1,482 results on '"Kimmel, Paul"'
Search Results
2. Adapting a pain coping skills training intervention for people with chronic pain receiving maintenance hemodialysis for end stage Kidney disease
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Steel, Jennifer L., Brintz, Carrie E., Heapy, Alicia A., Keefe, Francis, Cheatle, Martin D., Jhamb, Manisha, McNeil, Daniel W., Shallcross, Amanda J., Kimmel, Paul L., Dember, Laura M., White, David M., Williams, Joey, and Cukor, Daniel
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- 2024
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3. Urine Biomarkers of Kidney Tubule Health and Risk of Incident CKD in Persons Without Diabetes: The ARIC, MESA, and REGARDS Studies
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Amatruda, Jonathan G, Katz, Ronit, Rebholz, Casey M, Sarnak, Mark J, Gutierrez, Orlando M, Schrauben, Sarah J, Greenberg, Jason H, Coresh, Josef, Cushman, Mary, Waikar, Sushrut, Parikh, Chirag R, Schelling, Jeffrey R, Jogalekar, Manasi P, Bonventre, Joseph V, Vasan, Ramachandran S, Kimmel, Paul L, Ix, Joachim H, Shlipak, Michael G, and Consortium, CKD Biomarkers
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Biomedical and Clinical Sciences ,Clinical Sciences ,Kidney Disease ,Health Disparities ,Atherosclerosis ,Prevention ,Aging ,6.1 Pharmaceuticals ,Renal and urogenital ,Good Health and Well Being ,CKD Biomarkers Consortium ,Alpha-1-microglobulin ,case-cohort ,chitinase-3-like protein 1 ,chronic kidney disease ,epidermal growth factor ,kidney injury molecule-1 ,kidney tubules ,monocyte chemoattractant protein-1 ,tubulointerstitium ,urine biomarkers ,Clinical sciences - Abstract
Rationale & objectiveTubulointerstitial damage is a feature of early chronic kidney disease (CKD), but current clinical tests capture it poorly. Urine biomarkers of tubulointerstitial health may identify risk of CKD.Study designProspective cohort (Atherosclerosis Risk in Communities [ARIC]) and case-cohort (Multi-Ethnic Study of Atherosclerosis [MESA] and Reasons for Geographic and Racial Differences in Stroke [REGARDS]).Setting & participantsAdults with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 and without diabetes in the ARIC, REGARDS, and MESA studies.ExposuresBaseline urine monocyte chemoattractant protein-1 (MCP-1), alpha-1-microglobulin (α1m), kidney injury molecule-1, epidermal growth factor, and chitinase-3-like protein 1.OutcomeIncident CKD or end-stage kidney disease.Analytical approachMultivariable Cox proportional hazards regression for each cohort; meta-analysis of results from all 3 cohorts.Results872 ARIC participants (444 cases of incident CKD), 636 MESA participants (158 cases), and 924 REGARDS participants (488 cases) were sampled. Across cohorts, mean age ranged from 60 ± 10 to 63 ± 8 years, and baseline eGFR ranged from 88 ± 13 to 91 ± 14 mL/min/1.73 m2. In ARIC, higher concentrations of urine MCP-1, α1m, and kidney injury molecule-1 were associated with incident CKD. In MESA, higher concentration of urine MCP-1 and lower concentration of epidermal growth factor were each associated with incident CKD. In REGARDS, none of the biomarkers were associated with incident CKD. In meta-analysis of all 3 cohorts, each 2-fold increase α1m concentration was associated with incident CKD (HR, 1.19; 95% CI, 1.08-1.31).LimitationsObservational design susceptible to confounding; competing risks during long follow-up period; meta-analysis limited to 3 cohorts.ConclusionsIn 3 combined cohorts of adults without prevalent CKD or diabetes, higher urine α1m concentration was independently associated with incident CKD. 4 biomarkers were associated with incident CKD in at least 1 of the cohorts when analyzed individually. Kidney tubule health markers might inform CKD risk independent of eGFR and albuminuria.
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- 2024
4. Comparative CKD risk prediction using homocitrulline and carbamylated albumin: two circulating markers of protein carbamylation
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Awwad, Aya, Rhee, Eugene P., Grams, Morgan, Choles, Hernan Rincon, Sondheimer, James, He, Jiang, Chen, Jing, Hsu, Chi-yuan, Vasan, Ramachandran S, Kimmel, Paul L., Wulczyn, Kendra, Berg, Anders, Lash, Jim, Tang, Mengyao, and Kalim, Sahir
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- 2024
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5. Associations of Biomarkers of Kidney Tubule Health, Injury, and Inflammation with Left Ventricular Hypertrophy in Children with CKD.
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Jiang, Kuan, Greenberg, Jason, Abraham, Alison, Xu, Yunwen, Schelling, Jeffrey, Feldman, Harold, Schrauben, Sarah, Waikar, Sushrut, Shlipak, Michael, Coca, Steven, Vasan, Ramachandran, Gutierrez, Orlando, Ix, Joachim, Warady, Bradley, Kimmel, Paul, Bonventre, Joseph, Parikh, Chirag, Mitsnefes, Mark, Denburg, Michelle, Furth, Susan, and Wettersten, Nicholas
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Humans ,Child ,Hypertrophy ,Left Ventricular ,Inflammation ,Renal Insufficiency ,Chronic ,Kidney Tubules ,Biomarkers - Abstract
KEY POINTS: Higher plasma and urine kidney injury molecule-1, urine monocyte chemoattractant protein-1, and lower urine alpha-1-microglobulin were associated with left ventricular hypertrophy, even after adjustment for confounders. Biomarkers of tubular injury, dysfunction, and inflammation may indicate the severity of kidney pathology and are associated with left ventricular hypertrophy. BACKGROUND: Left ventricular hypertrophy (LVH) is common in children with CKD and is associated with an increased risk of cardiovascular disease and mortality. We have shown that several plasma and urine biomarkers are associated with increased risk of CKD progression. As CKD is associated with LVH, we sought to investigate the association between the biomarkers and LVH. METHODS: In the CKD in Children Cohort Study, children aged 6 months to 16 years with an eGFR of 30–90 ml/min per 1.73 m2 were enrolled at 54 centers in the United States and Canada. We measured plasma biomarkers kidney injury molecule-1 (KIM-1), tumor necrosis factor receptor-1, tumor necrosis factor receptor-2, soluble urokinase-type plasminogen activator receptor and urine KIM-1, monocyte chemoattractant protein-1 (MCP-1), YKL-40, alpha-1-microglobulin (alpha-1m), and epidermal growth factor in stored plasma and urine collected 5 months after enrollment. Echocardiograms were performed 1 year after enrollment. We assessed the cross-sectional association between the log2 biomarker levels and LVH (left ventricular mass index greater than or equal to the 95th percentile) using a Poisson regression model, adjusted for age, sex, race, body mass index, hypertension, glomerular diagnosis, urine protein-to-creatinine ratio, and eGFR at study entry. RESULTS: Among the 504 children, LVH prevalence was 12% (n=59) 1 year after enrollment. In a multivariable-adjusted model, higher plasma and urine KIM-1 and urine MCP-1 concentrations were associated with a higher prevalence of LVH (plasma KIM-1 prevalence ratio [PR] per log2: 1.27, 95% confidence interval [CI], 1.02 to 1.58; urine KIM-1 PR: 1.21, 95% CI, 1.11 to 1.48; and urine MCP-1 PR: 1.18, 95% CI, 1.04 to 1.34). After multivariable adjustment for covariates, lower urine alpha-1m was also associated with a higher prevalence of LVH (PR: 0.90, 95% CI, 0.82 to 0.99). CONCLUSIONS: Higher plasma and urine KIM-1, urine MCP-1, and lower urine alpha-1m were each associated with LVH prevalence in children with CKD. These biomarkers may better inform risk and help elucidate the pathophysiology of LVH in pediatric CKD.
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- 2023
6. Association of Kidney Tubule Biomarkers With Cardiac Structure and Function in the Multiethnic Study of Atherosclerosis
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Wettersten, Nicholas, Katz, Ronit, Greenberg, Jason H, Gutierrez, Orlando M, Lima, Joao AC, Sarnak, Mark J, Schrauben, Sarah, Deo, Rajat, Bonventre, Joseph, Vasan, Ramachandran S, Kimmel, Paul L, Shlipak, Michael, and Ix, Joachim H
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Biomedical and Clinical Sciences ,Clinical Sciences ,Prevention ,Heart Disease ,Kidney Disease ,Atherosclerosis ,Cardiovascular ,2.1 Biological and endogenous factors ,Renal and urogenital ,Good Health and Well Being ,Male ,Humans ,Middle Aged ,Aged ,Female ,Receptors ,Urokinase Plasminogen Activator ,Stroke Volume ,Albuminuria ,Ventricular Function ,Left ,Kidney Tubules ,Renal Insufficiency ,Chronic ,Cardiovascular Diseases ,Glomerular Filtration Rate ,Inflammation ,Biomarkers ,Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology - Abstract
Markers of glomerular disease, estimated glomerular filtration rate (eGFR) and albuminuria, are associated with cardiac structural abnormalities and incident cardiovascular disease (CVD). We aimed to determine whether biomarkers of kidney tubule injury, function, and systemic inflammation are associated with cardiac structural abnormalities. Among 393 Multi-Ethnic Study of Atherosclerosis participants without diabetes, CVD, or chronic kidney disease, we assessed the association of 12 biomarkers of kidney tubule injury, function, and systemic inflammation with the left ventricular mass/volume ratio (LVmvr) and left ventricular ejection fraction (LVEF) on cardiac magnetic resonance imaging using linear regression. The average age was 60 ± 10 years; 48% were men; mean eGFR was 96±16 ml/min/1.73 m2; mean LVmvr was 0.93±0.18 g/ml, and mean LVEF was 62±6%. Each twofold greater concentration of plasma soluble urokinase plasminogen activator receptor was associated with a 0.04 g/ml (95% confidence interval [CI] 0.01 to 0.08 g/ml) higher LVmvr and 2.1% (95% CI 0.6 to 3.5%) lower LVEF, independent of risk factors for CVD, eGFR, and albuminuria. Each twofold greater plasma monocyte chemoattractant protein 1 was associated with higher LVmvr with a similar coefficient to that of plasma soluble urokinase plasminogen activator receptor. Each twofold greater concentration of plasma chitinase-3-like protein 1 and urine alpha-1-microglobulin was associated with a 1.1% (95% CI 0.4 to 1.7%) and 1.2% (95% CI 0.2 to 2.2%) lower LVEF, respectively. In conclusion, abnormal kidney tubule health may lead to cardiac dysfunction above and beyond eGFR and albuminuria.
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- 2023
7. Proteomic Assessment of the Risk of Secondary Cardiovascular Events among Individuals with CKD
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Deo, Rajat, Dubin, Ruth F., Ren, Yue, Wang, Jianqiao, Feldman, Harold, Shou, Haochang, Coresh, Josef, Grams, Morgan E., Surapaneni, Aditya L., Cohen, Jordana B., Kansal, Mayank, Rahman, Mahboob, Dobre, Mirela, He, Jiang, Kelly, Tanika, Go, Alan S., Kimmel, Paul L., Vasan, Ramachandran S., Segal, Mark R., Li, Hongzhe, and Ganz, Peter
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- 2024
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8. Opioid Prescriptions for US Patients Undergoing Long-Term Dialysis or with Kidney Transplant from 2011 to 2020
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Kimmel, Paul L., Fwu, Chyng-Wen, Nolin, Thomas D., Schulman, Ivonne H., Givens, Shannon S., Wilkins, Kenneth J., Mendley, Susan R., Gipson, Debbie S., Greer, Raquel C., Norton, Jenna M., Chan, Kevin E., and Eggers, Paul W.
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- 2024
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9. Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease.
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Dubin, Ruth F, Deo, Rajat, Ren, Yue, Lee, Hongzhe, Shou, Haochang, Feldman, Harold, Kimmel, Paul, Waikar, Sushrut S, Rhee, Eugene P, Tin, Adrienne, Chen, Jingsha, Coresh, Joseph, Go, Alan S, Kelly, Tanika, Rao, Paduranga S, Chen, Teresa K, Segal, Mark R, and Ganz, Peter
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Biomedical and Clinical Sciences ,Clinical Sciences ,Kidney Disease ,Minority Health ,Women's Health ,4.1 Discovery and preclinical testing of markers and technologies ,Renal and urogenital ,Humans ,Female ,Proteomics ,Cohort Studies ,Renal Insufficiency ,Chronic ,Biomarkers ,Diabetes Mellitus - Abstract
BackgroundWe carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD).MethodsPlasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays.ResultsA total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all.ConclusionsIntra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.
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- 2023
10. Longitudinal biomarkers and kidney disease progression after acute kidney injury.
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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
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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).
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- 2023
11. Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.
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Coca, Steven, Vasquez-Rios, George, Mansour, Sherry, Moledina, Dennis, Thiessen-Philbrook, Heather, Wurfel, Mark, Bhatraju, Pavan, Himmelfarb, Jonathan, Siew, Eddie, Garg, Amit, Hsu, Chi-Yuan, Kimmel, Paul, Chinchilli, Vernon, Kaufman, James, Wilson, Michelle, Banks, Rosamonde, Packington, Rebecca, McCole, Eibhlin, Kurth, Mary, Richardson, Ciaran, Go, Alan, Selby, Nicholas, Parikh, Chirag, and Liu, Kathleen
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AKI follow-up ,Acute kidney injury (AKI) ,biomarker ,end-stage kidney disease (ESKD) ,heart failure ,hospitalization ,kidney disease progression ,mortality ,prognosis ,risk stratification ,sTNFR2 ,soluble tumor necrosis factor receptor 1 (sTNFR1) ,Humans ,Prospective Studies ,Receptors ,Tumor Necrosis Factor ,Acute Kidney Injury ,Hospitalization ,Biomarkers ,Heart Failure - Abstract
RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.
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- 2023
12. Association of Uremic Solutes With Cardiovascular Death in Diabetic Kidney Disease.
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Katz, Ronit, Ix, Joachim, Sarnak, Mark, Cushman, Mary, Rhee, Eugene, Kimmel, Paul, Vasan, Ramachandran, Schrauben, Sarah, Feldman, Harold, Seegmiller, Jesse, Brunengraber, Henri, Hostetter, Thomas, Schelling, Jeffrey, Sapa, Hima, Gutiérrez, Orlando, and Shlipak, Michael
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Asymmetric dimethylarginine (ADMA) ,biomarkers ,cardiovascular disease (CVD) ,diabetic kidney disease (DKD) ,end-stage kidney disease (ESKD) ,estimated glomerular filtration rate (eGFR) ,kidney function ,renal clearance ,risk stratification ,symmetric dimethylarginine (SDMA) ,trimethylamine-N-oxide (TMAO) ,uremic solute ,Arginine ,Biomarkers ,Cardiovascular Diseases ,Diabetes Mellitus ,Diabetic Nephropathies ,Humans ,Methylamines ,Oxides - Abstract
RATIONALE & OBJECTIVE: Cardiovascular disease (CVD) is a major cause of mortality among people with diabetic kidney disease (DKD). The pathophysiology is inadequately explained by traditional CVD risk factors. The uremic solutes trimethylamine-N-oxide (TMAO) and asymmetric and symmetric dimethylarginine (ADMA, SDMA) have been linked to CVD in kidney failure with replacement therapy (KFRT), but data are limited in populations with diabetes and less severe kidney disease. STUDY DESIGN: Observational cohort. SETTINGS & PARTICIPANTS: Random subcohort of 555 REGARDS (Reasons for Geographic and Racial Differences in Stroke) study participants with diabetes and estimated glomerular filtration rate (eGFR)
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- 2022
13. Longitudinal Plasma Metabolome Patterns and Relation to Kidney Function and Proteinuria in Pediatric CKD
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Lee, Arthur M., Xu, Yunwen, Hu, Jian, Xiao, Rui, Hooper, Stephen R., Hartung, Erum A., Coresh, Josef, Rhee, Eugene P., Vasan, Ramachandran S., Kimmel, Paul L., Warady, Bradley A., Furth, Susan L., Denburg, Michelle R., Abraham, Alison, Anderson, Amanda, Ballard, Shawn, Bonventre, Joseph, Clish, Clary, Collins, Heather, Coca, Steven, Coresh, Josef, Deo, Rajat, Denburg, Michelle, Dubin, Ruth, Feldman, Harold I., Ferket, Bart S., Foster, Meredith, Furth, Susan, Ganz, Peter, Gossett, Daniel, Grams, Morgan, Greenberg, Jason, Gutiérrez, Orlando M., Hostetter, Tom, Inker, Lesley A., Ix, Joachim, Kimmel, Paul L., Klein, Jon, Levey, Andrew S., Massaro, Joseph, McMahon, Gearoid, Mifflin, Theodore, Nadkarni, Girish N., Parikh, Chirag, Ramachandran, Vasan S., Rebholz, Casey, Rhee, Eugene, Rovin, Brad, Sarnak, Mark, Sabbisetti, Venkata, Schelling, Jeffrey, Seegmiller, Jesse, Shlipak, Michael G., Shou, Haochang, Tin, Adriene, Waikar, Sushrut, Warady, Bradley, Whitehead, Krista, and Xie, Dawei
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- 2024
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14. Serum and Urine Metabolites and Kidney Function
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Yeo, Wan-Jin, Surapaneni, Aditya L., Hasson, Denise, Schmidt, Insa M., Sekula, Peggy, Köttgen, Anna, Eckardt, Kai-Uwe, Rebholz, Casey M., Yu, Bing, Waikar, Sushrut S., Rhee, Eugene P., Schrauben, Sarah J., Feldman, Harold I., Vasan, Ramachandran S., Kimmel, Paul L., Coresh, Josef, Grams, Morgan E., and Schlosser, Pascal
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- 2024
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15. Considerations in Controlling for Urine Concentration for Biomarkers of Kidney Disease Progression After Acute Kidney Injury
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Wen, Yumeng, Thiessen-Philbrook, Heather, Moledina, Dennis G, Kaufman, James S, Reeves, W Brian, Ghahramani, Nasrollah, Ikizler, T Alp, Go, Alan S, Liu, Kathleen D, Siew, Eddie D, Himmelfarb, Jonathan, Kimmel, Paul L, Hsu, Chi-yuan, and Parikh, Chirag R
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Biomedical and Clinical Sciences ,Clinical Sciences ,Kidney Disease ,Detection ,screening and diagnosis ,4.2 Evaluation of markers and technologies ,Renal and urogenital ,Good Health and Well Being ,acute kidney injury ,biomarker ,chronic kidney disease ,urine concentration ,urine creatinine ,urine osmolarity ,Biomedical and clinical sciences ,Health sciences - Abstract
IntroductionBiomarkers of acute kidney injury (AKI) are often indexed to urine creatinine (UCr) or urine osmolarity (UOsm) to control for urine concentration. We evaluated how these approaches affect the biomarker-outcome association in patients with AKI.MethodsThe Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury Study was a cohort of hospitalized patients with and without AKI between 2009 and 2015. Using Cox proportional hazards regression, we assessed the associations and predictions (C-statistics) of urine biomarkers with a composite outcome of incident chronic kidney disease (CKD) and CKD progression. We used 4 approaches to account for urine concentration: indexing and adjusting for UCr and UOsm.ResultsAmong 1538 participants, 769 (50%) had AKI and 300 (19.5%) developed composite CKD outcome at median follow-up of 4.7 years. UCr and UOsm during hospitalization were inversely associated with the composite CKD outcome. The associations and predictions with CKD were significantly strengthened after indexing or adjusting for UCr or UOsm for urine kidney injury molecule-1 (KIM-1), interleukin-18 (IL-18), and monocyte chemoattractant protein-1 (MCP-1) in patients with AKI. There was no significant improvement with indexing or adjusting UCr or UOsm for albumin, neutrophil gelatinase-associated lipocalin (NGAL), and chitinase 3-like 1 (YKL-40). Uromodulin's (UMOD) inverse association with the outcome was significantly blunted after indexing but not adjusting for UCr or UOsm.ConclusionUCr and UOsm during hospitalization are inversely associated with development and progression of CKD. Indexing or adjusting for UCr or UOsm strengthened associations and improved predictions for CKD for only some biomarkers. Incorporating urinary concentration should be individualized for each biomarker in research and clinical applications.
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- 2022
16. Metabolites Associated With Uremic Symptoms in Patients With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study
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Dember, Laura M., Landis, J. Richard, Townsend, Raymond R., Appel, Lawrence, Fink, Jeffrey, Rahman, Mahboob, Horwitz, Edward J., Taliercio, Jonathan J., Rao, Panduranga, Sondheimer, James H., Lash, James P., Chen, Jing, Go, Alan S., Parsa, Afshin, Rankin, Tracy, Wulczyn, Kendra E., Shafi, Tariq, Anderson, Amanda, Rincon-Choles, Hernan, Clish, Clary B., Denburg, Michelle, Feldman, Harold I., He, Jiang, Hsu, Chi-yuan, Kelly, Tanika, Kimmel, Paul L., Mehta, Rupal, Nelson, Robert G., Ramachandran, Vasan, Ricardo, Ana, Shah, Vallabh O., Srivastava, Anand, Xie, Dawei, Rhee, Eugene P., and Kalim, Sahir
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- 2024
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17. Trans-ethnic genome-wide association study of blood metabolites in the Chronic Renal Insufficiency Cohort (CRIC) study
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Rhee, Eugene P, Surapaneni, Aditya, Zheng, Zihe, Zhou, Linda, Dutta, Diptavo, Arking, Dan E, Zhang, Jingning, Duong, ThuyVy, Chatterjee, Nilanjan, Luo, Shengyuan, Schlosser, Pascal, Mehta, Rupal, Waikar, Sushrut S, Saraf, Santosh L, Kelly, Tanika N, Hamm, Lee L, Rao, Panduranga S, Mathew, Anna V, Hsu, Chi-yuan, Parsa, Afshin, Vasan, Ramachandran S, Kimmel, Paul L, Clish, Clary B, Coresh, Josef, Feldman, Harold I, Grams, Morgan E, and Investigators, CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort Study
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Human Genome ,Genetics ,Kidney Disease ,Aetiology ,2.1 Biological and endogenous factors ,Renal and urogenital ,Cohort Studies ,Ethnicity ,Female ,Genome-Wide Association Study ,Humans ,Linkage Disequilibrium ,Male ,Polymorphism ,Single Nucleotide ,Renal Insufficiency ,Chronic ,GWAS ,metabolomics ,trans-ethnic meta-analysis ,CKD Biomarkers Consortium and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators ,Clinical Sciences ,Urology & Nephrology - Abstract
Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m2 in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.
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- 2022
18. Acute Kidney Injury, Systemic Inflammation and Long-term Cognitive Function: ASSESS-AKI
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Bhatraju, Pavan K., Zelnick, Leila R., Stanaway, Ian B., Ikizler, T. Alp, Menez, Steven, Chinchilli, Vernon M., Coca, Steve G., Kaufman, James S., Kimmel, Paul L., Parikh, Chirag R., Go, Alan S., Siew, Edward D., Wurfel., Mark M., and Himmelfarb, Jonathan
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- 2024
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19. Plasma Kidney Injury Molecule 1 in CKD: Findings From the Boston Kidney Biopsy Cohort and CRIC Studies
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Schmidt, Insa M, Srivastava, Anand, Sabbisetti, Venkata, McMahon, Gearoid M, He, Jiang, Chen, Jing, Kusek, John W, Taliercio, Jonathan, Ricardo, Ana C, Hsu, Chi-yuan, Kimmel, Paul L, Liu, Kathleen D, Mifflin, Theodore E, Nelson, Robert G, Vasan, Ramachandran S, Xie, Dawei, Zhang, Xiaoming, Palsson, Ragnar, Stillman, Isaac E, Rennke, Helmut G, Feldman, Harold I, Bonventre, Joseph V, Waikar, Sushrut S, and Investigators, Chronic Kidney Disease Biomarkers Consortium and the CRIC Study
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Biomedical and Clinical Sciences ,Clinical Sciences ,Kidney Disease ,Clinical Research ,Renal and urogenital ,Good Health and Well Being ,Biomarkers ,Biopsy ,Boston ,Cohort Studies ,Cross-Sectional Studies ,Disease Progression ,Humans ,Kidney ,Prospective Studies ,Renal Insufficiency ,Chronic ,Chronic Kidney Disease Biomarkers Consortium and the CRIC Study Investigators ,Public Health and Health Services ,Urology & Nephrology ,Clinical sciences - Abstract
Rationale & objectivePlasma kidney injury molecule 1 (KIM-1) is a sensitive marker of proximal tubule injury, but its association with risks of adverse clinical outcomes across a spectrum of kidney diseases is unknown.Study designProspective, observational cohort study.Setting & participants524 individuals enrolled into the Boston Kidney Biopsy Cohort (BKBC) Study undergoing clinically indicated native kidney biopsy with biopsy specimens adjudicated for semiquantitative scores of histopathology by 2 kidney pathologists and 3,800 individuals with common forms of chronic kidney disease (CKD) enrolled into the Chronic Renal Insufficiency Cohort (CRIC) Study.ExposureHistopathologic lesions and clinicopathologic diagnosis in cross-sectional analyses, baseline plasma KIM-1 levels in prospective analyses.OutcomesBaseline plasma KIM-1 levels in cross-sectional analyses, kidney failure (defined as initiation of kidney replacement therapy) and death in prospective analyses.Analytical approachMultivariable-adjusted linear regression models tested associations of plasma KIM-1 levels with histopathologic lesions and clinicopathologic diagnoses. Cox proportional hazards models tested associations of plasma KIM-1 levels with future kidney failure and death.ResultsIn the BKBC Study, higher plasma KIM-1 levels were associated with more severe acute tubular injury, tubulointerstitial inflammation, and more severe mesangial expansion after multivariable adjustment. Participants with diabetic nephropathy, glomerulopathies, and tubulointerstitial disease had significantly higher plasma KIM-1 levels after multivariable adjustment. In the BKBC Study, CKD in 124 participants progressed to kidney failure and 85 participants died during a median follow-up time of 5 years. In the CRIC Study, CKD in 1,153 participants progressed to kidney failure and 1,356 participants died during a median follow-up time of 11.5 years. In both cohorts, each doubling of plasma KIM-1 level was associated with an increased risk of kidney failure after multivariable adjustment (hazard ratios of 1.19 [95% CI, 1.03-1.38] and 1.10 [95% CI, 1.06-1.15] for BKBC and CRIC, respectively). There was no statistically significant association of plasma KIM-1 levels with death in either cohort.LimitationsGeneralizability and unmeasured confounding.ConclusionsPlasma KIM-1 is associated with underlying tubulointerstitial and mesangial lesions and progression to kidney failure in 2 cohort studies of individuals with kidney diseases.
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- 2022
20. Comparison of proteomic methods in evaluating biomarker-AKI associations in cardiac surgery patients
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Liu, Richard X, Thiessen-Philbrook, Heather R, Vasan, Ramachandran S, Coresh, Josef, Ganz, Peter, Bonventre, Joseph V, Kimmel, Paul L, and Parikh, Chirag R
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Biochemistry and Cell Biology ,Biomedical and Clinical Sciences ,Biological Sciences ,Biotechnology ,Clinical Research ,4.1 Discovery and preclinical testing of markers and technologies ,Good Health and Well Being ,Acute Kidney Injury ,Aged ,Aged ,80 and over ,Aptamers ,Peptide ,Biomarkers ,Blood Chemical Analysis ,Blood Proteins ,Cardiac Surgical Procedures ,Female ,Humans ,Immunoassay ,Male ,Middle Aged ,Preoperative Period ,Proteomics ,Clinical Sciences ,General Clinical Medicine ,Biochemistry and cell biology ,Clinical sciences - Abstract
Although immunoassays are the most widely used protein measurement method, aptamer-based methods such as the SomaScan platform can quantify up to 7000 proteins per biosample, creating new opportunities for unbiased discovery. However, there is limited research comparing the consistency of biomarker-disease associations between immunoassay and aptamer-based platforms. In a substudy of the TRIBE-AKI cohort, preoperative and postoperative plasma samples from 294 patients with previous immunoassay measurements were analyzed using the SomaScan platform. Inter-platform Spearman correlations (rs) and biomarker-AKI associations were compared across 30 preoperative and 34 postoperative immunoassay-aptamer pairs. Possible factors contributing to inter-platform differences were examined including target protein characteristics, immunoassay, and SomaScan coefficients of variation, other assay characteristics, and sample storage time. The median rs was 0.54 (interquartile range [IQR] 0.34-0.83) in postoperative samples and 0.41 (IQR 0.21-0.69) in preoperative samples. We observed a trend of greater rs in biomarkers with greater concentrations; the Spearman correlation between the concentration of protein and the inter-platform correlation was 0.64 in preoperative pairs and 0.53 in postoperative pairs. Of proteins measured by immunoassays, we observed significant biomarker-AKI associations for 13 proteins preop and 24 postop; of all corresponding aptamers, 8 proteins preop and 12 postop. All proteins significantly associated with AKI as measured by SomaScan were also significantly associated with AKI as measured by immunoassay. All biomarker-AKI odds ratios were significantly different (P < 0.05) between platforms in 14% of aptamer-immunoassay pairs, none of which had high (rs > 0.50) inter-platform correlations. Although similar biomarker-disease associations were observed overall, biomarkers with high physiological concentrations tended to have the highest-confidence inter-platform operability in correlations and biomarker-disease associations. Aptamer assays provide excellent precision and an unprecedented coverage and promise for disease associations but interpretation of results should keep in mind a broad range of correlations with immunoassays.
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- 2021
21. Plasma Metabolomics of Dietary Intake of Protein-Rich Foods and Kidney Disease Progression in Children
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Ren, Xuyuehe, Chen, Jingsha, Abraham, Alison G., Xu, Yunwen, Siewe, Aisha, Warady, Bradley A., Kimmel, Paul L., Vasan, Ramachandran S., Rhee, Eugene P., Furth, Susan L., Coresh, Josef, Denburg, Michelle, and Rebholz, Casey M.
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- 2024
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22. Biomarkers of eGFR decline after cardiac surgery in children: findings from the ASSESS-AKI study
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de Fontnouvelle, Christina, Zappitelli, Michael, Thiessen-Philbrook, Heather R., Jia, Yaqi, Kimmel, Paul L., Kaufman, James S., and Devarajan, Prasad
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Heart -- Surgery ,Acute renal failure -- Risk factors -- Diagnosis ,Biological markers -- Analysis ,Health - Abstract
Background Children who require surgery for congenital heart disease have increased risk for long-term chronic kidney disease (CKD). Clinical factors as well as urine biomarkers of tubular health and injury may help improve the prognostication of estimated glomerular filtration rate (eGFR) decline. Methods We enrolled children from 1 month to 18 years old undergoing cardiac surgery in the ASSESS-AKI cohort. We used mixed-effect models to assess the association between urinary biomarkers (log2-transformed uromodulin, NGAL, KIM-1, IL-18, L-FABP) measured 3 months after cardiac surgery and cyanotic heart disease with the rate of eGFR decline at annual in-person visits over 4 years. Results Of the 117 children enrolled, 30 (24%) had cyanotic heart disease. During 48 months of follow-up, the median eGFR in the subgroup of children with cyanotic heart disease was lower at all study visits as compared with children with acyanotic heart disease (p = 0.01). In the overall cohort, lower levels of both urine uromodulin and IL-18 after discharge were associated with eGFR decline. After adjustment for age, RACHS-1 surgical complexity score, proteinuria, and eGFR at the 3-month study visit, lower concentrations of urine uromodulin and IL-18 were associated with a monthly decline in eGFR (uromodulin [beta] = 0.04 (95% CI: 0.00-0.09; p = 0.07) IL-18 [beta] = 0.07 (95% CI: 0.01-0.13; p = 0.04), ml/min/1.73 m.sup.2 per month). Conclusions At 3 months after cardiac surgery, children with lower urine uromodulin and IL-18 concentrations experienced a significantly faster decline in eGFR. Children with cyanotic heart disease had a lower median eGFR at all time points but did not experience faster eGFR decline. Graphical abstract, Author(s): Christina de Fontnouvelle [sup.1] , Michael Zappitelli [sup.2] , Heather R. Thiessen-Philbrook [sup.3] , Yaqi Jia [sup.3] , Paul L. Kimmel [sup.4] , James S. Kaufman [sup.5] , Prasad [...]
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- 2023
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23. Proteomics of CKD progression in the chronic renal insufficiency cohort
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Dubin, Ruth F., Deo, Rajat, Ren, Yue, Wang, Jianqiao, Zheng, Zihe, Shou, Haochang, Go, Alan S., Parsa, Afshin, Lash, James P., Rahman, Mahboob, Hsu, Chi-yuan, Weir, Matthew R., Chen, Jing, Anderson, Amanda, Grams, Morgan E., Surapaneni, Aditya, Coresh, Josef, Li, Hongzhe, Kimmel, Paul L., Vasan, Ramachandran S., Feldman, Harold, Segal, Mark R., and Ganz, Peter
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- 2023
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24. The design and baseline characteristics for the HOPE Consortium Trial to reduce pain and opioid use in hemodialysis
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Dember, Laura M., Hsu, Jesse Y., Bernardo, Leah, Cavanaugh, Kerri L., Charytan, David M., Crowley, Susan T., Cukor, Daniel, Doorenbos, Ardith Z., Edwards, David A., Esserman, Denise, Fischer, Michael J., Jhamb, Manisha, Joffe, Steven, Johansen, Kirsten L., Kalim, Sahir, Keefe, Francis J., Kimmel, Paul L., Krebs, Erin E., Kuzla, Natalie, Mehrotra, Rajnish, Mishra, Puneet, Pellegrino, Bethany, Steel, Jennifer L., Unruh, Mark L., White, David M., Yabes, Jonathan G., and Becker, William C.
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- 2024
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25. Epidemiology of Infantile Ureteropelvic Junction Obstruction in the US
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Fwu, Chyng-Wen, Barthold, Julia S., Mendley, Susan R., Bennett, Kara, Chan, Kevin, Wilkins, Kenneth J., Parsa, Afshin, Norton, Jenna M., Eggers, Paul W., Kimmel, Paul L., Schulman, Ivonne H., and Kirkali, Ziya
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- 2024
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26. Circulating Metabolomic Associations with Neurocognitive Outcomes in Pediatric CKD
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Lee, Arthur M., Xu, Yunwen, Hooper, Stephen R., Abraham, Alison G., Hu, Jian, Xiao, Rui, Matheson, Matthew B., Brunson, Celina, Rhee, Eugene P., Coresh, Josef, Vasan, Ramachandran S., Schrauben, Sarah, Kimmel, Paul L., Warady, Bradley A., Furth, Susan L., Hartung, Erum A., Denburg, Michelle R., Abraham, Alison, Anderson, Amanda, Ballard, Shawn, Bonventre, Joseph, Clish, Clary, Collins, Heather, Coca, Steven, Coresh, Josef, Deo, Rajat, Denburg, Michelle, Dubin, Ruth, Feldman, Harold I., Ferket, Bart S., Foster, Meredith, Furth, Susan, Ganz, Peter, Gossett, Daniel, Grams, Morgan, Greenberg, Jason, Gutiérrez, Orlando M., Hostetter, Tom, Inker, Lesley A., Ix, Joachim, Kimmel, Paul L., Klein, Jon, Levey, Andrew S., Massaro, Joseph, McMahon, Gearoid, Mifflin, Theodore, Nadkarni, Girish N., Parikh, Chirag, Ramachandran, Vasan S., Rebholz, Casey, Rhee, Eugene, Rovin, Brad, Sarnak, M., Sabbisetti, Venkata, Schelling, Jeffrey, Seegmiller, Jesse, Shlipak, Michael G., Shou, Haochang, Tin, Adriene, Waikar, Sushrut, Warady, Bradley, Whitehead, Krista, and Xie, Dawei
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- 2024
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27. Achieved blood pressure post-acute kidney injury and risk of adverse outcomes after AKI: A prospective parallel cohort study.
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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
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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.
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- 2021
28. Age- and Race-Specific Changes in ESKD Incidence over Four Decades
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Fwu, Chyng-Wen, Eggers, Paul W., Norton, Jenna M., Gipson, Debbie S., Kimmel, Paul L., Schulman, Ivonne H., Chan, Kevin E., Bennett, Kara, and Mendley, Susan R.
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- 2024
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29. Age- and Race-Specific Changes in End Stage Kidney Disease Incidence over Four Decades
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Fwu, Chyng-Wen, Eggers, Paul W., Norton, Jenna M., Gipson, Debbie S., Kimmel, Paul L., Schulman, Ivonne H., Chan, Kevin E., Bennett, Kara, and Mendley, Susan R.
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- 2024
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30. The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events
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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.
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- 2023
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31. A New Panel-Estimated GFR, Including β2-Microglobulin and β-Trace Protein and Not Including Race, Developed in a Diverse Population
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Inker, Lesley A, Couture, Sara J, Tighiouart, Hocine, Abraham, Alison G, Beck, Gerald J, Feldman, Harold I, Greene, Tom, Gudnason, Vilmundur, Karger, Amy B, Eckfeldt, John H, Kasiske, Bertram L, Mauer, Michael, Navis, Gerjan, Poggio, Emilio D, Rossing, Peter, Shlipak, Michael G, Levey, Andrew S, Collaborators, CKD-EPI GFR, Andresdottir, Margret B, Gudmundsdottir, Hrefna, Indridason, Olafur S, Palsson, Runolfur, Kimmel, Paul, Weir, Matt, Kalil, Roberto, Pesavento, Todd, Porter, Anna, Taliercio, Jonathan, Hsu, Chi-yuan, Chen, Jing, Sinkeler, Steef, Wyatt, Christina, Krishnasami, Zipporah, Hellinger, James, Margolick, Joseph, Kingsley, Lawrence, Witt, Mallory, Wolinsky, Steven, Shafi, Tariq, Post, Wendy, Doria, Alessandro, and Parving, Hans-Henrik
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Biomedical and Clinical Sciences ,Clinical Sciences ,Health Disparities ,Clinical Research ,Kidney Disease ,Minority Health ,4.2 Evaluation of markers and technologies ,Renal and urogenital ,Adolescent ,Adult ,Black or African American ,Aged ,Aged ,80 and over ,Black People ,Case-Control Studies ,Chromium Radioisotopes ,Creatinine ,Cystatin C ,Edetic Acid ,Female ,Glomerular Filtration Rate ,Humans ,Intramolecular Oxidoreductases ,Iohexol ,Iothalamic Acid ,Lipocalins ,Male ,Middle Aged ,Renal Insufficiency ,Chronic ,Reproducibility of Results ,Severity of Illness Index ,White People ,Young Adult ,beta 2-Microglobulin ,CKD-EPI GFR Collaborators ,African American ,Black race ,GFR estimation ,Glomerular filtration rate ,bias ,creatinine ,cystatin C ,estimating equations ,filtration marker ,kidney disease diagnosis ,laboratory testing ,race ,race-based medicine ,renal function ,β(2)-microglobulin ,β-trace protein ,Public Health and Health Services ,Urology & Nephrology ,Clinical sciences - Abstract
Rationale and objectiveGlomerular filtration rate (GFR) estimation based on creatinine and cystatin C (eGFRcr-cys) is more accurate than estimated GFR (eGFR) based on creatinine or cystatin C alone (eGFRcr or eGFRcys, respectively), but the inclusion of creatinine in eGFRcr-cys requires specification of a person's race. β2-Microglobulin (B2M) and β-trace protein (BTP) are alternative filtration markers that appear to be less influenced by race than creatinine is.Study designStudy of diagnostic test accuracy.Setting and participantsDevelopment in a pooled population of 7 studies with 5,017 participants with and without chronic kidney disease. External validation in a pooled population of 7 other studies with 2,245 participants.Tests comparedPanel eGFR using B2M and BTP in addition to cystatin C (3-marker panel) or creatinine and cystatin C (4-marker panel) with and without age and sex or race.OutcomesGFR measured as the urinary clearance of iothalamate, plasma clearance of iohexol, or plasma clearance of [51Cr]EDTA.ResultsMean measured GFRs were 58.1 and 83.2 mL/min/1.73 m2, and the proportions of Black participants were 38.6% and 24.0%, in the development and validation populations, respectively. In development, addition of age and sex improved the performance of all equations compared with equations without age and sex, but addition of race did not further improve the performance. In validation, the 4-marker panels were more accurate than the 3-marker panels (P < 0.001). The 3-marker panel without race was more accurate than eGFRcys (percentage of estimates greater than 30% different from measured GFR [1 - P30] of 15.6% vs 17.4%; P = 0.01), and the 4-marker panel without race was as accurate as eGFRcr-cys (1 - P30 of 8.6% vs 9.4%; P = 0.2). Results were generally consistent across subgroups.LimitationsNo representation of participants with severe comorbid illness and from geographic areas outside of North America and Europe.ConclusionsThe 4-marker panel eGFR is as accurate as eGFRcr-cys without requiring specification of race. A more accurate race-free eGFR could be an important advance.
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- 2021
32. The Microbiome and p-Inulin in Hemodialysis: A Feasibility Study.
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Raj, Dominic S, Sohn, Michael B, Charytan, David M, Himmelfarb, Jonathan, Ikizler, T Alp, Mehrotra, Rajnish, Ramezani, Ali, Regunathan-Shenk, Renu, Hsu, Jesse Y, Landis, J Richard, Li, Hongzhe, Kimmel, Paul L, Kliger, Alan S, Dember, Laura M, and Hemodialysis Novel Therapies Consortium
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Hemodialysis Novel Therapies Consortium ,Feces ,Humans ,Inulin ,Renal Dialysis ,Feasibility Studies ,Microbiota ,crossover trial ,dialysis ,feasibility studies ,hemodialysis ,microbiome ,p-inulin ,prebiotic ,Clinical Research ,Clinical Trials and Supportive Activities ,Digestive Diseases ,Prevention - Abstract
BackgroundThe intestinal microbiome is an appealing target for interventions in ESKD because of its likely contribution to uremic toxicity. Before conducting clinical trials of microbiome-altering treatments, it is necessary to understand the within-person and between-person variability in the composition and function of the gut microbiome in patients with ESKD.MethodsWe conducted a multicenter, nonrandomized, crossover feasibility study of patients on maintenance hemodialysis consisting of three phases: pretreatment (8 weeks); treatment, during which the prebiotic, p-inulin, was administered at a dosage of 8 g twice daily (12 weeks); and post-treatment (8 weeks). Stool samples were collected 1-2 times per week and blood was collected weekly for 28 weeks. The gut microbiome was characterized using 16S ribosomal-RNA sequencing and metabolomic profiling.ResultsA total of 11 of the 13 participants completed the 28-week study. Interparticipant variability was greater than intraparticipant variability for microbiome composition (P
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- 2021
33. Plasma Biomarkers and Incident CKD Among Individuals Without Diabetes
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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.
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- 2023
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34. Biomarkers of inflammation and repair in kidney disease progression
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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
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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.
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- 2021
35. A prospective cohort study of acute kidney injury and kidney outcomes, cardiovascular events, and death.
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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
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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.
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- 2021
36. Integrated Analysis of Blood and Urine Biomarkers to Identify Acute Kidney Injury Subphenotypes and Associations With Long-term Outcomes
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Bhatraju, Pavan K., Prince, David K., Mansour, Sherry, Ikizler, T. Alp, Siew, Edward D., Chinchilli, Vernon M., Garg, Amit X., Go, Alan S., Kaufman, James S., Kimmel, Paul L., Coca, Steve G., Parikh, Chirag R., Wurfel, Mark M., and Himmelfarb, Jonathan
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- 2023
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37. APOL1 Long-term Kidney Transplantation Outcomes Network (APOLLO): Design and Rationale
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Freedman, Barry I, Moxey-Mims, Marva M, Alexander, Amir A, Astor, Brad C, Birdwell, Kelly A, Bowden, Donald W, Bowen, Gordon, Bromberg, Jonathan, Craven, Timothy E, Dadhania, Darshana M, Divers, Jasmin, Doshi, Mona D, Eidbo, Elling, Fornoni, Alessia, Gautreaux, Michael D, Gbadegesin, Rasheed A, Gee, Patrick O, Guerra, Giselle, Hsu, Chi-yuan, Iltis, Ana S, Jefferson, Nichole, Julian, Bruce A, Klassen, David K, Koty, Patrick P, Langefeld, Carl D, Lentine, Krista L, Ma, Lijun, Mannon, Roslyn B, Menon, Madhav C, Mohan, Sumit, Moore, J Brian, Murphy, Barbara, Newell, Kenneth A, Odim, Jonah, Ortigosa-Goggins, Mariella, Palmer, Nicholette D, Park, Meyeon, Parsa, Afshin, Pastan, Stephen O, Poggio, Emilio D, Rajapakse, Nishadi, Reeves-Daniel, Amber M, Rosas, Sylvia E, Russell, Laurie P, Sawinski, Deirdre, Smith, S Carrie, Spainhour, Mitzie, Stratta, Robert J, Weir, Matthew R, Reboussin, David M, Kimmel, Paul L, and Brennan, Daniel C
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Clinical Research ,Organ Transplantation ,Transplantation ,Kidney Disease ,Renal and urogenital ,Good Health and Well Being ,African Americans ,APOL1 ,chronic kidney disease ,graft failure ,kidney transplantation ,outcomes - Abstract
IntroductionMuch of the higher risk for end-stage kidney disease (ESKD) in African American individuals relates to ancestry-specific variation in the apolipoprotein L1 gene (APOL1). Relative to kidneys from European American deceased-donors, kidneys from African American deceased-donors have shorter allograft survival and African American living-kidney donors more often develop ESKD. The National Institutes of Health (NIH)-sponsored APOL1 Long-term Kidney Transplantation Outcomes Network (APOLLO) is prospectively assessing kidney allograft survival from donors with recent African ancestry based on donor and recipient APOL1 genotypes.MethodsAPOLLO will evaluate outcomes from 2614 deceased kidney donor-recipient pairs, as well as additional living-kidney donor-recipient pairs and unpaired deceased-donor kidneys.ResultsThe United Network for Organ Sharing (UNOS), Association of Organ Procurement Organizations, American Society of Transplantation, American Society for Histocompatibility and Immunogenetics, and nearly all U.S. kidney transplant programs, organ procurement organizations (OPOs), and histocompatibility laboratories are participating in this observational study. APOLLO employs a central institutional review board (cIRB) and maintains voluntary partnerships with OPOs and histocompatibility laboratories. A Community Advisory Council composed of African American individuals with a personal or family history of kidney disease has advised the NIH Project Office and Steering Committee since inception. UNOS is providing data for outcome analyses.ConclusionThis article describes unique aspects of the protocol, design, and performance of APOLLO. Results will guide use of APOL1 genotypic data to improve the assessment of quality in deceased-donor kidneys and could increase numbers of transplanted kidneys, reduce rates of discard, and improve the safety of living-kidney donation.
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- 2020
38. Readmission and Mortality After Hospitalization With Acute Kidney Injury
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Schulman, Ivonne H., Chan, Kevin, Der, Jane S., Wilkins, Kenneth J., Corns, Helen L., Sayer, Bryan, Ngo, Duc Anh, Eggers, Paul, Norton, Jenna, Shah, Neha, Mendley, Susan, Parsa, Afshin, Star, Robert A., and Kimmel, Paul L.
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- 2023
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39. Psychosocial Issues in Patients Treated With Dialysis
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Cukor, Daniel, primary, Donahue, Stephanie L., additional, and Kimmel, Paul L., additional
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- 2023
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40. Use of Measures of Inflammation and Kidney Function for Prediction of Atherosclerotic Vascular Disease Events and Death in Patients With CKD: Findings From the CRIC Study
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Amdur, Richard L, Feldman, Harold I, Dominic, Elizabeth A, Anderson, Amanda H, Beddhu, Srinivasan, Rahman, Mahboob, Wolf, Myles, Reilly, Muredach, Ojo, Akinlolu, Townsend, Raymond R, Go, Alan S, He, Jiang, Xie, Dawei, Thompson, Sally, Budoff, Matthew, Kasner, Scott, Kimmel, Paul L, Kusek, John W, Raj, Dominic S, Investigators, CRIC Study, Fink, Jeffrey, Appel, Lawrence J, and Lash, James P
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Biomedical and Clinical Sciences ,Clinical Sciences ,Prevention ,Kidney Disease ,Cardiovascular ,Clinical Research ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Renal and urogenital ,Good Health and Well Being ,Adult ,Aged ,Atherosclerosis ,Biomarkers ,Cohort Studies ,Female ,Humans ,Inflammation ,Kidney Function Tests ,Male ,Middle Aged ,Predictive Value of Tests ,Renal Insufficiency ,Chronic ,Young Adult ,CRIC Study Investigators ,C-reactive protein ,Myocardial infarction ,Pooled Cohort Equation probability ,albuminuria ,atherosclerosis ,atherosclerotic vascular disease ,cardiovascular disease ,chronic kidney function ,cytokines ,estimated glomerular filtration rate ,inflammatory biomarkers ,kidney function ,risk stratification ,stroke ,Public Health and Health Services ,Urology & Nephrology ,Clinical sciences - Abstract
RATIONALE & OBJECTIVE:Traditional risk estimates for atherosclerotic vascular disease (ASVD) and death may not perform optimally in the setting of chronic kidney disease (CKD). We sought to determine whether the addition of measures of inflammation and kidney function to traditional estimation tools improves prediction of these events in a diverse cohort of patients with CKD. STUDY DESIGN:Observational cohort study. SETTING & PARTICIPANTS:2,399 Chronic Renal Insufficiency Cohort (CRIC) Study participants without a history of cardiovascular disease at study entry. PREDICTORS:Baseline plasma levels of biomarkers of inflammation (interleukin 1β [IL-1β], IL-1 receptor antagonist, IL-6, tumor necrosis factor α [TNF-α], transforming growth factor β, high-sensitivity C-reactive protein, fibrinogen, and serum albumin), measures of kidney function (estimated glomerular filtration rate [eGFR] and albuminuria), and the Pooled Cohort Equation probability (PCEP) estimate. OUTCOMES:Composite of ASVD events (incident myocardial infarction, peripheral arterial disease, and stroke) and death. ANALYTICAL APPROACH:Cox proportional hazard models adjusted for PCEP estimates, albuminuria, and eGFR. RESULTS:During a median follow-up of 7.3 years, 86, 61, 48, and 323 participants experienced myocardial infarction, peripheral arterial disease, stroke, or death, respectively. The 1-decile greater levels of IL-6 (adjusted HR [aHR], 1.12; 95% CI, 1.08-1.16; P
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- 2019
41. Creation of a Single Institutional Review Board for Collaborative Research in Nephrology: The APOLLO Experience
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Moore, J. Brian, Smith, S. Carrie, Russell, Laurie P., Serdoz, Emily S., Dilts, Natalie A., Alexander, Amir A., Reboussin, David M., Bagwell, Benjamin M., Spainhour, Mitzie H., Reeves-Daniel, Amber M., Wesley-Farrington, Deborah J., Ma, Lijun, Freedman, Barry I., Fornoni, Alessia, Reeves-Daniel, Amber, Astor, Brad, Hsu, Chi-yuan, Brennan, Daniel, Dadhania, Darshana, Sawinski, Deidre, Poggio, Emilio, Agarwal, Gaurav, Guerra, Giselle, Bromberg, Jonathan, Birdwell, Kelly, Newell, Kenneth, Lentine, Krista L., Ortigosa-Goggins, Mariella, Weir, Matthew, Park, Meyeon, Doshi, Mona, Gbadegesin, Rasheed, Mannon, Roslyn, Farouk, Samira, Pastan, Stephen, Mohan, Sumit, Rosas, Sylvia, Parsa, Afshin, Odim, Jonah, Kimmel, Paul L., Gillman, Arielle, Alexander, Amir, Freedman, Barry I., Bagwell, Benjamin, Smith, S. Carrie, Reboussin, David, Russell, Laurie, Ma, Lijun, Spainhour, Mitzie, Guy, KaShawna, Roberts, Glenda, Jefferson, Nichole, and Moxey-Mims, Marva
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- 2023
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42. A randomized controlled pilot trial of anakinra for hemodialysis inflammation
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Dember, Laura M., Hung, Adriana, Mehrotra, Rajnish, Hsu, Jesse Y., Raj, Dominic S., Charytan, David M., Mc Causland, Finnian R., Regunathan-Shenk, Renu, Landis, J. Richard, Kimmel, Paul L., Kliger, Alan S., Himmelfarb, Jonathan, and Ikizler, T. Alp
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- 2022
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43. Association of Uremic Solutes With Cardiovascular Death in Diabetic Kidney Disease
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Massaro, Joseph, Clish, Clary, Denburg, Michelle, Furth, Susan, Warady, Bradley, Bonventre, Joseph, Waikar, Sushrut, McMahon, Gearoid, Sabbisetti, Venkata, Coresh, Josef, Grams, Morgan, Rebholz, Casey, Abraham, Alison, Tin, Adriene, Parikh, Chirag, Klein, Jon, Coca, Steven, Ferket, Bart S., Nadkarni, Girish N., Gossett, Daniel, Rovin, Brad, Levey, Andrew S., Inker, Lesley A., Foster, Meredith, Dubin, Ruth, Deo, Rajat, Anderson, Amanda, Mifflin, Theodore, Xie, Dawei, Shou, Haochang, Ballard, Shawn, Whitehead, Krista, Collins, Heather, Greenberg, Jason, Ganz, Peter, Sapa, Hima, Gutiérrez, Orlando M., Shlipak, Michael G., Katz, Ronit, Ix, Joachim H., Sarnak, Mark J., Cushman, Mary, Rhee, Eugene P., Kimmel, Paul L., Vasan, Ramachandran S., Schrauben, Sarah J., Feldman, Harold I., Seegmiller, Jesse C., Brunengraber, Henri, Hostetter, Thomas H., and Schelling, Jeffrey R.
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- 2022
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44. Biomarkers of Kidney Tubule Disease and Risk of End-Stage Kidney Disease in Persons With Diabetes and CKD
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Amatruda, Jonathan G., Katz, Ronit, Sarnak, Mark J., Gutierrez, Orlando M., Greenberg, Jason H., Cushman, Mary, Waikar, Sushrut, Parikh, Chirag R., Schelling, Jeffrey R., Jogalekar, Manasi P., Bonventre, Joseph V., Vasan, Ramachandran S., Kimmel, Paul L., Shlipak, Michael G., and Ix, Joachim H.
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- 2022
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45. Plasma Biomarkers as Risk Factors for Incident CKD
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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.
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- 2022
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46. Associations of Plasma Biomarkers of Inflammation, Fibrosis, and Kidney Tubular Injury With Progression of Diabetic Kidney Disease: A Cohort Study
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Gutiérrez, Orlando M., Shlipak, Michael G., Katz, Ronit, Waikar, Sushrut S., Greenberg, Jason H., Schrauben, Sarah J., Coca, Steven, Parikh, Chirag R., Vasan, Ramachandran S., Feldman, Harold I., Kimmel, Paul L., Cushman, Mary, Bonventre, Joseph V., Sarnak, Mark J., and Ix, Joachim H.
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- 2022
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47. Kidney Disease, Hypertension Treatment, and Cerebral Perfusion and Structure
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Whelton, Paul, Johnson, Karen C., Snyder, Joni, Bild, Diane, Bonds, Denise, Cook, Nakela, Cutler, Jeffrey, Fine, Lawrence, Kaufmann, Peter, Kimmel, Paul, Launer, Lenore, Moy, Claudia, Riley, William, Ryan, Laurie, Tolunay, Eser, Yang, Song, Reboussin, David, Williamson, Jeff, Ambrosius, Walter T., Applegate, William, Evans, Greg, Foy, Capri, Freedman, Barry I., Kitzman, Dalane, Lyles, Mary, Pajewski, Nick, Rapp, Steve, Rushing, Scott, Shah, Neel, Sink, Kaycee M., Vitolins, Mara, Wagenknecht, Lynne, Wilson, Valerie, Perdue, Letitia, Woolard, Nancy, Craven, Tim, Garcia, Katelyn, Gaussoin, Sarah, Lovato, Laura, Newman, Jill, Lovato, James, Lu, Lingyi, McLouth, Chris, Russell, Greg, Amoroso, Bobby, Davis, Patty, Griffin, Jason, Harris, Darrin, King, Mark, Lane, Kathy, Roberson, Wes, Steinberg, Debbie, Ashford, Donna, Babcock, Phyllis, Chamberlain, Dana, Christensen, Vickie, Cloud, Loretta, Collins, Christy, Cook, Delilah, Currie, Katherine, Felton, Debbie, Harpe, Stacy, Howard, Marjorie, Lewis, Michelle, Nance, Pamela, Puccinelli-Ortega, Nicole, Russell, Laurie, Walker, Jennifer, Craven, Brenda, Goode, Candace, Troxler, Margie, Davis, Janet, Hutchens, Sarah, Killeen, Anthony A., Lukkari, Anna M., Ringer, Robert, Dillard, Brandi, Archibeque, Norbert, Warren, Stuart, Sather, Mike, Pontzer, James, Taylor, Zach, Soliman, Elsayed Z., Zhang, Zhu-Ming, Li, Yabing, Campbell, Chuck, Hensley, Susan, Hu, Julie, Keasler, Lisa, Barr, Mary, Taylor, Tonya, Bryan, R. Nick, Davatzikos, Christos, Nasarallah, Ilya, Desiderio, Lisa, Elliott, Mark, Borthakur, Ari, Battapady, Harsha, Erus, Guray, Smith, Alex, Wang, Ze, Doshi, Jimit, Wright, Jackson T., Jr., Rahman, Mahboob, Lerner, Alan J., Still, Carolyn, Wiggers, Alan, Zamanian, Sara, Bee, Alberta, Dancie, Renee, Thomas, George, Schreiber, Martin, Jr., Navaneethan, Sankar Dass, Hickner, John, Lioudis, Michael, Lard, Michelle, Marczewski, Susan, Maraschky, Jennifer, Colman, Martha, Aaby, Andrea, Payne, Stacey, Ramos, Melanie, Horner, Carol, Drawz, Paul, Raghavendra, Pratibha P., Ober, Scott, Mourad, Ronda, Pallaki, Muralidhar, Russo, Peter, Raghavendra, Pratibha, Fantauzzo, Pual, Tucker, Lisa, Schwing, Bill, Sedor, John R., Horwitz, Edward J., Schellling, Jeffrey R., O’Toole, John F., Humbert, Lisa, Tutolo, Wendy, White, Suzanne, Gay, Alishea, Clark, Walter, Jr., Hughes, Robin, Dobre, Mirela, Still, Carolyn H., Williams, Monique, Bhatt, Udayan, Hebert, Lee, Agarwal, Anil, Murphy, Melissa Brown, Ford, Nicole, Stratton, Cynthia, Baxter, Jody, Lykins, Alicia A., McKinley Neal Leena Hirmath, Alison, Kwame, Osei, Soe, Kyaw, Miser, William F., Sagrilla, Colleen, Johnston, Jan, Anaya, Amber, Mintos, Ashley, Howell, Angel A., Rogers, Kelly, Taylor, Sara, Ebersbacher, Donald, Long, Lucy, Bednarchik, Beth, Schnall, Adrian, Smith, Jonathan, Peysha, Lori, Leach, Lisa, Tribout, Megan, Harwell, Carla, Ellington, Pinkie, Banerji, Mary Ann, Ghody, Pranav, Rambaud, Melissa Vahídeh, Townsend, Raymond, Cohen, Debbie, Huan, Yonghong, Duckworth, Mark, Ford, Virginia, Leshner, Juliet, Davison, Ann, Veen, Sarah Vander, Gadegbeku, Crystal A., Gillespie, Avi, Paranjape, Anuradha, Amoroso, Sandra, Pfeffer, Zoe, Quinn, Sally B., He, Jiang, Chen, Jing, Lustigova, Eva, Malone, Erin, Krousel-Wood, Marie, Deichmann, Richard, Ronney, Patricia, Muery, Susan, Trapani, Donnalee, Rocco, Michael, Goff, David, Rodriguez, Carlos, Coker, Laura, Hawfield, Amret, Yeboah, Joseph, Crago, Lenore, Summerson, John, Hege, Anita, Diamond, Matt, Mulloy, Laura, Hodges, Marcela, Collins, Michelle, Weathers, Charlene, Anderson, Heather, Stone, Emily, Walker, Walida, McWilliams, Andrew, Dulin, Michael, Kuhn, Lindsay, Standridge, Susan, Lowe, Lindsay, Everett, Kelly, Preston, Kelry, Norton, Susan, Gaines, Silena, Rizvi, Ali A., Sides, Andrew W., Herbert, Diamond, Hix, Matthew M., Whitmire, Melanie, Arnold, Brittany, Hutchinson, Philip, Espiritu, Joseph, Feinglos, Mark, Kovalik, Eugene, Gedon-Lipscomb, Georgianne, Evans, Kathryn, Thacker, Connie, Zimmer, Ronna, Furst, Mary, Mason, MaryAnn, Powell, James, Bolin, Paul, Zhang, Junhong, Pinion, Mary, Davis, Gail, Bryant, Winifred, Phelps, Presley, Garris-Sutton, Connie, Atkinson, Beatrice, Contreras, Gabriele, Suarez, Maritza, Schulman, Ivonne, Koggan, Don, Vassallo, Jackie, Peruyera, Gloria, Whittington, Sheri, Bethea, Cassandra, Gilliam, Laura, Pedley, Carolyn, Zurek, Geraldine, Baird, Miriam, Herring, Charles, Smoak, Mary Martha, Williams, Julie, Rogers, Samantha, Gordon, Lindsay, Kennedy, Erin, Belle, Beverly, McCorkle-Doomy, Jessica, Adams, Jonathan, Lopez, Ramon, Janavs, Juris, Rahbari-Oskoui, Frederic, Chapman, Arlene, Dollar, Allen, Williams, Olubunmi, Han, Yoosun, Haley, William, Fitzpatrick, Peter, Blackshear, Joseph, Shapiro, Brian, Harrell, Anna, Palaj, Arta, Henderson, Katelyn, Johnson, Ashley, Gonzalez, Heath, Robinson, Jermaine, Tamariz, Leonardo, Denizard, Jennifer, Barakat, Rody, Krishnamoorthy, Dhurga, Greenway, Frank, Monce, Ron, Church, Timothy, Hendrick, Chelsea, Yoches, Aimee, Sones, Leighanne, Baltazar, Markee, Pemu, Priscilla, Jones, Connie, Akpalu, Derrick, Cheung, Alfred K., Beddhu, Srinivasan, Chelune, Gordon, Childs, Jeffrey, Gren, Lisa, Randall, Anne, Dember, Laura, Soares, Denise, Yee, Jerry, Umanath, Kausik, Ogletree, Naima, Thaxton, Schawana, Campana, Karen, Sheldon, Dayna, MacArthur, Krista, Muhlestein, J. Brent, Allred, Nathan, Clements, Brian, Dhar, Ritesh, Meredith, Kent, Le, Viet, Miner, Edward, Orford, James, Riessen, Erik R., Ballantyne, Becca, Chisum, Ben, Johnson, Kevin, Peeler, Dixie, Chertow, Glenn, Tamura, Manju, Chang, Tara, Erickson, Kevin, Shen, Jenny, Stafford, Randall S., Zaharchuk, Gregory, Del Cid, Margareth, Dentinger, Michelle, Sabino, Jennifer, Sahay, Rukmani, Telminova, Ekaterina, Weiner, Daniel E., Sarnak, Mark, Chan, Lily, Civiletto, Amanda, Heath, Alyson, Kantor, Amy, Jain, Priyanka, Kirkpatrick, Bethany, Well, Andrew, Yuen, Barry, Chonchol, Michel, Farmer, Beverly, Farmer, Heather, Greenwald, Carol, Malaczewski, Mikaela, Lash, James, Porter, Anna, Ricardo, Ana, Rosman, Robert T., Cohan, Janet, Barrera, Nieves Lopez, Meslar, Daniel, Meslar, Patricia, Conroy, Margaret, Unruh, Mark, Hess, Rachel, Jhamb, Manisha, Thomas, Holly, Fazio, Pam, Klixbull, Elle, Komlos-Weimer, Melissa, Mandich, LeeAnne, Vita, Tina, Toto, Robert, Van Buren, Peter, Inrig, Julia, Cruz, Martha, Lightfoot, Tammy, Wang, Nancy, Webster, Lori, Raphael, Kalani, Stults, Barry, Zaman, Tahir, Simmons, Debra, Lavasani, Tooran, Filipowicz, Rebecca, Wei, Guo, Miller, Gracie Mary, Harerra, Jenice, Christensen, Jeff, Giri, Ajay, Chen, Xiaorui, Anderton, Natalie, Jensen, Arianna, Lewis, Julia, Burgner, Anna, Dwyer, Jamie P., Schulman, Gerald, Herrud, Terri, Leavell, Ewanda, McCray, Tiffany, McNeil-Simaan, Edwina, Poudel, Munmun, Reed, Malia, Sika, Mohammed, Woods, Delia, Zirkenbach, Janice L., Raj, Dominic S., Cohen, Scott, Patel, Samir, Velasquez, Manuel, Bastian, Roshni S., Wing, Maria, Roy-Chaudhury, Akshay, Depner, Thomas, Dalyrymple, Lorien, Kaysen, George, Anderson, Susan, Nord, John, Ix, Joachim H., Goldenstein, Leonard, Miracle, Cynthia M., Forbang, Nketi, Mircic, Maja, Thomas, Brenda, Tran, Tiffany, Rastogi, Anjay, Kim, Mihae, Rashid, Mohamad, Lizarraga, Bianca, Hocza, Amy, Sarmosyan, Kristine, Norris, Jason, Sharma, Tushar, Chioy, Amanda, Bernard, Eric, Cabrera, Eleanore, Lopez, Christina, Nunez, Susana, Riad, Joseph, Schweitzer, Suzanne, Sirop, Siran, Thomas, Sarah, Wada, Lauren, Kramer, Holly, Bansal, Vinod, Taylor, Corliss E., Segal, Mark S., Hall, Karen L., Kazory, Amir, Gilbert, Lesa, Owens, Linda, Poulton, Danielle, Whidden, Elaine, Wiggins, Jocelyn, Blaum, Caroline, Nyquist, Linda, Min, Lillian, Gure, Tanya, Lewis, Ruth, Mawby, Jennifer, Robinson, Eileen, Oparil, Suzanne, Lewis, Cora E., Bradley, Virginia, Calhoun, David, Glasser, Stephen, Jenkins, Kim, Ramsey, Tom, Qureshi, Nauman, Ferguson, Karen, Haider, Sumrah, James, Mandy, Jones, Christy, Renfroe, Kim, Seay, April, Weigart, Carrie, Thornley-Brown, Denyse, Rizik, Dana, Cotton, Bari, Fitz-Gerald, Meredith, Grimes, Tiffany, Johnson, Carolyn, Kennedy, Sara, Mason, Chanel, Rosato-Burson, Lesa, Willingham, Robin, Judd, Eric, Breaux-Shropshire, Tonya, Cook, Felice, Medina, Julia, Ghazi, Lama, Bhatt, Hemal, Lewis, James, Brantley, Roman, Brouilette, John, Glaze, Jeffrey, Hall, Stephanie, Hiott, Nancy, Tharpe, David, Boddy, Spencer, Mack, Catherine, Womack, Catherine, Asao, Keiko, Griffin, Beate, Hendrix, Carol, Johnson, Karen, Jones, Lisa, Towers, Chelsea, Punzi, Henry, Cassidy, Kathy, Schumacher, Kristin, Irizarry, Carmen, Colon, Ilma, Colon-Ortiz, Pedro, Colón-Hernández, Pedro J., Carrasquillo-Navarro, Orlando J., Carrasquillo, Merari, Vazquez, Nivea, Sosa-Padilla, Miguel, Cintron-Pinero, Alex, Ayala, Mayra, Pacheco, Olga, Rivera, Catalina, Sotomayor-Gonzalez, Irma, Claudio, Jamie, Lazaro, Jose, Arce, Migdalia, Heres, Lourdes, Perez, Alba, Tavarez-Valle, Jose, Arocho, Ferlinda, Torres, Mercedes, Vazquez, Melvaliz, Aurigemma, Gerard P., Takis-Smith, Rebecca, Andrieni, Julia, Bodkin, Noelle, Chaudhary, Kiran, Hu, Paula, Kostis, John, Cosgrove, Nora, Bankowski, Denise, Boleyn, Monica, Casazza, Laurie, Giresi, Victoria, Patel, Tosha, Squindo, Erin, Wu, Yan, Henson, Zeb, Wofford, Marion, Lowery, Jessica, Minor, Deborah, Harkins, Kimberley, Auchus, Alexander, Flessner, Michael, Adair, Cathy, Asher, Jordan, Loope, Debbie, Cobb, Rita, Venegas, Reiner, Bigger, Thomas, Bello, Natalie, Homma, Shunichi, Donovan, Daniel, Lopez-Jimenez, Carlos, Tirado, Amilcar, Getaneh, Asqual, Tang, Rocky, Durant, Sabrina, Maurer, Mathew, Teruya, Sergio, Helmke, Stephen, Alvarez, Julissa, Campbell, Ruth, Pisoni, Roberto, Sturdivant, Rachel, Brooks, Deborah, Counts, Caroline, Hunt, Vickie, Spillers, Lori, Brautigam, Donald, Kitchen, Timothy, Gorman, Timothy, Sayers, Jessica, Button, Sarah, Chiarot, June, Fischer, Rosemary, Lyon, Melissa, Resnick, Maria, Hodges, Nicole, Ferreira, Jennifer, Cushman, William, Wall, Barry, Nichols, Linda, Burns, Robert, Martindale-Adams, Jennifer, Berlowitz, Dan, Clark, Elizabeth, Walsh, Sandy, Geraci, Terry, Huff, Carol, Shaw, Linda, Servilla, Karen, Vigil, Darlene, Barrett, Terry, Sweeney, Mary Ellen, Johnson, Rebecca, McConnell, Susan, Salles, Khadijeh Shahid, Watson, Francoise, Schenk, Cheryl, Whittington, Laura, Maher, Maxine, Williams, Jonathan, Swartz, Stephen, Conlin, Paul, Alexis, George, Lamkin, Rebecca, Underwood, Patti, Gomes, Helen, Rosendorff, Clive, Atlas, Stephen, Khan, Saadat, Gonzalez, Waddy, Barcham, Samih, Kwon, Lawrence, Matar, Matar, Adhami, Anwar, Basile, Jan, John, Joseph, Ham, Deborah, Baig, Hadi, Saklayen, Mohammed, Yap, Jason, Neff, Helen, Miller, Carol, Zheng-Phelan, Ling, Gappy, Saib, Rau, Shiva, Raman, Arathi, Berchou, Vicki, Jones, Elizabeth, Olgren, Erin, Marbury, Cynthia, Yudd, Michael, Sastrasinh, Sithiporn, Michaud, Jennine, Fiore, Jessica, Kutza, Marianne, Shorr, Ronald, Mount, Rattana, Dunn, Helen, Stinson, Susan, Hunter, Jessica, Taylor, Addison, Bates, Jeffery, Anderson, Catherine, Kirchner, Kent, Stubbs, Jodi, Hinton, Ardell, Spencer, Anita, Sharma, Santosh, Wiegmann, Thomas, Mehta, Smita, Krause, Michelle, Dishongh, Kate, Childress, Richard, Gyamlani, Geeta, Niakan, Atossa, Thompson, Cathy, Moody, Janelle, Gresham, Carolyn, Whittle, Jeffrey, Barnas, Gary, Wolfgram, Dawn, Cortese, Heidi, Johnson, Jonette, Roumie, Christianne, Hung, Adriana, Wharton, Jennifer, Niesner, Kurt, Katz, Lois, Richardson, Elizabeth, Brock, George, Holland, Joanne, Dixon, Troy, Zias, Athena, Spiller, Christine, Baker, Penelope, Felicetta, James, Rehman, Shakaib, Bingham, Kelli, Watnick, Suzanne, Cohen, David, Weiss, Jessica, Johnston, Tera, Giddings, Stephen, Yamout, Hala, Klein, Andrew, Rowe, Caroline, Vargo, Kristin, Waidmann, Kristi, Papademetriou, Vasilios, Elkhoury, Jean Pierre, Gregory, Barbara, Amodeo, Susan, Bloom, Mary, Goldfarb-Waysman, Dalia, Treger, Richard, Kashefi, Mehran, Huang, Christina, Knibloe, Karen, Ishani, Areef, Slinin, Yelena, Olney, Christine, Rust, Jacqueline, Fanti, Paolo, Dyer, Christopher, Bansal, Shweta, Dunnam, Monica, Hu, Lih-Lan, Zarate-Abbott, Perla, Kurella Tamura, Manjula, Pajewski, Nicholas M., Zaharchuk, Greg, Rapp, Stephen R., Auchus, Alexander P., Haley, William E., Kendrick, Jessica, Roumie, Christianne L., Williamson, Jeff D., Detre, John A., Dolui, Sudipto, and Nasrallah, Ilya M.
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- 2022
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48. Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes
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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.
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- 2023
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49. Biological Variability of Estimated GFR and Albuminuria in CKD.
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Waikar, Sushrut S, Rebholz, Casey M, Zheng, Zihe, Hurwitz, Shelley, Hsu, Chi-Yuan, Feldman, Harold I, Xie, Dawei, Liu, Kathleen D, Mifflin, Theodore E, Eckfeldt, John H, Kimmel, Paul L, Vasan, Ramachandran S, Bonventre, Joseph V, Inker, Lesley A, Coresh, Josef, and Chronic Kidney Disease Biomarkers Consortium Investigators
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Chronic Kidney Disease Biomarkers Consortium Investigators ,Humans ,Albuminuria ,Creatinine ,Intramolecular Oxidoreductases ,beta 2-Microglobulin ,Glomerular Filtration Rate ,Urinalysis ,Blood Chemical Analysis ,Prognosis ,Severity of Illness Index ,Cross-Sectional Studies ,Predictive Value of Tests ,Adult ,Aged ,Middle Aged ,Female ,Male ,Renal Insufficiency ,Chronic ,Lipocalins ,Cystatin C ,Biomarkers ,beta trace protein ,biological variability ,biomarker ,clinically meaningful differences ,coefficient of variation ,cystatin C ,estimated glomerular filtration rate ,filtration marker ,intraindividual variation ,kidney function ,laboratory measurement ,reproducibility ,serum creatinine ,urinary albumin-creatinine ratio ,β(2)-microglobulin ,Kidney Disease ,Clinical Research ,Renal and urogenital ,Good Health and Well Being ,Clinical Sciences ,Public Health and Health Services ,Urology & Nephrology - Abstract
Rationale & objectiveDetermining whether a change in estimated glomerular filtration rate (eGFR) or albuminuria is clinically significant requires knowledge of short-term within-person variability of the measurements, which few studies have addressed in the setting of chronic kidney disease.Study designCross-sectional study with multiple collections over less than 4 weeks.Setting & participantsClinically stable outpatients with chronic kidney disease (N=50; mean age, 56.8 years; median eGFR, 40mL/min/1.73m2; median urinary albumin-creatinine ratio (UACR), 173mg/g).ExposureRepeat measurements from serially collected samples across 3 study visits.OutcomesMeasurements of urine albumin concentration (UAC), UACR, and plasma creatinine, cystatin C, β2-microglobulin (B2M), and beta trace protein (BTP).Analytical approachWe calculated within-person coefficients of variation (CVw) values and corresponding reference change positive and negative (RCVpos and RCVneg) values using log-transformed measurements.ResultsMedian CVw (RCVpos; RCVneg) values of filtration markers were 5.4% (+16%; -14%) for serum creatinine, 4.1% (+12%; -11%) for cystatin C, 7.4% (+23%; -18%) for BTP, and 5.6% (+17%; -14%) for B2M. Results for albuminuria were 33.2% (+145%; -59%) for first-morning UAC, 50.6% (+276%; -73%) for random spot UAC, 32.5% (+141%; -58%) for first-morning UACR, and 29.7% (124%; -55%) for random spot UACR. CVw values for filtration markers were comparable across the range of baseline eGFRs. CVw values for UAC and UACR were comparable across the range of baseline albuminuria values.LimitationsSmall sample size limits the ability to detect differences in variability across markers. Participants were recruited and followed up in a clinical and not research setting, so some preanalytical factors could not be controlled.ConclusionseGFR markers appear to have relatively low short-term within-person variability, whereas variability in albuminuria appears to be high, making it difficult to distinguish random variability from meaningful biologic changes.
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- 2018
50. Kidney disease in the setting of HIV infection: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference
- Author
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Swanepoel, Charles R, Atta, Mohamed G, D’Agati, Vivette D, Estrella, Michelle M, Fogo, Agnes B, Naicker, Saraladevi, Post, Frank A, Wearne, Nicola, Winkler, Cheryl A, Cheung, Michael, Wheeler, David C, Winkelmayer, Wolfgang C, Wyatt, Christina M, Participants, Conference, Abu-Alfa, Ali, Adu, Dwomoa, Agodoa, Lawrence Y, Alpers, Charles E, Arogundade, Fatiu A, Ashuntantang, Gloria, Bagnis, Corinne I, Bhimma, Raj, Brocheriou, Isabelle, Cohen, Arthur H, Cohen, Karen, Cook, H Terence, de Seigneux, Sophie, Fabian, June, Finkelstein, Fredric O, Haas, Mark, Hamzah, Lisa, Hendry, Bruce M, Imonje, Valentine, Jennette, J Charles, Kimmel, Paul L, Klotman, Mary E, Klotman, Paul E, Larsen, Chris P, McCulloch, Mignon I, Mosiane, Pulane, Nast, Cynthia C, Okpechi, Ikechi G, Ray, Patricio E, Rosenberg, Avi Z, Ross, Michael J, Ryom, Lene, Truong, Luan, Ulasi, Ifeoma, Vogt, Liffert, and Zeier, Martin
- Subjects
HIV/AIDS ,Pediatric ,Kidney Disease ,Prevention ,Infectious Diseases ,2.1 Biological and endogenous factors ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Aetiology ,Infection ,Renal and urogenital ,Good Health and Well Being ,AIDS-Associated Nephropathy ,Anti-HIV Agents ,Comorbidity ,Diagnosis ,Differential ,Evidence-Based Medicine ,Genetic Predisposition to Disease ,HIV ,Host-Pathogen Interactions ,Humans ,Kidney ,Nephrology ,Predictive Value of Tests ,Renal Insufficiency ,Chronic ,Risk Factors ,Treatment Outcome ,antiretroviral therapy ,APOL1 ,CKD progression ,immune complex kidney disease ,podocytopathy ,renal pathology ,Conference Participants ,Clinical Sciences ,Urology & Nephrology - Abstract
HIV-positive individuals are at increased risk for kidney disease, including HIV-associated nephropathy, noncollapsing focal segmental glomerulosclerosis, immune-complex kidney disease, and comorbid kidney disease, as well as kidney injury resulting from prolonged exposure to antiretroviral therapy or from opportunistic infections. Clinical guidelines for kidney disease prevention and treatment in HIV-positive individuals are largely extrapolated from studies in the general population, and do not fully incorporate existing knowledge of the unique HIV-related pathways and genetic factors that contribute to the risk of kidney disease in this population. We convened an international panel of experts in nephrology, renal pathology, and infectious diseases to define the pathology of kidney disease in the setting of HIV infection; describe the role of genetics in the natural history, diagnosis, and treatment of kidney disease in HIV-positive individuals; characterize the renal risk-benefit of antiretroviral therapy for HIV treatment and prevention; and define best practices for the prevention and management of kidney disease in HIV-positive individuals.
- Published
- 2018
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