scholarly journals Rehabilitation in Connective Tissue Diseases

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Salem Bouomrani
Keyword(s):  
Connective Tissue ◽  
Connective Tissue Diseases

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

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.

Current Scientific Considerations in Regard to Defining a “Silicone Syndrome”/Disease and the Formation of Silica from Silicone

1998 ◽  
Vol 17 (4) ◽  
pp. 449-463 ◽  
Author(s):  
John A. Todhunter ◽  
Michael G. Farrow
Keyword(s):  
Connective Tissue ◽  
Patient Population ◽  
Breast Implant ◽  
Connective Tissue Diseases ◽  
The Body ◽  
Silicone Implants ◽  
Augmentation Mammoplasty ◽  
Patient Case ◽  
Increased Risk ◽  
Epidemiology Studies

Whether the constellation of various symptoms reported in various case-study reports on some patients who have had augmentation mammoplasty with silicone implants reflects a distinct, novel “silicone syndrome”or disease is important to settingproper endpoints for the epidemiological study of this patient population. To date, epidemiology studies on breast implant patients have focused on end-points which are typical of connective tissue disease, rheumatoid disease, and/ or autoimmune disorders. The consensus at this time, as was recently stated in a paper authored by Food and Drug Administration (FDA) personnel, is that the weight of the evidence from existing epidemiology studies is that silicone breast implants do not appreciably, if at all, increase the risk of these types of diseases. Critics of the epidemiology database have countered that had the analysis of association in these studies been done for a “silicone syndrome,” as opposed to the disease types which were analyzed, an association between silicone breast implantation and increased risk of “silicone syndrome” would have been observed. In the present analysis, this question is approached from two directions: First, the available single or multi-patient case reports available in the open literature were evaluated. The objective was to define those symptoms/ complaints that were reported in all studies or in at least 50% of the patients reported and to assign frequency distributions to individual symptoms or complaints reported in breast implant patients presenting for various complaints. By definition, if a “silicone syndrome” exists, then it can only be characterized by those symptoms or complaints which appear with regular frequency in patients so afflicted. Second, the symptoms or complaints which were used as criteria in the existing epidemiology studies were correlated with their frequency of occurrence among single or multi-patient case-reported breast implant patients. The working hypothesis in this present study is that if the number of “silicone syndrome” symptoms or complaints that also are symptoms of the existing epidemiology endpoints is large, then a distinct “silicone syndrome” is not likely to exist, and it can be concluded that existing epidemiology studies have adequately addressed the relevant issues. Also, to the extent that the frequency of symptom occurrence in “silicone syndrome” is similar to the distribution seen for known connective tissue, rheumatoid, and/ or autoimmune diseases, this will then add to the weight of evidence that no distinct “silicone syndrome” needs be postulated. Conversely, if a different set of symptoms or complaints occurs in silicone breast-implanted patients than is seen in patients with connective tissue diseases, this will argue that a distinct syndrome may exist. In the present study, the more recent suggestion that silicone may be broken down to silica in the body, and evidence for and against this suggestion are also discussed. The present analysis does not support the contention that a distinct “silicone syndrome” exists, but does support the contention that the disease endpoints used in existing epidemiology studies are adequate for examining the patient population. Also, consideration of the chemistry of silicone and its potential hydrolysis or oxidative cleavage indicates that if such reactions occur in the body at any significant rate, the product will be silicic acid, a normal and necessary constituent of the body, and not silica (i.e., silicon dioxide).

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