Deep Learning Algorithm of the SPARCC Scoring System in SI Joint MRI.

BACKGROUND: The Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system is a sacroiliitis grading system. PURPOSE: To develop a deep learning-based pipeline for grading sacroiliitis using the SPARCC scoring system. STUDY TYPE: Prospective. POPULATION: The study included 389 participants (42.2-year-old, 44.6% female, 317/35/37 for training/validation/testing). A pretrained algorithm was used to differentiate image with/without sacroiliitis. FIELD STRENGTH/SEQUENCE: 3-T, short tau inversion recovery (STIR) sequence, fast spine echo. ASSESSMENT: The regions of interest as ground truth for models' training were identified by a rheumatologist (HYC, 10-year-experience) and a radiologist (KHL, 6-year-experience) using the Assessment of Spondyloarthritis International Society definition of MRI sacroiliitis independently. Another radiologist (YYL, 4.5-year-experience) solved the discrepancies. The bone marrow edema (BME) and sacroiliac region models were for segmentation. Frangi-filter detected vessels used as intense reference. Deep learning pipeline scored using SPARCC scoring system evaluating presence and features of BMEs. A rheumatologist (SCWC, 6-year-experience) and a radiologist (VWHL, 14-year-experience) scored using the SPARCC scoring system once. The radiologist (YYL) scored twice with 5-day interval. STATISTICAL TESTS: Independent samples t-tests and Chi-squared tests were used. Interobserver and intraobserver reliability by intraclass correlation coefficient (ICC) and Pearson coefficient evaluated consistency between readers and the deep learning pipeline. We evaluated the performance using sensitivity, accuracy, positive predictive value, and Dice coefficient. A P-value <0.05 was considered statistically significant. RESULTS: The ICC and the Pearson coefficient between the SPARCC scores from three readers and the deep learning pipeline were 0.83 and 0.86, respectively. The sensitivity in identifying BME and accuracy of identifying SI joints and blood vessels was 0.83, 0.90, and 0.88, respectively. The dice coefficients were 0.82 (sacrum) and 0.80 (ilium). DATA CONCLUSION: The high consistency with human readers indicated that deep learning pipeline may provide a SPARCC-informed deep learning approach for scoring of STIR images in spondyloarthritis. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

A deep neural network for MRI spinal inflammation in axial spondyloarthritis.

OBJECTIVE: To develop a deep neural network for the detection of inflammatory spine in short tau inversion recovery (STIR) sequence of magnetic resonance imaging (MRI) on patients with axial spondyloarthritis (axSpA). METHODS: A total 330 patients with axSpA were recruited. STIR MRI of the whole spine and clinical data were obtained. Regions of interests (ROIs) were drawn outlining the active inflammatory lesion consisting of bone marrow edema (BME). Spinal inflammation was defined by the presence of an active inflammatory lesion on the STIR sequence. The 'fake-color' images were constructed. Images from 270 and 60 patients were randomly separated into the training/validation and testing sets, respectively. Deep neural network was developed using attention UNet. The neural network performance was compared to the image interpretation by a radiologist blinded to the ground truth. RESULTS: Active inflammatory lesions were identified in 2891 MR images and were absent in 14,590 MR images. The sensitivity and specificity of the derived deep neural network were 0.80 ± 0.03 and 0.88 ± 0.02, respectively. The Dice coefficient of the true positive lesions was 0.55 ± 0.02. The area under the curve of the receiver operating characteristic (AUC-ROC) curve of the deep neural network was 0.87 ± 0.02. The performance of the developed deep neural network was comparable to the interpretation of a radiologist with similar sensitivity and specificity. CONCLUSION: The developed deep neural network showed similar sensitivity and specificity to a radiologist with four years of experience. The results indicated that the network can provide a reliable and straightforward way of interpreting spinal MRI. The use of this deep neural network has the potential to expand the use of spinal MRI in managing axSpA.

MRI for axial SpA: Diagnosis, disease activity assessment, and recent advances.

Magnetic resonance imaging (MRI) is a sensitive imaging modality to detect early inflammatory changes in axial spondyloarthritis (SpA). Over a decade has passed since the inclusion of MRI assessment in the 2009 Assessment of SpondyloArthritis International Society (ASAS) classification criteria for axial SpA. Evidence and clinical experience of MRI in axial SpA have accumulated rapidly since. This has led to a better understanding of the clinical utility of MRI in early diagnosis, disease activity assessment, and monitoring of treatment response in axial SpA. Furthermore, technological advancements have paved the way for the development of novel MRI sequences for the quantification of inflammation and image optimization. The field of artificial intelligence has also been explored to aid medical imaging interpretation, including MRI in axial SpA. This review serves to provide an update on the latest understanding of the evolving roles of MRI in axial SpA.

MRI lesions in SpA: a comparison with noninflammatory back pain using propensity score adjustment method.

Background: Magnetic resonance imaging (MRI) is important in the management of axial spondyloarthritis (SpA). However, many MRI lesions are not exclusive to axial SpA. Further characterization of these lesions may lead to better clinical decisions. Objective: The objective of this study was to compare the frequency of individual spinal MRI lesions between axial SpA and noninflammatory back pain. The factors associated with individual lesions in participants with axial SpA were also determined. Design: This was a cross-sectional observational study. Methods: MRI lesions in 447 participants with axial SpA and 122 participants with noninflammatory back pain were compared using the propensity score adjustment method. Individual lesions included discovertebral lesions (DVL), Modic type 1 lesions, DVL without Modic type 1 lesions, facet joint lesions, costovertebral joint lesions, corner inflammatory lesions (CIL), and fatty corner lesions (FCL). The factors associated with the lesions were determined using regression analyses. Results: Among participants with axial SpA, 81.9% were HLA-B27-positive, 55.0% had radiographic axial SpA, and 60.5% had radiographic features of spinal damage (mSASSS >2). Almost half (48.6% in axial SpA versus 31.1% in noninflammatory back pain) had inflammatory lesions on spinal MRI. In propensity score matching with noninflammatory back pain, axial SpA had an increased occurrence of DVL without Modic type 1 lesion (OR = 3.43, p = 0.01), costovertebral lesion (OR = 11.89, p = 0.02), number of CIL (B = 1.19, p < 0.001), and number of FCL (B = 3.33, p < 0.001). Similar associations were found in the regression models in the radiographic axial SpA subgroup: DVL without Modic type 1 lesion (OR = 2.46, p = 0.001), costovertebral lesion (OR = 3.86, p < 0.001), number of CIL (B = 1.13, p < 0.001), and FCL (B = 2.29, p < 0.01). Conclusion: MRI lesions including DVL without Modic type 1, costovertebral joint lesions, CIL, and FCL were more specific in axial SpA.

Clinical, radiological, and magnetic resonance imaging characteristics of axial spondyloarthritis with late onset.

We aimed to investigate the clinical, diagnostic, and imaging features of patients with late onset axial spondyloarthritis (SpA) with initial symptom manifestation aged over 45 years. Participants with axial SpA were consecutively recruited. Clinical, demographic, blood, and imaging parameters were compared between the groups with early (≤45 years) and late onset (>45 years) at a cross-sectional level. Logistic regressions were used to determine the independent associations with axial SpA with late onset. A total of 455 participants were recruited. Among them, 70 (15.4%) had late onset disease. Multivariate analyses showed that axial SpA with late onset was associated with higher C-reactive protein based ankylosing spondylitis disease activity index (ASDAS-CRP) (B = 0.10; P = .04), higher intensity of spinal inflammation as measured by maximum apparent diffusion coefficient (spinal ADC max) (B = 0.27; P = .03) and mean ADC (spinal ADC mean) (B = 0.30; P = .004), lower modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) (B = -0.12; P = .02), more tender joint count (B = 0.12; P = .02), and fewer inflammatory back pain (IBP) (OR = 0.26; P < .001). Axial SpA with late onset had higher clinical disease activity, higher intensity of spinal MRI inflammation, less radiographic damage, and more tender joint count. There was also less inflammatory back pain, which could make the diagnosis more difficult.

Risk of nonpulmonary infections requiring hospitalization in spondyloarthritis.

OBJECTIVES: To compare the risk of five nonpulmonary infections leading to hospitalization between spondyloarthritis (SpA) and nonspecific back pain (NSBP), and to identify the risk factors. METHODS: A total of 3018 patients with SpA and 2527 patients with NSBP were identified. Data from December 1995 to June 2019 was retrieved from a centralized electronic medical record system. The date of onset of five types of nonpulmonary infections including: urinary tract infection (UTI), skin infection, gastroenteritis (GE), septic arthritis, and pancreato-hepatobiliary tract infection were identified. Demographic data, comorbidities, and medications used were also retrieved. Comparative risk of each type of infection between SpA and NSBP was determined using propensity score adjustment method. Cox regression model was used to identified risk factors. RESULTS: Patients with SpA were younger in age, predominantly male, with fewer comorbid diabetes mellitus (DM), renal impairment, and depression. Compared with NSBP, patients with SpA had higher risk of UTI (hazard ratio [HR] 1.91; p < .001), skin infection (HR 1.79; p < .001), and septic arthritis (HR 4.57; p = .04). Risk of GE (HR 1.42; p = 1.00), and pancreato-hepatobiliary tract infection (HR 1.67; p = .06) were not increased. Infliximab was an independent risk factor for UTI (HR 2.21; p = .04). Duration of steroid therapy >6 months (HR 2.22; p < .001), smoker (HR 1.81; p < .001), and psoriasis (HR 2.47; p < .001) were risk factors for skin infection. CONCLUSION: SpA was associated with increased risk of UTI, skin infection, and septic arthritis. Infliximab, prolonged steroid therapy, smoking, and psoriasis were associated risk factors.

Deep learning algorithms for magnetic resonance imaging of inflammatory sacroiliitis in axial spondyloarthritis.

OBJECTIVE: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI. METHODS: A total of 326 participants with axial SpA, and 63 participants with non-specific back pain (NSBP) were recruited. STIR MRI of the SI joints was performed and clinical data were collected. Region of interests (ROIs) were drawn outlining bone marrow oedema, a reliable marker of active inflammation, which formed the ground truth masks from which 'fake-colour' images were derived. Both the original and fake-colour images were randomly allocated into either the training and validation dataset or the testing dataset. Attention U-net was used for the development of deep learning algorithms. As a comparison, an independent radiologist and rheumatologist, blinded to the ground truth masks, were tasked with identifying bone marrow oedema in the MRI scans. RESULTS: Inflammatory sacroiliitis was identified in 1398 MR images from 228 participants. No inflammation was found in 3944 MRI scans from 161 participants. The mean sensitivity of the algorithms derived from the original dataset and fake-colour image dataset were 0.86 (0.02) and 0.90 (0.01), respectively. The mean specificity of the algorithms derived from the original and the fake-colour image datasets were 0.92 (0.02) and 0.93 (0.01), respectively. The mean testing dice coefficients were 0.48 (0.27) for the original dataset and 0.51 (0.25) for the fake-colour image dataset. The area under the curve of the receiver operating characteristic (AUC-ROC) curve of the algorithms using the original dataset and the fake-colour image dataset were 0.92 and 0.96, respectively. The sensitivity and specificity of the algorithms were comparable with the interpretation by a radiologist, but outperformed that of the rheumatologist. CONCLUSION: An MRI deep learning algorithm was developed for detection of inflammatory sacroiliitis in axial SpA.

Both ASDAS and ADC are associated with spinal mobility in active axial spondyloarthritis: A comparison between early and later disease.

OBJECTIVE: Using diffusion-weighted imaging (DWI)-derived apparent diffusion coefficient (ADC), we aimed to determine the relationship between intensity of spinal inflammation and mobility in patients with axial spondyloarthritis (SpA) in early and later stages of active disease. The Ankylosing Spondylitis Disease Activity Score (ASDAS) was also used for a more comprehensive evaluation. METHODS: Participants with axial SpA and back pain were recruited from 10 rheumatology centers. Clinical, biochemical and radiological parameters were collected. Short tau inversion recovery (STIR) sequence magnetic resonance imaging (MRI) and DWI of the spine and sacroiliac (SI) joints were performed. ADC maps were generated. Participants were examined for Bath Ankylosing Spondylitis Metrology Index (BASMI). Linear regression models were used to determine associations between BASMI and various clinical, radiological, and MRI parameters in participants with active inflammation on spinal ADC maps. RESULTS: One-hundred and twenty-seven participants were included in the analyses. Multivariate linear regression showed that mean ADC spine (ß = .16; P = .03), ASDAS-C-reactive protein (CRP) (ß = .29, P < .001), and ASDAS-erythrocyte sedimentation rate (ESR) (ß = .25, P < .01) were associated with BASMI. In participants with duration of back pain ≤3 years, mean spine ADC (ß = .37; P = .03), ASDAS-CRP (ß = .44; P = .01), and ASDAS-ESR (ß = .42; P = .01) were associated with BASMI after adjustment for confounding factors. In participants with duration of back pain >3 years, only ASDAS-CRP (ß = .25; P < .01) and ASDAS-ESR (ß = .20; P = .20) were associated with BASMI. CONCLUSION: Intensity of inflammation and clinical disease activity were independently associated with impairment of spinal mobility. The associations were stronger in early (≤3 years) than later disease.

Conventional and Biologic Disease-Modifying Antirheumatic Drugs Are Not Associated With Increase in or Progression of Cervical Neoplasia Among Patients With Spondyloarthritis.

OBJECTIVES: Using a centralized electronic database, we investigated the risk of cervical neoplasia (CN) and progression of cervical intraepithelial neoplasia (CIN) among patients with spondyloarthritis (SpA) receiving disease-modifying antirheumatic drugs (DMARDs). METHOD: A total of 951 patients with SpA were reviewed. Incidence and progression of CN and clinical data including age, ethnicity, smoking and drinking status, dates of first and last follow-up, history of psoriasis, inflammatory bowel disease, medications used, mean dose and duration of medications, and comorbidities were reviewed. Cox regression models were used to evaluate the individual risk of DMARDs with CN and the risk of CIN progression. RESULTS: During a mean follow-up duration of 9.2 ± 5.9 years, 34 patients had developed CN, which translates to an incidence for development of CN in patients with SpA of 3.9 per 1000 patient-years. Univariate Cox regression analyses showed no differences in clinical characteristics (psoriasis hazards ratio [HR] = 0.92, p = 0.82; inflammatory bowel disease HR = 0.05, p = 0.61; diabetes mellitus HR = 2.82, p = 0.21; chronic kidney disease HR = 0.39, p = 0.35) and medications exposure (sulfasalazine HR = 0.49, p = 0.30; methotrexate HR = 0.52, p = 0.11; leflunomide HR = 0.52, p = 0.37; adalimumab HR = 0.83, p = 0.80; certolizumab HR = 0.05, p = 0.74; etanercept HR = 0.40, p = 0.36; golimumab HR = 0.05, p = 0.32; infliximab HR = 0.05, p = 0.39; secukinumab HR = 1.00, p = 1.00; ustekinumab HR = 0.05, p = 0.78) between patients who had and had not develop CN during the study period. Progression of CIN was independently associated with higher grades of CIN lesion (HR = 6.20; p = 0.05). CONCLUSIONS: There was low risk of development and progression of CN in patients with SpA on conventional or biologic DMARD therapy.

Malignancies in spondyloarthritis with and without concomitant psoriasis, and the effect of disease modifying anti-rheumatic drugs.

OBJECTIVES: To determine the risk of 6 types of malignancies in spondyloarthritis (SpA) with and without psoriasis (PsO) and on disease-modifying anti-rheumatic drugs (DMARDs), compared to non-specific back pain (NSBP). METHODS: Medical records were retrieved. Patients with SpA with and without PsO were identified and compared to those with NSBP. Clinical data; follow-up duration; comorbidities; dates and types of cancer diagnosed; types and duration of DMARD therapy were collected. Propensity score adjustment was used to compare the risks of malignancies between SpA, SpA with and without PsO, and NSBP. Cox regression analysis was used to determine the risk of malignancy in DMARD therapy. RESULTS: A total of 3020 patients with SpA and 2527 patients with NSBP were studied. The mean follow-up duration in patients with SpA and NSBP was 9.6 years and 13.5 years respectively. Incidence and risk of malignancies were compatible between SpA and NSBP. The incidences of various carcinomas (per 1000 patient-years) in SpA were: 1.37 for colorectal carcinoma; 0.30 for carcinoma of pancreas; 0.30 for carcinoma of stomach; and 0.91 for lymphomas. Risk of colorectal carcinoma (HR 2.46; p=0.03) and lymphomas (HR 2.86; p=0.04) was increased in SpA with concomitant PsO. DMARD therapy was not associated with increased risks of malignancies after adjustment for confounding factors. CONCLUSIONS: Risk of malignancy was increased in SpA with PsO but not in other subtypes of SpA or DMARD therapy.

Epidemiology, mortality and effectiveness of prophylaxis for Pneumocystis jiroveci pneumonia among rheumatic patients: a territory-wide study.

BACKGROUND: Pneumocystis jiroveci pneumonia (PJP) is an opportunistic infection affecting immunocompromised individuals. However, evidence regarding the burden and effectiveness of prophylaxis among rheumatic patients remains limited. Delineating the epidemiology and efficacy of prophylaxis among rheumatic patients is urgently needed. METHODS: We performed a territory-wide cohort study of rheumatic patients in Hong Kong. All patients with a diagnosis of anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV), immune-mediated myositis (IMM), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), or spondyloarthritis (SpA) between 2015 and 2019 were included. Prevalence, frequency of prophylaxis and mortality of PJP were calculated. Number needed to treat (NNT) analysis was also performed. RESULTS: Out of 21,587 patients (54% RA, 25% SLE, 13% SpA, 5% IMM, 2% AAV and 1% SSc), 1141 (5.3%) patients were prescribed PJP prophylaxis. 48/21,587 (0.2%) developed PJP. No patients who developed PJP received prophylaxis prior to infection. The incidence of PJP was highest among SSc, AAV, and IMM patients. Among these diseases, the majority of PJP occurred while patients were on glucocorticoids at daily prednisolone-equivalent doses of 15 mg/day (P15) or above. PJP prophylaxis was effective with NNT for SSc, AAV and IIM being 36, 48 and 114 respectively. There were 19 PJP-related mortalities and the mortality rate was 39.6%. CONCLUSION: PJP is an uncommon but important infection among rheumatic patients, PJP prophylaxis is effective and should be considered in patients with SSc, AAV and IMM, especially those receiving glucocorticoid doses above P15.

Cardiovascular risk in patients with spondyloarthritis and association with anti-TNF drugs.

BACKGROUND: Cardiovascular (CVS) diseases are the leading cause of death worldwide and patients with rheumatic diseases have an increased CVS. CVS risk factors and CVS events are common in spondyloarthritis (SpA). Delineating the CVS risk in patients with SpA and identifying modifiable risk factors would be useful. METHODS: Patients with SpA and patients with non-specific back pain (NSBP) were identified in rheumatology and orthopedics clinics, respectively. Clinical information and CVS events were retrieved. Baseline characteristics and incidence rates of CVS events were compared between two groups of patients using an age- and sex-matched cohort. Propensity score adjustment and Cox regression analysis were performed to determine the CVS risk associated with SpA. RESULTS: A total of 5046 patients (SpA 2616 and NSBP 2430) were included from eight centers. Over 56,484 person-years of follow up, 160 strokes, 84 myocardial infarction (MI) and 262 major adverse cardiovascular events (MACE) were identified. Hypercholesterolemia was more prevalent in SpA (SpA 34.2%, NSBP 28.7%, p < 0.01). Crude incidence rates of MACE and stroke were higher in SpA patients. SpA was associated with a higher risk of MACE [hazard ratio (HR) 1.70; 95% confidence interval (CI) 1.29-2.26; p < 0.01] and cerebrovascular events (HR 1.50; 95% CI 1.08-2.07; p = 0.02). SpA patients with anti-TNF use had a reduced risk of MACE (HR 0.37, 95%CI 0.17-0.80, p = 0.01) and cerebrovascular events (HR 0.21, 95%CI 0.06-0.78, p = 0.02) compared with SpA patients without anti-TNF use. CONCLUSION: SpA is an independent CVS risk factor. Anti-tumor necrosis factor (TNF) drugs were associated with a reduced CVS risk in these patients.

Systemic Lupus Erythematosus and Immunodeficiency.

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease caused by a combination of genetic, epigenetic, and environmental factors. Recent advances in genetic analysis coupled with better understanding of different immune regulatory and signaling pathways have revealed the complex relationship between autoimmunity, including SLE, and immunodeficiency. Furthermore, the expanding therapeutic armamentarium has led to the increasing awareness of secondary immunodeficiency in these patients. This article serves to update the current understanding of SLE and immunodeficiency by discussing the shared genetic factors and immunobiology. We also summarize the effects of immunosuppressive therapies with a focus on secondary antibody deficiency (SAD) after B-cell targeted therapies.

Risk of tuberculosis in patients with spondyloarthritis: data from a centralized electronic database in Hong Kong.

BACKGROUND/ OBJECTIVE: Tuberculosis (TB) is one of the most infectious comorbidities in spondyloarthritis (SpA). Our goals were to determine the crude incidence rate of and risk factors for TB in SpA. METHOD: Clinical data of 2984 patients with SpA from 11 rheumatology centres were reviewed. This included demographics, duration of follow-up, comorbidities including diabetes, chronic kidney disease, chronic heart disease, chronic lung disease, stroke and malignancies, date of diagnosis of tuberculosis, use of non-steroidal anti-inflammatory drugs, duration of glucocorticoid therapy for more than 6 months, conventional (cDMARD) and biological (bDMARD) disease modifying anti-rheumatic drug therapies. Crude incidence rates were reported. Cox regression models were used to determine the risk factors for TB in patients with SpA. RESULTS: Forty-three patients had TB, of which 4 (9.3%) were extra-pulmonary. The crude incidence rate of TB was 1.57 in patients with SpA, compared with 0.58 in the general population in Hong Kong. Independent risk factors identified from the multivariate Cox regression model were: alcohol use (HR 2.62; p = 0.03), previous TB (HR 13.62; p < 0.001), chronic lung disease (HR 3.39; p = 0.004), duration of glucocorticoid therapy greater than 6 months (HR 3.25; p = 0.01) and infliximab therapy (HR 5.06; p < 0.001). Age was associated with decreased risk (HR 0.93; p < 0.001). CONCLUSION: Incidence of TB was higher in patients with SpA. Glucocorticoid therapy beyond 6 months and infliximab therapy increased the risk of TB. Rheumatologists should avoid prolonged use of glucocorticoids and consider DMARDs other than infliximab in the treatment of at-risk patients.

Diagnostic utility of whole spine and thoracic spine MRI corner inflammatory lesions in axial spondyloarthritis.

BACKGROUND: The presence of ⩾3 corner inflammatory lesions has been proposed as the definition of a positive spinal magnetic resonance imaging (MRI) for axial spondyloarthritis (axSpA), but subsequent studies showed inconclusive findings. Our objective was to evaluate whether locations of corner inflammatory lesions (CILs) would affect the diagnostic utility of MRI in axSpA. METHOD: Two groups were consecutively recruited from eight rheumatology centers in Hong Kong. The 'axSpA' group included 369 participants with a known diagnosis of axSpA. The 'non-specific back pain' (NSBP) control group consisted of 117 participants. Clinical, biochemical, and radiological parameters were collected and all patients underwent MRI of the spine and sacroiliac joints. CILs were assessed based on their locations (cervical, thoracic or lumbar) to determine the optimal cutoff for diagnosis. RESULTS: The cutoff of ⩾5 whole spine CILs (W-CILs) and ⩾3 thoracic spine CILs (T-CILs) had comparable specificity to MRI sacroiliitis. Of 85/369 axSpA patients without sacroiliitis on conventional radiograph or MRI, 7 had ⩾5 W-CILs and 11 had ⩾3 T-CILs. Incorporating the proposed cutoffs into Assessment of SpondyloArthritis international Society axSpA criteria, ⩾5 W-CILs and ⩾3 T-CILs had similar performance when added to the imaging criteria for sacroiliitis (sensitivity 0.79 versus 0.80, specificity 0.92 versus 0.91). CONCLUSION: Spinal MRI provided little incremental diagnostic value in unselected axSpA patients. However, in patients without sacroiliitis on MRI or radiographs, 8-13% might be diagnosed by spinal MRI. Thoracic and whole spine MRI had similar diagnostic performance using the proposed cutoff of ⩾5 W-CILs and ⩾3 T-CILs.

Prevalence and Impact of Reported Drug Allergies among Rheumatology Patients.

BACKGROUND: Drug allergies (DA) are immunologically mediated adverse drug reactions and their manifestations depend on a variety of drug- and patient-specific factors. The dysregulated immune system underpinning rheumatological diseases may also lead to an increase in hypersensitivity reactions, including DA. The higher prevalence of reported DA, especially anti-microbials, also restricts the medication repertoire for these already immunocompromised patients. However, few studies have examined the prevalence and impact of reported DA in this group of patients. METHODS: Patients with a diagnosis of rheumatoid arthritis (RA), spondyloarthritis (SpA), or systemic lupus erythematosus (SLE) were recruited from the rheumatology clinics in a tertiary referral hospital between 2018 and 2019. Prevalence and clinical outcomes of reported DA among different rheumatological diseases were calculated and compared to a cohort of hospitalized non-rheumatology patients within the same period. RESULTS: A total of 6081 patients (2541 rheumatology patients: 1286 RA, 759 SpA, and 496 SLE; and 3540 controls) were included. DA was more frequently reported among rheumatology patients compared to controls (23.8% vs. 13.8%, p < 0.01). Antibiotics and non-steroidal anti-inflammatory drugs (NSAIDs) were the two most commonly reported categories of DA with a prevalence of 12.0% and 5.1%, respectively. Reported antibiotics allergies were more frequent in patients with RA (OR = 1.20, 95% CI = 1.02-1.62, p = 0.03) and SLE (OR = 4.69, 95% CI = 3.69-5.95, p < 0.01); and associated with increased infection-related admissions among rheumatology patients (OR = 1.79, 95% CI = 1.09-2.95, p = 0.02). Among the subgroup of patients referred for allergy testing, 85.7% of beta-lactam antibiotic allergy labels were found to be inaccurate and de-labelled after negative drug provocation testing. CONCLUSION: The prevalence of reported DA was significantly higher in rheumatology patients. Reported antibiotic allergy was associated with increased rate of infection-related admissions. However, the rate of genuine antibiotic allergy was low. Further studies are needed to guide proper assessment of reported DA and impact of comprehensive allergy testing in this group of patients.

Risk of community-acquired pneumonia requiring hospitalization in patients with spondyloarthritis.

AIMS: To compare the risk of community-acquired pneumonia (CAP) requiring hospitalization in spondyloarthritis (SpA) and non-specific back pain (NSBP), and to identify the risk factors for CAP in SpA. METHODS: A total of 2984 patients with SpA from 11 rheumatology centers and 2526 patients with NSBP from orthopedic units were reviewed from the centralized electronic database in Hong Kong. Incidence of CAP requiring hospitalization and demographic data including age, gender, smoking and drinking status, use of sulfasalazine, individual biological-disease modifying anti-rheumatic drugs (DMARDs) used, micro-organisms, other immunosuppressants or immunosuppressive states, use of steroid for more than ½ year, and co-morbidities were identified. Risks of CAP in SpA were compared with those in NSBP using propensity score regression method. Multivariate Cox regression model was used to identify the risk factors in SpA. RESULTS: CAP requiring hospitalization was found in 183 patients with SpA and 138 patients with NSBP. Increased risk for CAP was found in the following groups with SpA: all subgroups (hazard ratio (HR) 2.14, p < 0.001), without use of DMARDs (HR 2.64, p < 0.001), without psoriasis and not taking DMARDs (HR 2.38, p < 0.001). Infliximab (HR2.55, p = 0.04), smoking (HR 1.68, p = 0.003), comorbid psoriasis (HR 1.67, p = 0.003), and use of steroid for more than ½ year (HR 1.94, p = 0.003) were found to associate with CAP after adjustments for traditional risk factors. CONCLUSION: Risk of CAP is increased in patients with SpA. Our data favor universal influenza and pneumococcal vaccination programs in the population. Rheumatologists should also advise smoking cessation and avoid long term steroid therapy.

Intensity of spinal inflammation is associated with radiological structural damage in patients with active axial spondyloarthritis.

OBJECTIVE: The aim was to investigate the relationship between the intensity of spinal inflammation using the apparent diffusion coefficient (ADC) and radiographic progression in axial SpA. METHODS: This is a cross-sectional study of participants with axial SpA and back pain. Clinical, biochemical and radiological parameters were collected. The ankylosing spondylitis disease activity score (ASDAS)-CRP was determined. Radiographic progression was represented by the modified Stoke ankylosing spondylitis spine score (mSASSS). MRI with short tau inversion recovery (STIR) and diffusion-weighted imaging sequences were performed simultaneously. Inflammatory lesions on STIR were used for the Spondyloarthritis Research Consortium of Canada (SPARCC) MRI indexes and as references in outlining regions of interest in ADC maps to produce mean (ADCmean) and maximal (ADCmax) ADC values. Univariate and multivariate linear regression analyses were used to determine independent associations between ADC and radiographic progression. RESULTS: The 84 participants with identifiable lesions on spinal ADC maps recruited were characterized by a mean (s.d.) age of 45.01 (13.68) years, long disease duration [13.40 (11.01) years] and moderate clinical disease activity [ASDAS-CRP 2.07 (0.83)]. Multivariate regression analysis using ADCmean as the independent variable showed that age (regression coefficient [B] = 0.34; P = 0.01), male sex (B = 0.25; P = 0.04) and ADCmean (B = 0.30; P = 0.01) were positively associated with mSASSS. Multivariate regression analysis using ADCmax as the independent variable showed a tendency for ADCmax to be associated with mSASSS (B = 0.21; P = 0.07). CONCLUSION: The intensity of spinal inflammation as determined by ADC is associated with radiographic progression in participants with active axial SpA.

Clinical Associations of Uveitis in Axial Spondyloarthritis Group and Ankylosing Spondylitis Group: Do They Represent the Same Disease?

OBJECTIVE: The aim of this study was to determine the prevalence and associated factors for uveitis in ethnic Chinese patients with axial spondyloarthritis (SpA) and ankylosing spondylitis (AS). METHODS: This was a cross-sectional study. Patients fulfilling the Assessment of SpondyloArthritis international Society axial SpA criteria were recruited consecutively from 3 rheumatology centers in Hong Kong from March 2014 to July 2017. Clinical and biochemical parameters were collected. History of uveitis was inquired from both history and medical records. All patients received lumbosacral spine x-rays and whole-spine and sacroiliac joint magnetic resonance imaging. Patients were defined as axial SpA if they fulfilled the Assessment of SpondyloArthritis international Society criteria and AS if they fulfilled the modified New York criteria. Clinical and radiological findings were compared between patients with and without uveitis in the 2 groups. Factors associated with uveitis were identified with univariate analyses and multivariate logistic regression analyses. RESULTS: Among 252 patients, 67 patients (26.6%) had a history of uveitis. The male-to-female ratio was 55.4 to 44.6. Disease duration was 12.3 ± 11.7 years. In the axial SpA group, multivariate regression showed that older age (odds ratio [OR], 1.05; p = 0.01), human leukocyte antigen B27 positivity (OR, 11.79; p = 0.01), and history of inflammatory bowel disease (OR, 9.74; p = 0.04) were positively associated with uveitis. In the AS group, multivariate regression showed that back pain duration (OR, 1.05; p = 0.01) and male sex (OR, 3.46; p = 0.03) were associated with uveitis. CONCLUSIONS: Axial SpA represents a spectrum of diseases. Its clinical associations with uveitis should be distinguished from those of traditional AS.