scholarly journals Peripheral Neuropathy in Connective Tissue Diseases

2019 ◽  
Author(s):  
Mouna Snoussi ◽  
Faten Frikha ◽  
Zouhir Bahloul
Keyword(s):  
Peripheral Neuropathy ◽  
Connective Tissue ◽  
Connective Tissue Diseases

Neuropathy of Connective Tissue Diseases and Other Systemic Diseases

2019 ◽  
Vol 39 (05) ◽  
pp. 651-668
Author(s):  
Peter H. Jin ◽  
Susan C. Shin
Keyword(s):  
Peripheral Neuropathy ◽  
Connective Tissue ◽  
Clinical Features ◽  
Connective Tissue Diseases ◽  
Chemotherapeutic Agents ◽  
Nutritional Deficiencies ◽  
Systemic Diseases ◽  
Monoclonal Gammopathies ◽  
Diagnosis And Management

AbstractPeripheral neuropathy is associated with numerous systemic diseases. It is often the heralding finding, which can lead to earlier diagnoses and better outcomes. An understanding of the epidemiology and clinical features of these diseases is paramount to their diagnosis and management. This article will focus on neuropathy associated with connective tissue diseases, monoclonal gammopathies, paraneoplastic disorders, medications including chemotherapeutic agents, nutritional deficiencies, alcohol, and toxins.

Serologic Tests for Connective Tissue Diseases and the Primary Vasculitides

1994 ◽  
Vol 12 (1) ◽  
pp. 161-173 ◽  
Author(s):  
Noranna Burridge Warner
Keyword(s):  
Connective Tissue ◽  
Connective Tissue Diseases ◽  
Serologic Tests

scholarly journals P170 The validity and utility of the SLE-key® rule-out serological test when applied in a selected cohort of patients with SLE and other connective tissue diseases

Rheumatology ◽  
2021 ◽  
Vol 60 (Supplement_1) ◽  
Author(s):  
Sheilla Achieng ◽  
John A Reynolds ◽  
Ian N Bruce ◽  
Marwan Bukhari
Keyword(s):  
Linear Regression ◽  
Connective Tissue ◽  
Connective Tissue Disease ◽  
Negative Correlation ◽  
Connective Tissue Diseases ◽  
Inflammatory Myositis ◽  
The Mean ◽  
Negative Rule ◽  
Spearman’S Correlation ◽  
Rule Out

Abstract Background/Aims  We aimed to establish the validity of the SLE-key® rule-out test and analyse its utility in distinguishing systemic lupus erythematosus (SLE) from other autoimmune rheumatic connective tissue diseases. Methods  We used data from the Lupus Extended Autoimmune Phenotype (LEAP) study, which included a representative cross-sectional sample of patients with a variety of rheumatic connective tissue diseases, including SLE, mixed connective tissue disease (MCTD), inflammatory myositis, systemic sclerosis, primary Sjögren’s syndrome and undifferentiated connective tissue disease (UCTD). The modified 1997 ACR criteria were used to classify patients with SLE. Banked serum samples were sent to Immune-Array’s CLIA- certified laboratory Veracis (Richmond, VA) for testing. Patients were assigned test scores between 0 and 1 where a score of 0 was considered a negative rule-out test (i.e. SLE cannot be excluded) whilst a score of 1 was assigned for a positive rule-out test (i.e. SLE excluded). Performance measures were used to assess the test’s validity and measures of association determined using linear regression and Spearman’s correlation. Results  Our study included a total of 155 patients of whom 66 had SLE. The mean age in the SLE group was 44.2 years (SD 13.04). 146 patients (94.1%) were female. 84 (54.2%) patients from the entire cohort had ACR SLE scores of ≤ 3 whilst 71 (45.8%) had ACR SLE scores ≥ 4. The mean ACR SLE total score for the SLE patients was 4.85 (SD 1.67), ranging from 2 to 8, with mean disease duration of 12.9 years. The Sensitivity of the SLE-Key® Rule-Out test in diagnosing SLE from other connective tissue diseases was 54.5%, specificity was 44.9%, PPV 42.4% and NPV 57.1 %. 45% of the SLE patients had a positive rule-out test. SLE could not be ruled out in 73% of the MCTD patients whilst 51% of the UCTD patients had a positive Rule-Out test and >85% of the inflammatory myositis patients had a negative rule-out test. ROC analysis generated an AUC of 0.525 illustrating weak class separation capacity. Linear regression established a negative correlation between the SLE-key Rule-Out score and ACR SLE total scores. Spearman’s correlation was run to determine the relationship between ACR SLE total scores and SLE-key rule-out score and showed very weak negative correlation (rs = -0.0815, n = 155, p = 0.313). Conclusion  Our findings demonstrate that when applied in clinical practice in a rheumatology CTD clinic setting, the SLE-key® rule-out test does not accurately distinguish SLE from other CTDs. The development of a robust test that could achieve this would be pivotal. It is however important to highlight that the test was designed to distinguish healthy subjects from SLE patients and not for the purpose of differentiating SLE from other connective tissue diseases. Disclosure  S. Achieng: None. J.A. Reynolds: None. I.N. Bruce: Other; I.N.B is a National Institute for Health Research (NIHR) Senior Investigator and is funded by the NIHR Manchester Biomedical Research Centre. M. Bukhari: None.

scholarly journals AB0605 CLINICAL PROFILE AND CHEST HIGH-RESOLUTION COMPUTED TOMOGRAPHY (HRCT) FINDINGS IN PATIENTS WITH CONNECTIVE TISSUE DISEASES AND INTERSTITIAL LUNG DISEASE: EXPERIENCE OF A SINGLE REFERENCE RHEUMATOLOGY CENTER

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1598.2-1599
Author(s):  
I. Rusu ◽  
L. Muntean ◽  
M. M. Tamas ◽  
I. Felea ◽  
L. Damian ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Systemic Sclerosis ◽  
High Resolution ◽  
Interstitial Lung Disease ◽  
Connective Tissue ◽  
Lung Disease ◽  
Interstitial Pneumonia ◽  
Connective Tissue Diseases ◽  
High Resolution Computed Tomography ◽  
Hrct Patterns

Background:Interstitial lung disease (ILD) is a common manifestation of connective tissue diseases (CTDs), and is associated with significant morbidity and mortality. Chest high-resolution computed tomography (HRCT) play an important role in the diagnosis of ILD and may provide prognostic information.Objectives:We aimed to characterize the clinical profile and chest HRCT abnormalities and patterns of patients diagnosed with CTDs and ILD.Methods:In this retrospective, observational study we included 80 consecutive patients with CTDs and ILD referred to a tertiary rheumatology center between 2015 and 2019. From hospital charts we collected clinical data, immunologic profile, chest HRCT findings. HRCT patterns were defined according to new international recommendations.Results:Out of 80 patients, 64 (80%) were women, with a mean age of 55 years old. The most common CTD associated with ILD was systemic sclerosis (38.8%), followed by polymyositis (22.5%) and rheumatoid arthritis (18.8%). The majority of patients had dyspnea on exertion (71.3%), bibasilar inspiratory crackles were present in 56.3% patients and 10% had clubbing fingers. Antinuclear antibodies (ANA) were present in 78.8% patients, and the most frequently detected autoantibodies against extractable nuclear antigen were anti-Scl 70 (28.8%), followed by anti-SSA (anti-Ro, 17.5%), anti-Ro52 (11.3%) and anti-Jo (7.5%). Intravenous cyclophosphamide therapy for 6-12 months was used in 35% of patients, while 5% of patients were treated with mycophenolate mofetil.The most frequent HRCT abnormalities were reticular abnormalities and ground glass opacity. Non-specific interstitial pneumonia (NSIP) was identified in 46.3% CTDs patients. A pattern suggestive of usual interstitial pneumonia (UIP) was present in 32.5% patients, mainly in patients with systemic sclerosis. In 21.3% patients the HRCT showed reticulo-nodular pattern, micronodules and other abnormalities, not diagnostic for UIP or NSIP pattern.Conclusion:Nonspecific interstitial pneumonia (NSIP) is the most common HRCT pattern associated with CTDs. Further prospective longitudinal studies are needed in order to determine the clinical and prognostic significance of various HRCT patterns encountered in CTD-associated ILD and for better patient management.References:[1]Ohno Y, Koyama H, Yoshikaua T, Seki S. State-of-the-Art Imaging of the Lung for Connective Tissue Disease (CTD). Curr Rheumatol Rep. 2015;17(12):69.[2]Walsh SLF, Devaraj A, Enghelmeyer JI, Kishi K, Silva RS, Patel N, et al. Role of imaging in progressive-fibrosing interstitial lung diseases. Eur Respir Rev. 2018;27(150)Disclosure of Interests:None declared

Nailfold videocapillaroscopic changes in patients with pulmonary arterial hypertension associated with connective tissue diseases

2021 ◽  
Author(s):  
Alexandra Arvanitaki ◽  
George Giannakoulas ◽  
Eva Triantafyllidou ◽  
Eleni Pagkopoulou ◽  
Afroditi Boutou ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Connective Tissue ◽  
Arterial Hypertension ◽  
Connective Tissue Diseases ◽  
Pulmonary Arterial

scholarly journals A hierarchical bivariate meta-analysis of diagnostic test accuracy to provide direct comparisons of immunoassays vs. indirect immunofluorescence for initial screening of connective tissue diseases

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Michelle Elaine Orme ◽  
Carmen Andalucia ◽  
Sigrid Sjölander ◽  
Xavier Bossuyt
Keyword(s):  
Connective Tissue ◽  
Indirect Immunofluorescence ◽  
Meta Analysis ◽  
Connective Tissue Diseases ◽  
Test Accuracy ◽  
Initial Screening ◽  
Case Control Studies ◽  
Cross Sectional ◽  
Mixed Effect ◽  
Mixed Effect Models

AbstractObjectivesTo compare indirect immunofluorescence (IIF) for antinuclear antibodies (ANA) against immunoassays (IAs) as an initial screening test for connective tissue diseases (CTDs).MethodsA systematic literature review identified cross-sectional or case-control studies reporting test accuracy data for IIF and enzyme-linked immunosorbent assays (ELISA), fluorescence enzyme immunoassay (FEIA), chemiluminescent immunoassay (CLIA) or multiplex immunoassay (MIA). The meta-analysis used hierarchical, bivariate, mixed-effect models with random-effects by test.ResultsDirect comparisons of IIF with ELISA showed that both tests had good sensitivity (five studies, 2321 patients: ELISA: 90.3% [95% confidence interval (CI): 80.5%, 95.5%] vs. IIF at a cut-off of 1:80: 86.8% [95% CI: 81.8%, 90.6%]; p = 0.4) but low specificity, with considerable variance across assays (ELISA: 56.9% [95% CI: 40.9%, 71.5%] vs. IIF 1:80: 68.0% [95% CI: 39.5%, 87.4%]; p = 0.5). FEIA sensitivity was lower than IIF sensitivity (1:80: p = 0.005; 1:160: p = 0.051); however, FEIA specificity was higher (seven studies, n = 12,311, FEIA 93.6% [95% CI: 89.9%, 96.0%] vs. IIF 1:80 72.4% [95% CI: 62.2%, 80.7%]; p < 0.001; seven studies, n = 3251, FEIA 93.5% [95% CI: 91.1%, 95.3%] vs. IIF 1:160 81.1% [95% CI: 73.4%, 86.9%]; p < 0.0001). CLIA sensitivity was similar to IIF (1:80) with higher specificity (four studies, n = 1981: sensitivity 85.9% [95% CI: 64.7%, 95.3%]; p = 0.86; specificity 86.1% [95% CI: 78.3%, 91.4%]). More data are needed to make firm inferences for CLIA vs. IIF given the wide prediction region. There were too few studies for the meta-analysis of MIA vs. IIF (MIA sensitivity range 73.7%–86%; specificity 53%–91%).ConclusionsFEIA and CLIA have good specificity compared to IIF. A positive FEIA or CLIA test is useful to support the diagnosis of a CTD. A negative IIF test is useful to exclude a CTD.

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