Systemic lupus erythematosus (SLE) is the prototypical autoimmune disease that can affect any organ of the body. Multiple mechanisms may contribute to the pathophysiology of systemic lupus, including failure to remove apoptotic bodies, hyperactivity of self-reactive B and T lymphocytes, abnormal exposure to autoantigens, and increased levels of B-cell stimulatory cytokines. The involvement of the kidney, called lupus nephritis (LN), during the course of the disease affects between 30% and 60% of adult SLE patients, and up to 70% of children. LN is an immune-mediated glomerulonephritis that is a common and serious finding in patients with SLE. Nowadays, renal biopsy is considered the gold standard for classifying LN, besides its degree of activity or chronicity. Nevertheless, renal biopsy lacks the ability to predict which patients will respond to immunosuppressive therapy and is a costly and risky procedure that is not practical in the monitoring of LN because serial repetitions would be necessary. Consequently, many serum and urinary biomarkers have been studied in SLE patients for the complementary study of LN, existing conventional biomarkers like proteinuria, protein/creatinine ratio in spot urine, 24 h urine proteinuria, creatinine clearance, among others and non-conventional biomarkers, like Monocyte chemoattractant protein-1 (MCP-1), have been correlated with the histological findings of the different types of LN. In this article, we review the advances in lupus nephritis urinary biomarkers. Such markers ideally should be capable of predicting early sub-clinical flares and could be used to follow response to therapy. In addition, some of these markers have been found to be involved in the pathogenesis of lupus nephritis.
Systemic lupus erythematosus (SLE) is an autoimmune disease with heterogeneous pathophysiologic mechanisms and diverse clinical manifestations. SLE is a frequent cause of intensive care unit (ICU) admissions. Multiple studies with controversial findings on the causes, evolution and outcomes of ICU-admitted patients with SLE have been published. The aim of this paper is to review the literature reporting the clinical characteristics and outcomes, such as mortality and associated factors, in such patients. Among the main causes of ICU admissions are SLE disease activity, respiratory failure, multi-organ failure and infections. The main factors associated with mortality are a high Acute Physiology and Chronic Health Evaluation (APACHE) score, the need for mechanical ventilation, and vasoactive and inotropic agent use. Reported mortality rates are 18.4%–78.5%. Therefore, it is important to evaluate SLE disease severity for optimizing clinical management and patient outcomes.
Polyautoimmunity (PolyA) is an emerging concept that may help to develop a better classification of autoimmune diseases (ADs). Thus, we aimed to develop new taxonomy based on PolyA. Two-hundred and fifty-four consecutive patients were included with rheumatoid arthritis (RA, n:146), systemic lupus erythematosus (SLE, n:45), Sjögrens syndrome (SS, n:29), autoimmune thyroid disease (AITD, n:17) and systemic sclerosis (SSc, n:17). Clinical features, autoantigen array chip, lymphocytes immunophenotype and cytokine profile were assessed simultaneously. The coexistence of two or more ADs with classification criteria was termed Overt PolyA, whereas the presence of autoantibodies unrelated to the index AD, without criteria fulfillment, was named Latent PolyA. Combination of IgG autoantibodies yielded high accuracy for classification of ADs. In SLE, Histone H2A, Sm/RNP, ssDNA, and dsDNA IgG autoantibodies were the most predictive autoantibodies for this condition. Laminin, Ro/SSA (52 kDa), and U1−snRNP B/B for SS; Thyroglobulin for AITD; Ribo Phosphoprotein P1, and CENP-A for SSc. Interestingly, Thyroglobulin and U1−snRNP B/B' were mutual diagnostic biomarkers in SS and SSc. Latent PolyA showed in nearly 70% of patients, whereas overt PolyA was most common in AITD (82.4%) and SLE (40%). Cluster analysis based on autoantibodies yielded three clusters of which clusters 2 and 3 exhibited high frequency of latent and overt PolyA with distinctive clinical and immunological phenotypes. Combination of autoantibodies demonstrated high performance for classification of ADs. Patients with both latent and overt PolyA cluster together and exhibit differential clinical and immunological features. High prevalence of latent and overt PolyA advocates for routinary surveillance in clinical settings.
Background/Objective Studies on the clinical characteristics, prognosis, and factors associated with mortality in patients with Sjögren syndrome (SS), particularly those in the intensive care unit (ICU), are limited. The present study aimed to describe clinical and immunological variables associated with mortality in patients with SS admitted to ICU at a single center in Cali, Colombia. Methods An observational, medical records review study was performed between 2011 and 2019 by reviewing the clinical records of patients with SS admitted to ICU at a high-complexity center. Results Seventy-two patients were included with a total of 117 ICU admissions (17 cases required readmission and 1 case required 17 readmissions): 103 (86.32%) were attributable to medical issues, and 14 corresponded to surgical admissions. Major causes of ICU medical admission were infection (44/103) followed by organ involvement. Only 5 admissions were related to SS due to neurological involvement. The APACHE (Acute Physiology, Age, and Chronic Health Evaluation) score was 10 (interquartile range [IQR], 7–16), the SOFA (Sequential Organ Failure Assessment) score was 2 (IQR, 0–14), and the EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI) score was 0 (IQR, 0–12) with higher values in the nonsurvivor group. Intensive care unit mortality was 12/72 (16.67%). Conclusions The main cause of ICU admission was infection. Patients with increased medical requirements, such as mechanical ventilation and vasopressor support, and with higher APACHE, SOFA, and ESSDAI scores were more susceptible to poor outcomes. Moreover, 50% of deaths were attributable to SS and 25% to infection.
The presentation of data on the Table 3 of the published version of the above mentioned article was incorrect. The heading BBacterial infections^should be presented under the heading BInfections^. The original article has been corrected. Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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