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1. Biomarkers in Primary Focal Segmental Glomerulosclerosis in Optimal Diagnostic-Therapeutic Strategy

Author

Aleksandra Musiała, Piotr Donizy, Hanna Augustyniak-Bartosik, Katarzyna Jakuszko, Mirosław Banasik, Katarzyna Kościelska-Kasprzak, Magdalena Krajewska, and Dorota Kamińska

Subjects
primary FSGS, biomarkers, glomerulonephritis, Medicine
Abstract

Focal segmental glomerulosclerosis (FSGS) involves podocyte injury. In patients with nephrotic syndrome, progression to end-stage renal disease often occurs over the course of 5 to 10 years. The diagnosis is based on a renal biopsy. It is presumed that primary FSGS is caused by an unknown plasma factor that might be responsible for the recurrence of FSGS after kidney transplantation. The nature of circulating permeability factors is not explained and particular biological molecules responsible for inducing FSGS are still unknown. Several substances have been proposed as potential circulating factors such as soluble urokinase-type plasminogen activator receptor (suPAR) and cardiolipin-like-cytokine 1 (CLC-1). Many studies have also attempted to establish which molecules are related to podocyte injury in the pathogenesis of FSGS such as plasminogen activator inhibitor type-1 (PAI-1), angiotensin II type 1 receptors (AT1R), dystroglycan(DG), microRNAs, metalloproteinases (MMPs), forkheadbox P3 (FOXP3), and poly-ADP-ribose polymerase-1 (PARP1). Some biomarkers have also been studied in the context of kidney tissue damage progression: transforming growth factor-beta (TGF-β), human neutrophil gelatinase-associated lipocalin (NGAL), malondialdehyde (MDA), and others. This paper describes molecules that could potentially be considered as circulating factors causing primary FSGS.

Published
2022
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2. Kidney failure prediction models

Author

Ramspek, Chava L, Evans, Marie, Wanner, Christoph, Drechsler, Christiane, Chesnaye, Nicholas C, Szymczak, Maciej, Krajewska, Magdalena, Torino, Claudia, Porto, Gaetana, Hayward, Samantha, Caskey, Fergus, Dekker, Friedo W, Jager, Kitty J, van Diepen, Merel, EQUAL Study Investigators: Adamasco Cupisti, Adelia Sagliocca, Alberto Ferraro, Aleksandra Musiała, Alessandra Mele, Alessandro Naticchia, Alex Còsaro, Alistair Woodman, Andrea Ranghino, Andrea Stucchi, Andreas Jonsson, Andreas Schneider, Angelo Pignataro, Anita Schrander, Anke Torp, Anna McKeever, Anna Szymczak, Anna-Lena Blom, Antonella De Blasio, Antonello Pani, Aris Tsalouichos, Asad Ullah, Barbara McLaren, Bastiaan van Dam, Beate Iwig, Bellasi Antonio, Biagio Raffaele Di Iorio, Björn Rogland, Boris Perras, Butti Alessandra, Camille Harron, Carin Wallquist, Carl Siegert, Carla Barrett, Carlo Gaillard, Carlo Garofalo, Cataldo Abaterusso, Charles Beerenhout, Charlotte O'Toole, Chiara Somma, Christian Marx, Christina Summersgill, Christof Blaser, Claudia D'alessandro, Claudia Emde, Claudia Zullo, Claudio Pozzi, Colin Geddes, Cornelis Verburgh, Daniela Bergamo, Daniele Ciurlino, Daria Motta, Deborah Glowski, Deborah McGlynn, Denes Vargas, Detlef Krieter, Domenico Russo, Dunja Fuchs, Dympna Sands, Ellen Hoogeveen, Ellen Irmler, Emöke Dimény, Enrico Favaro, Eva Platen, Ewelina Olczyk, Ewout Hoorn, Federica Vigotti, Ferruccio Ansali, Ferruccio Conte, Francesca Cianciotta, Francesca Giacchino, Francesco Cappellaio, Francesco Pizzarelli, Fredrik Sundelin, Fredrik Uhlin, Gaetano Greco, Geena Roy, Gaetana Porto, Giada Bigatti, Giancarlo Marinangeli, Gianfranca Cabiddu, Gillian Hirst, Giordano Fumagalli, Giorgia Caloro, Giorgina Piccoli, Giovanbattista Capasso, Giovanni Gambaro, Giuliana Tognarelli, Giuseppe Bonforte, Giuseppe Conte, Giuseppe Toscano, Goffredo Del Rosso, Gunilla Welander, Hanna Augustyniak-Bartosik, Hans Boots, Hans Schmidt-Gürtler, Hayley King, Helen McNally, Hendrik Schlee, Henk Boom, Holger Naujoks, Houda Masri-Senghor, Hugh Murtagh, Hugh Rayner, Ilona Miśkowiec-Wiśniewska, Ines Schlee, Irene Capizzi, Isabel Bascaran Hernandez, Ivano Baragetti, Jacek Manitius, Jane Turner, Jan-Willem Eijgenraam, Jeroen Kooman, Joachim Beige, Joanna Pondel, Joanne Wilcox, Jocelyn Berdeprado, Jochen Röthele, Jonathan Wong, Joris Rotmans, Joyce Banda, Justyna Mazur, Kai Hahn, Kamila Jędrzejak, Katarzyna Nowańska, Katja Blouin, Katrin Neumeier, Kirsteen Jones, Kirsten Anding-Rost, Knut-Christian Gröntoft, Lamberto Oldrizzi, Lesley Haydock, Liffert Vogt, Lily Wilkinson, Loreto Gesualdo, Lothar Schramm, Luigi Biancone, Łukasz Nowak, Maarten Raasveld, Magdalena Durlik, Manuela Magnano, Marc Vervloet, Marco Ricardi, Margaret Carmody, Maria Di Bari, Maria Laudato, Maria Luisa Sirico, Maria Stendahl, Maria Svensson, Maria Weetman, Marjolijn van Buren, Martin Joinson, Martina Ferraresi, Mary Dutton, Merel van Diepen, Michael Matthews, Michele Provenzano, Monika Hopf, Moreno Malaguti, Nadja Wuttke, Neal Morgan, Nicola Palmieri, Nikolaus Frischmuth, Nina Bleakley, Paola Murrone, Paul Cockwell, Paul Leurs, Paul Roderick, Pauline Voskamp, Pavlos Kashioulis, Pawlos Ichtiaris, Peter Blankestijn, Petra Kirste, Petra Schulz, Phil Mason, Philip Kalra, Pietro Cirillo, Pietro Dattolo, Pina Acampora, Rincy Sajith, Rita Nigro, Roberto Boero, Roberto Scarpioni, Rosa Sicoli, Rosella Malandra, Sabine Aign, Sabine Cäsar, Sadie van Esch, Sally Chapman, Sandra Biribauer, Santee Navjee, Sarah Crosbie, Sharon Brown, Sheila Tickle, Sherin Manan, Silke Röser, Silvana Savoldi, Silvio Bertoli, Silvio Borrelli, Siska Boorsma, Stefan Heidenreich, Stefan Melander, Stefania Maxia, Stefano Maffei, Stefano Mangano, Stephanie Palm, Stijn Konings, Suresh Mathavakkannan, Susanne Schwedler, Sylke Delrieux, Sylvia Renker, Sylvia Schättel, Szyszkowska Dorota, Teresa Cicchetti, Teresa Nieszporek, Theresa Stephan, Thomas Schmiedeke, Thomas Weinreich, Til Leimbach, Tiziana Rappa, Tora Almquist, Torsten Stövesand, Udo Bahner, Ulrika Jensen, Valentina Palazzo, Walter De Simone, Wolfgang Seeger, Ying Kuan, Zbigniew Heleniak, Zeynep Aydin, Internal Medicine, Chava L, Ramspek, Marie, Evan, Christoph, Wanner, Christiane, Drechsler, Nicholas C, Chesnaye, Maciej, Szymczak, Magdalena, Krajewska, Claudia, Torino, Gaetana, Porto, Samantha, Hayward, Fergus, Caskey, Friedo W, Dekker, Kitty J, Jager, Merel, van Diepen, Study Investigators: Adamasco Cupisti, Equal, Sagliocca, Adelia, Ferraro, Alberto, Musiała, Aleksandra, Mele, Alessandra, Naticchia, Alessandro, Còsaro, Alex, Woodman, Alistair, Ranghino, Andrea, Stucchi, Andrea, Jonsson, Andrea, Schneider, Andrea, Pignataro, Angelo, Schrander, Anita, Torp, Anke, Mckeever, Anna, Szymczak, Anna, Blom, Anna-Lena, De Blasio, Antonella, Pani, Antonello, Tsalouichos, Ari, Ullah, Asad, Mclaren, Barbara, van Dam, Bastiaan, Iwig, Beate, Antonio, Bellasi, Raffaele Di Iorio, Biagio, Rogland, Björn, Perras, Bori, Alessandra, Butti, Harron, Camille, Wallquist, Carin, Siegert, Carl, Barrett, Carla, Gaillard, Carlo, Garofalo, Carlo, Abaterusso, Cataldo, Beerenhout, Charle, O'Toole, Charlotte, Somma, Chiara, Marx, Christian, Summersgill, Christina, Blaser, Christof, D'Alessandro, Claudia, Emde, Claudia, Zullo, Claudia, Pozzi, Claudio, Geddes, Colin, Verburgh, Corneli, Bergamo, Daniela, Ciurlino, Daniele, Motta, Daria, Glowski, Deborah, Mcglynn, Deborah, Vargas, Dene, Krieter, Detlef, Russo, Domenico, Fuchs, Dunja, Sands, Dympna, Hoogeveen, Ellen, Irmler, Ellen, Dimény, Emöke, Favaro, Enrico, Platen, Eva, Olczyk, Ewelina, Hoorn, Ewout, Vigotti, Federica, Ansali, Ferruccio, Conte, Ferruccio, Cianciotta, Francesca, Giacchino, Francesca, Cappellaio, Francesco, Pizzarelli, Francesco, Sundelin, Fredrik, Uhlin, Fredrik, Greco, Gaetano, Roy, Geena, Porto, Gaetana, Bigatti, Giada, Marinangeli, Giancarlo, Cabiddu, Gianfranca, Hirst, Gillian, Fumagalli, Giordano, Caloro, Giorgia, Piccoli, Giorgina, Capasso, Giovanbattista, Gambaro, Giovanni, Tognarelli, Giuliana, Bonforte, Giuseppe, Conte, Giuseppe, Toscano, Giuseppe, Del Rosso, Goffredo, Welander, Gunilla, Augustyniak-Bartosik, Hanna, Boots, Han, Schmidt-Gürtler, Han, King, Hayley, Mcnally, Helen, Schlee, Hendrik, Boom, Henk, Naujoks, Holger, Masri-Senghor, Houda, Murtagh, Hugh, Rayner, Hugh, Miśkowiec-Wiśniewska, Ilona, Schlee, Ine, Capizzi, Irene, Bascaran Hernandez, Isabel, Baragetti, Ivano, Manitius, Jacek, Turner, Jane, Eijgenraam, Jan-Willem, Kooman, Jeroen, Beige, Joachim, Pondel, Joanna, Wilcox, Joanne, Berdeprado, Jocelyn, Röthele, Jochen, Wong, Jonathan, Rotmans, Jori, Banda, Joyce, Mazur, Justyna, Hahn, Kai, Jędrzejak, Kamila, Nowańska, Katarzyna, Blouin, Katja, Neumeier, Katrin, Jones, Kirsteen, Anding-Rost, Kirsten, Gröntoft, Knut-Christian, Oldrizzi, Lamberto, Haydock, Lesley, Vogt, Liffert, Wilkinson, Lily, Gesualdo, Loreto, Schramm, Lothar, Biancone, Luigi, Nowak, Łukasz, Raasveld, Maarten, Durlik, Magdalena, Magnano, Manuela, Vervloet, Marc, Ricardi, Marco, Carmody, Margaret, Di Bari, Maria, Laudato, Maria, Luisa Sirico, Maria, Stendahl, Maria, Svensson, Maria, Weetman, Maria, van Buren, Marjolijn, Joinson, Martin, Ferraresi, Martina, Dutton, Mary, van Diepen, Merel, Matthews, Michael, Provenzano, Michele, Hopf, Monika, Malaguti, Moreno, Wuttke, Nadja, Morgan, Neal, Palmieri, Nicola, Frischmuth, Nikolau, Bleakley, Nina, Murrone, Paola, Cockwell, Paul, Leurs, Paul, Roderick, Paul, Voskamp, Pauline, Kashioulis, Pavlo, Ichtiaris, Pawlo, Blankestijn, Peter, Kirste, Petra, Schulz, Petra, Mason, Phil, Kalra, Philip, Cirillo, Pietro, Dattolo, Pietro, Acampora, Pina, Sajith, Rincy, Nigro, Rita, Boero, Roberto, Scarpioni, Roberto, Sicoli, Rosa, Malandra, Rosella, Aign, Sabine, Cäsar, Sabine, van Esch, Sadie, Chapman, Sally, Biribauer, Sandra, Navjee, Santee, Crosbie, Sarah, Brown, Sharon, Tickle, Sheila, Manan, Sherin, Röser, Silke, Savoldi, Silvana, Bertoli, Silvio, Borrelli, Silvio, Boorsma, Siska, Heidenreich, Stefan, Melander, Stefan, Maxia, Stefania, Maffei, Stefano, Mangano, Stefano, Palm, Stephanie, Konings, Stijn, Mathavakkannan, Suresh, Schwedler, Susanne, Delrieux, Sylke, Renker, Sylvia, Schättel, Sylvia, Dorota, Szyszkowska, Cicchetti, Teresa, Nieszporek, Teresa, Stephan, Theresa, Schmiedeke, Thoma, Weinreich, Thoma, Leimbach, Til, Rappa, Tiziana, Almquist, Tora, Stövesand, Torsten, Bahner, Udo, Jensen, Ulrika, Palazzo, Valentina, De Simone, Walter, Seeger, Wolfgang, Kuan, Ying, Heleniak, Zbigniew, Aydin, Zeynep, Medical Informatics, ACS - Pulmonary hypertension & thrombosis, APH - Aging & Later Life, APH - Health Behaviors & Chronic Diseases, APH - Methodology, APH - Quality of Care, and APH - Global Health

Subjects
Male, progression of chronic renal failure, medicine.medical_specialty, Time Factors, epidemiology and outcome, 030232 urology & nephrology, Risk Assessment, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Older patients, external validation, Predictive Value of Tests, medicine, Humans, Failure risk, Clinical Epidemiology, In patient, comprehensive external validation, 030212 general & internal medicine, Statistic, Aged, Aged, 80 and over, Kidney, Models, Statistical, business.industry, External validation, General Medicine, prediction, kidney failure, Europe, prediction model, medicine.anatomical_structure, chronic kidney disease, epidemiology and outcomes, prognosis, Nephrology, Emergency medicine, Disease Progression, Kidney Failure, Chronic, Female, business, prognostic, Predictive modelling, prognosi, Cohort study
Abstract

Background Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks. Methods To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration. Results The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%-\18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts. Conclusions Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years).

Published
2021

3. The use of different dialysis membranes in therapy of patients with multiple myeloma

Author

Aleksandra Musiała, Maciej Szymczak, and Dorota Zielińska

Subjects
medicine.medical_specialty, Dialysis membranes, Chemistry, Urology, Hemodiafiltration, General Medicine, Immunoglobulin light chain, medicine.disease, Membrane, Renal Dialysis, Kidney injury, medicine, Humans, Effective treatment, Immunoglobulin Light Chains, Kidney Diseases, In patient, Multiple Myeloma, Dialysis (biochemistry), Multiple myeloma
Abstract

Free light chains accumulation is the reason of kidney injury in patients with multiple myeloma. The removal of free light chains can improve patients prognosis and survival, and in some cases allows for dialysotherapy discontinuation. Unfortunately, conventional dialysis is not effective enough in terms of free light chains removal. New high cut-off (HCO) techniques remove free light chains more effectively than conventional dialysis. In some cases, this technique may turn out better than hemodiafiltration. However, there are some differences between specific techniques in the removal of kappa and lambda light chains. Lambda light chains are better removed by polymethyl methacrylate membranes with a change of filter during dialysis. Kappa light chains are thoroughly removed by polymethyl methacrylate membranes and HCO (35,000 Da) polysulfone membranes. Unfortunately, it is very difficult to differentiate between the effect of HCO dialysis therapy and concomitant chemotherapy because some of the data is not fully conclusive. Using the proper technique for an individual patient may give optimally effective treatment results.

Published
2020

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