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

Author

Matsushita, K, Ballew, Sh, Coresh, J, Arima, H, Ärnlöv, J, Cirillo, Massimo, Ebert, N, Hiramoto, Js, Kimm, H, Shlipak, Mg, Visseren, Flj, Gansevoort, Rt, Kovesdy, Cp, Shalev, V, Woodward, M, Kronenberg, F, Chronic Kidney Disease Prognosis Consortium: Chalmers, J, Perkovic, V, Grams, Me, Sang, Y, Schaeffner, E, Martus, P, Levin, A, Djurdjev, O, Tang, M, Heine, G, Seiler, S, Zawada, A, Emrich, I, Sarnak, M, Katz, R, Brenner, H, Schöttker, B, Rothenbacher, D, Saum, Ku, Köttgen, A, Schneider, M, Eckardt, Ku, Green, J, Kirchner, Hl, Chang, Ar, Black, C, Marks, A, Prescott, G, Clark, L, Fluck, N, Jee, Sh, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, Van, Zuilen, Bots, M, Peralta, C, Hiromoto, J, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Kenealy, T, Elley, Cr, Collins, Jf, Drury, Pl, Bakker, Sj, Heerspink, Hjl, Jassal, Sk, Bergstrom, J, Jh, Ix, Barrett Connor, E, Kalantar Zadeh, K, Carrero, Jj, Gasparini, A, Qureshi, Ar, Barany, P, Algra, A, Van, Der, Graaf, Y, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Lannfelt, L, Larsson, A, Hallan, S, Levey, As, Chen, J, Kwak, L, Sang, Y., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Matsushita, K, Ballew, Sh, Coresh, J, Arima, H, Ärnlöv, J, Cirillo, Massimo, Ebert, N, Hiramoto, J, Kimm, H, Shlipak, Mg, Visseren, Flj, Gansevoort, Rt, Kovesdy, Cp, Shalev, V, Woodward, M, Kronenberg, F, Chronic Kidney Disease Prognosis Consortium: Chalmers, J, Perkovic, V, Grams, Me, Sang, Y, Schaeffner, E, Martus, P, Levin, A, Djurdjev, O, Tang, M, Heine, G, Seiler, S, Zawada, A, Emrich, I, Sarnak, M, Katz, R, Brenner, H, Schöttker, B, Rothenbacher, D, Saum, Ku, Köttgen, A, Schneider, M, Eckardt, Ku, Green, J, Kirchner, Hl, Chang, Ar, Black, C, Marks, A, Prescott, G, Clark, L, Fluck, N, Jee, Sh, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, Van, Zuilen, Ad, Bots, M, Peralta, C, Hiromoto, J, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Kenealy, T, Elley, Cr, Collins, Jf, Drury, Pl, Bakker, Sj, Heerspink, Hjl, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett Connor, E, Kalantar Zadeh, K, Carrero, Jj, Gasparini, A, Qureshi, Ar, Barany, P, Algra, A, Van, Der, Graaf, Y, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Lannfelt, L, Larsson, A, Hallan, S, Levey, A, Chen, J, Kwak, L, and Sang, Y.

Subjects
Male, Databases, Factual, Endocrinology, Diabetes and Metabolism, nefropatia, arteriopatia periferica, epidemiologia, 030204 cardiovascular system & hematology, GLOMERULAR-FILTRATION-RATE, arteriopatia periferica, 0302 clinical medicine, Endocrinology, Risk Factors, CRITICAL LIMB ISCHEMIA, 030212 general & internal medicine, epidemiologia, POPULATION, biology, CYSTATIN C, Incidence, Middle Aged, PREVALENCE, Diabetes and Metabolism, nefropatia, Creatinine, Female, medicine.symptom, Glomerular Filtration Rate, Adult, medicine.medical_specialty, Renal function, ATHEROSCLEROSIS RISK, HEART-ASSOCIATION, CARDIOVASCULAR OUTCOMES, 03 medical and health sciences, Peripheral Arterial Disease, Internal medicine, Diabetes mellitus, medicine, Internal Medicine, Albuminuria, Humans, Risk factor, Renal Insufficiency, Chronic, Aged, business.industry, Critical limb ischemia, medicine.disease, Intermittent claudication, Surgery, Cystatin C, biology.protein, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Kidney disease
Abstract

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

Published
2017

3. Relative risks of Chronic Kidney Disease for mortality and End Stage Renal Disease across races is similar

Author

Wright, Jt, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, L, Menon, V, Fried, Lf, Kramer, H, Boer, De, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Wu, Be, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright, Jt, Jr, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Levey, A, Inker, L, Menon, V, Fried, Lf, Kramer, H, De, Boer, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, De, Jong, Pe, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, De, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Be, Wu, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, GLOMERULAR-FILTRATION-RATE, Cohort Studies, Risk Factors, eGFR, Odds Ratio, ASSOCIATIONS, African Continental Ancestry Group, Aged, 80 and over, education.field_of_study, end-stage renal disease, Hazard ratio, PROTEINURIA, Urology & Nephrology, Middle Aged, CKD-EPI EQUATION, 3. Good health, PREVALENCE, Nephrology, Cardiovascular Diseases, Creatinine, ethnicity, Female, medicine.symptom, epidemiology and outcomes, Glomerular Filtration Rate, Asian Continental Ancestry Group, Adult, medicine.medical_specialty, Population, European Continental Ancestry Group, Renal function, Black People, ALL-CAUSE, Article, White People, End stage renal disease, Asian People, Internal medicine, medicine, Chronic Kidney Disease Prognosis Consortium, Albuminuria, Humans, Renal Insufficiency, Chronic, education, Aged, business.industry, 1103 Clinical Sciences, Odds ratio, POPULATION COHORTS, medicine.disease, INDIVIDUALS, Endocrinology, Relative risk, COLLABORATIVE METAANALYSIS, mortality risk, Kidney Failure, Chronic, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, HIGHER ALBUMINURIA, chronic kidney disease, Kidney disease
Abstract

Item does not contain fulltext Some suggest race-specific cutpoints for kidney measures to define and stage chronic kidney disease (CKD), but evidence for race-specific clinical impact is limited. To address this issue, we compared hazard ratios of estimated glomerular filtration rates (eGFR) and albuminuria across races using meta-regression in 1.1 million adults (75% Asians, 21% Whites, and 4% Blacks) from 45 cohorts. Results came mainly from 25 general population cohorts comprising 0.9 million individuals. The associations of lower eGFR and higher albuminuria with mortality and end-stage renal disease (ESRD) were largely similar across races. For example, in Asians, Whites, and Blacks, the adjusted hazard ratios (95% confidence interval) for eGFR 45-59 versus 90-104 ml/min per 1.73 m(2) were 1.3 (1.2-1.3), 1.1 (1.0-1.2), and 1.3 (1.1-1.7) for all-cause mortality, 1.6 (1.5-1.7), 1.4 (1.2-1.7), and 1.4 (0.7-2.9) for cardiovascular mortality, and 27.6 (11.1-68.7), 11.2 (6.0-20.9), and 4.1 (2.2-7.5) for ESRD, respectively. The corresponding hazard ratios for urine albumin-to-creatinine ratio 30-299 mg/g or dipstick 1+ versus an albumin-to-creatinine ratio under 10 or dipstick negative were 1.6 (1.4-1.8), 1.7 (1.5-1.9), and 1.8 (1.7-2.1) for all-cause mortality, 1.7 (1.4-2.0), 1.8 (1.5-2.1), and 2.8 (2.2-3.6) for cardiovascular mortality, and 7.4 (2.0-27.6), 4.0 (2.8-5.9), and 5.6 (3.4-9.2) for ESRD, respectively. Thus, the relative mortality or ESRD risks of lower eGFR and higher albuminuria were largely similar among three major races, supporting similar clinical approach to CKD definition and staging, across races.

Published
2014

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

Author

Ichikawa K., Collins J.F., Drury P.L., Ellis S.G., Nadukuru R., Metzger M., Flamant M., Houillier P., Haymann J.-P., Froissart M., Kenealy T., Elley R.C., Cuddeback J.K., Ciemins E.L., Stempniewicz R., Nelson R.G., Knowler W.C., Bakker S.J., Major R.W., Medcalf J.F., Shepherd D., Barrett-Connor E., Bergstrom J., Ix J.H., Molnar M.Z., Maciulaitis R., Manley T., Smith K., Stockbridge N., Thompson A., Vetter T., Willis K., Zhang L., Coresh J., Heerspink H.J.L., Sang Y., Matsushita K., Arnlov J., Astor B.C., Black C., Brunskill N.J., Carrero J.-J., Feldman H.I., Fox C.S., Inker L.A., Ishani A., Ito S., Jassal S., Konta T., Polkinghorne K., Romundstad S., Solbu M.D., Stempniewicz N., Stengel B., Tonelli M., Umesawa M., Waikar S.S., Wen C.-P., Wetzels J.F.M., Woodward M., Grams M.E., Kovesdy C.P., Levey A.S., Gansevoort R.T., Appel L.J., Greene T., Chen T.K., Chalmers J., Arima H., Perkovic V., Levin A., Djurdjev O., Tang M., Nally J., Navaneethan S.D., Schold J.D., Weldegiorgis M., Herrington W.G., Smith M., Hsu C.Y., Hwang S.-J., Chang A.R., Kirchner H.L., Green J.A., Ho K., Marks A., Prescott G., Clark L.E., Fluck N., Shalev V., Chodick G., Blankestijn P.J., Van Zuilen A., Van den Brand J.A., Sarnak M.J., Bottinger E., Nadkarni G.N., Sumida K., de Zeeuw D., Brenner B., Qureshi A.R., Elinder C.-G., Runesson B., Evans M., Segelmark M., Stendahl M., Schon S., Naimark D.M., Tangri N., Sud M., Hirayama A., Bilo H.J., Landman G.W., Van Hateren K.J., Kleefstra N., Hallan S.I., Ballew S.H., Chen J., Kwak L., Surapaneni A., Parving H.-H., Rodby R.A., Rohde R.D., Lewis J.B., Lewis E., Perrone R.D., Abebe K.Z., Hou F.F., Xie D., Hunsicker L.G., Imai E., Kobayashi F., Makino H., Remuzzi G., Ruggenenti P., Eckardt K.-U., Gudmundsdottir H., Ichikawa K., Collins J.F., Drury P.L., Ellis S.G., Nadukuru R., Metzger M., Flamant M., Houillier P., Haymann J.-P., Froissart M., Kenealy T., Elley R.C., Cuddeback J.K., Ciemins E.L., Stempniewicz R., Nelson R.G., Knowler W.C., Bakker S.J., Major R.W., Medcalf J.F., Shepherd D., Barrett-Connor E., Bergstrom J., Ix J.H., Molnar M.Z., Maciulaitis R., Manley T., Smith K., Stockbridge N., Thompson A., Vetter T., Willis K., Zhang L., Coresh J., Heerspink H.J.L., Sang Y., Matsushita K., Arnlov J., Astor B.C., Black C., Brunskill N.J., Carrero J.-J., Feldman H.I., Fox C.S., Inker L.A., Ishani A., Ito S., Jassal S., Konta T., Polkinghorne K., Romundstad S., Solbu M.D., Stempniewicz N., Stengel B., Tonelli M., Umesawa M., Waikar S.S., Wen C.-P., Wetzels J.F.M., Woodward M., Grams M.E., Kovesdy C.P., Levey A.S., Gansevoort R.T., Appel L.J., Greene T., Chen T.K., Chalmers J., Arima H., Perkovic V., Levin A., Djurdjev O., Tang M., Nally J., Navaneethan S.D., Schold J.D., Weldegiorgis M., Herrington W.G., Smith M., Hsu C.Y., Hwang S.-J., Chang A.R., Kirchner H.L., Green J.A., Ho K., Marks A., Prescott G., Clark L.E., Fluck N., Shalev V., Chodick G., Blankestijn P.J., Van Zuilen A., Van den Brand J.A., Sarnak M.J., Bottinger E., Nadkarni G.N., Sumida K., de Zeeuw D., Brenner B., Qureshi A.R., Elinder C.-G., Runesson B., Evans M., Segelmark M., Stendahl M., Schon S., Naimark D.M., Tangri N., Sud M., Hirayama A., Bilo H.J., Landman G.W., Van Hateren K.J., Kleefstra N., Hallan S.I., Ballew S.H., Chen J., Kwak L., Surapaneni A., Parving H.-H., Rodby R.A., Rohde R.D., Lewis J.B., Lewis E., Perrone R.D., Abebe K.Z., Hou F.F., Xie D., Hunsicker L.G., Imai E., Kobayashi F., Makino H., Remuzzi G., Ruggenenti P., Eckardt K.-U., and Gudmundsdottir H.

Abstract

Background: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. Method(s): In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. Finding(s): Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the C

Published
2019

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

Author

Coresh, J, Heerspink, HJL, Sang, Y, Matsushita, K, Arnlov, J, Astor, BC, Black, C, Brunskill, NJ, Carrero, JJ, Feldman, HI, Fox, CS, Inker, LA, Ishani, A, Ito, S, Jassal, S, Konta, T, Polkinghorne, K, Romundstad, S, Solbu, MD, Stempniewicz, N, Stengel, B, Tonelli, M, Umesawa, M, Waikar, SS, Wen, CP, Wetzels, JFM, Woodward, M, Grams, ME, Kovesdy, CP, Levey, AS, Gansevoort, RT, Appel, LJ, Greene, T, Chen, TK, Chalmers, J, Arima, H, Perkovic, V, Levin, A, Djurdjev, O, Tang, M, Nally, J, Navaneethan, SD, Schold, JD, Weldegiorgis, M, Herrington, WG, Smith, M, Hsu, CY, Hwang, SJ, Chang, AR, Kirchner, HL, Green, JA, Ho, K, Marks, A, Prescott, G, Clark, LE, Fluck, N, Shalev, V, Chodick, G, Blankestijn, PJ, Van Zuilen, A, Van den Brand, JA, Sarnak, MJ, Bottinger, E, Nadkarni, GN, Ellis, SG, Nadukuru, R, Metzger, M, Flamant, M, Houillier, P, Haymann, JP, Froissart, M, Kenealy, T, Elley, RC, Collins, JF, Drury, PL, Cuddeback, JK, Ciemins, EL, Stempniewicz, R, Nelson, RG, Knowler, WC, Bakker, SJ, Major, RW, Medcalf, JF, Shepherd, D, Barrett-Connor, E, Bergstrom, J, Ix, JH, Molnar, MZ, Sumida, K, de Zeeuw, D, Brenner, B, Qureshi, AR, Elinder, CG, Runesson, B, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Naimark, DM, Tangri, N, Coresh, J, Heerspink, HJL, Sang, Y, Matsushita, K, Arnlov, J, Astor, BC, Black, C, Brunskill, NJ, Carrero, JJ, Feldman, HI, Fox, CS, Inker, LA, Ishani, A, Ito, S, Jassal, S, Konta, T, Polkinghorne, K, Romundstad, S, Solbu, MD, Stempniewicz, N, Stengel, B, Tonelli, M, Umesawa, M, Waikar, SS, Wen, CP, Wetzels, JFM, Woodward, M, Grams, ME, Kovesdy, CP, Levey, AS, Gansevoort, RT, Appel, LJ, Greene, T, Chen, TK, Chalmers, J, Arima, H, Perkovic, V, Levin, A, Djurdjev, O, Tang, M, Nally, J, Navaneethan, SD, Schold, JD, Weldegiorgis, M, Herrington, WG, Smith, M, Hsu, CY, Hwang, SJ, Chang, AR, Kirchner, HL, Green, JA, Ho, K, Marks, A, Prescott, G, Clark, LE, Fluck, N, Shalev, V, Chodick, G, Blankestijn, PJ, Van Zuilen, A, Van den Brand, JA, Sarnak, MJ, Bottinger, E, Nadkarni, GN, Ellis, SG, Nadukuru, R, Metzger, M, Flamant, M, Houillier, P, Haymann, JP, Froissart, M, Kenealy, T, Elley, RC, Collins, JF, Drury, PL, Cuddeback, JK, Ciemins, EL, Stempniewicz, R, Nelson, RG, Knowler, WC, Bakker, SJ, Major, RW, Medcalf, JF, Shepherd, D, Barrett-Connor, E, Bergstrom, J, Ix, JH, Molnar, MZ, Sumida, K, de Zeeuw, D, Brenner, B, Qureshi, AR, Elinder, CG, Runesson, B, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Naimark, DM, and Tangri, N

Abstract

Background: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. Methods: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. Findings: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-P

Published
2019

6. Age and Association of Kidney Measures With Mortality and End-stage Renal Disease

Author

Wright, Jt, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Brenner, Be, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright JT Jr, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, de Jong PE, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, BLOOD-PRESSURE, urologic and male genital diseases, Kidney, età, GLOMERULAR-FILTRATION-RATE, Cohort Studies, eGFR, Young adult, Renal disorder [IGMD 9], ALL-CAUSE MORTALITY, GENERAL-POPULATION, insufficienza renale, biology, CYSTATIN C, CARDIOVASCULAR RISK, Age Factors, General Medicine, Middle Aged, female genital diseases and pregnancy complications, RISK POPULATION COHORTS, medicine.anatomical_structure, Female, medicine.symptom, Glomerular Filtration Rate, albuminuria, rischio, mortalità, Adult, Risk, medicine.medical_specialty, Adolescent, Renal function, Context (language use), End stage renal disease, Young Adult, Internal medicine, medicine, Albuminuria, Humans, OLDER-ADULTS, Aged, urogenital system, business.industry, URINARY ALBUMIN EXCRETION, medicine.disease, Endocrinology, Cystatin C, COLLABORATIVE METAANALYSIS, biology.protein, Kidney Failure, Chronic, business, Kidney disease
Abstract

Context Chronic kidney disease (CKD) is prevalent in older individuals, but the risk implications of low estimated glomerular filtration rate (eGFR) and high albuminuria across the full age range are controversial.Objective To evaluate possible effect modification (interaction) by age of the association of eGFR and albuminuria with clinical risk, examining both relative and absolute risks.Design, Setting, and Participants Individual-level meta-analysis including 2 051 244 participants from 33 general population or high-risk (of vascular disease) cohorts and 13 CKD cohorts from Asia, Australasia, Europe, and North/South America, conducted in 1972-2011 with a mean follow-up time of 5.8 years (range, 0-31 years).Main Outcome Measures Hazard ratios (HRs) of mortality and end-stage renal disease (ESRD) according to eGFR and albuminuria were meta-analyzed across age categories after adjusting for sex, race, cardiovascular disease, diabetes, systolic blood pressure, cholesterol, body mass index, and smoking. Absolute risks were estimated using HRs and average incidence rates.Results Mortality (112 325 deaths) and ESRD (8411 events) risks were higher at lower eGFR and higher albuminuria in every age category. In general and high-risk cohorts, relative mortality risk for reduced eGFR decreased with increasing age; eg, adjusted HRs at an eGFR of 45 mL/min/1.73 m(2) vs 80 mL/min/1.73 m(2) were 3.50 (95% CI, 2.55-4.81), 2.21 (95% CI, 2.02-2.41), 1.59 (95% CI, 1.42-1.77), and 1.35 (95% CI, 1.23-1.48) in age categories 18-54, 55-64, 65-74, and >= 75 years, respectively (P Conclusions Both low eGFR and high albuminuria were independently associated with mortality and ESRD regardless of age across a wide range of populations. Mortality showed lower relative risk but higher absolute risk differences at older age.

Published
2012
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7. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis

Author

Fox, Cs, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, Jong, De, Wen, Cp, Nelson, Rg, Chronic, Kidney, Disease, Prognosis, Consortium, Investigators/collaborators:, Wright, J, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Menon, V, Kramer, Hj, Boer, De, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Lambers, Heerspink, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Groningen Kidney Center (GKC), Methods in Medicines evaluation & Outcomes research (M2O), Lifestyle Medicine (LM), Fox, C, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, de Jong PE, Wen, Cp, Nelson, Rg, Investigators/Collaborators: Wright J, Chronic Kidney Disease Prognosis Consortium, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer IH, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink HJ, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
medicine.medical_specialty, Population, UNITED-STATES, Renal function, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, albuminuria, End stage renal disease, Diabetic nephropathy, CKD-PC Consortium, Diabetes mellitus, Internal medicine, eGFR, Medicine, ESTIMATED GFR, education, Intensive care medicine, Renal disorder [IGMD 9], OUTCOMES, education.field_of_study, end-stage renal disease, diabetes, business.industry, Hazard ratio, PROTEINURIA, General Medicine, mortality, medicine.disease, RISK POPULATION COHORTS, PREVALENCE, diabete, COLLABORATIVE METAANALYSIS, Albuminuria, medicine.symptom, HIGHER ALBUMINURIA, business, Kidney disease
Abstract

Item does not contain fulltext BACKGROUND: Chronic kidney disease is characterised by low estimated glomerular filtration rate (eGFR) and high albuminuria, and is associated with adverse outcomes. Whether these risks are modified by diabetes is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and end-stage renal disease (ESRD) associated with eGFR and albuminuria in individuals with and without diabetes. FINDINGS: We analysed data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts. In the combined general population and high-risk cohorts with data for all-cause mortality, 75,306 deaths occurred during a mean follow-up of 8.5 years (SD 5.0). In the 23 studies with data for cardiovascular mortality, 21,237 deaths occurred from cardiovascular disease during a mean follow-up of 9.2 years (SD 4.9). In the general and high-risk cohorts, mortality risks were 1.2-1.9 times higher for participants with diabetes than for those without diabetes across the ranges of eGFR and albumin-to-creatinine ratio (ACR). With fixed eGFR and ACR reference points in the diabetes and no diabetes groups, HR of mortality outcomes according to lower eGFR and higher ACR were much the same in participants with and without diabetes (eg, for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) [vs 95 mL/min per 1.73 m(2)], HR 1.35; 95% CI 1.18-1.55; vs 1.33; 1.19-1.48 and at ACR 30 mg/g [vs 5 mg/g], 1.50; 1.35-1.65 vs 1.52; 1.38-1.67). The overall interactions were not significant. We identified much the same findings for ESRD in the chronic kidney disease cohorts. INTERPRETATION: Despite higher risks for mortality and ESRD in diabetes, the relative risks of these outcomes by eGFR and ACR are much the same irrespective of the presence or absence of diabetes, emphasising the importance of kidney disease as a predictor of clinical outcomes. FUNDING: US National Kidney Foundation.

Published
2012
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8. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate

Author

Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, As, Chronic, Kidney, Disease, Prognosis, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, Es, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Menon, V, Boer, De, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Jong, De, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, Zeeuw, De, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, A, Chronic, Kidney, Disease, Prognosi, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, E, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Menon, V, De, Boer, Ih, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, De, Jong, Pe, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, De, Zeeuw, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
CHRONIC KIDNEY-DISEASE, Gerontology, Male, EVALUATION PROGRAM KEEP, Population, Renal function, Black People, Ckd epi equation, urologic and male genital diseases, Risk Assessment, White People, Article, Decision Support Techniques, Cohort Studies, Sex Factors, Asian People, EPIDEMIOLOGY COLLABORATION EQUATION, Diabetes mellitus, CYSTATIN-C, Medicine, Humans, education, ALL-CAUSE MORTALITY, Cardiovascular mortality, Aged, Renal disorder [IGMD 9], GENERAL-POPULATION, education.field_of_study, business.industry, CARDIOVASCULAR RISK, Hazard ratio, STAGE RENAL-DISEASE, General Medicine, POPULATION COHORTS, Middle Aged, Models, Theoretical, medicine.disease, female genital diseases and pregnancy complications, Net reclassification improvement, SERUM CREATININE VALUES, Cardiovascular Diseases, Kidney Failure, Chronic, Female, business, Algorithms, Demography, Glomerular Filtration Rate
Abstract

Contains fulltext : 110640.pdf (Publisher’s version ) (Closed access) CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged >/= 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS: Estimated GFR was classified into 6 categories (>/=90, 60-89, 45-59, 30-44, 15-29, and /=65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

Published
2012

9. CKD GENERAL AND CLINICAL EPIDEMIOLOGY 2

Author

Davids, M. R., Marais, N., Jacobs, J., Cohen, E., Krause, I., Goldberg, E., Garty, M., Dursun, B., Sahan, Y., Tanriverdi, H., Rota, S., Uslu, S., Senol, H., Minutolo, R., Gabbai, F. B., Agarwal, R., Chiodini, P., Borrelli, S., Stanzione, G., Nappi, F., Bellizzi, V., Conte, G., Nicola, L. D., J. V., De, Johnson, S., Fremeaux Bacchi, V., Ardissino, G., Ariceta, G., Beauchamp, J., Cohen, D., Greenbaum, L. A., Ogawa, M., Schaefer, F., Licht, C., Scalzotto, E., Nalesso, F., Zaglia, T., Corradi, V., Neri, M., Martino, F., Zanella, M., Brendolan, A., Mongillo, M., Ronco, C., Chinnappa, S., Mooney, A., A. M., El, Y. K., Tu, Tan, L. B., Jung, J. Y., Kim, A. J., Ro, H., Lee, C., Chang, J. H., Lee, H. H., Chung, W., Clarke, A. L., Young, H. M., Hull, K. L., Hudson, N., Burton, J. O., Smith, A. C., Marx, S., Petrilla, A., Filipovic, I., Lee, W. C., Meijers, B., Poesen, R., Storr, M., Claes, K., Kuypers, D., Evenepoel, P., Aukland, M., Betriu, A., Martinez Alonso, M., Arcidiacono, M. V., Cannata Andia, J., Pascual, J., Valdivielso, J. M., Fernandez Giraldez, E., Kingswood, J. C., Zonnenberg, B., Sauter, M., Zakar, G., Biro, B., Besenczi, B., Varga, A., Pekacs, P., Pizzini, P., Pisano, A., Leonardis, D., Panuccio, V., Cutrupi, S., Tripepi, G., Mallamaci, F., Zoccali, C., Arnold, J., Baharani, J., Rayner, H., B. H., So, Blackwell, S., Jardine, A. G., Macgregor, M. S., Cunha, C., Barreto, P., Pereira, S., Ventura, A., Mota, M., Seabra, J., Sakaguchi, T., Kobayashi, S., Yano, T., Yoshimoto, W., Bancu, I., Bastons, J. B., Escayola, M. C., Vallespin, E. V., Poblet, M. B., Luque, D. M., Fabregas, M. P., Chen, J., Chen, S., Chang, J., Hwang, S., Chen, H., Ahbap, E., Kara, E., Basturk, T., Sahutoglu, T., Koc, Y., Sakaci, T., Sevinc, M., Akgol, C., Ozagari, A. A., Unsal, A., Minami, S., Hesaka, A., Yamaguchi, S., Iwahashi, E., Sakai, S., Fujimoto, T., Sasaki, K., Fujita, Y., Yokoyama, K., Marks, A., Fluck, N., Prescott, G., Robertson, L., Smith, W. C., Black, C., Ohsawa, M., Fujioka, T., Omori, S., Isurugi, T., Tanno, K., Onoda, T., Omama, S., Ishibashi, Y., Makita, S., Okayama, A., Garland, J. S., Simpson, C. S., Metangi, M. F., Parfrey, B., Johri, A. M., Sloan, L., Mcauley, J., Cunningham, R., Mullan, R., Quinn, M., Harron, C., Chiu, H., Murphy Burke, D., Werb, R., Jung, B., Chan Yan, C., Duncan, J., Forzley, B., Lowry, R., Hargrove, G., Carson, R., Levin, A., Karim, M., Reznik, E. V., G. I. V., Rollino, C., Troiano, M., Bagatella, M., Liuzzo, C., Quarello, F., Roccatello, D., Blaslov, K., Bulum, T., Prkacin, I., Duvnjak, L., Heleniak, Z., Cieplinska, M., Szychlinski, T., Pryczkowska, M., Bartosinska, E., Wiatr, H., Kotlowska, H., Tylicki, L., Rutkowski, B., Song, Y. R., Kim, S. G., Kim, H. J., Noh, J. W., Tong, A., Jesudason, S., Craig, J. C., Winkelmayer, W. C., Hung, P. H., Huang, Y. T., Hsiao, C. Y., Sung, P. S., Guo, H. R., Tsai, K. J., Wu, C., Su, S., Kao, S., Lu, K., Lin, Y., Lin, W., Lee, H., Cheng, M., Wang, W., Yang, L., Wang, M., Lela, I. V., Sekoranja, M., Poljicanin, T., Karanovic, S., Abramovic, M., Matijevic, V., Stipancic, Z., Leko, N., Cvitkovic, A., Dika, Z., Kos, J., Laganovic, M., Grollman, A. P., Jelakovic, B., Dryl Rydzynska, T., Prystacki, T., Malyszko, J., Trifiro', Gianluca, Sultana, J., Giorgianni, F., Ingrasciotta, Y., Muscianisi, M., Tari, D. U., Perrotta, M., Buemi, Michele, Canale, V., Arcoraci, Vincenzo, Santoro, Domenico, Rizzo, M., Iheanacho, I., Van, F. E., Goldsmith, D., Grandtnerova, B., Beratsova, Z., Cervenˇova, M., Cˇervenˇ, J., Markech, M., Stefanikova, A., Engelen, W., Elseviers, M., Gheuens, E., Colson, C., Muyshondt, I., and Daelemans, R.

Subjects
Transplantation, medicine.medical_specialty, business.industry, urologic and male genital diseases, medicine.disease, Gastroenterology, female genital diseases and pregnancy complications, Nephrology, Internal medicine, mental disorders, Medicine, Stage (cooking), Metabolic syndrome, business, Kidney disease
Published
2014
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10. Past Decline Versus Current eGFR and Subsequent Mortality Risk

Author

Naimark DMJ, Grams ME, Matsushita K, Black C, Drion I, Fox CS, Inker LA, Ishani A, Jee SA, Kitamura A, Lea JP, Nally J, Peralta CA, Rothenbacher D, Ryu S, Tonelli M, Yatsuya H, Coresh J, Gansevoort RT, Warnock DG, Woodward M, de Jong PE, the CKD Prognosis Consortium, Wright JTJr, Appel LJ, Greene T, MacMahon S, Chalmers J, Arima H, Yamashita K, Toyoshima H, Tamakoshi K, Hemmelgarn B, James M, Sang Y, Atkins RC, Polkinghorne KR, Chadban S, Shankar A, Klein R, Klein BEK, Lee KE, Levin A, Djurdjev O, Sacks FM, Curhan GC, Zawada AM, Rogacev KS, Seiler S, Heine GH, Navaneethan SD, Schold JD, Shlipak M, Sarnak MJ, Katz R, Imano H, Yamagishi K, Wheeler DC, Emberson J, Townend JN, Landray MJ, Brenner H, Müller H, Schöttker B, Hwang S-J, Meigs JB, Uphadhay A, Green J, Kirchner HL, Perkins R, Chang AR, Fluck N, Prescott GJ, Cirillo M, Hallan S, Aasarød K, Øien CM, Radtke M, Irie F, Iso H, Sairenchi T, Smith DH, Thorp ML, Johnson ES, Lee BJ, Guallar E, Chang SY, Cho J, Shin H, Chodick G, Shalev V, Birnbaum YC, Shainberg B, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Levey AS, Neaton JD, Froissart M, Stengel B, Metzger M, Haymann J-P, Houillier P, Flamant M, Elley CR, Kenealy T, Moyes SA, Collins JF, Drury PL, Ohkubo T, Metoki H, Nakayama M, Imai Y, Iseki K, Nelson RG, Knowler WC, Bakker SJL, LHillege H, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Heerspink HJL, Brenner BE, de Zeeuw D, Kimm H, Mok Y, Tangri N, Wen C-P, Wen S-F, Tsao C-K, Tsai M-K, Ärnlöv J, Lannfelt L, Larsson A, Kovesdy CP, Kalantar-Zadeh K, Bilo HJ, Kleefstra N, Groenier KH, Joosten H, Ballew SH, Naimark, Dmj, Grams, Me, Matsushita, K, Black, C, Drion, I, Fox, C, Inker, La, Ishani, A, Jee, Sa, Kitamura, A, Lea, Jp, Nally, J, Peralta, Ca, Rothenbacher, D, Ryu, S, Tonelli, M, Yatsuya, H, Coresh, J, Gansevoort, Rt, Warnock, Dg, Woodward, M, de Jong, Pe, the CKD Prognosis, Consortium, Wright, Jtjr, Appel, Lj, Greene, T, Macmahon, S, Chalmers, J, Arima, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Hemmelgarn, B, James, M, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Zawada, Am, Rogacev, K, Seiler, S, Heine, Gh, Navaneethan, Sd, Schold, Jd, Shlipak, M, Sarnak, Mj, Katz, R, Imano, H, Yamagishi, K, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Müller, H, Schöttker, B, Hwang, S-J, Meigs, Jb, Uphadhay, A, Green, J, Kirchner, Hl, Perkins, R, Chang, Ar, Fluck, N, Prescott, Gj, Cirillo, M, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Iso, H, Sairenchi, T, Smith, Dh, Thorp, Ml, Johnson, E, Lee, Bj, Guallar, E, Chang, Sy, Cho, J, Shin, H, Chodick, G, Shalev, V, Birnbaum, Yc, Shainberg, B, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Levey, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, Pl, Ohkubo, T, Metoki, H, Nakayama, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Lhillege, H, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Heerspink, Hjl, Brenner, Be, de Zeeuw, D, Kimm, H, Mok, Y, Tangri, N, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Ärnlöv, J, Lannfelt, L, Larsson, A, Kovesdy, Cp, Kalantar-Zadeh, K, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Ballew, Sh, Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
Gerontology, Male, CHRONIC KIDNEY-DISEASE, medicine.medical_specialty, Time Factors, 030232 urology & nephrology, Renal function, 030204 cardiovascular system & hematology, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Cause of Death, Epidemiology, Risk of mortality, medicine, EQUATION, Humans, Clinical Epidemiology, Renal Insufficiency, Chronic, Aged, Proportional Hazards Models, business.industry, Hazard ratio, STAGE RENAL-DISEASE, DEATH, General Medicine, Middle Aged, POPULATION COHORTS, Confidence interval, Increased risk, Nephrology, CARDIOVASCULAR-DISEASE, COLLABORATIVE METAANALYSIS, Female, business, HIGHER ALBUMINURIA, All cause mortality, Glomerular Filtration Rate
Abstract

A single determination of eGFR associates with subsequent mortality risk. Prior decline in eGFR indicates loss of kidney function, but the relationship to mortality risk is uncertain. We conducted an individual-level meta-analysis of the risk of mortality associated with antecedent eGFR slope, adjusting for established risk factors, including last eGFR, among 1.2 million subjects from 12 CKD and 22 other cohorts within the CKD Prognosis Consortium. Over a 3-year antecedent period, 12% of participants in the CKD cohorts and 11% in the other cohorts had an eGFR slope-5 ml/min per 1.73 m(2) per year, whereas 7% and 4% had a slope5 ml/min per 1.73 m(2) per year, respectively. Compared with a slope of 0 ml/min per 1.73 m(2) per year, a slope of -6 ml/min per 1.73 m(2) per year associated with adjusted hazard ratios for all-cause mortality of 1.25 (95% confidence interval [95% CI], 1.09 to 1.44) among CKD cohorts and 1.15 (95% CI, 1.01 to 1.31) among other cohorts during a follow-up of 3.2 years. A slope of +6 ml/min per 1.73 m(2) per year also associated with higher all-cause mortality risk, with adjusted hazard ratios of 1.58 (95% CI, 1.29 to 1.95) among CKD cohorts and 1.43 (95% CI, 1.11 to 1.84) among other cohorts. Results were similar for cardiovascular and noncardiovascular causes of death and stronger for longer antecedent periods (3 versus3 years). We conclude that prior decline or rise in eGFR associates with an increased risk of mortality, independent of current eGFR.

Published
2016

11. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts

Author

Astor, BC, Matsushita, K, Gansevoort, RT, van der Velde, M, Woodward, M, Levey, AS, Jong, PE, Coresh, J, de Jong, PE, El-Nahas, M, Eckardt, KU, Kasiske, BL, Wright, J, Appel, L, Greene, T, Levin, A, Djurdjev, O, Wheeler, DC, Landray, MJ, Townend, JN, Emberson, J, Clark, LE, Macleod, A, Marks, A, Ali, T, Fluck, N, Prescott, G, Smith, DH, Weinstein, JR, Johnson, ES, Thorp, ML, Wetzels, JF, Blankestijn, PJ, van Zuilen, AD, Menon, V, Sarnak, M, Beck, G, Kronenberg, F, Kollerits, B, Froissart, M, Stengel, B, Metzger, M, Remuzzi, G, Ruggenenti, P, Perna, A, Heerspink, HJ, Brenner, B, de Zeeuw, D, Rossing, P, Parving, HH, Auguste, P, Veldhuis, K, Wang, Y, Camarata, L, Thomas, B, Manley, T, Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
Male, PROGRESSION, Kidney, urologic and male genital diseases, Cohort Studies, Risk Factors, Renal disorder [IGMD 9], education.field_of_study, OUTCOMES, CARDIOVASCULAR RISK, Hazard ratio, Confounding, Middle Aged, Prognosis, female genital diseases and pregnancy complications, Nephrology, Disease Progression, Regression Analysis, Female, Kidney Diseases, epidemiology, TRIAL, medicine.symptom, epidemiology and outcomes, Glomerular Filtration Rate, Adult, medicine.medical_specialty, Population, Renal function, Risk Assessment, Article, albuminuria, End stage renal disease, Predictive Value of Tests, Internal medicine, medicine, CKD, Humans, education, Aged, Proportional Hazards Models, Chi-Square Distribution, Proportional hazards model, business.industry, urogenital system, A300, medicine.disease, Creatine, Endocrinology, Albuminuria, Kidney Failure, Chronic, business, Biomarkers, chronic kidney disease, Kidney disease
Abstract

We studied here the independent associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality and end-stage renal disease (ESRD) in individuals with chronic kidney disease (CKD). We performed a collaborative meta-analysis of 13 studies totaling 21,688 patients selected for CKD of diverse etiology. After adjustment for potential confounders and albuminuria, we found that a 15 ml/min per 1.73 m(2) lower eGFR below a threshold of 45 ml/min per 1.73 m(2) was significantly associated with mortality and ESRD (pooled hazard ratios (HRs) of 1.47 and 6.24, respectively). There was significant heterogeneity between studies for both HR estimates. After adjustment for risk factors and eGFR, an eightfold higher albumin-or protein-to-creatinine ratio was significantly associated with mortality (pooled HR 1.40) without evidence of significant heterogeneity and with ESRD (pooled HR 3.04), with significant heterogeneity between HR estimates. Lower eGFR and more severe albuminuria independently predict mortality and ESRD among individuals selected for CKD, with the associations stronger for ESRD than for mortality. Thus, these relationships are consistent with CKD stage classifications based on eGFR and suggest that albuminuria provides additional prognostic information among individuals with CKD. Kidney International (2011) 79, 1331-1340; doi:10.1038/ki.2010.550; published online 2 February 2011

Published
2011
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12. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis

Author

Mahmoodi, Bk, Matsushita, K., Woodward, M., Blankestijn, Pj, Cirillo, Massimo, Ohkubo, T., Rossing, P., Sarnak, Mj, Stengel, B., Yamagishi, K., Yamashita, K., Zhang, L., Coresh, J., PE de Jong, Wright, BC Astor for the Chronic Kidney Disease Prognosis C. o. n. s. o. r. t. i. u. m. Investigators/Collaborators: J., Appel, L., Greene, T., Astor, Bc, Chalmers, J., Macmahon, S., Arima, H., Yatsuya, H., Toyoshima, H., Tamakoshi, K., Sang, Y., Atkins, R. C., Polkinghorne, Kr, Chadban, S., Shankar, A., Klein, R., Bek, Klein, Lee, Ke, Wang, H., Wang, F., Zuo, L., Levin, A., Djurdjev, O., Tonelli, M., Sacks, Fm, Curhan, Gc, Shlipak, M., Peralta, C., Katz, R., Fried, L., Iso, H., Kitamura, A., Ohira, T., Jafar, Th, Islam, M., Hatcher, J., Poulter, N., Chaturvedi, N., Landray, M. J., Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D., Brenner, H., Muller, H., Schottker, B., Fox, Cs, Hwang, S. J., Meigs, Jb, Perkins, Rm, Fluck, N., Clark, Le, Prescott, Gj, Marks, A., Black, C., Hallan, S., Aasarod, K., Oien, Cm, Radtke, M., Irie, F., Sairenchi, T., Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S., Chen, S. C., Lee, Bj, Wetzels, Jf, AD van Zuilen, Sarnak, M., Levey, As, Menon, V., Kramer, Hj, IH de Boer, Kronenberg, F., Kollerits, B., Roderick, E. R. i. t. z. P., Nitsch, D., Fletcher, A., Bulpitt, C., Ishani, A., Neaton, Jd, Froissart, M., Metzger, M., Haymann, J. P., Houillier, P., Flamant, M., Metoki, H., Nakayama, M., Kikuya, M., Imai, Y., Iseki, K., Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H., Jassal, Sk, Barrett Connor, E., Bergstrom, J., HJ Lambers Heerspink, Brenner, Be, de Zeeuw, D., Warnock, Dg, Muntner, P., Judd, S., Mcclellan, W., Jee, Sh, Kimm, H., Jo, J., Mok, Y., Parving, H. H., Tangri, N., Naimark, D., Wen, C. P., Wen, S. F., Tsao, C. K., Tsai, M. K., Arnlov, J., Lannfelt, L., Larsson, A., Bilo, Hj, Joosten, H., Kleefstra, N., Groenier, Kh, Steering Committee: BC Astor, I. D. r. i. o. n., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M. W. o. o. d. w. a. r. d., Grams, M., Camarata, L., Hui, X., Seltzer, J., Winegrad, H., Mahmoodi, Bk, Matsushita, K, Woodward, M, Blankestijn, Pj, Cirillo, M, Ohkubo, T, Rossing, P, Sarnak, Mj, Stengel, B, Yamagishi, K, Yamashita, K, Zhang, L, Coresh, J, de Jong, Pe, Investigators/Collaborators: J Wright, BC Astor for the Chronic Kidney Disease Prognosis Consortium., Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Sang, Y, C Atkins, R, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Wang, H, Wang, F, Zuo, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, J Landray, M, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Muller, H, Schottker, B, Fox, C, Hwang, S-J, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Hallan, S, Aasarod, K, Oien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, S-C, Lee, Bj, Wetzels, Jf, van Zuilen, Ad, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer, Ih, Kronenberg, F, Kollerits, B, P Roderick, E Ritz., Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink, Hj, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Parving, H-H, Tangri, N, Naimark, D, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Arnlov, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Steering Committee: BC Astor, I Drion., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M Woodward., Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad., H

Subjects
Male, medicine.medical_specialty, hypertension, Blood Pressure, BLOOD-PRESSURE, GLOMERULAR-FILTRATION-RATE, Article, albuminuria, DIABETIC-NEPHROPATHY, End stage renal disease, CKD-PC Consortium, Risk Factors, Cause of Death, Internal medicine, REVERSE EPIDEMIOLOGY, eGFR, EQUATION, medicine, Humans, Intensive care medicine, Aged, Proportional Hazards Models, ALL-CAUSE MORTALITY, Renal disorder [IGMD 9], Aged, 80 and over, end-stage renal disease, business.industry, General Medicine, Middle Aged, medicine.disease, mortality, RISK POPULATION COHORTS, PREVALENCE, Chronic Disease, COLLABORATIVE METAANALYSIS, Kidney Failure, Chronic, Female, HIGHER ALBUMINURIA, business, Glomerular Filtration Rate, Kidney disease
Abstract

Item does not contain fulltext BACKGROUND: Hypertension is the most prevalent comorbidity in individuals with chronic kidney disease. However, whether the association of the kidney disease measures, estimated glomerular filtration rate (eGFR) and albuminuria, with mortality or end-stage renal disease (ESRD) differs by hypertensive status is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and ESRD associated with eGFR and albuminuria in individuals with and without hypertension. FINDINGS: We analysed data for 45 cohorts (25 general population, seven high-risk, and 13 chronic kidney disease) with 1,127,656 participants, 364,344 of whom had hypertension. Low eGFR and high albuminuria were associated with mortality irrespective of hypertensive status in the general population and high-risk cohorts. All-cause mortality risk was 1.1-1.2 times higher in individuals with hypertension than in those without hypertension at preserved eGFR. A steeper relative risk gradient in individuals without hypertension than in those with hypertension at eGFR range 45-75 mL/min per 1.73 m(2) led to much the same mortality risk at lower eGFR. With a reference eGFR of 95 mL/min per 1.73 m(2) in each group to explicitly assess interaction, adjusted HR for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) was 1.77 (95% CI 1.57-1.99) in individuals without hypertension versus 1.24 (1.11-1.39) in those with hypertension (p for overall interaction=0.0003). Similarly, for albumin-creatinine ratio of 300 mg/g (vs 5 mg/g), HR was 2.30 (1.98-2.68) in individuals without hypertension versus 2.08 (1.84-2.35) in those with hypertension (p for overall interaction=0.019). We recorded much the same results for cardiovascular mortality. The associations of eGFR and albuminuria with ESRD, however, did not differ by hypertensive status. Results for chronic kidney disease cohorts were similar to those for general and high-risk population cohorts. INTERPRETATION: Chronic kidney disease should be regarded as at least an equally relevant risk factor for mortality and ESRD in individuals without hypertension as it is in those with hypertension. FUNDING: US National Kidney Foundation.

Published
2012

15. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts

Author

Astor, B.C., Matsushita, K., Gansevoort, R.T., Velde, M. van de, Woodward, M., Levey, A.S., Jong, P.E. de, Coresh, J., El-Nahas, M., Eckardt, K.U., Kasiske, B.L., Wright, J., Appel, L., Greene, T., Levin, A., Djurdjev, O., Wheeler, D.C., Landray, M.J., Townend, J.N., Emberson, J., Clark, L.E., Macleod, A., Marks, A., Ali, T., Fluck, N., Prescott, G., Smith, D.H., Weinstein, J.R., Johnson, E.S., Thorp, M.L., Wetzels, J.F.M., Blankestijn, P.J., Zuilen, A.D. van, Menon, V., Sarnak, M., Beck, G., Kronenberg, F., Kollerits, B., Froissart, M., Stengel, B., Metzger, M., Remuzzi, G., Ruggenenti, P., Perna, A., Heerspink, H.J., Brenner, B., Zeeuw, D. de, Rossing, P., Parving, H.H., Auguste, P., Veldhuis, K., Wang, Y., Camarata, L., Thomas, B., Manley, T., Astor, B.C., Matsushita, K., Gansevoort, R.T., Velde, M. van de, Woodward, M., Levey, A.S., Jong, P.E. de, Coresh, J., El-Nahas, M., Eckardt, K.U., Kasiske, B.L., Wright, J., Appel, L., Greene, T., Levin, A., Djurdjev, O., Wheeler, D.C., Landray, M.J., Townend, J.N., Emberson, J., Clark, L.E., Macleod, A., Marks, A., Ali, T., Fluck, N., Prescott, G., Smith, D.H., Weinstein, J.R., Johnson, E.S., Thorp, M.L., Wetzels, J.F.M., Blankestijn, P.J., Zuilen, A.D. van, Menon, V., Sarnak, M., Beck, G., Kronenberg, F., Kollerits, B., Froissart, M., Stengel, B., Metzger, M., Remuzzi, G., Ruggenenti, P., Perna, A., Heerspink, H.J., Brenner, B., Zeeuw, D. de, Rossing, P., Parving, H.H., Auguste, P., Veldhuis, K., Wang, Y., Camarata, L., Thomas, B., and Manley, T.

Abstract

Item does not contain fulltext, We studied here the independent associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality and end-stage renal disease (ESRD) in individuals with chronic kidney disease (CKD). We performed a collaborative meta-analysis of 13 studies totaling 21,688 patients selected for CKD of diverse etiology. After adjustment for potential confounders and albuminuria, we found that a 15 ml/min per 1.73 m(2) lower eGFR below a threshold of 45 ml/min per 1.73 m(2) was significantly associated with mortality and ESRD (pooled hazard ratios (HRs) of 1.47 and 6.24, respectively). There was significant heterogeneity between studies for both HR estimates. After adjustment for risk factors and eGFR, an eightfold higher albumin- or protein-to-creatinine ratio was significantly associated with mortality (pooled HR 1.40) without evidence of significant heterogeneity and with ESRD (pooled HR 3.04), with significant heterogeneity between HR estimates. Lower eGFR and more severe albuminuria independently predict mortality and ESRD among individuals selected for CKD, with the associations stronger for ESRD than for mortality. Thus, these relationships are consistent with CKD stage classifications based on eGFR and suggest that albuminuria provides additional prognostic information among individuals with CKD.

Published
2011

16. Chronic diseases: studying and understanding outcome using routine data: chronic kidney disease (CKD), an example

Author

Marks, A., Fluck, N., Prescott, Gordon, MacLeod, A., Smith, W. C. S., Black, C., Marks, A., Fluck, N., Prescott, Gordon, MacLeod, A., Smith, W. C. S., and Black, C.

Abstract

Internationally, chronic disease represents a major healthcare challenge for the 21st century. Prognostic tools that streamline and target care have been developed for cardiovascular disease. This study illustrates how routine data can be used to develop tools for other chronic diseases; using chronic kidney disease (a precursor of renal replacement therapy (RRT: dialysis or transplantation) requirement) as a model. Routine clinical data—serum creatinine (a measure of kidney function), RRT initiation and death registration were used to identify a CKD cohort, and follow them over 6 years. Mortality was compared to the general population. 3426 persons were identified with CKD (median age 79 years, 56% female). RRT initiation rates decreased with age from 14.3 to 0.7 per 100 person-years among those aged 15–25 and 75–85 years at baseline respectively (absolute numbers 6 and 34). Mortality rates increased with age from 1.9 to 33.8 per 100 person-years for those aged 15–45 and over 85 years at baseline—a 19 and 2 fold increase in mortality risk compared to the general population respectively (2 and 17 excess deaths per 100 person-years). CKD has been labelled a public health concern, and provides a typical pattern for chronic disease. Personal risk is low for the majority, but they represent a high societal cost; whereas those with high personal risk are few, with lower societal cost. Exploitation of routinely collected data are an efficient way of following up health outcome, and informing the development of prognostic tools for a chronic disease cohort.

Published
2011

17. Early referral strategies for management of people with markers of renal disease: a systematic review of the evidence of clinical effectiveness, costeffectiveness and economic analysis

Author

Black, C, Sharma, P, Scotland, G, McCullough, K, McGurn, D, Robertson, L, Fluck, N, MacLeod, A, McNamee, P, Prescott, Gordon, Smith, C, Black, C, Sharma, P, Scotland, G, McCullough, K, McGurn, D, Robertson, L, Fluck, N, MacLeod, A, McNamee, P, Prescott, Gordon, and Smith, C

Abstract

Background Chronic kidney disease (CKD) is a long-term condition and has been described as the gradual loss of kidney function over time. Early in the disease process, people with CKD often experience no symptoms. For a long time, CKD has been an underdiagnosed condition. Even in the absence of symptoms, CKD appears to add significantly to the burden of cardiovascular disease and death and, for an important minority, can progress to kidney failure. Objective To systematically review the evidence of the clinical effectiveness and cost-effectiveness of early referral strategies for management of people with markers of renal disease. Data sources Electronic searches of 12 major databases (such as MEDLINE, EMBASE, CINAHL, etc.) were conducted for the time period of 1990 to April 2008 to identify studies comparing early referral to other care options for people with CKD. Additional searching was performed in the NHS Economic Evaluation Database to support the cost-effectiveness literature review. Review methods Two authors reviewed all titles, abstracts and full papers to select relevant literature. A Markov model was constructed to represent the natural history of CKD. The model allowed cohorts to be tracked according to estimated glomerular filtration rate (eGFR) status and the presence of other complications known to influence CKD progression and the incidence of cardiovascular events. Results From 36 relevant natural history studies, CKD was found to be, despite marked heterogeneity between studies, a marker of increased risk of mortality, renal progression and end-stage renal disease. Mortality was generally high and increased with stage of CKD. After adjustment for comorbidities, the relative risk of mortality among those with CKD identified from the general population increased with stage. For clinical populations, the relative risk was higher. All three outcomes increased as eGFR fell. Only seven studies, and no randomised controlled trials, were identified as re

Published
2010

18. Identifying Individuals with CKD

Author

Clark, L, Prescott, Gordon, Fluck, N, Smith, C, Simpson, W, MacLeod, A, Clark, L, Prescott, Gordon, Fluck, N, Smith, C, Simpson, W, and MacLeod, A

Published
2007

25. Early referral strategies for management of people with markers of renal disease: a systematic review of the evidence of clinical effectiveness, cost-effectiveness and economic analysis

Author

Black, C, primary, Sharma, P, additional, Scotland, G, additional, McCullough, K, additional, McGurn, D, additional, Robertson, L, additional, Fluck, N, additional, MacLeod, A, additional, McNamee, P, additional, Prescott, G, additional, and Smith, C, additional

Published
2010
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29. Poster Abstracts

Author

Clark, L. E., primary, Prescott, G., additional, Fluck, N., additional, Simpson, W., additional, Smith, W. Cairns. S., additional, Macleod, A. M., additional, Ali, T. Z., additional, MacLeod, A. M., additional, Townend, J., additional, Smith, W. C., additional, Khan, I. H., additional, Minter, J., additional, Halliday, K., additional, Gawthorp, J., additional, Mackenzie, P., additional, Carmichael, D., additional, Houston, K., additional, Houston, B., additional, Preiss, D., additional, Godber, I., additional, Lamb, E., additional, Dalton, N., additional, Gunn, I., additional, Porter, L. F., additional, MacWalter, R. S., additional, Quinn, M., additional, Rainey, A., additional, Cairns, K. J., additional, Marshall, A. H., additional, Kee, F., additional, Savage, G., additional, Fogarty, D. G., additional, Conway, B., additional, Ramsay, G., additional, Webster, A., additional, Neary, J., additional, Whitworth, C., additional, Harty, J., additional, Saweirs, W. W. M., additional, Gibson, P. H., additional, Giles, P., additional, Hartland, A., additional, Rylance, P., additional, Nicholas, J., additional, Ashby, H., additional, Askey, A., additional, Crothers, D., additional, Patel, B., additional, Main, J., additional, Roy, D., additional, Dasgupta, I., additional, Rayner, H., additional, Richards, N. T., additional, Eames, M., additional, Lewis, R., additional, Mansell, M., additional, Thomas, S., additional, O'Donoghue, D., additional, and Harris, K., additional

Published
2007
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31. Maria Jozefa Hari Richard Garrett George Barry Roy Gibb Blues William Armstrong Davidson David Charles Fluck William Stanley Hill Fausto Iannotti Alan Oakley John William Gray McEwen John Marcus Stowers

Author

Sutton, A., primary, O'Donohoe, N V, additional, Davidson, A. J L, additional, Davidson, P. N, additional, Fluck, N., additional, Crockard, A., additional, Boll, M., additional, Law, P., additional, Hunter, J D., additional, and Stowers, C. D, additional

Published
2001
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34. The induction of transplantation tolerance by intrathymic (i.t.) delivery of alloantigen: a critical relationship between i.t. deletion, thymic export of new T cells and the timing of transplantation

Author

Mellor, A., Wood, K., Jones, N., Fluck, N., and Morris, P.

Abstract

Intrathymic (i.t.) injection of donor alloantigens has proved to be an effective strategy for the induction of tolerance. However, the mechanisms by which tolerance is induced and maintained after transplantation remain unclear. In this report we show that tolerance to donor cardiac allografts can be induced across a MHC class I difference by i.t. injection of donor splenocytes and transient T cell depletion. Furthermore, using H-2Kb-specific TCR transgenic mice (BM3), we demonstrate that prolonged deletion of donor-reactive thymocytes was essential to induce tolerance by i.t. injection and this was dependent upon donor cells persisting in the thymus. Examination of the kinetics of thymic export following i.t. injection revealed that prolonged deletion of thymocytes was required to delay export of new T cells to the periphery until the time of transplantation. Importantly, after transplantation donor cell persistence in the thymus and i.t. deletion were no longer necessary to maintain tolerance. The graft itself or cells from the graft was responsible for maintaining tolerance at this stage. These findings reveal that multiple mechanisms are responsible for the induction and maintenance phases of tolerance to alloantigens in vivo after i.t. delivery, and that a complex inter-relationship between donor cell persistence in the thymus, i.t. deletion, thymic export of T cells and the timing of transplantation is involved.
Keywords:cardiac allograft, TCR transgenic mice

Published
1998

35. The induction of transplantation tolerance by intrathymic (i.t.) delivery of alloantigen: a critical relationship between i.t. deletion, thymic export of new T cells and the timing of transplantation.

Author

Jones, N D, Fluck, N C, Mellor, A L, Morris, P J, and Wood, K J

Abstract

Intrathymic (i.t.) injection of donor alloantigens has proved to be an effective strategy for the induction of tolerance. However, the mechanisms by which tolerance is induced and maintained after transplantation remain unclear. In this report we show that tolerance to donor cardiac allografts can be induced across a MHC class I difference by i.t. injection of donor splenocytes and transient T cell depletion. Furthermore, using H-2K(b)-specific TCR transgenic mice (BM3), we demonstrate that prolonged deletion of donor-reactive thymocytes was essential to induce tolerance by i.t. injection and this was dependent upon donor cells persisting in the thymus. Examination of the kinetics of thymic export following i.t. injection revealed that prolonged deletion of thymocytes was required to delay export of new T cells to the periphery until the time of transplantation. Importantly, after transplantation donor cell persistence in the thymus and i.t. deletion were no longer necessary to maintain tolerance. The graft itself or cells from the graft was responsible for maintaining tolerance at this stage. These findings reveal that multiple mechanisms are responsible for the induction and maintenance phases of tolerance to alloantigens in vivo after i.t. delivery, and that a complex inter-relationship between donor cell persistence in the thymus, i.t. deletion, thymic export of T cells and the timing of transplantation is involved.

Published
1998
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36. Identifying key health system components associated with improved outcomes to inform the re-configuration of services for adults with rare autoimmune rheumatic diseases: a mixed-methods study.

Author

Hollick RJ, James WRG, Nicoll A, Locock L, Black C, Dhaun N, Egan AC, Fluck N, Laidlaw L, Lanyon PC, Little MA, Luqmani RA, Moir L, McBain M, and Basu N

Subjects
Humans, Female, Male, Adult, Middle Aged, Ireland epidemiology, Autoimmune Diseases therapy, United Kingdom epidemiology, Rare Diseases therapy, Aged, Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis therapy, Delivery of Health Care organization & administration, Rheumatic Diseases therapy
Abstract

Background: Adults with rare autoimmune rheumatic diseases face unique challenges and struggles to navigate health-care systems designed to manage common conditions. Evidence to inform an optimal service framework for their care is scarce. Using systemic vasculitis as an exemplar, we aimed to identify and explain the key service components underpinning effective care for rare diseases., Methods: In this mixed-methods study, data were collected as part of a survey of vasculitis service providers across the UK and Ireland, interviews with patients, and from organisational case studies to identify key service components that enable good care. The association between these components and patient outcomes (eg, serious infections, mortality) and provider outcomes (eg, emergency hospital admissions) were examined in a population-based data linkage study using routine health-care data obtained from patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis from national health datasets in Scotland. We did univariable and multivariable analyses using Bayesian poisson and negative binomial regression to estimate incident rate ratios (IRRs), and Cox proportional hazards models to estimate hazard ratios (HRs). People with lived experiences were involved in the research and writing process., Findings: Good care was characterised by service components that supported timely access to services, integrated care, and expertise. In 1420 patients with ANCA-associated vasculitis identified from national health datasets, service-reported average waiting times for new patients of less than 1 week were associated with fewer serious infections (IRR 0·70 [95% credibility interval 0·55-0·88]) and fewer emergency hospital admissions (0·78 [0·68-0·92]). Nurse-led advice lines were associated with fewer serious infections (0·76 [0·58-0·93]) and fewer emergency hospital admissions (0·85 [0·74-0·96]). Average waiting times for new patients of less than 1 week were also associated with reduced mortality (HR 0·59 [95% credibility interval 0·37-0·93]). Cohorted clinics, nurse-led clinics, and specialist vasculitis multi-disciplinary team meetings were associated with fewer serious infections (IRR 0·75 [0·59-0·96] for cohorted clinics; 0·65 [0·39-0·84] for nurse-led clinics; 0·72 [0·57-0·90] for specialist vasculitis multi-disciplinary team meetings) and emergency hospital admissions (0·81 [0·71-0·91]; 0·75 [0·65-0·94]; 0·86 [0·75-0·96]). Key components were characterised by their ability to overcome professional tensions between specialties., Interpretation: Key service components associated with important health outcomes and underpinning factors were identified to inform initiatives to improve the design, delivery, and effectiveness of health-care models for rare autoimmune rheumatic diseases., Funding: Versus Arthritis., Competing Interests: Declaration of interest NB has received speaker fees and research funding from VSL Vifor. RJH has received funding for the present study from Versus Arthritis; is clinical lead of the Scottish Systemic Vasculitis Managed Clinical Network; and has received speaker fees from CSL Vifor. PCL is co-chair of the Rare Autoimmune Rheumatic Disease Alliance (RAIRDA), the joint national clinical lead for the Rheumatology, Getting It Right First Time programme, NHS England, and the clinical lead for Rare Diseases, National Disease Registration Service, NHS England; has received speaker fees from CSL Vifor and Pfizer; and expenses for attending conferences and research funding from CSL Vifor. MAL has received speaker fees from CSL Vifor. LL's research time for this study was supported by the Health Services Research Unit, University of Aberdeen, which received core funding from the Chief Scientist's Office (Scotland). All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.)

Published
2024
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37. Care processes and outcomes of deprivation across the clinical course of kidney disease: findings from a high-income country with universal healthcare.

Author

Sawhney S, Blakeman T, Blana D, Boyers D, Fluck N, Nath M, Methven S, Rzewuska M, and Black C

Subjects
Male, Humans, Universal Health Care, Disease Progression, Glomerular Filtration Rate, Risk Factors, Renal Insufficiency, Chronic epidemiology, Renal Insufficiency, Chronic therapy, Renal Insufficiency, Chronic complications, Acute Kidney Injury epidemiology, Acute Kidney Injury etiology, Acute Kidney Injury therapy
Abstract

Background: No single study contrasts the extent and consequences of inequity of kidney care across the clinical course of kidney disease., Methods: This population study of Grampian (UK) followed incident presentations of acute kidney injury (AKI) and incident estimated glomerular filtration rate (eGFR) thresholds of <60, <45 and <30 mL/min/1.73 m2 in separate cohorts (2011-2021). The key exposure was area-level deprivation (lowest quintile of the Scottish Index of Multiple Deprivation). Outcomes were care processes (monitoring, prescribing, appointments, unscheduled care), long-term mortality and kidney failure. Modelling involved multivariable logistic regression, negative binomial regression and cause-specific Cox models with and without adjustment of comorbidities., Results: There were 41 313, 51 190, 32 171 and 17 781 new presentations of AKI and eGFR thresholds <60, <45 and <30  mL/min/1.73 m2. A total of 6.1-7.8% of the population was from deprived areas and (versus all others) presented on average 5 years younger, with more diabetes and pulmonary and liver disease. Those from deprived areas were more likely to present initially in hospital, less likely to receive community monitoring, less likely to attend appointments and more likely to have an unplanned emergency department or hospital admission episode. Deprivation had the greatest association with long-term kidney failure at the eGFR <60 mL/min/1.73 m2 threshold {adjusted hazard ratio [HR] 1.48 [95% confidence interval (CI) 1.17-1.87]} and this association decreased with advancing disease severity [HR 1.09 (95% CI 0.93-1.28) at eGFR <30 mL/min/1.73 m2), with a similar pattern for mortality. Across all analyses the most detrimental associations of deprivation were an eGFR threshold <60 mL/min/1.73 m2, AKI, males and those <65 years of age., Conclusions: Even in a high-income country with universal healthcare, serious and consistent inequities in kidney care exist. The poorer care and outcomes with area-level deprivation were greater earlier in the disease course., (© The Author(s) 2022. Published by Oxford University Press on behalf of the ERA.)

Published
2023
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38. A real-world assessment of mycophenolate mofetil for remission induction in eosinophilic granulomatosis with polyangiitis.

Author

Philobos M, Perkins A, Karabayas M, Dospinescu P, Fluck N, Kidder D, Chapman FA, Dhaun N, and Basu N

Subjects
Adult, Aged, Antibodies, Antineutrophil Cytoplasmic blood, Female, Granulomatosis with Polyangiitis complications, Humans, Male, Middle Aged, Prednisolone, Recurrence, Remission Induction methods, Retrospective Studies, Granulomatosis with Polyangiitis drug therapy, Mycophenolic Acid administration & dosage
Abstract

Eosinophilic granulomatosis with polyangiitis (EGPA) is a form of ANCA-associated vasculitis (AAV). Clinical trials demonstrating the efficacy of mycophenolate mofetil (MMF) for remission induction in AAV excluded patients with EGPA. Despite this, MMF is commonly used in these patients. The objective of this study was to evaluate, for the first time, the effectiveness and tolerance of MMF in EGPA remission induction. A retrospective, two-center, real-world study was conducted in patients with EGPA who received MMF in addition to prednisolone for newly diagnosed or relapsing disease between 2009 and 2019. Baseline, 3-, 6- and 12-month outcome data were extracted from electronic health records. The primary outcome was disease remission, defined as a Birmingham Vasculitis Activity Score of 0 at 6 months. Secondary outcomes included disease relapse, median prednisolone dose at 12 months and drug tolerance. In total, 15 patients (73% male, median age 57) with EGPA (11 newly diagnosed/4 relapsing) were identified. At 6 months, 67% had achieved disease remission. At 12 months, this was maintained (66.7%) and 4 patients had relapsed. All but one patient remained on MMF at study completion and all patients tolerated MMF. Our real-world data suggest that MMF is an effective and well-tolerated agent for achieving disease remission in EGPA. A future randomized controlled trial of MMF in this neglected orphan disease is now warranted., (© 2021. The Author(s).)

Published
2021
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39. Evaluation of adjunctive mycophenolate for large vessel giant cell arteritis.

Author

Karabayas M, Dospinescu P, Fluck N, Kidder D, Fordyce G, Hollick RJ, De Bari C, and Basu N

Abstract

Objectives: GCA patients with large vessel involvement (LV-GCA) experience greater CS requirements and higher relapse rates compared with classical cranial GCA. Despite the distinct disease course, interventions in LV-GCA have yet to be investigated specifically. This study aimed to evaluate the CS-sparing effect and tolerability of first-line mycophenolate in LV-GCA., Methods: A retrospective cohort study was conducted in patients with LV-GCA identified from a regional clinical database between 2005 and 2019. All cases were prescribed mycophenolate derivatives (MYC; MMF or mycophenolic acid) at diagnosis and were followed up for ≥2 years. The primary outcome was the cumulative CS dose at 1 year. Secondary outcomes included MYC tolerance, relapse rates and CRP levels at 1 and 2 years., Results: A total of 37 patients (65% female; mean age 69.4 years, SD 7.9 years) were identified. All cases demonstrated large vessel involvement via CT/PET ( n  = 34), CT angiography ( n  = 5) or magnetic resonance angiography ( n  = 2). After 2 years, 31 patients remained on MYC, whereas 6 had switched to MTX or tocilizumab owing to significant disease relapse. The mean (±SD) cumulative prednisolone dose at 1 year was 4960 (±1621) mg. Relapse rates at 1 and 2 years were 16.2 and 27%, respectively, and CRP levels at 1 and 2 years were 4 [interquartile range (IQR) 4-6] and 4 (IQR 4-4) mg/l, respectively., Conclusion: To our knowledge, this is the first attempt to assess the effectiveness of any specific agent in LV-GCA. MYC might be both effective in reducing CS exposure and well tolerated in this subpopulation. A future randomized controlled trial is warranted., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Published
2020
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42. Late-onset Pneumocystis jirovecii pneumonia (PJP) in patients with ANCA-associated vasculitis.

Author

Matraiah EH, Olisaka N, Philipos M, Walbaum D, Dospinescu P, Fluck N, Basu N, and Kidder D

Subjects
Adaptor Proteins, Signal Transducing, Age of Onset, Aged, Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis drug therapy, Female, Humans, Immunosuppressive Agents therapeutic use, Male, Middle Aged, Opportunistic Infections diagnosis, Opportunistic Infections mortality, Pneumonia, Pneumocystis diagnosis, Pneumonia, Pneumocystis mortality, Retrospective Studies, Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis complications, Opportunistic Infections etiology, Pneumocystis carinii, Pneumonia, Pneumocystis etiology
Abstract

Immunosuppression in anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is complicated by increasing risk of infections including opportunistic infections like Pneumocystis jirovecii pneumonia (PJP). Available evidence on risk factors and indications for prophylaxis in AAV is derived from PJP occurring early in the course of AAV. In this retrospective study, we characterized the profile of PJP in patients with AAV. PJP cases were identified retrospectively based on positive polymerase chain reaction test from electronic record followed by confirmation from medical records over a 10-year period. AAV patients without PJP over the same period were used as control group. Sixteen PJP+AAV+ were identified; in 14 of them, we were able to confirm they received PJP prophylaxis during induction therapy, while in two cases, data were missing. The onset of the infection was after 6 months from AAV diagnosis in 80% of cases. Escalations in immunosuppression prior to PJP were observed in six cases within 3 months prior to PJP onset. Overall mortality was 12.5%. By univariate analysis, renal involvement at AAV diagnosis was associated with PJP. These results indicate that PJP is not limited to the first 6 months following AAV diagnosis. Late-onset infection can occur in context of augmented immunotherapy, particularly with concurrent lymphopenia. Other risk factors that can independently predict late-onset PJP remain to be identified.

Published
2018
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43. Hip fracture incidence and mortality in chronic kidney disease: the GLOMMS-II record linkage cohort study.

Author

Robertson L, Black C, Fluck N, Gordon S, Hollick R, Nguyen H, Prescott G, and Marks A

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Cohort Studies, Female, Hip Fractures mortality, Humans, Incidence, Male, Medical Record Linkage, Middle Aged, Risk Factors, Scotland epidemiology, Young Adult, Hip Fractures epidemiology, Renal Insufficiency, Chronic epidemiology
Abstract

Background: Individuals on renal replacement therapy (RRT) have increased fracture risk, but risk in less advanced chronic kidney disease (CKD) is unclear., Objective: To investigate CKD associations with hip fracture incidence and mortality., Design: Record linkage cohort study Grampian Laboratory Outcomes Mortality and Morbidity Study II., Setting: Single health region in Scotland., Participants: All individuals (≥15 years) with sustained CKD stages 3-5 and those on RRT, and a 20% random sample of those with normal renal function, in the resident population in 2003., Outcome Measures: Outcomes were (1) incident hip fracture measured with (A) admissions or (B) deaths, with at least 5.5 years follow-up and (2) post-hip fracture mortality. Unadjusted and adjusted, incident rate ratios (IRRs) and mortality rate ratios were calculated using Poisson regression., Results: Of 39 630 individuals identified in 2003 (41% males, mean age 63.3 years), 19 537 had CKD stages 3-5, 345 were on RRT and 19 748 had normal estimated glomerular filtration rate (eGFR). Hip fracture incidence, measured by admissions, was increased in CKD stages 3-5 (compared with normal eGFR), both overall (adjusted IRR 1.49 (95% CI 1.24 to 1.79)) and for individual CKD stages 3a, 3b and 4. Hip fracture incidence, measured using deaths, was increased in those with CKD stages 3b and 4. Post-hip fracture mortality was only increased in CKD stage 4. There was only a small number of individuals and events for CKD stage 5, resulting in insufficient statistical power., Conclusion: Hip fracture incidence was higher in CKD stages 3-5 compared with normal eGFR. Post-hip fracture mortality was only increased in CKD stage 4. Reducing hip fracture incidence in CKD through regular fall and fracture risk review should reduce overall deaths after hip fracture in the population., Competing Interests: Competing interests: LR was supported by NHS Grampian Endowment (grant no: 14/30)., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Published
2018
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44. Post-discharge kidney function is associated with subsequent ten-year renal progression risk among survivors of acute kidney injury.

Author

Sawhney S, Marks A, Fluck N, Levin A, McLernon D, Prescott G, and Black C

Subjects
Acute Kidney Injury complications, Acute Kidney Injury epidemiology, Aged, Aged, 80 and over, Disease Progression, Female, Follow-Up Studies, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic epidemiology, Male, Middle Aged, United Kingdom epidemiology, Acute Kidney Injury physiopathology, Kidney physiopathology, Kidney Failure, Chronic etiology
Abstract

The extent to which renal progression after acute kidney injury (AKI) arises from an initial step drop in kidney function (incomplete recovery), or from a long-term trajectory of subsequent decline, is unclear. This makes it challenging to plan or time post-discharge follow-up. This study of 14651 hospital survivors in 2003 (1966 with AKI, 12685 no AKI) separates incomplete recovery from subsequent renal decline by using the post-discharge estimated glomerular filtration rate (eGFR) rather than the pre-admission as a new reference point for determining subsequent renal outcomes. Outcomes were sustained 30% renal decline and de novo CKD stage 4, followed from 2003-2013. Death was a competing risk. Overall, death was more common than subsequent renal decline (37.5% vs 11.3%) and CKD stage 4 (4.5%). Overall, 25.7% of AKI patients had non-recovery. Subsequent renal decline was greater after AKI (vs no AKI) (14.8% vs 10.8%). Renal decline after AKI (vs no AKI) was greatest among those with higher post-discharge eGFRs with multivariable hazard ratios of 2.29 (1.88-2.78); 1.50 (1.13-2.00); 0.94 (0.68-1.32) and 0.95 (0.64-1.41) at eGFRs of 60 or more; 45-59; 30-44 and under 30, respectively. The excess risk after AKI persisted over ten years of study, irrespective of AKI severity, or post-episode proteinuria. Thus, even if post-discharge kidney function returns to normal, hospital admission with AKI is associated with increased renal progression that persists for up to ten years. Follow-up plans should avoid false reassurance when eGFR after AKI returns to normal., (Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Published
2017
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45. Acute kidney injury as an independent risk factor for unplanned 90-day hospital readmissions.

Author

Sawhney S, Marks A, Fluck N, McLernon DJ, Prescott GJ, and Black C

Subjects
Acute Disease, Aged, Aged, 80 and over, Cohort Studies, Decision Support Techniques, Female, Glomerular Filtration Rate, Hospitalization, Humans, Information Storage and Retrieval, Kaplan-Meier Estimate, Logistic Models, Male, Middle Aged, Mortality, Multivariate Analysis, Odds Ratio, Prognosis, Pulmonary Edema epidemiology, Risk Assessment, Risk Factors, Scotland epidemiology, Acute Kidney Injury epidemiology, Patient Readmission statistics & numerical data
Abstract

Background: Reducing readmissions is an international priority in healthcare. Acute kidney injury (AKI) is common, serious and also a global concern. This analysis evaluates AKI as a candidate risk factor for unplanned readmissions and determines the reasons for readmissions., Methods: GLOMMS-II is a large population cohort from one health authority in Scotland, combining hospital episode data and complete serial biochemistry results through data-linkage. 16453 people (2623 with AKI and 13830 without AKI) from GLOMMS-II who survived an index hospital admission in 2003 were used to identify the causes of and predict readmissions. The main outcome was "unplanned readmission or death" within 90 days of discharge. In a secondary analysis, the outcome was limited to readmissions with acute pulmonary oedema. 26 candidate predictors during the index admission included AKI (defined and staged 1-3 using an automated e-alert algorithm), prior AKI episodes, baseline kidney function, index admission circumstances and comorbidities. Prediction models were developed and assessed using multivariable logistic regression (stepwise variable selection), C statistics, bootstrap validation and decision curve analysis., Results: Three thousand sixty-five (18.6%) patients had the main outcome (2702 readmitted, 363 died without readmission). The outcome was strongly predicted by AKI. Multivariable odds ratios for AKI stage 3; 2 and 1 (vs no AKI) were 2.80 (2.22-3.53); 2.23 (1.85-2.68) and 1.50 (1.33-1.70). Acute pulmonary oedema was the reason for readmission in 26.6% with AKI and eGFR < 60; and 4.0% with no AKI and eGFR ≥ 60. The best stepwise model from all candidate predictors had a C statistic of 0.698 for the main outcome. In a secondary analysis, a model for readmission with acute pulmonary oedema had a C statistic of 0.853. In decision curve analysis, AKI improved clinical utility when added to any model, although the incremental benefit was small when predicting the main outcome., Conclusions: AKI is a strong, consistent and independent risk factor for unplanned readmissions - particularly readmissions with acute pulmonary oedema. Pre-emptive planning at discharge should be considered to minimise avoidable readmissions in this high risk group.

Published
2017
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46. Intermediate and Long-term Outcomes of Survivors of Acute Kidney Injury Episodes: A Large Population-Based Cohort Study.

Author

Sawhney S, Marks A, Fluck N, Levin A, Prescott G, and Black C

Subjects
Aged, Aged, 80 and over, Cohort Studies, Female, Humans, Male, Middle Aged, Prognosis, Survival Rate, Survivors, Time Factors, Treatment Outcome, Acute Kidney Injury mortality, Acute Kidney Injury therapy
Abstract

Background: The long-term prognosis after acute kidney injury (AKI) is variable. It is unclear how the prognosis of AKI and its relationship to prognostic factors (baseline kidney function, AKI severity, prior AKI episodes, and recovery of kidney function) change as follow-up progresses., Study Design: Observational cohort study., Setting & Participants: The Grampian Laboratory Outcomes Morbidity and Mortality Study II (GLOMMS-II) is a large regional population cohort with complete serial biochemistry and outcome data capture through data linkage. From GLOMMS-II, we followed up 17,630 patients hospitalized in 2003 through to 2013., Predictors: AKI identified using KDIGO (Kidney Disease: Improving Global Outcomes) serum creatinine criteria, characterized by baseline kidney function (estimated glomerular filtration rate [eGFR] ≥ 60, 45-59, 30-44, and <30mL/min/1.73m 2 ), AKI severity (KDIGO stage), 90-day recovery of kidney function, and prior AKI episodes., Outcomes: Intermediate- (30-364 days) and long-term (1-10 years) mortality and long-term renal replacement therapy., Measurements: Poisson regression in time discrete intervals. Multivariable Cox regression for those at risk in the intermediate and long term, adjusted for age, sex, baseline comorbid conditions, and acute admission circumstances., Results: Of 17,630 patients followed up for a median of 9.0 years, 9,251 died. Estimated incidences of hospital AKI were 8.4% and 17.6% for baseline eGFRs≥60 and <60mL/min/1.73m 2 , respectively. Intermediate-term (30-364 days) adjusted mortality HRs for AKI versus no AKI were 2.48 (95% CI, 2.15-2.88), 2.50 (95% CI, 2.04-3.06), 1.90 (95% CI, 1.51-2.39), and 1.63 (95% CI, 1.20-2.22) for eGFRs≥60, 45 to 59, 30 to 44, and <30mL/min/1.73m 2 , respectively. Among 1-year survivors, long-term HRs were attenuated: 1.44 (95% CI, 1.31-1.58), 1.25 (95% CI, 1.09-1.43), 1.21 (95% CI, 1.03-1.42), and 1.08 (95% CI, 0.85-1.36), respectively. The excess long-term hazards in AKI were lower for lower baseline eGFRs (P for interaction = 0.01)., Limitations: Nonprotocolized observational data. No adjustment for albuminuria., Conclusions: The prognostic importance of a discrete AKI episode lessens over time. Baseline kidney function is of greater long-term importance., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2017
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47. KDIGO-based acute kidney injury criteria operate differently in hospitals and the community-findings from a large population cohort.

Author

Sawhney S, Fluck N, Fraser SD, Marks A, Prescott GJ, Roderick PJ, and Black C

Subjects
Aged, Aged, 80 and over, Cohort Studies, England epidemiology, Female, Humans, Male, Middle Aged, Acute Kidney Injury diagnosis, Acute Kidney Injury epidemiology, Clinical Decision-Making methods, Community-Based Participatory Research, Database Management Systems standards, Databases, Factual, Hospitals
Abstract

Background: Early recognition of acute kidney injury (AKI) is important. It frequently develops first in the community. KDIGO-based AKI e-alert criteria may help clinicians recognize AKI in hospitals, but their suitability for application in the community is unknown., Methods: In a large renal cohort (n = 50 835) in one UK health authority, we applied the NHS England AKI 'e-alert' criteria to identify and follow three AKI groups: hospital-acquired AKI (HA-AKI), community-acquired AKI admitted to hospital within 7 days (CAA-AKI) and community-acquired AKI not admitted within 7 days (CANA-AKI). We assessed how AKI criteria operated in each group, based on prior blood tests (number and time lag). We compared 30-day, 1- and 5-year mortality, 90-day renal recovery and chronic renal replacement therapy (RRT)., Results: In total, 4550 patients met AKI e-alert criteria, 61.1% (2779/4550) with HA-AKI, 22.9% (1042/4550) with CAA-AKI and 16.0% (729/4550) with CANA-AKI. The median number of days since last blood test differed between groups (1, 52 and 69 days, respectively). Thirty-day mortality was similar for HA-AKI and CAA-AKI, but significantly lower for CANA-AKI (24.2, 20.2 and 2.6%, respectively). Five-year mortality was high in all groups, but followed a similar pattern (67.1, 64.7 and 46.2%). Differences in 5-year mortality among those not admitted could be explained by adjusting for comorbidities and restricting to 30-day survivors (hazard ratio 0.91, 95% confidence interval 0.80-1.04, versus hospital AKI). Those with CANA-AKI (versus CAA-AKI) had greater non-recovery at 90 days (11.8 versus 3.5%, P < 0.001) and chronic RRT at 5 years (3.7 versus 1.2%, P < 0.001)., Conclusions: KDIGO-based AKI criteria operate differently in hospitals and in the community. Some patients may not require immediate admission but are at substantial risk of a poor long-term outcome., (© The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA.)

Published
2016
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48. Is routine hospital episode data sufficient for identifying individuals with chronic kidney disease? A comparison study with laboratory data.

Author

Robertson LM, Denadai L, Black C, Fluck N, Prescott G, Simpson W, Wilde K, and Marks A

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Data Mining, Female, Glomerular Filtration Rate, Humans, Male, Medical Record Linkage methods, Middle Aged, Clinical Laboratory Information Systems statistics & numerical data, Electronic Health Records statistics & numerical data, Hospitals, Renal Insufficiency, Chronic
Abstract

Internationally, investment in the availability of routine health care data for improving health, health surveillance and health care is increasing. We assessed the validity of hospital episode data for identifying individuals with chronic kidney disease compared to biochemistry data in a large population-based cohort, the Grampian Laboratory Outcomes, Morbidity and Mortality Study-II (n = 70,435). Grampian Laboratory Outcomes, Morbidity and Mortality Study-II links hospital episode data to biochemistry data for all adults in a health region with impaired kidney function and random samples of individuals with normal and unmeasured kidney function in 2003. We compared identification of individuals with chronic kidney disease by hospital episode data (based on International Classification of Diseases-10 codes) to the reference standard of biochemistry data (at least two estimated glomerular filtration rates <60 mL/min/1.73 m(2) at least 90 days apart). Hospital episode data, compared to biochemistry data, identified a lower prevalence of chronic kidney disease and had low sensitivity (<10%) but high specificity (>97%). Using routine health care data from multiple sources offers the best opportunity to identify individuals with chronic kidney disease., (© The Author(s) 2014.)

Published
2016
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49. Acute kidney injury-how does automated detection perform?

Author

Sawhney S, Fluck N, Marks A, Prescott G, Simpson W, Tomlinson L, and Black C

Subjects
Adult, Aged, Aged, 80 and over, Early Diagnosis, Female, Humans, Kidney Function Tests, Male, Middle Aged, Scotland epidemiology, Acute Kidney Injury diagnosis, Acute Kidney Injury epidemiology, Algorithms, Pattern Recognition, Automated
Abstract

Background: Early detection of acute kidney injury (AKI) is important for safe clinical practice. NHS England is implementing a nationwide automated AKI detection system based on changes in blood creatinine. Little has been reported on the similarities and differences of AKI patients detected by this algorithm and other definitions of AKI in the literature., Methods: We assessed the NHS England AKI algorithm and other definitions using routine biochemistry in our own health authority in Scotland in 2003 (adult population 438 332). Linked hospital episode codes (ICD-10) were used to identify patients where AKI was a major clinical diagnosis. We compared how well the algorithm detected this subset of AKI patients in comparison to other definitions of AKI. We also evaluated the potential 'alert burden' from using the NHS England algorithm in comparison to other AKI definitions., Results: Of 127 851 patients with at least one blood test in 2003, the NHS England AKI algorithm identified 5565 patients. The combined NHS England algorithm criteria detected 91.2% (87.6-94.0) of patients who had an ICD-10 AKI code and this was better than any individual AKI definition. Some of those not captured could be identified by algorithm modifications to identify AKI in retrospect after recovery, but this would not be practical in real-time. Any modifications also increased the number of alerted patients (2-fold in the most sensitive model)., Conclusions: The NHS England AKI algorithm performs well as a diagnostic adjunct in clinical practice. In those without baseline data, AKI may only be seen in biochemistry in retrospect, therefore proactive clinical care remains essential. An alternative algorithm could increase the diagnostic sensitivity, but this would also produce a much greater burden of patient alerts., (© The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA.)

Published
2015
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50. Looking to the future: predicting renal replacement outcomes in a large community cohort with chronic kidney disease.

Author

Marks A, Fluck N, Prescott GJ, Robertson L, Simpson WG, Cairns Smith W, and Black C

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Calibration, Cohort Studies, Disease Progression, Female, Follow-Up Studies, Humans, Kidney Function Tests, Male, Middle Aged, Prognosis, Risk Factors, Survival Rate, Young Adult, Glomerular Filtration Rate, Models, Theoretical, Outcome Assessment, Health Care, Renal Insufficiency, Chronic therapy, Renal Replacement Therapy
Abstract

Background: Chronic kidney disease (CKD) is common and important due to poor outcomes. An ability to stratify CKD care based on outcome risk should improve care for all. Our objective was to develop and validate 5-year outcome prediction tools in a large population-based CKD cohort. Model performance was compared with the recently reported 'kidney failure risk equation' (KFRE) models., Methods: Those with CKD in the Grampian Laboratory Outcomes Mortality and Morbidity Study-I (3396) and -II (18 687) cohorts were used to develop and validate a renal replacement therapy (RRT) prediction tool. The discrimination, calibration and overall performance were assessed. The net reclassification index compared performance of the developed model and the 3- and 4-variable KFRE model to predict RRT in the validation cohort., Results: The developed model (with measures of age, sex, excretory renal function and proteinuria) performed well with a C-statistic of 0.938 (0.918-0.957) and Hosmer-Lemeshow (HL) χ(2) statistic 4.6. In the validation cohort (18 687), the developed model falsely identified fewer as high risk (414 versus 3278 individuals) compared with the KFRE 3-variable model (measures of age, sex and excretory renal function), but had more false negatives (58 versus 21 individuals). The KFRE 4-variable model could only be applied to 2274 individuals because of a lack of baseline urinary albumin creatinine ratio data, thus limiting its use in routine clinical practice., Conclusions: CKD outcome prediction tools have been developed by ourselves and others. These tools could be used to stratify care, but identify both false positives and -negatives. Further refinement should optimize the balance between identifying those at increased risk with clinical utility for stratifying care., (© The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

Published
2015
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