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1. Longitudinal biomarkers and kidney disease progression after acute kidney injury.

Author

Wen, Yumeng, Xu, Leyuan, Melchinger, Isabel, Thiessen-Philbrook, Heather, Moledina, Dennis G, Coca, Steven G, Hsu, Chi-Yuan, Go, Alan S, Liu, Kathleen D, Siew, Edward D, Ikizler, T Alp, Chinchilli, Vernon M, Kaufman, James S, Kimmel, Paul L, Himmelfarb, Jonathan, Cantley, Lloyd G, Parikh, Chirag R, and ASSESS-AKI Consortium

Subjects
ASSESS-AKI Consortium, Kidney, Animals, Mice, Disease Progression, Inflammation, Prospective Studies, Renal Insufficiency, Chronic, Acute Kidney Injury, Biomarkers, Chronic kidney disease, Diagnostics, Epidemiology, Nephrology, Prevention, Kidney Disease, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Renal and urogenital, Good Health and Well Being
Abstract

BACKGROUNDLongitudinal investigations of murine acute kidney injury (AKI) suggest that injury and inflammation may persist long after the initial insult. However, the evolution of these processes and their prognostic values are unknown in patients with AKI.METHODSIn a prospective cohort of 656 participants hospitalized with AKI, we measured 7 urine and 2 plasma biomarkers of kidney injury, inflammation, and tubular health at multiple time points from the diagnosis to 12 months after AKI. We used linear mixed-effect models to estimate biomarker changes over time, and we used Cox proportional hazard regressions to determine their associations with a composite outcome of chronic kidney disease (CKD) incidence and progression. We compared the gene expression kinetics of biomarkers in murine models of repair and atrophy after ischemic reperfusion injury (IRI).RESULTSAfter 4.3 years, 106 and 52 participants developed incident CKD and CKD progression, respectively. Each SD increase in the change of urine KIM-1, MCP-1, and plasma TNFR1 from baseline to 12 months was associated with 2- to 3-fold increased risk for CKD, while the increase in urine uromodulin was associated with 40% reduced risk for CKD. The trajectories of these biological processes were associated with progression to kidney atrophy in mice after IRI.CONCLUSIONSustained tissue injury and inflammation, and slower restoration of tubular health, are associated with higher risk of kidney disease progression. Further investigation into these ongoing biological processes may help researchers understand and prevent the AKI-to-CKD transition.FUNDINGNIH and NIDDK (grants U01DK082223, U01DK082185, U01DK082192, U01DK082183, R01DK098233, R01DK101507, R01DK114014, K23DK100468, R03DK111881, K01DK120783, and R01DK093771).

Published
2023

3. Proteomic characterization of acute kidney injury in patients hospitalized with SARS-CoV2 infection

Author

Paranjpe, Ishan, Jayaraman, Pushkala, Su, Chen-Yang, Zhou, Sirui, Chen, Steven, Thompson, Ryan, Del Valle, Diane Marie, Kenigsberg, Ephraim, Zhao, Shan, Jaladanki, Suraj, Chaudhary, Kumardeep, Ascolillo, Steven, Vaid, Akhil, Gonzalez-Kozlova, Edgar, Kauffman, Justin, Kumar, Arvind, Paranjpe, Manish, Hagan, Ross O., Kamat, Samir, Gulamali, Faris F., Xie, Hui, Harris, Joceyln, Patel, Manishkumar, Argueta, Kimberly, Batchelor, Craig, Nie, Kai, Dellepiane, Sergio, Scott, Leisha, Levin, Matthew A., He, John Cijiang, Suarez-Farinas, Mayte, Coca, Steven G., Chan, Lili, Azeloglu, Evren U., Schadt, Eric, Beckmann, Noam, Gnjatic, Sacha, Merad, Miram, Kim-Schulze, Seunghee, Richards, Brent, Glicksberg, Benjamin S., Charney, Alexander W., and Nadkarni, Girish N.

Published
2023
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5. The Association of Posttraumatic Stress Disorder With Longitudinal Change in Glomerular Filtration Rate in World Trade Center Responders

Author

Koraishy, Farrukh M, Coca, Steven G, Cohen, Beth E, Scherrer, Jeffery F, Mann, Frank, Kuan, Pei-Fen, Luft, Benjamin J, and Clouston, Sean AP

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Anxiety Disorders, Brain Disorders, Clinical Research, Post-Traumatic Stress Disorder (PTSD), Mental Health, Good Health and Well Being, Adult, Emergency Responders, Female, Glomerular Filtration Rate, Humans, Middle Aged, Risk Factors, September 11 Terrorist Attacks, Stress Disorders, Post-Traumatic, PTSD, GFR, depression, kidney disease, BMI = body mass index, CKD = chronic kidney disease, CVD = cardiovascular disease, DM = diabetes mellitus, eGFR = estimated glomerular filtration rate, ESKD = end-stage kidney disease, GFR = glomerular filtration rate, PCL=17-item PTSD Checklist, PHQ-9=Patient Health Questionnaire, PTSD = posttraumatic stress disorder, WTC = World Trade Center, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology
Abstract

ObjectiveHigh levels of psychological distress increase the risk of a wide range of medical diseases. In this study, we investigated the association between posttraumatic stress disorder (PTSD) and kidney disease.MethodsWorld Trade Center (WTC) responders were included if they had two or more measures of estimated glomerular filtration rate (eGFR). The PTSD Checklist (PCL) was used to define no PTSD (PCL < 40), "mild" PTSD (40 ≤ PCL

Published
2021

8. Achieved blood pressure post-acute kidney injury and risk of adverse outcomes after AKI: A prospective parallel cohort study.

Author

McCoy, Ian, Brar, Sandeep, Liu, Kathleen D, Go, Alan S, Hsu, Raymond K, Chinchilli, Vernon M, Coca, Steven G, Garg, Amit X, Himmelfarb, Jonathan, Ikizler, T Alp, Kaufman, James, Kimmel, Paul L, Lewis, Julie B, Parikh, Chirag R, Siew, Edward D, Ware, Lorraine B, Zeng, Hui, Hsu, Chi-Yuan, and Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study investigators

Subjects
Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study investigators, AKI, blood pressure, hypertension, Kidney Disease, Cardiovascular, Clinical Research, Patient Safety, 2.1 Biological and endogenous factors, 2.4 Surveillance and distribution, Renal and urogenital, Urology & Nephrology, Clinical Sciences
Abstract

BackgroundThere has recently been considerable interest in better understanding how blood pressure should be managed after an episode of hospitalized AKI, but there are scant data regarding the associations between blood pressure measured after AKI and subsequent adverse outcomes. We hypothesized that among AKI survivors, higher blood pressure measured three months after hospital discharge would be associated with worse outcomes. We also hypothesized these associations between blood pressure and outcomes would be similar among those who survived non-AKI hospitalizations.MethodsWe quantified how systolic blood pressure (SBP) observed three months after hospital discharge was associated with risks of subsequent hospitalized AKI, loss of kidney function, mortality, and heart failure events among 769 patients in the prospective ASSESS-AKI cohort study who had hospitalized AKI. We repeated this analysis among the 769 matched non-AKI ASSESS-AKI enrollees. We then formally tested for AKI interaction in the full cohort of 1538 patients to determine if these associations differed among those who did and did not experience AKI during the index hospitalization.ResultsAmong 769 patients with AKI, 42 % had subsequent AKI, 13 % had loss of kidney function, 27 % died, and 18 % had heart failure events. SBP 3 months post-hospitalization did not have a stepwise association with the risk of subsequent AKI, loss of kidney function, mortality, or heart failure events. Among the 769 without AKI, there was also no stepwise association with these risks. In formal interaction testing using the full cohort of 1538 patients, hospitalized AKI did not modify the association between post-discharge SBP and subsequent risks of adverse clinical outcomes.ConclusionsContrary to our first hypothesis, we did not observe that higher stepwise blood pressure measured three months after hospital discharge with AKI was associated with worse outcomes. Our data were consistent with our second hypothesis that the association between blood pressure measured three months after hospital discharge and outcomes among AKI survivors is similar to that observed among those who survived non-AKI hospitalizations.

Published
2021

9. The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events

Author

Menez, Steven, Wen, Yumeng, Xu, Leyuan, Moledina, Dennis G., Thiessen-Philbrook, Heather, Hu, David, Obeid, Wassim, Bhatraju, Pavan K., Ikizler, T. Alp, Siew, Edward D., Chinchilli, Vernon M., Garg, Amit X., Go, Alan S., Liu, Kathleen D., Kaufman, James S., Kimmel, Paul L., Himmelfarb, Jonathan, Coca, Steven G., Cantley, Lloyd G., and Parikh, Chirag R.

Published
2023
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11. Plasma Biomarkers and Incident CKD Among Individuals Without Diabetes

Author

Le, Dustin, Chen, Jingsha, Shlipak, Michael G., Ix, Joachim H., Sarnak, Mark J., Gutierrez, Orlando M., Schelling, Jeffrey R., Bonventre, Joseph V., Sabbisetti, Venkata S., Schrauben, Sarah J., Coca, Steven G., Kimmel, Paul L., Vasan, Ramachandran S., Grams, Morgan E., Parikh, Chirag, Coresh, Josef, and Rebholz, Casey M.

Published
2023
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12. Characteristics and Outcomes of Individuals With Pre-existing Kidney Disease and COVID-19 Admitted to Intensive Care Units in the United States

Author

Flythe, Jennifer E, Assimon, Magdalene M, Tugman, Matthew J, Chang, Emily H, Gupta, Shruti, Shah, Jatan, Sosa, Marie Anne, Renaghan, Amanda DeMauro, Melamed, Michal L, Wilson, F Perry, Neyra, Javier A, Rashidi, Arash, Boyle, Suzanne M, Anand, Shuchi, Christov, Marta, Thomas, Leslie F, Edmonston, Daniel, Leaf, David E, Walther, Carl P, Anumudu, Samaya J, Arunthamakun, Justin, Kopecky, Kathleen F, Milligan, Gregory P, McCullough, Peter A, Nguyen, Thuy-Duyen, Shaefi, Shahzad, Krajewski, Megan L, Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D, Waikar, Sushrut S, Kibbelaar, Zoe A, Athavale, Ambarish M, Hart, Peter, Upadhyay, Shristi, Vohra, Ishaan, Green, Adam, Rachoin, Jean-Sebastien, Schorr, Christa A, Shea, Lisa, Edmonston, Daniel L, Mosher, Christopher L, Shehata, Alexandre M, Cohen, Zaza, Allusson, Valerie, Bambrick-Santoyo, Gabriela, Bhatti, Noor ul aain, Mehta, Bijal, Williams, Aquino, Brenner, Samantha K, Walters, Patricia, Go, Ronaldo C, Rose, Keith M, Chan, Lili, Mathews, Kusum S, Coca, Steven G, Altman, Deena R, Saha, Aparna, Soh, Howard, Wen, Huei Hsun, Bose, Sonali, Leven, Emily A, Wang, Jing G, Mosoyan, Gohar, Nadkarni, Girish N, Pattharanitima, Pattharawin, Gallagher, Emily J, Friedman, Allon N, Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Kelly, Katherine J, Parikh, Chirag R, Garibaldi, Brian T, Corona-Villalobos, Celia P, Wen, Yumeng, Menez, Steven, Malik, Rubab F, Cervantes, Carmen Elena, Gautam, Samir C, Mallappallil, Mary C, Ouyang, Jie, John, Sabu, Yap, Ernie, Melaku, Yohannes, Mohamed, Ibrahim, Bajracharya, Siddhartha, Puri, Isha, Thaxton, Mariah, Bhattacharya, Jyotsna, Wagner, John, Boudourakis, Leon, Nguyen, H Bryant, Ahoubim, Afshin, Kashani, Kianoush, Tehranian, Shahrzad, Sirganagari, Dheeraj Reddy, Guru, Pramod K, and Zhou, Yan

Subjects
Clinical Research, Cardiovascular, Clinical Trials and Supportive Activities, Kidney Disease, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Renal and urogenital, Good Health and Well Being, Aged, COVID-19, Comorbidity, Critical Illness, Female, Hospital Mortality, Humans, Intensive Care Units, Kidney Function Tests, Male, Renal Dialysis, Renal Insufficiency, Chronic, Retrospective Studies, Risk Factors, SARS-CoV-2, Treatment Outcome, United States, STOP-COVID Investigators, COVID-19 outcome, Coronavirus disease 2019, altered mental status, chronic kidney disease, clinical course, clinical trajectory, critical illness, dialysis, end-stage kidney disease, end-stage renal disease, glomerular filtration rate, in-hospital mortality, intensive care unit, prognosis, renal function, severe COVID-19, severe acute respiratory syndrome coronavirus 2, Clinical Sciences, Public Health and Health Services, Urology & Nephrology
Abstract

Rationale & objectiveUnderlying kidney disease is an emerging risk factor for more severe coronavirus disease 2019 (COVID-19) illness. We examined the clinical courses of critically ill COVID-19 patients with and without pre-existing chronic kidney disease (CKD) and investigated the association between the degree of underlying kidney disease and in-hospital outcomes.Study designRetrospective cohort study.Settings & participants4,264 critically ill patients with COVID-19 (143 patients with pre-existing kidney failure receiving maintenance dialysis; 521 patients with pre-existing non-dialysis-dependent CKD; and 3,600 patients without pre-existing CKD) admitted to intensive care units (ICUs) at 68 hospitals across the United States.Predictor(s)Presence (vs absence) of pre-existing kidney disease.Outcome(s)In-hospital mortality (primary); respiratory failure, shock, ventricular arrhythmia/cardiac arrest, thromboembolic events, major bleeds, and acute liver injury (secondary).Analytical approachWe used standardized differences to compare patient characteristics (values>0.10 indicate a meaningful difference between groups) and multivariable-adjusted Fine and Gray survival models to examine outcome associations.ResultsDialysis patients had a shorter time from symptom onset to ICU admission compared to other groups (median of 4 [IQR, 2-9] days for maintenance dialysis patients; 7 [IQR, 3-10] days for non-dialysis-dependent CKD patients; and 7 [IQR, 4-10] days for patients without pre-existing CKD). More dialysis patients (25%) reported altered mental status than those with non-dialysis-dependent CKD (20%; standardized difference=0.12) and those without pre-existing CKD (12%; standardized difference=0.36). Half of dialysis and non-dialysis-dependent CKD patients died within 28 days of ICU admission versus 35% of patients without pre-existing CKD. Compared to patients without pre-existing CKD, dialysis patients had higher risk for 28-day in-hospital death (adjusted HR, 1.41 [95% CI, 1.09-1.81]), while patients with non-dialysis-dependent CKD had an intermediate risk (adjusted HR, 1.25 [95% CI, 1.08-1.44]).LimitationsPotential residual confounding.ConclusionsFindings highlight the high mortality of individuals with underlying kidney disease and severe COVID-19, underscoring the importance of identifying safe and effective COVID-19 therapies in this vulnerable population.

Published
2021

13. Biomarkers of inflammation and repair in kidney disease progression

Author

Puthumana, Jeremy, Thiessen-Philbrook, Heather, Xu, Leyuan, Coca, Steven G, Garg, Amit X, Himmelfarb, Jonathan, Bhatraju, Pavan K, Ikizler, Talat Alp, Siew, Edward, Ware, Lorraine B, Liu, Kathleen D, Go, Alan S, Kaufman, James S, Kimmel, Paul L, Chinchilli, Vernon M, Cantley, Lloyd, and Parikh, Chirag R

Subjects
Kidney Disease, Clinical Research, 4.2 Evaluation of markers and technologies, 2.1 Biological and endogenous factors, Detection, screening and diagnosis, Aetiology, Renal and urogenital, Acute Kidney Injury, Aged, Animals, Biomarkers, Chemokine CCL2, Chitinase-3-Like Protein 1, Disease Models, Animal, Disease Progression, Female, Follow-Up Studies, Glomerular Filtration Rate, Humans, Inflammation, Male, Mice, Middle Aged, Renal Insufficiency, Chronic, Chronic kidney disease, Clinical practice, Molecular diagnosis, Nephrology, Medical and Health Sciences, Immunology
Abstract

INTRODUCTIONAcute kidney injury and chronic kidney disease (CKD) are common in hospitalized patients. To inform clinical decision making, more accurate information regarding risk of long-term progression to kidney failure is required.METHODSWe enrolled 1538 hospitalized patients in a multicenter, prospective cohort study. Monocyte chemoattractant protein 1 (MCP-1/CCL2), uromodulin (UMOD), and YKL-40 (CHI3L1) were measured in urine samples collected during outpatient follow-up at 3 months. We followed patients for a median of 4.3 years and assessed the relationship between biomarker levels and changes in estimated glomerular filtration rate (eGFR) over time and the development of a composite kidney outcome (CKD incidence, CKD progression, or end-stage renal disease). We paired these clinical studies with investigations in mouse models of renal atrophy and renal repair to further understand the molecular basis of these markers in kidney disease progression.RESULTSHigher MCP-1 and YKL-40 levels were associated with greater eGFR decline and increased incidence of the composite renal outcome, whereas higher UMOD levels were associated with smaller eGFR declines and decreased incidence of the composite kidney outcome. A multimarker score increased prognostic accuracy and reclassification compared with traditional clinical variables alone. The mouse model of renal atrophy showed greater Ccl2 and Chi3l1 mRNA expression in infiltrating macrophages and neutrophils, respectively, and evidence of progressive renal fibrosis compared with the repair model. The repair model showed greater Umod expression in the loop of Henle and correspondingly less fibrosis.CONCLUSIONSBiomarker levels at 3 months after hospitalization identify patients at risk for kidney disease progression.FUNDINGNIH.

Published
2021

14. A prospective cohort study of acute kidney injury and kidney outcomes, cardiovascular events, and death.

Author

Ikizler, T Alp, Parikh, Chirag R, Himmelfarb, Jonathan, Chinchilli, Vernon M, Liu, Kathleen D, Coca, Steven G, Garg, Amit X, Hsu, Chi-Yuan, Siew, Edward D, Wurfel, Mark M, Ware, Lorraine B, Faulkner, Georgia Brown, Tan, Thida C, Kaufman, James S, Kimmel, Paul L, Go, Alan S, and ASSESS-AKI Study Investigators

Subjects
ASSESS-AKI Study Investigators, Kidney, Humans, Cardiovascular Diseases, Glomerular Filtration Rate, Aftercare, Patient Discharge, Risk Factors, Prospective Studies, Adult, Acute Kidney Injury, acute kidney injury, acute renal failure, cardiovascular disease, chronic kidney disease, heart failure, mortality, Cardiovascular, Clinical Research, Kidney Disease, Aging, Renal and urogenital, Urology & Nephrology, Clinical Sciences
Abstract

Acute kidney injury (AKI) has been reported to be associated with excess risks of death, kidney disease progression and cardiovascular events although previous studies have important limitations. To further examine this, we prospectively studied adults from four clinical centers surviving three months and more after hospitalization with or without AKI who were matched on center, pre-admission CKD status, and an integrated priority score based on age, prior cardiovascular disease or diabetes mellitus, preadmission estimated glomerular filtration rate (eGFR) and treatment in the intensive care unit during the index hospitalization between December 2009-February 2015, with follow-up through November 2018. All participants had assessments of kidney function before (eGFR) and at three months and annually (eGFR and proteinuria) after the index hospitalization. Associations of AKI with outcomes were examined after accounting for pre-admission and three-month post-discharge factors. Among 769 AKI (73% Stage 1, 14% Stage 2, 13% Stage 3) and 769 matched non-AKI adults, AKI was associated with higher adjusted rates of incident CKD (adjusted hazard ratio 3.98, 95% confidence interval 2.51-6.31), CKD progression (2.37,1.28-4.39), heart failure events (1.68, 1.22-2.31) and all-cause death (1.78, 1.24-2.56). AKI was not associated with major atherosclerotic cardiovascular events in multivariable analysis (0.95, 0.70-1.28). After accounting for degree of kidney function recovery and proteinuria at three months after discharge, the associations of AKI with heart failure (1.13, 0.80-1.61) and death (1.29, 0.84-1.98) were attenuated and no longer significant. Thus, assessing kidney function recovery and proteinuria status three months after AKI provides important prognostic information for long-term clinical outcomes.

Published
2021

15. Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19

Author

Deng, Jie, Atta, Mo, Bagnasco, Serena M., Ko, Albert, Iwasaki, Akiko, Farhadian, Shelli, Nelson, Allison, Casanovas-Massana, Arnau, White, Elizabeth B., Schulz, Wade, Coppi, Andreas, Young, Patrick, Nunez, Angela, Shepard, Denise, Matos, Irene, Strong, Yvette, Anastasio, Kelly, Brower, Kristina, Kuang, Maxine, Chiorazzi, Michael, Bermejo, Santos, Vijayakumar, Pavithra, Geng, Bertie, Fournier, John, Minasyan, Maksym, Muenker, M. Catherine, Moore, Adam J., Nadkarni, Girish, Menez, Steven, Coca, Steven G., Moledina, Dennis G., Wen, Yumeng, Chan, Lili, Thiessen-Philbrook, Heather, Obeid, Wassim, Garibaldi, Brian T., Azeloglu, Evren U., Ugwuowo, Ugochukwu, Sperati, C. John, Arend, Lois J., Rosenberg, Avi Z., Kaushal, Madhurima, Jain, Sanjay, Wilson, F. Perry, and Parikh, Chirag R.

Published
2023
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16. Patient-Specific Pharmacokinetics and Dasatinib Nephrotoxicity

Author

Adegbite, Benjamin O., Abramson, Matthew H., Gutgarts, Victoria, Musteata, Florin M., Chauhan, Kinsuk, Muwonge, Alecia N., Meliambro, Kristin A., Salvatore, Steven P., El Ghaity-Beckley, Sebastian, Kremyanskaya, Marina, Marcellino, Bridget, Mascarenhas, John O., Campbell, Kirk N., Chan, Lili, Coca, Steven G., Berman, Ellin M., Jaimes, Edgar A., and Azeloglu, Evren U.

Published
2023
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17. The Association of Angiogenesis Markers With Acute Kidney Injury and Mortality After Cardiac Surgery

Author

Mansour, Sherry G, Zhang, William R, Moledina, Dennis G, Coca, Steven G, Jia, Yaqi, Thiessen-Philbrook, Heather, McArthur, Eric, Inoue, Kazunori, Koyner, Jay L, Shlipak, Michael G, Wilson, F Perry, Garg, Amit X, Ishibe, Shuta, Parikh, Chirag R, and Consortium, TRIBE-AKI

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Cardiovascular, Clinical Research, Kidney Disease, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Aged, Biomarkers, Cardiac Surgical Procedures, Creatinine, Endpoint Determination, Female, Humans, Kidney, Male, Middle Aged, Neovascularization, Physiologic, Outcome Assessment, Health Care, Postoperative Complications, Prospective Studies, Receptors, Vascular Endothelial Growth Factor, Risk Assessment, United States, Vascular Endothelial Growth Factor A, TRIBE-AKI Consortium, AKI duration, Acute kidney injury, VEGF-A, angiogenesis, angiogenic growth factor, biomarker, cardiac surgery, cytokine, mortality, placental growth factor, soluble VEGF receptor 1, vascular endothelial growth factor A, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

Rationale & objectiveThe process of angiogenesis after kidney injury may determine recovery and long-term outcomes. We evaluated the association of angiogenesis markers with acute kidney injury (AKI) and mortality after cardiac surgery.Study designProspective cohort.Setting & participants1,444 adults undergoing cardiac surgery in the TRIBE-AKI (Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury) cohort.ExposuresPlasma concentrations of 2 proangiogenic markers (vascular endothelial growth factor A [VEGF] and placental growth factor [PGF]) and 1 antiangiogenic marker (soluble VEGF receptor 1 [VEGFR1]), measured pre- and postoperatively within 6 hours after surgery.OutcomesAKI, long AKI duration (≥7 days), and 1-year all-cause mortality.Analytical approachMultivariable logistic regression.ResultsFollowing cardiac surgery, plasma VEGF concentrations decreased 2-fold, and PGF and VEGFR1 concentrations increased 1.5- and 8-fold, respectively. There were no meaningful associations of preoperative concentrations of angiogenic markers with outcomes of AKI and mortality. Higher postoperative VEGF and PGF concentrations were independently associated with lower odds of AKI (adjusted ORs of 0.89 [95% CI, 0.82-0.98] and 0.69 [95% CI, 0.55-0.87], respectively), long AKI duration (0.65 [95% CI, 0.49-0.87] and 0.48 [95% CI, 0.28-0.82], respectively), and mortality (0.74 [95% CI, 0.62-0.89] and 0.46 [95% CI, 0.31-0.68], respectively). In contrast, higher postoperative VEGFR1 concentrations were independently associated with higher odds of AKI (1.56; 95% CI, 1.31-1.87), long AKI duration (1.75; 95% CI, 1.09-2.82), and mortality (2.28; 95% CI, 1.61-3.22).LimitationsAngiogenesis markers were not measured after hospital discharge, so we were unable to determine long-term trajectories of angiogenesis marker levels during recovery and follow-up.ConclusionsHigher levels of postoperative proangiogenic markers, VEGF and PGF, were associated with lower AKI and mortality risk, whereas higher postoperative antiangiogenic VEGFR1 levels were associated with higher risk for AKI and mortality.

Published
2019

18. Effect of Intensive Blood Pressure Lowering on Kidney Tubule Injury: Findings From the ACCORD Trial Study Participants

Author

Nadkarni, Girish N, Chauhan, Kinsuk, Rao, Veena, Ix, Joachim H, Shlipak, Michael G, Parikh, Chirag R, and Coca, Steven G

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Trials and Supportive Activities, Kidney Disease, Prevention, Clinical Research, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Cardiovascular, Renal and urogenital, Good Health and Well Being, Aged, Biomarkers, Female, Glomerular Filtration Rate, Humans, Hypertension, Kidney Tubules, Longitudinal Studies, Male, Middle Aged, Renal Insufficiency, Chronic, CKD progression, Chronic kidney disease, blood pressure, eGFR decline, estimated glomerular filtration rate, hemodynamics, hypertension, intensive BP control, kidney tubule, renal perfusion, tubular injury, urinary biomarkers, urine, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

Rationale & objectiveRandom assignment to intensive blood pressure (BP) lowering (systolic BP

Published
2019

19. Plasma Biomarkers as Risk Factors for Incident CKD

Author

Sarnak, Mark J., Katz, Ronit, Ix, Joachim H., Kimmel, Paul L., Bonventre, Joseph V., Schelling, Jeffrey, Cushman, Mary, Vasan, Ramachandran S., Waikar, Sushrut S., Greenberg, Jason H., Parikh, Chirag R., Coca, Steven G., Sabbisetti, Venkata, Jogalekar, Manasi P., Rebholz, Casey, Zheng, Zihe, Gutierrez, Orlando M., and Shlipak, Michael G.

Published
2022
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20. Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes

Author

Vasquez-Rios, George, Oh, Wonsuk, Lee, Samuel, Bhatraju, Pavan, Mansour, Sherry G., Moledina, Dennis G., Gulamali, Faris F., Siew, Edward D., Garg, Amit X., Sarder, Pinaki, Chinchilli, Vernon M., Kaufman, James S., Hsu, Chi-yuan, Liu, Kathleen D., Kimmel, Paul L., Go, Alan S., Wurfel, Mark M., Himmelfarb, Jonathan, Parikh, Chirag R., Coca, Steven G., and Nadkarni, Girish N.

Published
2023
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23. Kidney Recovery and Death in Critically Ill Patients With COVID-19–Associated Acute Kidney Injury Treated With Dialysis: The STOP-COVID Cohort Study

Author

Gupta, Hsu, Faugno, Goyal, Raichoudhury, Tariq, Meyer, Sharma, Leaf, Kshirsagar, Walther, Carl P., Anumudu, Samaya J., Arunthamakun, Justin, Kopecky, Kathleen F., Milligan, Gregory P., McCullough, Peter A., Nguyen, Thuy-Duyen, Shaefi, Shahzad, Krajewski, Megan L., Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D., Bauer, Kenneth A., Waikar, Sushrut S., Kibbelaar, Zoe A., Athavale, Ambarish M., Hart, Peter, Upadhyay, Shristi, Vohra, Ishaan, Oyintayo, Ajiboye, Green, Adam, Rachoin, Jean-Sebastien, Schorr, Christa A., Shea, Lisa, Edmonston, Daniel L., Mosher, Christopher L., Shehata, Alexandre M., Cohen, Zaza, Allusson, Valerie, Bambrick-Santoyo, Gabriela, Bhatti, Noor ul aain, Mehta, Bijal, WilliamsSamantha K. Brenner, Aquino, Walters, Patricia, Go, Ronaldo C., Rose, Keith M., Hernán, Miguel A., Zhou, Amy M., Kim, Ethan C., Lisk, Rebecca, Chan, Lili, Mathews, Kusum S., Coca, Steven G., Altman, Deena R., Saha, Aparna, Soh, Howard, Wen, Huei Hsun, Bose, Sonali, Leven, Emily A., Wang, Jing G., Mosoyan, Gohar, Pattharanitima, Pattharawin, Gallagher, Emily J., Friedman, Allon N., Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Kelly, Katherine J., Parikh, Chirag R., Garibaldi, Brian T., Corona-Villalobos, Celia P., Wen, Yumeng, Menez, Steven, Malik, Rubab F., Cervantes, Carmen Elena, Gautam, Samir C., Mallappallil, Mary C., Ouyang, Jie, John, Sabu, Yap, Ernie, Melaku, Yohannes, Mohamed, Ibrahim, Bajracharya, Siddhartha, Puri, Isha, Thaxton, Mariah, Bhattacharya, Jyotsna, Wagner, John, Boudourakis, Leon, Nguyen, H. Bryant, Ahoubim, Afshin, Thomas, Leslie F., Sirganagari, Dheeraj Reddy, Guru, Pramod K., Kashani, Kianoush, Tehranian, Shahrzad, Zhou, Yan, Bergl, Paul A., Rodriguez, Jesus, Shah, Jatan A., Gupta, Mrigank S., Kumar, Princy N., Lazarous, Deepa G., Kassaye, Seble G., Melamed, Michal L., Johns. Ryan Mocerino, Tanya S., Prudhvi, Kalyan, Zhu, Denzel, Levy, Rebecca V., Azzi, Yorg, Fisher, Molly, Yunes, Milagros, Sedaliu, Kaltrina, Golestaneh, Ladan, Brogan, Maureen, Thakkar, Jyotsana, Kumar, Neelja, Ross, Michael J., Chang, Michael, Athreya, Akshay, Farag, Mohamed, Schenck, Edward J., Cho, Soo Jung, Plataki, Maria, Alvarez-Mulett, Sergio L., Gomez-Escobar, Luis G., Pan, Di, Lee, Stefi, Krishnan, Jamuna, Whalen, William, Charytan, David, Macina, Ashley, Srivastava, Anand, Leidner, Alexander S., Martinez, Carlos, Kruser, Jacqueline M., Wunderink, Richard G., Hodakowski, Alexander J., Velez, Juan Carlos Q., Price-Haywood, Eboni G., Matute-Trochez, Luis A., Hasty, Anna E., Mohamed, Muner M.B., Avasare, Rupali S., Zonies, David, Al-Samkari, Hanny, Leaf, Rebecca Karp, Rosovsky, Rachel, Sise, Meghan E., Newman, Erik T., Omar, Samah Abu, Pokharel, Kapil K., Sharma, Shreyak, Singh, Harkarandeep, Correa, Simon, Shaukat, Tanveer, Kamal, Omer, Wang, Wei, Lee, Meghan, Strohbehn, Ian A., Li, Jiahua, Mueller, Ariel L., Redfern, Roberta E., Cairl, Nicholas S., Naimy, Gabriel, Abu-Saif, Abeer, Hall, Danyell, Bickley, Laura, Rowan, Chris, Madhani-Lovely, Farah, Peev, Vasil, Reiser, Jochen, Byun, John J., Vissing, Andrew, Kapania, Esha M., Post, Zoe, Patel, Nilam P., Hermes, Joy-Marie, Sutherland, Anne K., Patrawalla, Amee, Finkel, Diana G., Danek, Barbara A., Arikapudi, Sowminya, Paer, Jeffrey M., Cangialosi, Peter, Liotta, Mark, Radbel, Jared, Puri, Sonika, Sunderram, Jag, Scharf, Matthew T., Ahmed, Ayesha, Berim, Ilya, Vatson, Jayanth S., Karp, George, Anand, Shuchi, Levitt, Joseph E., Garcia, Pablo, Boyle, Suzanne M., Song, Rui, Zhang, Jingjing, Woo, Sang Hoon, Deng, Xiaoying, Katz-Greenberg, Goni, Sharshir, Moh’d A., Rusnak, Vadym V., Bansal, Anip, Podoll, Amber S., Chonchol, Michel, Sharma, Sunita, Burnham, Ellen L., Rashidi, Arash, Hejal, Rana, Judd, Eric, Latta, Laura, Tolwani, Ashita, Albertson, Timothy E., Adams, Jason Y., Chang, Steven Y., Beutler, Rebecca M., Schulze, Carl E., Macedo, Etienne, RheeKa, Harin, thleen D. Liu, Jotwani, Vasantha K., Koyner, Jay L., Shah, Chintan V., Jaikaransingh, Vishal, Toth-Manikowski, Stephanie M., Joo, Min J., Lash, James P., Neyra, Javier A., Chaaban, Nourhan, Elias, Madona, Ahmad, Yahya, Dy, Rajany, Iardino, Alfredo, Au, Elizabeth H., Sosa, Marie Anne, Taldone, Sabrina, Contreras, Gabriel, De La Zerda, David, Gershengorn, Hayley B., Fornoni, Alessia, Hayek, Salim S., Blakely, Pennelope, Berlin, Hanna, Azam, Tariq U., Shadid, Husam, Pan, Michael, O’Hayer, Patrick, Meloche, Chelsea, Feroze, Rafey, Padalia, Kishan J., Leya, Jeff, Donnelly, John P., Admon, Andrew J., Flythe, Jennifer E., Tugman, Matthew J., Chang, Emily H., Brown, Brent R., Leonberg-Yoo, Amanda K., Spiardi, Ryan C., Miano, Todd A., Roche, Meaghan S., Vasquez, Charles R., Bansal, Amar D., Ernecoff, Natalie C., Kapoor, Sanjana, Verma, Siddharth, Chen, Huiwen, Kovesdy, Csaba P., Molnar, Miklos Z., Azhar, Ambreen, Hedayati, S. Susan, Nadamuni, Mridula V., Shastri, Shani, Willett, Duwayne L., Short, Samuel A.P., Renaghan, Amanda D., Enfield, Kyle B., Bhatraju, Pavan K., Malik, A. Bilal, Semler, Matthew W., Vijayan, Anitha, Joy, Christina Mariyam, Li, Tingting, Goldberg, Seth, Kao, Patricia F., Schumaker, Greg L., Christov, Marta, Griffiths, Jennifer, Gupta, Sanjeev, Kapoor, Aromma, Chugh, Savneek, Wilson, Perry, Arora, Tanima, Ugwuowo, Ugochukwu, Hsu, Caroline M., Gupta, Shruti, Tighiouart, Hocine, Goyal, Nitender, Faugno, Anthony J., Tariq, Asma, Raichoudhury, Ritesh, Sharma, Jill H., Meyer, Leah, Kshirsagar, Ravi K., Jose, Aju, Leaf, David E., and Weiner, Daniel E.

Published
2022
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25. Pre-exposure Prophylaxis With Tenofovir Disoproxil Fumarate/Emtricitabine and Kidney Tubular Dysfunction in HIV-Uninfected Individuals

Author

Jotwani, Vasantha, Scherzer, Rebecca, Glidden, David V, Mehrotra, Megha, Defechereux, Patricia, Liu, Albert, Gandhi, Monica, Bennett, Michael, Coca, Steven G, Parikh, Chirag R, Grant, Robert M, and Shlipak, Michael G

Subjects
Public Health, Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Sexually Transmitted Infections, Clinical Research, Health Disparities, Prevention, Kidney Disease, Infectious Diseases, Clinical Trials and Supportive Activities, HIV/AIDS, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Renal and urogenital, Adult, Albuminuria, Alpha-Globulins, Anti-HIV Agents, Biomarkers, Cross-Sectional Studies, Emtricitabine, Female, Glomerular Filtration Rate, HIV, HIV Infections, Humans, Kidney Diseases, Kidney Function Tests, Male, Pre-Exposure Prophylaxis, Proteinuria, Tenofovir, Transgender Persons, Urine, Young Adult, HIV prevention, pre-exposure prophylaxis, nephrotoxicity, tubular dysfunction, kidney injury, urine biomarkers, alpha-1 microglobulin, Public Health and Health Services, Virology, Clinical sciences, Epidemiology, Public health
Abstract

BackgroundPre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) is becoming increasingly adopted for HIV prevention. Tenofovir can cause proximal tubular damage and chronic kidney disease in HIV-infected persons, but little is known regarding its nephrotoxic potential among HIV-uninfected persons. In this study, we evaluated the effects of PrEP on urine levels of the following: α1-microglobulin (α1m), a marker of impaired tubular reabsorption; albuminuria, a measure of glomerular injury; and total proteinuria.SettingThe Iniciativa Profilaxis Pre-Exposicion (iPrEx) study randomized HIV-seronegative men and transgender women who have sex with men to oral TDF/FTC or placebo. The iPrEx open-label extension (iPrEx-OLE) study enrolled former PrEP trial participants to receive open-label TDF/FTC.MethodsA cross-sectional analysis compared urine biomarker levels by study arm in iPrEx (N = 100 treatment arm, N = 100 placebo arm). Then, urine biomarker levels were compared before and after PrEP initiation in 109 participants of iPrEx-OLE.ResultsIn iPrEx, there were no significant differences in urine α1m, albuminuria, or proteinuria by treatment arm. In iPrEx-OLE, after 24 weeks on PrEP, urine α1m and proteinuria increased by 21% [95% confidence interval (CI): 10 to 33] and 18% (95% CI: 8 to 28), respectively. The prevalence of detectable α1m increased from 44% to 65% (P < 0.001) and estimated glomerular filtration rate declined by 4 mL/min/1.73 m (P < 0.001). There was no significant change in albuminuria (6%; 95% CI: -7% to 20%).ConclusionPrEP with TDF/FTC was associated with a statistically significant rise in urine α1m and proteinuria after 6 months, suggesting that PrEP may result in subclinical tubule dysfunction.

Published
2018

26. Group analysis identifies differentially elevated biomarkers with distinct outcomes for advanced acute kidney injury in cardiac surgery

Author

Lin, Haiqun, Scherzer, Rebecca, Philbrook, Heather Thiessen, Coca, Steven G, Wilson, Francis Perry, Garg, Amit X, Shlipak, Michael G, and Parikh, Chirag R

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Clinical Research, Kidney Disease, Patient Safety, Cardiovascular, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Aged, Aged, 80 and over, Biomarkers, Cardiac Surgical Procedures, Female, Humans, Male, Middle Aged, Postoperative Complications, advanced AKI, biomarkers of AKI, group-based analysis, Medicinal and Biomolecular Chemistry, Medical Biochemistry and Metabolomics, Oncology & Carcinogenesis, Clinical sciences, Medical biochemistry and metabolomics, Medicinal and biomolecular chemistry
Abstract

AIM:To investigate early postoperative biomarkers for risk discrimination of advanced acute kidney injury (AKI). MATERIALS & METHODS:Postoperative plasma biomarkers including NGAL, h-FABP, CK-MB, hsTNT, NT-proBNP, IL-6, IL-10 and VEGF were analyzed using group-based method among 426 patients with AKI after cardiac surgery. RESULTS:Six patient groups with distinct biomarker patterns were identified. Individual biomarker displayed significant difference across the groups. The groups showed better discrimination for advanced AKI than any single biomarker either with or without adjusting for clinical variables. Average concentration of a single biomarker within each group, mortality and risk of a secondary outcome all demonstrated an approximately U-shaped relationship with proportion of advanced AKI within each group. CONCLUSION:The group-based analysis revealed that the order of the patient groups with an increasing likelihood of advanced AKI had a nonlinear relationship with average concentration of an individual biomarker, mortality and risk of other outcomes.

Published
2017

31. A prospective cohort study of acute kidney injury and kidney outcomes, cardiovascular events, and death

Author

Chinchilli, Vernon M., Go, Alan S., Himmelfarb, Jonathan, Ikizler, T. Alp, Kaufman, James S., Kimmel, Paul L., Parikh, Chirag R., Stokes, John B., Coca, Steven, Garg, Amit, Zheng, Sijie, Pravoverov, Leonid, Hsu, Chi-yuan, Hsu, Raymond K., Liu, Kathleen D., Reeves, W. Brian, Siew, Edward D., Lewis, Julia B., Ware, Lorraine, Devarajan, Prasad, Krawczeski, Catherine, Bennett, Michael, Zappitelli, Michael, Wurfel, Mark, Coca, Steven G., Garg, Amit X., Wurfel, Mark M., Ware, Lorraine B., Faulkner, Georgia Brown, and Tan, Thida C.

Published
2021
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32. National Trends and Impact of Acute Kidney Injury Requiring Hemodialysis in Hospitalizations With Atrial Fibrillation.

Author

Chan, Lili, Mehta, Swati, Chauhan, Kinsuk, Poojary, Priti, Patel, Sagar, Pawar, Sumeet, Patel, Achint, Correa, Ashish, Patel, Shanti, Garimella, Pranav S, Annapureddy, Narender, Agarwal, Shiv Kumar, Gidwani, Umesh, Coca, Steven G, and Nadkarni, Girish N

Subjects
Humans, Sepsis, Liver Failure, Respiratory Insufficiency, Atrial Fibrillation, Respiration, Artificial, Hospitalization, Renal Dialysis, Hospital Mortality, Multivariate Analysis, Logistic Models, Odds Ratio, Comorbidity, Population Growth, Databases, Factual, Adolescent, Adult, Aged, Middle Aged, United States, Female, Male, Young Adult, Acute Kidney Injury, acute kidney injury, atrial fibrillation, dialysis, mortality, Kidney Disease, Assistive Technology, Bioengineering, 2.4 Surveillance and distribution, Renal and urogenital, Cardiovascular, Cardiorespiratory Medicine and Haematology
Abstract

BackgroundAtrial fibrillation (AF) is a common cause for hospitalization, but there are limited data regarding acute kidney injury requiring dialysis (AKI-D) in AF hospitalizations. We aimed to assess temporal trends and outcomes in AF hospitalizations complicated by AKI-D utilizing a nationally representative database.Methods and resultsUtilizing the Nationwide Inpatient Sample, AF hospitalizations and AKI-D were identified using diagnostic and procedure codes. Trends were analyzed overall and within subgroups and utilized multivariable logistic regression to generate adjusted odds ratios (aOR) for predictors and outcomes including mortality and adverse discharge. Between 2003 and 2012, 3751 (0.11%) of 3 497 677 AF hospitalizations were complicated by AKI-D. The trend increased from 0.3/1000 hospitalizations in 2003 to 1.5/1000 hospitalizations in 2012, with higher increases in males and black patients. Temporal changes in demographics and comorbidities explained a substantial proportion but not the entire trend. Significant comorbidities associated with AKI-D included mechanical ventilation (aOR 13.12; 95% CI 9.88-17.43); sepsis (aOR 8.20; 95% CI 6.00-11.20); and liver failure (aOR 3.72; 95% CI 2.92-4.75). AKI-D was associated with higher risk of in-hospital mortality (aOR 3.54; 95% CI 2.81-4.47) and adverse discharge (aOR 4.01; 95% CI 3.12-5.17). Although percentage mortality within AKI-D decreased over the decade, attributable risk percentage mortality remained stable.ConclusionsAF hospitalizations complicated by AKI-D have quintupled over the last decade with differential increase by demographic groups. AKI-D is associated with significant morbidity and mortality. Without effective AKI-D therapies, focus should be on early risk stratification and prevention to avoid this devastating complication.

Published
2016

33. Modulation of the Association Between Age and Death by Risk Factor Burden in Critically Ill Patients With COVID-19

Author

Sunderraj, Ashwin, Cho, Chloe, Cai, Xuan, Gupta, Shruti, Mehta, Rupal, Isakova, Tamara, Leaf, David E., Srivastava, Anand, Walther, Carl P., Anumudu, Samaya J., Arunthamakun, Justin, Kopecky, Kathleen F., Milligan, Gregory P., McCullough, Peter A., Nguyen, Thuy-Duyen, Shaefi, Shahzad, Krajewski, Megan L., Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D., Waikar, Sushrut S., Kibbelaar, Zoe A., Athavale, Ambarish M., Hart, Peter, Upadhyay, Shristi, Vohra, Ishaan, Oyintayo, Ajiboye, Green, Adam, Rachoin, Jean-Sebastien, Schorr, Christa A., Shea, Lisa, Edmonston, Daniel L., Mosher, Christopher L., Shehata, Alexandre M., Cohen, Zaza, Allusson, Valerie, Bambrick-Santoyo, Gabriela, Bhatti, Noor ul aain, Mehta, Bijal, Williams, Aquino, Brenner, Samantha K., Walters, Patricia, Go, Ronaldo C., Rose, Keith M., Hernán, Miguel A., Zhou, Amy M., Kim, Ethan C., Lisk, Rebecca, Chan, Lili, Mathews, Kusum S., Coca, Steven G., Altman, Deena R., Saha, Aparna, Soh, Howard, Hsun Wen, Huei, Bose, Sonali, Leven, Emily A., Wang, Jing G., Mosoyan, Gohar, Nadkarni, Girish N., Pattharanitima, Pattharawin, Gallagher, Emily J., Friedman, Allon N., Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Kelly, Katherine J., Parikh, Chirag R., Garibaldi, Brian T., Corona-Villalobos, Celia P., Wen, Yumeng, Menez, Steven, Malik, Rubab F., Elena Cervantes, Carmen, Gautam, Samir C., Mallappallil, Mary C., Ouyang, Jie, John, Sabu, Yap, Ernie, Melaku, Yohannes, Mohamed, Ibrahim, Bajracharya, Siddhartha, Puri, Isha, Thaxton, Mariah, Bhattacharya, Jyotsna, Wagner, John, Boudourakis, Leon, Bryant Nguyen, H., Ahoubim, Afshin, Thomas, Leslie F., Sirganagari, Dheeraj Reddy, Guru, Pramod K., Kashani, Kianoush, Tehranian, Shahrzad, Zhou, Yan, Bergl, Paul A., Rodriguez, Jesus, Shah, Jatan A., Gupta, Mrigank S., Kumar, Princy N., Lazarous, Deepa G., Kassaye, Seble G., Melamed, Michal L., Johns, Tanya S., Mocerino, Ryan, Prudhvi, Kalyan, Zhu, Denzel, Levy, Rebecca V., Azzi, Yorg, Fisher, Molly, Yunes, Milagros, Sedaliu, Kaltrina, Golestaneh, Ladan, Brogan, Maureen, Kumar, Neelja, Chang, Michael, Thakkar, Jyotsana, Raichoudhury, Ritesh, Athreya, Akshay, Farag, Mohamed, Schenck, Edward J., Cho, Soo Jung, Plataki, Maria, Alvarez-Mulett, Sergio L., Gomez-Escobar, Luis G., Pan, Di, Lee, Stefi, Krishnan, Jamuna, Whalen, William, Charytan, David, Macina, Ashley, Chaudhry, Sobaata, Wu, Benjamin, Modersitzki, Frank, Srivastava, Anand, Leidner, Alexander S., Martinez, Carlos, Kruser, Jacqueline M., Wunderink, Richard G., Hodakowski, Alexander J., Velez, Juan Carlos Q., Price-Haywood, Eboni G., Matute-Trochez, Luis A., Hasty, Anna E., Mohamed, Muner MB., Avasare, Rupali S., Zonies, David, Leaf, David E., Gupta, Shruti, Sise, Meghan E., Newman, Erik T., Abu Omar, Samah, Pokharel, Kapil K., Sharma, Shreyak, Singh, Harkarandeep, Correa, Simon, Shaukat, Tanveer, Kamal, Omer, Wang, Wei, Yang, Heather, Boateng, Jeffery O., Lee, Meghan, Strohbehn, Ian A., Li, Jiahua, Mueller, Ariel L., Redfern, Roberta E., Cairl, Nicholas S., Naimy, Gabriel, Abu-Saif, Abeer, Hall, Danyell, Bickley, Laura, Rowan, Chris, Madhani-Lovely, Farah, Cruz, Vivian S., Hess, Kristen M., Jacobs, Alanna L., Peev, Vasil, Reiser, Jochen, Byun, John J., Vissing, Andrew, Kapania, Esha M., Post, Zoe, Patel, Nilam P., Hermes, Joy-Marie, Sutherland, Anne K., Patrawalla, Amee, Finkel, Diana G., Danek, Barbara A., Arikapudi, Sowminya, Paer, Jeffrey M., Cangialosi, Peter, Liotta, Mark, Radbel, Jared, Puri, Sonika, Sunderram, Jag, Scharf, Matthew T., Ahmed, Ayesha, Berim, Ilya, Vatson, Jayanth S., Anand, Shuchi, Levitt, Joseph E., Garcia, Pablo, Boyle, Suzanne M., Song, Rui, Zhang, Jingjing, Hoon Woo, Sang, Deng, Xiaoying, Katz-Greenberg, Goni, Senter, Katharine, Sharshir, Moh’d A., Rusnak, Vadym V., Ali, Muhammad Imran, Bansal, Anip, Podoll, Amber S., Chonchol, Michel, Sharma, Sunita, Burnham, Ellen L., Douin, David J., Rashidi, Arash, Hejal, Rana, Judd, Eric, Latta, Laura, Tolwani, Ashita, Albertson, Timothy E., Adams, Jason Y., Chang, Steven Y., Beutler, Rebecca M., Schulze, Carl E., Macedo, Etienne, Rhee, Harin, Liu, Kathleen D., Jotwani, Vasantha K., Koyner, Jay L., Shah, Chintan V., Jaikaransingh, Vishal, Toth-Manikowski, Stephanie M., Joo, Min J., Lash, James P., Neyra, Javier A., Chaaban, Nourhan, Elias, Madona, Ahmad, Yahya, Iardino, Alfredo, Au, Elizabeth H., Sharma, Jill H., Anne Sosa, Marie, Taldone, Sabrina, Contreras, Gabriel, De La Zerda, David, Gershengorn, Hayley B., Shukla, Bhavarth, Fornoni, Alessia, Ferreira, Tanira, Hayek, Salim S., Blakely, Pennelope, Berlin, Hanna, Azam, Tariq U., Shadid, Husam, Pan, Michael, O’ Hayer, Patrick, Meloche, Chelsea, Feroze, Rafey, Kaakati, Rayan, Perry, Danny, Bitar, Abbas, Anderson, Elizabeth, Padalia, Kishan J., Donnelly, John P., Admon, Andrew J., Flythe, Jennifer E., Tugman, Matthew J., Chang, Emily H., Brown, Brent R., Leonberg-Yoo, Amanda K., Spiardi, Ryan C., Miano, Todd A., Roche, Meaghan S., Vasquez, Charles R., Bansal, Amar D., Ernecoff, Natalie C., Kapoor, Sanjana, Verma, Siddharth, Chen, Huiwen, Kovesdy, Csaba P., Molnar, Miklos Z., Azhar, Ambreen, Susan Hedayati, S., Nadamuni, Mridula V., Shastri, Shani, Willett, Duwayne L., Short, Samuel A.P., Renaghan, Amanda D., Enfield, Kyle B., Bhatraju, Pavan K., Bilal Malik, A., Semler, Matthew W., Vijayan, Anitha, Mariyam Joy, Christina, Li, Tingting, Goldberg, Seth, Kao, Patricia F., Schumaker, Greg L., Goyal, Nitender, Faugno, Anthony J., Schumaker, Greg L., Hsu, Caroline M., Tariq, Asma, Meyer, Leah, Kshirsagar, Ravi K., Weiner, Daniel E., Jose, Aju, Christov, Marta, Griffiths, Jennifer, Gupta, Sanjeev, Kapoor, Aromma, Wilson, Perry, Arora, Tanima, and Ugwuowo, Ugochukwu

Published
2022
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39. Association of Peak Changes in Plasma Cystatin C and Creatinine With Death After Cardiac Operations

Author

Park, Meyeon, Shlipak, Michael G, Thiessen-Philbrook, Heather, Garg, Amit X, Koyner, Jay L, Coca, Steven G, Parikh, Chirag R, and Consortium, Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury

Subjects
Kidney Disease, Heart Disease, Cardiovascular, Clinical Research, Renal and urogenital, Acute Kidney Injury, Adult, Aged, Aged, 80 and over, Biomarkers, Cardiac Surgical Procedures, Creatinine, Cystatin C, Female, Hospitalization, Humans, Longitudinal Studies, Male, Middle Aged, Time Factors, Translational Research Investigating Biomarker Endpoints in Acute Kidney Injury Consortium, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Respiratory System
Abstract

BackgroundAcute kidney injury is a risk factor for death in cardiac surgical patients. Plasma cystatin C and creatinine have different temporal profiles in the postoperative setting, but the associations of simultaneous changes in both filtration markers compared with change in only one marker with prognosis after hospital discharge are not well described.MethodsThis is a longitudinal study of 1,199 high-risk adult cardiac surgical patients in the TRIBE-AKI (Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury) Consortium who survived hospitalization. We examined in-hospital peak changes of cystatin C and creatinine in the 3 days after cardiac operations. We evaluated associations of these filtration markers with death, adjusting for demographics, operative characteristics, medical comorbidities, preoperative estimated glomerular filtration rate, preoperative urinary albumin-to-creatinine ratio, and site.ResultsDuring the first 3 days of hospitalization, nearly twice as many patients had a 25% or higher rise in creatinine (30%) compared with a 25% or higher peak rise in cystatin C (15%). The risk of death was higher in those with elevations in cystatin C (adjusted hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.4 to 2.37) or creatinine (adjusted HR, 1.90; 95% CI, 1.32 to 2.72) compared with patients who experienced a postoperative decrease in either filtration marker. Patients who had simultaneous elevations of 25% or higher in cystatin C and creatinine were at similar adjusted risk for 3-year mortality (HR, 1.79; 95% CI, 1.03 to 3.1) as those with a 25% or higher increase in cystatin C alone (HR, 2.2; 95% CI, 1.09 to 4.47).ConclusionsElevations in creatinine postoperatively are more common than elevations in cystatin C. However, elevations in cystatin C appeared to be associated with a higher risk of death after hospital discharge.

Published
2016

40. Urine Biomarkers and Perioperative Acute Kidney Injury: The Impact of Preoperative Estimated GFR

Author

Koyner, Jay L, Coca, Steven G, Thiessen-Philbrook, Heather, Patel, Uptal D, Shlipak, Michael G, Garg, Amit X, Parikh, Chirag R, Consortium, Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury, Raman, Jai, Jeevanandam, Valluvan, Akhter, Shahab, Devarajan, Prasad, Bennett, Michael, Ma, Qing, Griffiths, Rachel, Edelstein, Charles, Passik, Cary, Nagy, Judy, Swaminathan, Madhav, Chu, Michael, Goldbach, Martin, Guo, Lin Ruo, McKenzie, Neil, Myers, Mary Lee, Novick, Richard, Quantz, Mac, Schumann, Virginia, Webster, Laura, Zappitelli, Michael, Palijan, Ana, Dewar, Michael, Darr, Umer, Hashim, Sabet, Elefteriades, John, Geirsson, Arnar, Garwood, Susan, Kemp, Rowena, and Butrymowicz, Isabel

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Kidney Disease, Clinical Research, Renal and urogenital, Acute Kidney Injury, Aged, Aged, 80 and over, Biomarkers, Cardiac Surgical Procedures, Cohort Studies, Creatinine, Cystatin C, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Postoperative Complications, Prospective Studies, Urine biomarkers, interleukin 18, liver-type fatty acid binding protein, acute renal failure, acute kidney injury, perioperative AKI, effect modification, estimated glomerular filtration rate, prognosis, cardiac surgery, surgical complication, Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury (TRIBE-AKI) Consortium, Translational Research Investigating Biomarker Endpoints for Acute Kidney Injury TRIBE-AKI Consortium, Public Health and Health Services, Urology & Nephrology, Clinical sciences
Abstract

BackgroundThe interaction between baseline kidney function and the performance of biomarkers of acute kidney injury (AKI) on the development of AKI is unclear.Study designPost hoc analysis of prospective cohort study.Setting & participantsThe 1,219 TRIBE-AKI Consortium adult cardiac surgery cohort participants.PredictorUnadjusted postoperative urinary biomarkers of AKI measured within 6 hours of surgery.OutcomeAKI was defined as AKI Network stage 1 (any AKI) or higher, as well as a doubling of serum creatinine level from the preoperative value or the need for post-operative dialysis (severe AKI).MeasurementsStratified analyses by preoperative estimated glomerular filtration rate (eGFR) ≤ 60 versus > 60mL/min/1.73m(2).Results180 (42%) patients with preoperative eGFRs≤60mL/min/1.73m(2) developed clinical AKI compared with 246 (31%) of those with eGFRs>60mL/min/1.73m(2) (P

Published
2015

46. Association Between Preoperative Statin Use and Acute Kidney Injury Biomarkers in Cardiac Surgical Procedures

Author

Molnar, Amber O, Parikh, Chirag R, Coca, Steven G, Thiessen-Philbrook, Heather, Koyner, Jay L, Shlipak, Michael G, Myers, Mary Lee, Garg, Amit X, and Consortium, TRIBE-AKI

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease, Clinical Research, Kidney Disease, Cardiovascular, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Renal and urogenital, Good Health and Well Being, Acute Kidney Injury, Acute-Phase Proteins, Adult, Aged, Biomarkers, Cardiac Surgical Procedures, Cohort Studies, Female, Hepatitis A Virus Cellular Receptor 1, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Interleukin-18, Lipocalin-2, Lipocalins, Male, Membrane Glycoproteins, Middle Aged, Prospective Studies, Proto-Oncogene Proteins, Receptors, Virus, TRIBE-AKI Consortium, Cardiorespiratory Medicine and Haematology, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract

BackgroundAcute kidney injury (AKI) is a serious complication of cardiac operations for which there remains no specific therapy. Animal data and several observational studies suggest that statins prevent AKI, but the results are not conclusive, and many studies are retrospective in nature.MethodsWe conducted a multicenter prospective cohort study of 625 adult patients undergoing elective cardiac operations. All patients were taking statins and were grouped according to whether statins were continued or held in the 24 hours before operation. The primary outcome was AKI as defined by a doubling of serum creatinine or dialysis. The secondary outcome was the peak level of several kidney injury biomarkers. The results were adjusted for demographic and clinical factors.ResultsContinuing (vs holding) a statin before operation was not associated with a lower risk of AKI, as defined by a doubling of serum creatinine or dialysis (adjusted relative risk [RR] 1.09; 95% confidence interval [CI] 0.44, 2.70). However, continuing a statin was associated with a lower risk of elevation of the following AKI biomarkers: urine interleukin-18, urine neutrophil gelatinase-associated lipocalin, urine kidney injury molecule-1, and plasma neutrophil gelatinase-associated lipocalin (adjusted RR 0.34; 95% CI 0.18, 0.62), (adjusted RR 0.41; 95% CI 0.22, 0.76), (adjusted RR 0.37; 95% CI 0.20, 0.76), (adjusted RR 0.62; 95% CI 0.39, 0.98), respectively.ConclusionsStatins may prevent kidney injury after cardiac operations, as evidenced by lower levels of kidney injury biomarkers.

Published
2014

47. Comparison of predicting cardiovascular disease hospitalization using individual, ZIP code-derived, and machine learning model-predicted educational attainment in New York City.

Author

Takkavatakarn, Kullaya, Dai, Yang, Hsun Wen, Huei, Kauffman, Justin, Charney, Alexander, Coca, Steven G., Nadkarni, Girish N., and Chan, Lili

Subjects
EDUCATIONAL attainment, MACHINE learning, AMERICAN Community Survey, CARDIOVASCULAR diseases, ETHNICITY, ZIP codes
Abstract

Background: Area-level social determinants of health (SDOH) based on patients' ZIP codes or census tracts have been commonly used in research instead of individual SDOHs. To our knowledge, whether machine learning (ML) could be used to derive individual SDOH measures, specifically individual educational attainment, is unknown. Methods: This is a retrospective study using data from the Mount Sinai BioMe Biobank. We included participants that completed a validated questionnaire on educational attainment and had home addresses in New York City. ZIP code-level education was derived from the American Community Survey matched for the participant's gender and race/ethnicity. We tested several algorithms to predict individual educational attainment from routinely collected clinical and demographic data. To evaluate how using different measures of educational attainment will impact model performance, we developed three distinct models for predicting cardiovascular (CVD) hospitalization. Educational attainment was imputed into models as either survey-derived, ZIP code-derived, or ML-predicted educational attainment. Results: A total of 20,805 participants met inclusion criteria. Concordance between survey and ZIP code-derived education was 47%, while the concordance between survey and ML model-predicted education was 67%. A total of 13,715 patients from the cohort were included into our CVD hospitalization prediction models, of which 1,538 (11.2%) had a history of CVD hospitalization. The AUROC of the model predicting CVD hospitalization using survey-derived education was significantly higher than the model using ZIP code-level education (0.77 versus 0.72; p < 0.001) and the model using ML model-predicted education (0.77 versus 0.75; p < 0.001). The AUROC for the model using ML model-predicted education was also significantly higher than that using ZIP code-level education (p = 0.003). Conclusion: The concordance of survey and ZIP code-level educational attainment in NYC was low. As expected, the model utilizing survey-derived education achieved the highest performance. The model incorporating our ML model-predicted education outperformed the model relying on ZIP code-derived education. Implementing ML techniques can improve the accuracy of SDOH data and consequently increase the predictive performance of outcome models. [ABSTRACT FROM AUTHOR]

Published
2024
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48. A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease.

Author

Tokita, Joji, Lam, David, Vega, Aida, Wang, Stephanie, Amoruso, Leonard, Muller, Tamara, Naik, Nidhi, Rathi, Shivani, Martin, Sharlene, Zabetian, Azadeh, Liu, Catherine, Sinfield, Catherine, McNicholas, Tony, Fleming, Fergus, Coca, Steven G., Nadkarni, Girish N, Tun, Roger, Kattan, Mike, Donovan, Michael J., and Rahim, Arshad K.

Subjects
BIOMARKERS, IN vitro studies, KIDNEYS, CONFIDENCE intervals, MACHINE learning, TYPE 2 diabetes, PRE-tests & post-tests, T-test (Statistics), RESEARCH funding, ODDS ratio, EARLY diagnosis, DIABETIC nephropathies
Abstract

Introduction/Objective: The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health. Methods: The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program. Results: A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m2, urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group (P <.001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from −7.08 ml/min/1.73 m2/year to −4.27 ml/min/1.73 m2/year in high-risk patients (P =.0003), −2.65 to −1.04 in intermediate risk, and −3.26 ml/min/1.73 m2/year to +0.45 ml/min/1.73 m2/year in patients with low-risk (P <.001). Conclusions: Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Machine Learning Prediction of Death in Critically Ill Patients With Coronavirus Disease 2019

Author

Churpek, Matthew M., Gupta, Shruti, Spicer, Alexandra B., Hayek, Salim S., Srivastava, Anand, Chan, Lili, Melamed, Michal L., Brenner, Samantha K., Radbel, Jared, Madhani-Lovely, Farah, Bhatraju, Pavan K., Bansal, Anip, Green, Adam, Goyal, Nitender, Shaefi, Shahzad, Parikh, Chirag R., Semler, Matthew W., Leaf, David E., Walther, Carol P., Anumudu, Samaya J., Arunthamakun, Justin, Kopecky, Kathleen F., Milligan, Gregory P., McCullough, Peter A., Nguyen, ThuyDuyen, Shaefi, Shahzad, Krajewski, Megan L., Shankar, Sidharth, Pannu, Ameeka, Valencia, Juan D., Waikar, Sushrut S., Kibbelaar, Zoe A., Athavale, Ambarish M., Hart, Peter, Ajiboye, Oyintayo, Itteera, Matthew, Green, Adam, Rachoin, Jean-Sebastien, Schorr, Christa A., Shea, Lisa, Edmonston, Daniel L., Mosher, Christopher L., Shehata, Alexandre M., Cohen, Zaza, Allusson, Valerie, Bambrick-Santoyo, Gabriela, Bhatti, Noor ul aain, Metha, Bijal, Williams, Aquino, Brenner, Samantha K., Walters, Patricia, Go, Ronaldo C., Rose, Keith M., Hernán, Miguel A., Zhou, Amy M., Kim, Ethan C., Lisk, Rebecca, Chan, Lili, Mathews, Kusum S., Coca, Steven G., Altman, Deena R., Saha, Aparna, Soh, Howard, Wen, Huei Hsun, Bose, Sonali, Leven, Emily, Wang, Jing G., Mosoyan, Gohar, Nadkarni, Girish N., Friedman, Allon N., Guirguis, John, Kapoor, Rajat, Meshberger, Christopher, Parikh, Chirag R., Garibaldi, Brian T., Corona-Villalobos, Celia P., Wen, Yumeng, Menez, Steven, Malik, Rubab F., Cervantes, Carmen Elena, Gautam, Samir C., Chang, Crystal, Nguyen, H. Bryant, Ahoubim, Afshin, Thomas, Leslie F., Guru, Pramod K., Bergl, Paul A., Zhou, Yan, Rodriguez, Jesus, Shah, Jatan A., Gupta, Mrigank S., Kumar, Princy N., Lazarous, Deepa G., Kassaye, Seble G., Melamed, Michal L., Johns, Tanya S., Mocerino, Ryan, Prudhvi, Kalyan, Zhu, Denzel, Levy, Rebecca V., Azzi, Yorg, Fisher, Molly, Yunes, Milagros, Sedaliu, Kaltrina, Golestaneh, Ladan, Brogan, Maureen, Thakkar, Jyotsana, Kumar, Neelja, Ross, Michael J., Chang, Michael, Raichoudhury, Ritesh, Schenck, Edward J., Cho, Soo Jung, Plataki, Maria, Alvarez-Mulett, Sergio L., Gomez-Escobar, Luis G., Pan, Di, Lee, Stefi, Krishnan, Jamuna, Whalen, William, Charytan, David, Macina, Ashley, Ross, Daniel W., Srivastava, Anand, Leidner, Alexander S., Martinez, Carlos, Kruser, Jacqueline M., Wunderink, Richard G., Hodakowski, Alexander J., Velez, Juan Carlos Q., Price-Haywood, Eboni G., Matute-Trochez, Luis A., Hasty, Anna E., Mohamed, Muner MB., Avasare, Rupali S., Zonies, David, Leaf, David E., Gupta, Shruti, Baron, Rebecca M., Sise, Meghan E., Newman, Erik T., Omar, Samah Abu, Pokharel, Kapil K., Sharma, Shreyak, Singh, Harkarandeep, Gaviria, Simon Correa, Shaukat, Tanveer, Kamal, Omer, Wang, Wei, Yang, Heather, Boateng, Jeffery O., Lee, Meghan, Strohbehn, Ian A., Li, Jiahua, Muhsin, Saif A., Mandel, Ernest I., Mueller, Ariel L., Cairl, Nicholas S., Madhani-Lovely, Farah, Rowan, Chris, Madhai-Lovely, Farah, Peev, Vasil, Reiser, Jochen, Byun, John J., Vissing, Andrew, Kapania, Esha M., Post, Zoe, Patel, Nilam P., Hermes, Joy-Marie, Sutherland, Anne K., Patrawalla, Amee, Finkel, Diana G., Danek, Barbara A., Arikapudi, Sowminya, Paer, Jeffrey M., Radbel, Jared, Puri, Sonika, Sunderram, Jag, Scharf, Matthew T., Ahmed, Ayesha, Berim, Ilya, Vatson, Jayanth, Anand, Shuchi, Levitt, Joseph E., Garcia, Pablo, Boyle, Suzanne M., Song, Rui, Zhang, Jingjing, Sharshir, Moh’d A., Rusnak, Vadym V., Bansal, Anip, Podoll, Amber S., Chonchol, Michel, Sharma, Sunita, Burnham, Ellen L., Rashidi, Arash, Hejal, Rana, Judd, Eric, Latta, Laura, Tolwani, Ashita, Albertson, Timothy E., Adams, Jason Y., Chang, Steven Y., Beutler, Rebecca M., Schulze, Carl E., Macedo, Etienne, Rhee, Harin, Liu, Kathleen D., Jotwani, Vasantha K., Koyner, Jay L., Shah, Chintan V., Jaikaransingh, Vishal, Toth-Manikowski, Stephanie M., Joo, Min J., Lash, James P., Neyra, Javier A., Chaaban, Nourhan, Iardino, Alfredo, Au, Elizabeth H., Sharma, Jill H., Anne Sosa, Marie, Taldone, Sabrina, Contreras, Gabriel, De La Zerda, David, Gershengorn, Hayley B., Hayek, Salim S., Blakely, Pennelope, Berlin, Hanna, Azam, Tariq U., Shadid, Husam, Pan, Michael, Hayer, Patrick O’, Meloche, Chelsea, Feroze, Rafey, Padalia, Kishan J., Leya, Jeff, Donnelly, John P., Admon, Andrew J., Flythe, Jennifer E., Tugman, Matthew J., Brown, Brent R., Leonberg-Yoo, Amanda K., Spiardi, Ryan C., Miano, Todd A., Roche, Meaghan S., Vasquez, Charles R., Bansal, Amar D., Ernecoff, Natalie C., Kovesdy, Csaba P., Molnar, Miklos Z., Hedayati, S. Susan, Nadamuni, Mridula V., Khan, Sadaf S., Willett, Duwayne L., Short, Samuel A.P., Renaghan, Amanda D., Bhatraju, Pavan, Malik, A. Bilal, Semler, Matthew W., Vijayan, Anitha, Mariyam Joy, Christina, Li, Tingting, Goldberg, Seth, Kao, Patricia F., Schumaker, Greg L., Goyal, Nitender, Faugno, Anthony J., Schumaker, Greg L., Hsu, Caroline M., Tariq, Asma, Meyer, Leah, Christov, Marta, Wilson, Francis P., Arora, Tanima, and Ugwuowo, Ugochukwu

Published
2021
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