Predicting Kidney Failure, Cardiovascular Disease and Death in Advanced CKD Patients

Ramspek C. L.;Boekee R.;Evans M.;Heimburger O.;Snead C. M.;Caskey F. J.;Torino C.;Porto G.;Szymczak M.;Krajewska M.;Drechsler C.;Wanner C.;Chesnaye N. C.;Jager K. J.;Dekker F. W.;Snoeijs M. G. J.;Rotmans J. I.;van Diepen M.;Cupisti A.;Sagliocca A.;Ferraro A.;Musiala A.;Mele A.;Naticchia A.;Cosaro A.;Woodman A.;Ranghino A.;Stucchi A.;Jonsson A.;Schneider A.;Pignataro A.;Schrander A.;Torp A.;McKeever A.;Szymczak A.;Blom A. -L.;De Blasio A.;Pani A.;Tsalouichos A.;Ullah A.;McLaren B.;van Dam B.;Iwig B.;Antonio B.;Di Iorio B. R.;Rogland B.;Perras B.;Alessandra B.;Harron C.;Wallquist C.;Siegert C.;Barrett C.;Gaillard C.;Garofalo C.;Abaterusso C.;Beerenhout C.;O'Toole C.;Somma C.;Marx C.;Summersgill C.;Blaser C.;D'alessandro C.;Emde C.;Zullo C.;Pozzi C.;Geddes C.;Verburgh C.;Bergamo D.;Ciurlino D.;Motta D.;Glowski D.;McGlynn D.;Vargas D.;Krieter D.;Russo D.;Fuchs D.;Sands D.;Hoogeveen E.;Irmler E.;Dimeny E.;Favaro E.;Platen E.;Olczyk E.;Hoorn E.;Vigotti F.;Ansali F.;Conte F.;Cianciotta F.;Giacchino F.;Cappellaio F.;Pizzarelli F.;Sundelin F.;Uhlin F.;Greco G.;Roy G.;Bigatti G.;Marinangeli G.;Cabiddu G.;Hirst G.;Fumagalli G.;Caloro G.;Piccoli G.;Capasso G.;Gambaro G.;Tognarelli G.;Bonforte G.;Conte G.;Toscano G.;Del Rosso G.;Welander G.;Augustyniak-Bartosik H.;Boots H.;Schmidt-Gurtler H.;King H.;McNally H.;Schlee H.;Boom H.;Naujoks H.;Masri-Senghor H.;Murtagh H.;Rayner H.;Miskowiec-Wisniewska I.;Schlee I.;Capizzi I.;Hernandez I. B.;Baragetti I.;Manitius J.;Turner J.;Eijgenraam J. -W.;Kooman J.;Beige J.;Pondel J.;Wilcox J.;Berdeprado J.;Rothele J.;Wong J.;Rotmans J.;Banda J.;Mazur J.;Hahn K.;Jedrzejak K.;Nowanska K.;Blouin K.;Neumeier K.;Jones K.;Anding-Rost K.;Grontoft K. -C.;Oldrizzi L.;Haydock L.;Vogt L.;Wilkinson L.;Gesualdo L.;Schramm L.;Biancone L.;Nowak L.;Raasveld M.;Durlik M.;Magnano M.;Vervloet M.;Ricardi M.;Carmody M.;Di Bari M.;Laudato M.;Sirico M. L.;Stendahl M.;Svensson M.;Weetman M.;van Buren M.;Joinson M.;Ferraresi M.;Dutton M.;Matthews M.;Provenzano M.;Hopf M.;Malaguti M.;Wuttke N.;Morgan N.;Palmieri N.;Frischmuth N.;Bleakley N.;Murrone P.;Cockwell P.;Leurs P.;Roderick P.;Voskamp P.;Kashioulis P.;Ichtiaris P.;Blankestijn P.;Kirste P.;Schulz P.;Mason P.;Kalra P.;Cirillo P.;Dattolo P.;Acampora P.;Sajith R.;Nigro R.;Boero R.;Scarpioni R.;Sicoli R.;Malandra R.;Aign S.;Casar S.;van Esch S.;Chapman S.;Biribauer S.;Navjee S.;Crosbie S.;Brown S.;Tickle S.;Manan S.;Roser S.;Savoldi S.;Bertoli S.;Borrelli S.;Boorsma S.;Heidenreich S.;Melander S.;Maxia S.;Maffei S.;Mangano S.;Palm S.;Konings S.;Mathavakkannan S.;Schwedler S.;Delrieux S.;Renker S.;Schattel S.;Dorota S.;Cicchetti T.;Nieszporek T.;Stephan T.;Schmiedeke T.;Weinreich T.;Leimbach T.;Rappa T.;Almquist T.;Stovesand T.;Bahner U.;Jensen U.;Palazzo V.;De Simone W.;Seeger W.;Kuan Y.;Heleniak Z.;Aydin Z.

2022-01-01

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Abstract

Introduction: Predicting the timing and occurrence of kidney replacement therapy (KRT), cardiovascular events, and death among patients with advanced chronic kidney disease (CKD) is clinically useful and relevant. We aimed to externally validate a recently developed CKD G4+ risk calculator for these outcomes and to assess its potential clinical impact in guiding vascular access placement. Methods: We included 1517 patients from the European Quality (EQUAL) study, a European multicentre prospective cohort study of nephrology-referred advanced CKD patients aged ≥65 years. Model performance was assessed based on discrimination and calibration. Potential clinical utility for timing of referral for vascular access placement was studied with diagnostic measures and decision curve analysis (DCA). Results: The model showed a good discrimination for KRT and “death after KRT,” with 2-year concordance (C) statistics of 0.74 and 0.76, respectively. Discrimination for cardiovascular events (2-year C-statistic: 0.70) and overall death (2-year C-statistic: 0.61) was poorer. Calibration was fairly accurate. Decision curves illustrated that using the model to guide vascular access referral would generally lead to less unused arteriovenous fistulas (AVFs) than following estimated glomerular filtration rate (eGFR) thresholds. Conclusion: This study shows moderate to good predictive performance of the model in an older cohort of nephrology-referred patients with advanced CKD. Using the model to guide referral for vascular access placement has potential in combating unnecessary vascular surgeries.