RESUMO
In order to develop an equation that integrates multiple clinical factors including signs and symptoms associated with uraemia to assess the initiation of dialysis, we conducted a retrospective cohort study including 25 haemodialysis centres in Mainland China. Patients with ESRD (n = 1281) who commenced haemodialysis from 2008 to 2011 were enrolled in the development cohort, whereas 504 patients who began haemodialysis between 2012 and 2013 were enrolled in the validation cohort comprised. An artificial neural network model was used to select variables, and a fuzzy neural network model was then constructed using factors affecting haemodialysis initiation as input variables and 3-year survival as the output variable. A logistic model was set up using the same variables. The equation's performance was compared with that of the logistic model and conventional eGFR-based assessment. The area under the bootstrap-corrected receiver-operating characteristic curve of the equation was 0.70, and that of two conventional eGFR-based assessments were 0.57 and 0.54. In conclusion, the new equation based on Fuzzy mathematics, covering laboratory and clinical variables, is more suitable for assessing the timing of dialysis initiation in a Chinese ESRD population than eGFR, and may be a helpful tool to quantitatively evaluate the initiation of haemodialysis.
Assuntos
Falência Renal Crônica/patologia , Redes Neurais de Computação , Adulto , Idoso , Área Sob a Curva , Feminino , Taxa de Filtração Glomerular , Humanos , Falência Renal Crônica/mortalidade , Falência Renal Crônica/terapia , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Curva ROC , Diálise Renal , Estudos Retrospectivos , Fatores de TempoRESUMO
INTRODUCTION: Starting dialysis early or late both result in a low quality of life and a poor prognosis in patients undergoing haemodialysis. However, there remains no consensus on the optimal timing of dialysis initiation, mainly because of a lack of suitable methods to assess variations in dialysis initiation time. We have established a novel equation named DIFE (Dialysis Initiation based on Fuzzy-mathematics Equation) through a retrospective, multicentre clinical cohort study in China to determine the most suitable timing of dialysis initiation. The predictors of the DIFE include nine biochemical markers and clinical variables that together influence dialysis initiation. To externally validate the clinical accuracy of DIFE, we designed the assessment of DIFE (ADIFE) study as a prospective, open-label, multicentre, randomised controlled trial to assess the clinical outcomes among patients who initiate dialysis in an optimal start dialysis group and a late-start dialysis group, based on DIFE. METHODS AND ANALYSIS: A total of 388 enrolled patients with end-stage renal disease will be randomised 1:1 to the optimal start dialysis group, with a DIFE value between 30 and 35, or the late-start dialysis group, with a DIFE value less than 30, using the Randomization and Trial Supply Management system. Participants will be assessed for changes in signs and symptoms, dialysis mode and parameters, biochemical and inflammatory markers, Subjective Global Assessment, Kidney Disease Quality of Life Short Form, Cognitive Assessment, medical costs, adverse events and concomitant medication at baseline, predialysis visiting stage and postdialysis visiting stage, every 12-24 weeks. The following data will be recorded on standardised online electronic case report forms. The primary endpoint is 3-year all-cause mortality. The secondary endpoints include non-fatal cerebrocardiovascular events, annual hospitalisation rate, quality of life, medical costs and haemodialysis related complications. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Ethics Committee of the First Affiliated Hospital of Dalian Medical University China (registration no: YJ-KY-2017-119) and the ethics committees of all participating centres. The final results of the ADIFE trial will be presented to the study sponsor, clinical researchers and the patient and public involvement reference group. Findings will be disseminated through peer-reviewed journals, Clinical Practice Guidelines and at scientific meetings. TRIAL REGISTRATION NUMBER: ClinicalTrial.gov. Registry (NCT03385902); pre-results.
Assuntos
Falência Renal Crônica/terapia , Ensaios Clínicos Controlados Aleatórios como Assunto , Diálise Renal/normas , Tempo para o Tratamento/normas , Adulto , Algoritmos , Estudos de Coortes , Feminino , Lógica Fuzzy , Humanos , Masculino , Estudos Prospectivos , Projetos de PesquisaRESUMO
Pericytes have been identified as a major source of myofibroblasts in renal interstitial fibrosis (RIF). The overactivation of several signaling pathways, mainly the TGF-ß and PDGF pathways, initiates the pericyte-myofibroblast transition during RIF. Key receptors in these two pathways have been shown to be modified by fucosyltransferase 8 (FUT8), the enzyme that catalyzes core fucosylation. This study postulated that core fucosylation might play an important role in regulating the pericyte transition in RIF. The data showed that core fucosylation increased with the extent of RIF in patients with IgA nephropathy (IgAN). Similarly, core fucosylation of pericytes increased in both a unilateral ureteral occlusion (UUO) mouse model and an in vitro model of pericyte transition. Inhibition of core fucosylation by adenoviral-mediated FUT8 shRNA in vivo and FUT8 siRNA in vitro significantly reduced pericyte transition and RIF. In addition, the activation of both the TGF-ß/Smad and PDGF/ERK pathways was blocked by core fucosylation inhibition. In conclusion, core fucosylation may regulate the pericyte transition in RIF by modifying both the TGF-ß/Smad and PDGF/ERK pathways. Glycosylation might be a novel "hub" target to prevent RIF.