scholarly journals Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care

2018 ◽  
Vol 35 (5) ◽  
pp. 836-845 ◽  
Author(s):  
Simon Sawhney ◽  
Monica Beaulieu ◽  
Corri Black ◽  
Ognjenka Djurdjev ◽  
Gabriela Espino-Hernandez ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Kidney Failure ◽  
Prediction Models ◽  
Kidney Diseases ◽  
Kidney Injury ◽  
Operating Characteristics ◽  
Cox Models ◽  
Risk Equation ◽  
Failure Risk ◽  
Long Term Prognosis

Abstract Background Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous AKI episodes when used in this setting. Methods This observational cohort study included 7491 people referred for nephrology clinic care in British Columbia in 2003–09 followed to 2016. Predictors were previous Kidney Disease: Improving Global Outcomes–based AKI, age, sex, proteinuria, estimated glomerular filtration rate (eGFR) and renal diagnosis. Outcomes were 5-year kidney failure and death. We developed cause-specific Cox models (AKI versus no AKI) for kidney failure and death, stratified by eGFR (</≥30 mL/min/1.73 m2). We also compared prediction models comparing the 5-year KFRE with two refitted models, one with and one without AKI as a predictor. Results AKI was associated with increased kidney failure (33.1% versus 26.3%) and death (23.8% versus 16.8%) (P  < 0.001). In Cox models, AKI was independently associated with increased kidney failure in those with an eGFR ≥30 mL/min/1.73 m2 {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m2 ([HR 1.05 95% CI 0.91–1.21)] and increased mortality in both subgroups [respective HRs 1.89 (95% CI 1.56–2.30) and 1.43 (1.16–1.75)]. Incorporating AKI into a refitted kidney failure prediction model did not improve predictions on comparison of receiver operating characteristics (P = 0.16) or decision curve analysis. The original KFRE calibrated poorly in this setting, underpredicting risk. Conclusions AKI carries a poorer long-term prognosis among those already under nephrology care. AKI may not alter kidney failure risk predictions, but the use of prediction models without appreciating the full impact of AKI, including increased mortality, would be simplistic. People with kidney diseases have risks beyond simply kidney failure. This complexity and variability of outcomes of individuals is important.

scholarly journals MO1031FROM MARCELLO MALPIGHI  THROUGH  JEAN REDMAN OLIVER AND JOSEP TRUETA: A CONTINUING CONTRIBUTION TO THE “BLACK BOX”  CLINICAL PREDICTION MODELS IN NEPHROLOGY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Enrico Favaro ◽  
Roberta Lazzarin ◽  
Daniela Cremasco ◽  
Erika Pierobon ◽  
Marta Guizzo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Kidney Injury ◽  
Prediction Models ◽  
Kidney Diseases ◽  
Kidney Injury ◽  
Black Box ◽  
Renal Physiology ◽  
Clinical Prediction ◽  
Renal Circulation ◽  
Clinical Prediction Models

Abstract Background and Aims The modern development of the black box approach in clinical nephrology is inconceivable without a logical theory of renal function and a comprehension of anatomical architecture of the kidney, in health and disease: this is the undisputed contribution offered by Malpighi, Oliver and Trueta starting from the seventeenth century. The machine learning model for the prediction of acute kidney injury, progression of renal failure and tubulointerstitial nephritis is a good example of how different knowledge about kidney are an indispensable tool for the interpretation of model itself. Method Historical data were collected from literature, textbooks, encyclopedias, scientific periodicals and laboratory experimental data concerning these three authors. Results The Italian Marcello Malpighi (1628-1694), born in Crevalcore near Bologna, was Professor of anatomy at Bologna, Pisa and Messina. The historic description of the pulmonary capillaries was made in his second epistle to Borelli published in 1661 and intitled De pulmonibus, by means of the frog as “the microscope of nature” (Fig. 1). It is the first description of capillaries in any circulation. William Harvey in De motu cordis in 1628 (year of publication the same of date of birth of Italian anatomist!) could not see the capillary vessels. This thriumphant discovery will serve for the next reconnaissance of characteristic renal rete mirabile.in the corpuscle of Malpighi, lying within the capsule of Bowman. Jean Redman Oliver (1889-1976), a pathologist born and raised in Northern California, was able to bridge the gap between the nephron and collecting system through meticulous dissections, hand drawn illustrations and experiments which underpin our current understanding of renal anatomy and physiology. In the skillful lecture “When is the kidney not a kidney?” (1949) Oliver summarizes his far-sighted vision on renal physiology and disease in the following sentence: the Kidney in health, if you will, but the Nephrons in disease. Because, the “nephron” like the “kidney” is an abstraction that must be qualified in terms of its various parts, its cellular components and the molecular mechanisms involved in each discrete activity (Fig. 2). The Catalan surgeon Josep Trueta I Raspall (1897-1977) was born in the Poblenou neighborhood of Barcelona. His impact of pioneering and visionary contribution to the changes in renal circulation for the pathogenesis of acute kidney injury was pivotal for history of renal physiology. “The kidney has two potential circulatory circulations. Blood may pass either almost exclusively through one or other of two pathways, or to a varying degree through both”. (Studies of the Renal Circulation, published in 1947). Now this diversion of blood from cortex to the less resistant medullary circulation is known with the eponym Trueta shunt. Conclusion The black box approach to the kidney diseases should be considered by practitioners as a further tool to help to inform model update in many clinical setting. The number of machine learning clinical prediction models being published is rising, as new fields of application are being explored in medicine (Fig. 3). A challenge in the clinical nephrology is to explore the “kidney machine” during each therapeutic diagnostic procedure. Always, the intriguing relationship between the set of nephrological syndromes and kidney diseases cannot disregard the precious notions the specific organization of kidney microcirculation, fruit of many scientific contributions of the work by Malpighi, Oliver and Trueta (Fig. 3).

scholarly journals A simple nomogram to predict contrast-induced acute kidney injury in patients with congestive heart failure undergoing coronary angiography

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L Lei ◽  
Y He ◽  
Z Guo ◽  
B Liu ◽  
J Liu ◽  
...  
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Acute Kidney Injury ◽  
Coronary Angiography ◽  
Prediction Models ◽  
Validation Cohort ◽  
Kidney Injury ◽  
Class Ii ◽  
Functional Class ◽  
Killip Class

Abstract Background Patients with congestive heart failure (CHF) are vulnerable to contrast-induced acute kidney injury (CI-AKI), but few prediction models are currently available. Objectives We aimed to establish a simple nomogram for CI-AKI risk assessment for patients with CHF undergoing coronary angiography. Methods A total of 1876 consecutive patients with CHF (defined as New York Heart Association functional class II-IV or Killip class II-IV) were enrolled and randomly (2:1) assigned to a development cohort and a validation cohort. The endpoint was CI-AKI defined as serum creatinine elevation of ≥0.3 mg/dL or 50% from baseline within the first 48–72 hours following the procedure. Predictors for the nomogram were selected by multivariable logistic regression with a stepwise approach. The discriminative power was assessed using the area under the receiver operating characteristic (ROC) curve and was compared with the classic Mehran score in the validation cohort. Calibration was assessed using the Hosmer–Lemeshow test and 1000 bootstrap samples. Results The incidence of CI-AKI was 9.06% (n=170) in the total sample, 8.64% (n=109) in the development cohort and 9.92% (n=61) in the validation cohort (p=0.367). The simple nomogram including four predictors (age, intra-aortic balloon pump, acute myocardial infarction and chronic kidney disease) demonstrated a similar predictive power as the Mehran score (area under the curve: 0.80 vs 0.75, p=0.061), as well as a well-fitted calibration curve. Conclusions The present simple nomogram including four predictors is a simple and reliable tool to identify CHF patients at risk of CI-AKI, whereas further external validations are needed. Figure 1 Funding Acknowledgement Type of funding source: None

scholarly journals Granulomatous interstitial nephritis in a patient with SARS-CoV-2 infection

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Katarzyna Szajek ◽  
Marie-Elisabeth Kajdi ◽  
Valerie A. Luyckx ◽  
Thomas Hans Fehr ◽  
Ariana Gaspert ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Interstitial Nephritis ◽  
Kidney Biopsy ◽  
Kidney Diseases ◽  
Case Reports ◽  
Kidney Injury ◽  
Maculopapular Rash ◽  
Tubular Injury ◽  
Granulomatous Interstitial Nephritis ◽  
First Case

Abstract Background Acute kidney injury (AKI) associated with severe coronavirus disease 19 (COVID-19) is common and is a significant predictor of morbidity and mortality, especially when dialysis is required. Case reports and autopsy series have revealed that most patients with COVID-19 – associated acute kidney injury have evidence of acute tubular injury and necrosis - not unexpected in critically ill patients. Others have been found to have collapsing glomerulopathy, thrombotic microangiopathy and diverse underlying kidney diseases. A primary kidney pathology related to COVID-19 has not yet emerged. Thus far direct infection of the kidney, or its impact on clinical disease remains controversial. The management of AKI is currently supportive. Case Presentation The patient presented here was positive for SARS-CoV-2, had severe acute respiratory distress syndrome and multi-organ failure. Within days of admission to the intensive care unit he developed oliguric acute kidney failure requiring dialysis. Acute kidney injury developed in the setting of hemodynamic instability, sepsis and a maculopapular rash. Over the ensuing days the patient also developed transfusion-requiring severe hemolysis which was Coombs negative. Schistocytes were present on the peripheral smear. Given the broad differential diagnoses for acute kidney injury, a kidney biopsy was performed and revealed granulomatous tubulo-interstitial nephritis with some acute tubular injury. Based on the biopsy findings, a decision was taken to adjust medications and initiate corticosteroids for presumed medication-induced interstitial nephritis, hemolysis and maculo-papular rash. The kidney function and hemolysis improved over the subsequent days and the patient was discharged to a rehabilitation facility, no-longer required dialysis. Conclusions Acute kidney injury in patients with severe COVID-19 may have multiple causes. We present the first case of granulomatous interstitial nephritis in a patient with COVID-19. Drug-reactions may be more frequent than currently recognized in COVID-19 and are potentially reversible. The kidney biopsy findings in this case led to a change in therapy, which was associated with subsequent patient improvement. Kidney biopsy may therefore have significant value in pulling together a clinical diagnosis, and may impact outcome if a treatable cause is identified.

scholarly journals A validation study of the 4-variable and 8-variable kidney failure risk equation in transplant recipients in the United Kingdom

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ibrahim Ali ◽  
Philip A. Kalra
Keyword(s):  
United Kingdom ◽  
Kidney Failure ◽  
Graft Failure ◽  
Risk Scores ◽  
Transplant Recipients ◽  
Good Discrimination ◽  
Risk Equation ◽  
The United Kingdom ◽  
Failure Risk ◽  
Risk Patients

Abstract Background There is emerging evidence that the 4-variable Kidney Failure Risk Equation (KFRE) can be used for risk prediction of graft failure in transplant recipients. However, geographical validation of the 4-variable KFRE in transplant patients is lacking, as is whether the more extensive 8-variable KFRE improves predictive accuracy. This study aimed to validate the 4- and 8-variable KFRE predictions of the 5-year death-censored risk of graft failure in patients in the United Kingdom. Methods A retrospective cohort study involved 415 transplant recipients who had their first renal transplant between 2003 and 2015 and were under follow-up at Salford Royal NHS Foundation Trust. The KFRE risk scores were calculated on variables taken 1-year post-transplant. The area under the receiver operating characteristic curves (AUC) and calibration plots were evaluated to determine discrimination and calibration of the 4- and 8-variable KFREs in the whole cohort as well as in a subgroup analysis of living and deceased donor recipients and in patients with an eGFR< 45 ml/min/1.73m2. Results There were 16 graft failure events (4%) in the whole cohort. The 4- and 8-variable KFREs showed good discrimination with AUC of 0.743 (95% confidence interval [CI] 0.610–0.876) and 0.751 (95% CI 0.629–0.872) respectively. In patients with an eGFR< 45 ml/min/1.73m2, the 8-variable KFRE had good discrimination with an AUC of 0.785 (95% CI 0.558–0.982) but the 4-variable provided excellent discrimination in this group with an AUC of 0.817 (0.646–0.988). Calibration plots however showed poor calibration with risk scores tending to underestimate risk of graft failure in low-risk patients and overestimate risk in high-risk patients, which was seen in the primary and subgroup analyses. Conclusions Despite adequate discrimination, the 4- and 8-variable KFREs are imprecise in predicting graft failure in transplant recipients using data 1-year post-transplant. Larger, international studies involving diverse patient populations should be considered to corroborate these findings.

scholarly journals External Validation of the Kidney Failure Risk Equation and Re-Calibration with Addition of Ultrasound Parameters

2016 ◽  
Vol 11 (4) ◽  
pp. 609-615 ◽  
Author(s):  
Claudia S. Lennartz ◽  
John William Pickering ◽  
Sarah Seiler-Mußler ◽  
Lucie Bauer ◽  
Kathrin Untersteller ◽  
...  
Keyword(s):  
Kidney Failure ◽  
External Validation ◽  
Risk Equation ◽  
Failure Risk ◽  
Ultrasound Parameters

scholarly journals Prediction models for acute kidney injury in patients with gastrointestinal cancers: a real-world study based on Bayesian networks

Renal Failure ◽  
2020 ◽  
Vol 42 (1) ◽  
pp. 869-876
Author(s):  
Yang Li ◽  
Xiaohong Chen ◽  
Ziyan Shen ◽  
Yimei Wang ◽  
Jiachang Hu ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Bayesian Networks ◽  
Real World ◽  
Prediction Models ◽  
Kidney Injury ◽  
Gastrointestinal Cancers

scholarly journals Complicações renais decorrentes da infecção por SARS-CoV-2 em pessoas com COVID-19 hospitalizadas: scoping review

2022 ◽  
Vol 11 (1) ◽  
pp. e40811125217
Author(s):  
Anyele Albuquerque Lima ◽  
Alda Graciele Claudio dos Santo Almeida ◽  
Izabelly Carollynny Maciel Nunes ◽  
Patrícia de Albuquerque Sarmento ◽  
Wanda Tenório Barros Passos Alves
Keyword(s):  
Acute Kidney Injury ◽  
Scoping Review ◽  
Web Of Science ◽  
Kidney Diseases ◽  
Grey Literature ◽  
Kidney Injury ◽  
Glomerular Disease ◽  
Google Scholar ◽  
Cochrane Library

Objetivos: Identificar complicações/sequelas renais decorrentes da infecção por SARS-CoV-2 em pessoas com COVID-19; e descrever a característica de idade da população estudada. Metodologia: Scoping Review realizada nas bases de dados Web of Science, BVS, Cochrane Library, MEDLINE/PubMed, CINAHL, SCOPUS, Embase, LILACS. E nos sites online: ProQuest Dissertations and Theses, Grey Literature e Google Scholar. Os descritores utilizados foram (comorbidity OR sequel OR complications), (kidney diseases OR glomerular disease OR acute kidney injury OR nephropathy) AND (coronavirus OR SARS-CoV-2 OR COVID-19). Critérios de inclusão: artigos em português, inglês e espanhol, com abordagens metodológicas diversas, disponíveis na íntegra, online, publicados no período de 01 de janeiro de 2020 a 29 de setembro de 2021. E de exclusão: pessoas com diagnósticos prévios de patologias renais agudas e/ou crônicas; cartas ao editor; artigos de opinião; editoriais; e notas. Resultados: Selecionaram-se 10 artigos, que evidenciaram que o processo infeccioso causado pelo SARS-CoV-2 pode iniciar com uma leve proteinúria e hematúria, e evoluir para uma injúria renal aguda causada pela diminuição da capacidade de filtração glomerular, que favorece a retenção de algumas escórias nitrogenadas, causando o aumento dos níveis de creatinina e de ureia. Ademais, informaram que indivíduos entre 52-69 anos foram os mais acometidos. Considerações finais: As complicações/sequelas renais decorrentes da infecção por SARS-CoV-2 são: deposição de imunocomplexos nas células renais, proteinúria, hematúria, aumento da creatinina sérica, aumento da ureia nitrogenada no sangue, diminuição da TFG, e IRA estágio 1, 2 e 3. Tais complicações ocorreram principalmente em pessoas com idade ≥ 52 anos.

scholarly journals The Kidney Failure Risk Equation Score and CKD Care Delivery Measures: A Cross-sectional Study

2021 ◽  
Author(s):  
Salman Ahmed ◽  
Suraj Sarvode Mothi ◽  
Thomas Sequist ◽  
Navdeep Tangri ◽  
Roaa M. Khinkar ◽  
...  
Keyword(s):  
Kidney Failure ◽  
Care Delivery ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Risk Equation ◽  
Failure Risk

scholarly journals Use of the Kidney Failure Risk Equation to Determine the Risk of Progression to End-stage Renal Disease in Children With Chronic Kidney Disease

2018 ◽  
Vol 172 (2) ◽  
pp. 174 ◽  
Author(s):  
Erica Winnicki ◽  
Charles E. McCulloch ◽  
Mark M. Mitsnefes ◽  
Susan L. Furth ◽  
Bradley A. Warady ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Renal Disease ◽  
Kidney Failure ◽  
End Stage Renal Disease ◽  
Risk Equation ◽  
Failure Risk ◽  
Risk Of Progression ◽  
Stage Renal Disease ◽  
End Stage

scholarly journals Validation of the Kidney Failure Risk Equation in Manitoba

2017 ◽  
Vol 4 ◽  
pp. 205435811770537 ◽  
Author(s):  
Reid H. Whitlock ◽  
Mariette Chartier ◽  
Paul Komenda ◽  
Jay Hingwala ◽  
Claudio Rigatto ◽  
...  
Keyword(s):  
Kidney Failure ◽  
Risk Equation ◽  
Failure Risk
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