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      The Spectrum of Renal Involvement in Patients With Inflammatory Myopathies

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          Abstract

          Data regarding the incidence and outcome of renal involvement in patients with inflammatory myopathies (IM) remain scarce. We assessed the incidence and causes of acute kidney injury (AKI) and chronic kidney disease (CKD) in 150 patients with dermatomyositis, polymyositis, and antisynthetase syndrome followed in 3 French referral centers. Renal involvement occurred in 35 (23.3%) patients: AKI in 16 (10.7%), and CKD in 31 (20.7%) patients. The main cause of AKI was drug or myoglobinuria-induced acute tubular necrosis. Male sex, cardiovascular risk factors, cardiac involvement, and initial proteinuria >0.3 g/d were associated with the occurrence of AKI. The outcome of patients with AKI was poor: 13 (81%) progressed to CKD and 2 (12.5%) reached end-stage renal disease. In multivariate survival analysis, age at IM onset, male sex, a history of cardiovascular events, and a previous episode of AKI were associated with the risk of CKD. We also identified 14 IM patients who underwent a kidney biopsy in 10 nephrology centers. Renal pathology disclosed a wide range of renal disorders, mainly immune-complex glomerulonephritis. We identified in 5 patients a peculiar pattern of severe acute renal vascular damage consisting mainly of edematous thickening of the intima of arterioles.

          We found that AKI and CKD are frequent in patients with IM. Prevention of AKI is crucial in these patients, as AKI is a major contributor to their relatively high risk of CKD. A peculiar pattern of acute vascular damage is part of the spectrum of renal diseases associated with IM.

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          Most cited references27

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          Time-dependent ROC curves for censored survival data and a diagnostic marker.

          ROC curves are a popular method for displaying sensitivity and specificity of a continuous diagnostic marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t), and ROC curves that vary as a function of time may be more appropriate. A common example of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and zero otherwise. We propose summarizing the discrimination potential of a marker X, measured at baseline (t = 0), by calculating ROC curves for cumulative disease or death incidence by time t, which we denote as ROC(t). A typical complexity with survival data is that observations may be censored. Two ROC curve estimators are proposed that can accommodate censored data. A simple estimator is based on using the Kaplan-Meier estimator for each possible subset X > c. However, this estimator does not guarantee the necessary condition that sensitivity and specificity are monotone in X. An alternative estimator that does guarantee monotonicity is based on a nearest neighbor estimator for the bivariate distribution function of (X, T), where T represents survival time (Akritas, M. J., 1994, Annals of Statistics 22, 1299-1327). We present an example where ROC(t) is used to compare a standard and a modified flow cytometry measurement for predicting survival after detection of breast cancer and an example where the ROC(t) curve displays the impact of modifying eligibility criteria for sample size and power in HIV prevention trials.
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            119th ENMC international workshop: trial design in adult idiopathic inflammatory myopathies, with the exception of inclusion body myositis, 10-12 October 2003, Naarden, The Netherlands.

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              Rhabdomyolysis and myohemoglobinuric acute renal failure.

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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MD
                Medicine
                Wolters Kluwer Health
                0025-7974
                1536-5964
                January 2014
                02 January 2014
                : 93
                : 1
                : 33-41
                Affiliations
                From Department of Nephrology and Immunology (GC-D, FF), UMR S 1064, ITUN, Department of Internal Medicine (A. Masseau, JM-M, MH), and Department of Pathology (A. Moreau), CHU de Nantes, Nantes; Department 1 (OB) (French Reference Centre for Neuromuscular diseases), Department 2 (BH) (French Reference Centre for Lupus) of Internal Medicine, and Department of Pathology (P. Rouvier), CHU de la Pitié-Salpêtrière, APHP, Paris; SPHERE (bioStatistics, Pharmacoepidemiology and Human sciEnces Research) Laboratory (AB, ED)—EA 4275, LabEx Transplantex, Nantes University, Nantes; Department of Pathology (DB) and Department of Internal Medicine (EH), CHU de Lille, Lille; Department of Nephrology (P. Remy), CHU Henri Mondor, Creteil; Department of Nephrology ( RA), CH de Dunkerque; Dunkerque; Department of Nephrology (EMN), CH de Bethune, Bethune; Department of Pathology (BM) and Department of Nephrology (ML), CHU Edouard Herriot, Lyon; Department of Pathology (LD), CHU la Timone, Marseille; Department of Nephrology (AL), CHU de Bordeaux, Bordeaux; Department of Neurology (TDB), Centre Hospitalier de Saint-Denis, Saint Denis; and Department of Internal Medicine (PC), Hôpital de Sainte-Anne, Toulon; France.
                Author notes
                Reprints: Fadi Fakhouri, INSERM U643, ITUN, Université de Nantes and Nephrology Department, CHU de Nantes, Nantes, France (e-mail: fadi.fakhouri@ 123456univ-nantes.fr ).
                Article
                MD130025 00004
                10.1097/MD.0000000000000015
                4616328
                24378741
                9d707bd0-f960-4665-a86b-82229b2a000e
                Copyright © 2014 by Lippincott Williams & Wilkins
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