosis Consortium, White People, Black or African American, Clinical Sciences, Public Health and Health Services, Urology & Nephrology
Abstract

BackgroundAcute kidney injury (AKI) is a serious global public health problem. We aimed to quantify the risk of AKI associated with estimated glomerular filtration rate (eGFR), albuminuria (albumin-creatinine ratio [ACR]), age, sex, and race (African American and white).Study designCollaborative meta-analysis.Setting & population8 general-population cohorts (1,285,049 participants) and 5 chronic kidney disease (CKD) cohorts (79,519 participants).Selection criteria for studiesAvailable eGFR, ACR, and 50 or more AKI events.PredictorsAge, sex, race, eGFR, urine ACR, and interactions.OutcomeHospitalized with or for AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results.Results16,480 (1.3%) general-population cohort participants had AKI over a mean follow-up of 4 years; 2,087 (2.6%) CKD participants had AKI over a mean follow-up of 1 year. Lower eGFR and higher ACR were strongly associated with AKI. Compared with eGFR of 80mL/min/1.73m(2), the adjusted HR of AKI at eGFR of 45mL/min/1.73m(2) was 3.35 (95% CI, 2.75-4.07). Compared with ACR of 5mg/g, the risk of AKI at ACR of 300mg/g was 2.73 (95% CI, 2.18-3.43). Older age was associated with higher risk of AKI, but this effect was attenuated with lower eGFR or higher ACR. Male sex was associated with higher risk of AKI, with a slight attenuation in lower eGFR but not in higher ACR. African Americans had higher AKI risk at higher levels of eGFR and most levels of ACR.LimitationsOnly 2 general-population cohorts could contribute to analyses by race; AKI identified by diagnostic code.ConclusionsReduced eGFR and increased ACR are consistent strong risk factors for AKI, whereas associations of AKI with age, sex, and race may be weaker in more advanced stages of CKD.

Published
2015

39. Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies

Author

Appel, Lawrence J, Greene, Tom, Chen, Teresa K, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Nally, Joseph, Navaneethan, Sankar D, Schold, Jesse D, Weldegiorgis, Misghina, Herrington, William G, Smith, Margaret, Hsu, C Yenchih, Hwang, Shih-Jen, Chang, Alex R, Kirchner, H. Lester, Green, Jamie A, Ho, Kevin, Marks, Angharad, Prescott, Gordon, Clark, Laura E, Fluck, Nick, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Van Zuilen, Arjan, Van den Brand, Jan A, Sarnak, Mark J, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen G, Nadukuru, Rajiv, Metzger, Marie, Flamant, Martin, Houillier, Pascal, Haymann, Jean-Philippe, Froissart, Marc, Kenealy, Timothy, Elley, Raina C, Collins, John F, Drury, Paul L, Cuddeback, John K, Ciemins, Elizabeth L, Stempniewicz, Rich, Nelson, Robert G, Knowler, William C, Bakker, Stephen J, Major, Rupert W, Medcalf, James F, Shepherd, David, Barrett-Connor, Elizabeth, Bergstrom, Jaclyn, Ix, Joachim H, Molnar, Miklos Z, Sumida, Keiichi, de Zeeuw, Dick, Brenner, Barry, Qureshi, Abdul R, Elinder, Carl-Gustaf, Runesson, Bjorn, Evans, Marie, Segelmark, Marten, Stendahl, Maria, Schön, Staffan, Naimark, David M, Tangri, Navdeep, Sud, Maneesh, Hirayama, Atsushi, Ichikawa, Kazunobu, Bilo, Henk JG, Landman, Gijs WD, Van Hateren, Kornelis JJ, Kleefstra, Nanne, Hallan, Stein I, Ballew, Shoshana H, Chen, Jingsha, Kwak, Lucia, Surapaneni, Aditya, Parving, Hans-Henrik, Rodby, Roger A., Rohde, Richard D, Lewis, Julia B, Lewis, Edmund, Perrone, Ronald D, Abebe, Kaleab Z, Hou, Fan F, Xie, Di, Hunsicker, Lawrence G, Imai, Enyu, Kobayashi, Fumiaki, Makino, Hirofumi, Ito, Sadayoshi, Remuzzi, Giuseppe, Ruggenenti, Piero, Eckardt, Kai-Uwe, Gudmundsdottir, Hrefna, Maciulaitis, Romaldas, Manley, Tom, Smith, Kimberly, Stockbridge, Norman, Thompson, Aliza, Vetter, Thorsten, Willis, Kerry, Zhang, Luxia, Coresh, Josef, Heerspink, Hiddo J L, Sang, Yingying, Matsushita, Kunihiro, Arnlov, Johan, Astor, Brad C, Black, Corri, Brunskill, Nigel J, Carrero, Juan-Jesus, Feldman, Harold I, Fox, Caroline S, Inker, Lesley A, Ishani, Areef, Jassal, Simerjot, Konta, Tsuneo, Polkinghorne, Kevan, Romundstad, Solfrid, Solbu, Marit D, Stempniewicz, Nikita, Stengel, Benedicte, Tonelli, Marcello, Umesawa, Mitsumasa, Waikar, Sushrut S, Wen, Chi-Pang, Wetzels, Jack F M, Woodward, Mark, Grams, Morgan E, Kovesdy, Csaba P, Levey, Andrew S, and Gansevoort, Ron T

Published
2019
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40. Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium

Author

Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Woodward, Mark, Arima, Hisatomi, Perkovic, Vlado, Yatsuya, Hiroshi, Tamakoshi, Koji, Li, Yuanying, Hirakawa, Yoshihisa, Coresh, Josef, Matsushita, Kunihiro, Grams, Morgan, Sang, Yingying, Polkinghorne, Kevan, Chadban, Steven, Atkins, Robert, Levin, Adeera, Djurdjev, Ognjenka, Zhang, Luxia, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Schaeffner, Elke, Ebert, Natalie, Martus, Peter, Tang, Mila, Heine, Gunnar, Emrich, Insa, Seiler, Sarah, Zawada, Adam, Nally, Joseph, Navaneethan, Sankar, Schold, Jesse, Shlipak, Michael, Sarnak, Mark, Katz, Ronit, Hiramoto, Jade, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hamano, Takayuki, Hasegawa, Takeshi, Fujii, Naohiko, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Brenner, Hermann, Schöttker, Ben, Saum, Kai-Uwe, Rothenbacher, Dietrich, Fox, Caroline, Hwang, Shih-Jen, Köttgen, Anna, Kronenberg, Florian, Schneider, Markus P., Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, Chang, Alex R., Ho, Kevin, Ito, Sadayoshi, Miyazaki, Mariko, Nakayama, Masaaki, Yamada, Gen, Cirillo, Massimo, Irie, Fujiko, Sairenchi, Toshimi, Ishikawa, Shizukiyo, Yano, Yuichiro, Kotani, Kazuhiko, Nakamura, Takeshi, Jee, Sun Ha, Kimm, Heejin, Mok, Yejin, Chodick, Gabriel, Shalev, Varda, Wetzels, Jack F.M., Blankestijn, Peter J., van Zuilen, Arjan D., van den Brand, Jan, Inker, Lesley, Peralta, Carmen, Kollerits, Barbara, Ritz, Eberhard, Nitsch, Dorothea, Roderick, Paul, Fletcher, Astrid, Bottinger, Erwin, Nadkarni, Girish N., Ellis, Stephen B., Nadukuru, Rajiv, Ueshima, Hirotsugu, Okayama, Akira, Miura, Katsuyuki, Tanaka, Sachiko, Okamura, Tomonori, Kadota, Aya, Kenealy, Timothy, Elley, C Raina, Collins, John F., Drury, Paul L., Ohkubo, Takayoshi, Asayama, Kei, Metoki, Hirohito, Kikuya, Masahiro, Nelson, Robert G., Knowler, William C., Gansevoort, Ron T., Bakker, Stephan JL., Hak, Eelco, Heerspink, Hiddo J.L., Brunskill, Nigel, Major, Rupert, Shepherd, David, Medcalf, James, Jassal, Simerjot K., Bergstrom, Jaclyn, Ix, Joachim H., Barrett-Connor, Elizabeth, Kovesdy, Csaba, Kalantar-Zadeh, Kamyar, Sumida, Keiichi, Gutierrez, Orlando M., Muntner, Paul, Warnock, David, McClellan, William, de Zeeuw, Dick, Brenner, Barry, Sedaghat, Sanaz, Ikram, M Arfan, Hoorn, Ewout J., Dehghan, Abbas, Carrero, Juan J., Gasparini, Alessandro, Wettermark, Björn, Elinder, Carl-Gustaf, Wong, Tien Yin, Sabanayagam, Charumathi, Cheng, Ching-Yu, Visseren, Frank L.J., Evans, Marie, Segelmark, Mårten, Stendahl, Maria, Schön, Staffan, Tangri, Navdeep, Sud, Maneesh, Naimark, David, Wen, Chi-Pang, Tsao, Chwen-Keng, Tsai, Min-Kugng, Chen, Chien-Hua, Konta, Tsuneo, Hirayama, Atsushi, Ichikawa, Kazunobu, Lannfelt, Lars, Larsson, Anders, Ärnlöv, Johan, Bilo, Henk J.G., Landman, Gijs W.D., van Hateren, Kornelis J.J., Kleefstra, Nanne, Coresh (Chair, Josef, Grams, Morgan E., Hallan, Stein, Kovesdy, Csaba P., Levey, Andrew S., Ballew, Shoshana H., Chen, Jingsha, Kwak, Lucia, Surapaneni, Aditya, Inker, Lesley A., Heine, Gunnar H., Landray, Martin J., Peralta, Carmen A., Shlipak, Michael G., and Hallan, Stein I.

Published
2019
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41. Decline in Estimated Glomerular Filtration Rate and Subsequent Risk of End-Stage Renal Disease and Mortality

Author

Coresh, Josef, Turin, Tanvir Chowdhury, Matsushita, Kunihiro, Sang, Yingying, Ballew, Shoshana H, Appel, Lawrence J, Arima, Hisatomi, Chadban, Steven J, Cirillo, Massimo, Djurdjev, Ognjenka, Green, Jamie A, Heine, Gunnar H, Inker, Lesley A, Irie, Fujiko, Ishani, Areef, Ix, Joachim H, Kovesdy, Csaba P, Marks, Angharad, Ohkubo, Takayoshi, Shalev, Varda, Shankar, Anoop, Wen, Chi Pang, de Jong, Paul E, Iseki, Kunitoshi, Stengel, Benedicte, Gansevoort, Ron T, and Levey, Andrew S

Subjects
Kidney Disease, Clinical Research, Renal and urogenital, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Cohort Studies, Creatinine, Disease Progression, Endpoint Determination, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Reference Values, Risk, Medical and Health Sciences, General & Internal Medicine
Abstract

ImportanceThe established chronic kidney disease (CKD) progression end point of end-stage renal disease (ESRD) or a doubling of serum creatinine concentration (corresponding to a change in estimated glomerular filtration rate [GFR] of −57% or greater) is a late event.ObjectiveTo characterize the association of decline in estimated GFR with subsequent progression to ESRD with implications for using lesser declines in estimated GFR as potential alternative end points for CKD progression. Because most people with CKD die before reaching ESRD, mortality risk also was investigated.Data sources and study selectionIndividual meta-analysis of 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine concentration over 1 to 3 years and outcome data.Data extraction and synthesisTransfer of individual participant data or standardized analysis of outputs for random-effects meta-analysis conducted between July 2012 and September 2013, with baseline estimated GFR values collected from 1975 through 2012.Main outcomes and measuresEnd-stage renal disease (initiation of dialysis or transplantation) or all-cause mortality risk related to percentage change in estimated GFR over 2 years, adjusted for potential confounders and first estimated GFR.ResultsThe adjusted hazard ratios (HRs) of ESRD and mortality were higher with larger estimated GFR decline. Among participants with baseline estimated GFR of less than 60 mL/min/1.73 m2, the adjusted HRs for ESRD were 32.1 (95% CI, 22.3-46.3) for changes of −57% in estimated GFR and 5.4 (95% CI, 4.5-6.4) for changes of −30%. However, changes of −30% or greater (6.9% [95% CI, 6.4%-7.4%] of the entire consortium) were more common than changes of −57% (0.79% [95% CI, 0.52%-1.06%]). This association was strong and consistent across the length of the baseline period (1 to 3 years), baseline estimated GFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD (in patients with a baseline estimated GFR of 35 mL/min/1.73 m2) was 99% (95% CI, 95%-100%) for estimated GFR change of −57%, was 83% (95% CI, 71%-93%) for estimated GFR change of −40%, and was 64% (95% CI, 52%-77%) for estimated GFR change of −30% vs 18% (95% CI, 15%-22%) for estimated GFR change of 0%. Corresponding mortality risks were 77% (95% CI, 71%-82%), 60% (95% CI, 56%-63%), and 50% (95% CI, 47%-52%) vs 32% (95% CI, 31%-33%), showing a similar but weaker pattern.Conclusions and relevanceDeclines in estimated GFR smaller than a doubling of serum creatinine concentration occurred more commonly and were strongly and consistently associated with the risk of ESRD and mortality, supporting consideration of lesser declines in estimated GFR (such as a 30% reduction over 2 years) as an alternative end point for CKD progression.

Published
2014

48. Risk Factors for Prognosis in Patients With Severely Decreased GFR

Author

Evans, Marie, Grams, Morgan E., Sang, Yingying, Astor, Brad C., Blankestijn, Peter J., Brunskill, Nigel J., Collins, John F., Kalra, Philip A., Kovesdy, Csaba P., Levin, Adeera, Mark, Patrick B., Moranne, Olivier, Rao, Panduranga, Rios, Pablo G., Schneider, Markus P., Shalev, Varda, Zhang, Haitao, Chang, Alex R., Gansevoort, Ron T., Matsushita, Kunihiro, Zhang, Luxia, Eckardt, Kai-Uwe, Hemmelgarn, Brenda, and Wheeler, David C.

Published
2018
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