OBJECTIVE: To determine and compare the clinical phenotype and organ damage between male and female patients with SLE in Malaysia.
METHODOLOGY: This was a cross-sectional study involving SLE patients from Universiti Kebangsaan Malaysia Medical Centre from June 2016 until June 2017. Information on their socio-demographics and disease characteristics were obtained from the clinical records. Disease damage was assessed using the Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) damage index (SDI) scores. The disease characteristics, autoantibody profiles and organ damage were compared between male and female patients, and multivariable analysis using male sex as dependent variable was then performed.
RESULTS: A total of 418 patients were recruited and a total of 59 (14.1%) patients were male. Male patients presented with lower SLE ACR criteria at initial presentation but a significantly higher number of them had renal involvement (lupus nephritis) (78.0% versus 63.8%, p = 0.04). Male patients had less musculoskeletal involvement (45.8% versus 63.0%, p = 0.02) and tended to have lesser mucocutaneous involvement. Immunologic profile revealed that a lower number of male patients had positive anti-Ro antibody (22.7% versus 44.7%, p = 0.04) and they tended to have positive lupus anticoagulant antibody (27.6% versus 14.3%, p = 0.06). Presence of organ damage (SDI score ≥ 1) was significantly higher among males (55.9% versus 39.6%, p = 0.02) with higher renal damage (25.4% versus 9.2%, p = 0.004) and cardiovascular event of ischaemic heart disease or stroke (20.3% versus 7.0%, p = 0.004). They were also inclined to develop damage much earlier as compared to female patients, 3 (interquartile range (IQR) 7.5) versus 5 (IQR 7) years, p = 0.08. The occurrence of disease damage was independently associated with male gender with odds ratio of 1.9 (95% confidence interval 1.1-3.5), p = 0.02.
CONCLUSION: Male patients with SLE have more severe disease with renal damage and cardiovascular event.
AIMS: This study aimed to determine the prevalence of mild cognitive impairment (MCI) using the Montreal Cognitive Assessment (MoCA) and its associated factors among patients diagnosed with SLE in Malaysia.
METHODS: A total of 200 SLE patients were recruited prospectively from the outpatient clinics of two tertiary hospitals in Malaysia. Standardized clinical interview was utilized to obtain information on socio-demographic characteristics. All patients were then assessed using the MoCA questionnaire for presence of cognitive impairment; the Patient Health Questionnaire 9 (PHQ-9) for presence of depressive symptoms; and the Wong-Baker Faces Pain Scale (WBFPS) for severity of pain. The evaluation of disease activity and severity were performed by the treating rheumatologists and nephrologists using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and Systemic Lupus International Collaborating Clinics Damage Index (SLICC DI).
RESULTS: The prevalence of MCI was 35%. The significant associated factors from the bivariate analysis were male gender (p = 0.04), educational level (p = 0.00), WBFPS score (p = 0.035) and anticardiolipin IgM (p = 0.01). Further analysis using logistic regression model found that male gender (OR = 7.43, 95% confidence interval 1.06-52.06, p = 0.04), lower educational level (OR = 4.4, 95% confidence interval 1.47-13.21, p = 0.01) and presence of anticardiolipin IgM (OR = 6.81, 95% confidence interval 1.45-32.01, p = 0.031) were associated with impaired MoCA scores. Also, increasing pain scores increased the risk of patients being affected by cognitive impairment.
CONCLUSION: Over one-third of patients with SLE in our cohort were found to have MCI. Risk factors included male gender, lower educational level, higher pain score and presence of anticardiolipin IgM. Physicians are encouraged to perform routine screening to detect cognitive dysfunction in patients with SLE in their clinical practice as part of a more comprehensive management.
METHODS: A cross-sectional study was performed involving SLE patients (n = 120 patients) from Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Serum and urinary IL-17A levels were determined by immunoassay while disease activity was assessed using Systemic Lupus Erythematosus Disease Activity Index-2000 (SLEDAI-2K) and British Isles Lupus Assessment Group's 2004 index (BILAG 2004) scores. The correlations between serum and urinary IL-17A levels with total SLEDAI-2K and BILAG 2004 scores were determined using bivariate correlation analyses. Receiver operating characteristic curves were calculated to determine their sensitivity and specificity as disease activity biomarkers.
RESULTS: Both serum and urinary IL-17A levels correlated with total scores of BILAG 2004, BILAG renal, BILAG mucocutaneous, and SLEDAI-2K (P
METHODS: This cross-sectional study was conducted from June 2021 until April 2022, and SLE patients were recruited to complete the SLEQoL, LupusQoL and Short Form Health Survey (SF-36) in Malay language. Disease activity were recorded using the modified SLE Disease Activity Index (M- SLEDAI) and British Isles Lupus Assessment Group 2004 (BILAG-2004) index. Presence of organ damage was determined using the SLICC Damage index. Cronbach's alpha was calculated to determine internal consistency while exploratory factor analysis was done to determine the construct validity. Concurrent validity was evaluated using correlation with SF-36. Multiple linear regression analysis was deployed to determine the factors affecting each domain of SLEQoL and LupusQoL.
RESULTS: A total of 125 subjects were recruited. The Cronbach's α value for the Malay-SLEQoL (M-SLEQoL) and Malay-LupusQOL (M-LupusQoL) was 0.890 and 0.944 respectively. Exploratory factor analysis found formation of similar number of components with the original version of questionnaires and all items have good factor loading of >0.4. Both instruments also had good concurrent validity with SF-36. M-SLEQoL had good correlations with BILAG-2004 and M-SLEDAI scores. Musculoskeletal (MSK) involvement was independently associated with lower M-SLEQoL in physical function, activity and symptom domains. Meanwhile, MSK and NPSLE were associated with fatigue in M-LupusQoL.
CONCLUSION: Both M-SLEQoL and M-LupusQoL are reliable and valid as disease -specific QoL instruments for Malaysian patients. The M-Lupus QoL has better discriminative validity compared to the M-SLEQoL. SLE patients with MSK involvement are at risk of poor QoL in multiple domains including physical function, activity, symptoms and fatigue.
METHODOLOGY: This was a cross-sectional study involving SLE patients who visited our institute between January 2020 and June 2021. A review of the medical records and face-to-face interviews were conducted to obtain sociodemographics, SLE disease characteristics and the intervals from the first symptoms to the diagnosis. Health-seeking behaviours were assessed by asking about the patients' first action during the initial symptoms and were divided into: (i) seeking professional health personnel; (ii) self-treatment; and (iii) the use of the internet as a primary source of information. Diagnostic delays were defined as the interval between initial symptoms and SLE diagnosis of more than 6 months. Low-level disease activity state (LLDAS) at 12 months was assessed from the medical records. Univariate and multivariate logistic regression analysis was subsequently conducted to determine factors associated with diagnostic delays.
RESULTS: Among the 154 patients included in the study, 24% (n = 37) had delayed diagnosis. The delay was significantly higher among the Indian versus Malay versus Chinese (42.9% vs 28% vs 10.8%, p = 0.037). Patients with rash tend to have delayed diagnosis (37.8% vs 22.2%, p = 0.08) while fewer patients with frothy urine had delayed diagnosis (8.1% vs 21.4%, p = 0.09). No significant association was found between health-seeking behaviours and diagnostic delays. The rate of LLDAS at 12 months was significantly lower among patients with delayed diagnosis (43.2% vs 70.0%, p = 0.006). Chinese ethnicity remained the only significant factor associated with lesser diagnostic delays in the multivariate analysis, with OR 0.30 (CI 0.09-0.93), p = 0.037.
CONCLUSION: There were ethnic disparities in the early diagnosis of SLE in Malaysia, with Indian patients having a longer interval between the first symptom and diagnosis while the Chinese were associated with lower diagnostic delays. Early diagnosis predicted early attainment of LLDAS, suggesting that prompt recognition of the initial SLE symptoms is important.
METHODS: Research questions were formulated focusing on diagnosis and treatment of adult patients with RMD within the context of the pandemic, including the management of RMD in patients who developed COVID-19. MEDLINE was searched for eligible studies to address the questions, and the APLAR COVID-19 task force convened 2 meetings through video conferencing to discuss its findings and integrate best available evidence with expert opinion. Consensus statements were finalized using the modified Delphi process.
RESULTS: Agreement was obtained around key aspects of screening for or diagnosis of COVID-19; management of patients with RMD without confirmed COVID-19; and management of patients with RMD with confirmed COVID-19. The task force achieved consensus on 25 statements covering the potential risk of acquiring COVID-19 in RMD patients, advice on RMD medication adjustment and continuation, the roles of telemedicine and vaccination, and the impact of the pandemic on quality of life and on treatment adherence.
CONCLUSIONS: Available evidence primarily from descriptive research supported new recommendations for aspects of RMD care not covered in the previous document, particularly with regard to risk factors for complicated COVID-19 in RMD patients, modifications to RMD treatment regimens in the context of the pandemic, and COVID-19 vaccination in patients with RMD.
METHODS: The study was based on data from 7035 fully vaccinated respondents to the online COVAD questionnaire with SLE (N = 852), rAIDs (N = 3098), or nrAIDs (N = 414), and HCs (N = 2671). BI was defined as COVID-19 infection occurring in individuals vaccinated with ≥ 2 doses (or 1 dose of J&J) ≥ 14 days after vaccination and not after 6 months since the last vaccine dose. Data were analysed using linear and logistic regression models.
RESULTS: A total of 91/852 (10.7%) SLE patients reported at least one BI. The frequency of BIs in SLE patients was comparable to that among HCs (277/2671; p = 0.847) and patients with nrAID (39/414; p = 0.552) but higher than that among patients with other rAIDs (235/3098; p = 0.005). No demographic factors or treatments were associated with BIs in SLE patients (p ≥ 0.05 for all). Joint pain was more frequent in SLE patients than in HCs (odds ratio [OR]: 3.38; 95% confidence interval [CI]: 1.89-6.04; p
METHODS: A validated patient self-reporting e-survey was circulated by the COVAD study group to collect data on COVID-19 infection and vaccination in 2022. BIs were defined as COVID-19 occurring ≥14 days after 2 vaccine doses. We compared BIs characteristics and severity among IIMs, other autoimmune rheumatic and non-rheumatic diseases (AIRD, nrAID), and healthy controls (HC). Multivariable Cox regression models assessed the risk factors for BI, severe BI and hospitalisations among IIMs.
RESULTS: Among 9449 included response, BIs occurred in 1447 (15.3%) respondents, median age 44 years (IQR 21), 77.4% female, and 182 BIs (12.9%) occurred among 1406 IIMs. Multivariable Cox regression among IIMs showed age as a protective factor for BIs [Hazard Ratio (HR)=0.98, 95%CI = 0.97-0.99], hydroxychloroquine and sulfasalazine use were risk factors (HR = 1.81, 95%CI = 1.24-2.64, and HR = 3.79, 95%CI = 1.69-8.42, respectively). Glucocorticoid use was a risk factor for severe BI (HR = 3.61, 95%CI = 1.09-11.8). Non-White ethnicity (HR = 2.61, 95%CI = 1.03-6.59) was a risk factor for hospitalisation. Compared with other groups, patients with IIMs required more supplemental oxygen therapy (IIM = 6.0% vs AIRD = 1.8%, nrAID = 2.2%, and HC = 0.9%), intensive care unit admission (IIM = 2.2% vs AIRD = 0.6%, nrAID, and HC = 0%), advanced treatment with antiviral or monoclonal antibodies (IIM = 34.1% vs AIRD = 25.8%, nrAID = 14.6%, and HC = 12.8%), and had more hospitalisation (IIM = 7.7% vs AIRD = 4.6%, nrAID = 1.1%, and HC = 1.5%).
CONCLUSION: Patients with IIMs are susceptible to severe COVID-19 BI. Age and immunosuppressive treatments were related to the risk of BIs.
METHODS: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models.
RESULTS: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P