METHODS: From January 2005 to December 2014, we conducted a nationwide case-control study, using Taiwan's National Health Insurance Research Database. Obstetric complications and perinatal outcomes in SLE patients were compared with those without SLE.
RESULTS: 2059 SLE offspring and 8236 age-matched, maternal healthy controls were enrolled. We found increased obstetric and perinatal complications in SLE population compared with healthy controls. SLE patients exhibited increased risk of preeclampsia/eclampsia (8.98% vs.1.98%, odds ratio [OR]: 3.87, 95% confidence interval [95% CI]: 3.08-4.87, p<0.0001). Their offspring tended to have lower Apgar scores (<7) at both 1 min (10.7% vs. 2.58%, p<0.0001) and 5 min (4.25% vs. 1.17%, p<0.0001), as well as higher rates of intrauterine growth restriction (IUGR, 9.91% vs. 4.12%, OR: 2.24, 95% CI: 1.85-2.71, p<0.0001), preterm birth (23.70% vs 7.56%, OR: 3.00, 95% CI: 2.61-3.45, p<0.0001), and stillbirth (4.23% vs. 0.87%, OR: 3.59, 95% CI: 2.54-5.06, p<0.0001). The risks of preterm birth and stillbirth were markedly increased in SLE patients with concomitant preeclampsia/eclampsia or IUGR. Preterm birth of SLE patients was 1~4 gestational weeks earlier than that of healthy controls and the peak occurrence of stillbirth in SLE population was at 20~30 gestational weeks.
CONCLUSIONS: Asian SLE patients exhibited increased risks of maternal complications and adverse birth outcomes. Frequent antenatal visits before 20 gestational weeks are recommended in high-risk SLE patients.
METHODS: Demographics, diagnosis, comorbidities, disease activity, treatments and PROMIS instrument data were analysed. Primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis.
RESULTS: We analysed responses from 1582 IIM, 4700 non-IIM AIRD and 545 nrAID patients and 3675 controls gathered through 23 May 2022. The median GPH scores were the lowest in IIM and non-IIM AIRD patients {13 [interquartile range (IQR) 10-15] IIMs vs 13 [11-15] non-IIM AIRDs vs 15 [13-17] nrAIDs vs 17 [15-18] controls, P
METHODS: The first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups.
RESULTS: We analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, 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
METHODS: The COVAD surveys were used to extract data on flare demographics, comorbidities, COVID-19 history, and vaccination details for patients with AIRDs. Flares following vaccination were identified as patient-reported (a), increased immunosuppression (b), clinical exacerbations (c) and worsening of PROMIS scores (d). We studied flare characteristics and used regression models to differentiate flares among various AIRDs.
RESULTS: Of 15 165 total responses, the incidence of flares in 3453 patients with AIRDs was 11.3%, 14.8%, 9.5% and 26.7% by definitions a-d, respectively. There was moderate agreement between patient-reported and immunosuppression-defined flares (K = 0.403, P = 0.022). Arthritis (61.6%) and fatigue (58.8%) were the most commonly reported symptoms. Self-reported flares were associated with higher comorbidities (P = 0.013), mental health disorders (MHDs) (P
METHODS: Delayed-onset (>7 days) vaccine-related adverse events (AE), disease flares (DF), and AID-related treatment modifications were analyzed upon diagnosis of AID versus healthy controls (HC) and the pregnancy/breastfeeding status at the time of at least one dose of vaccine.
RESULTS: Among the 9201 participants to the self-administered online survey, 6787 (73.8%) were women. Forty pregnant and 52 breastfeeding patients with AID were identified, of whom the majority had received at least one dose of COVID-19 vaccine (100% and 96.2%, respectively). AE were reported significantly more frequently in pregnant than in non-pregnant patients (overall AE 45% vs 26%, p= 0.01; minor AE 40% vs 25.9%, p= 0.03; major AE 17.5% vs 4.6%, p< 0.01), but no difference was found in comparison with pregnant HC. No difference was observed between breastfeeding patients and HC with respect to AE. Post-vaccination DF were reported by 17.5% of pregnant and 20% of breastfeeding patients, and by 18.3% of age- and disease-matched non-pregnant and non-breastfeeding patients (n = 262). All pregnant/breastfeeding patients who experienced a DF were managed with glucocorticoids; 28.6% and 20% of them required initiation or change in immunosuppressants, respectively.
CONCLUSION: This study provides reassuring insights into the safety of COVID-19 vaccines administered to women with AID during the gestational and post-partum periods, helping overcome hesitant attitudes, as the benefits for the mother and the fetus by passive immunization appear to outweigh potential risks.
METHODS: Patients testing HBs antigen (Ag) or HCV antibody (Ab) positive within enrollment into TAHOD were considered HBV or HCV co-infected. Factors associated with HBV and/or HCV co-infection were assessed by logistic regression models. Factors associated with post-ART HIV immunological response (CD4 change after six months) and virological response (HIV RNA <400 copies/ml after 12 months) were also determined. Survival was assessed by the Kaplan-Meier method and log rank test.
RESULTS: A total of 7,455 subjects were recruited by December 2012. Of patients tested, 591/5656 (10.4%) were HBsAg positive, 794/5215 (15.2%) were HCVAb positive, and 88/4966 (1.8%) were positive for both markers. In multivariate analysis, HCV co-infection, age, route of HIV infection, baseline CD4 count, baseline HIV RNA, and HIV-1 subtype were associated with immunological recovery. Age, route of HIV infection, baseline CD4 count, baseline HIV RNA, ART regimen, prior ART and HIV-1 subtype, but not HBV or HCV co-infection, affected HIV RNA suppression. Risk factors affecting mortality included HCV co-infection, age, CDC stage, baseline CD4 count, baseline HIV RNA and prior mono/dual ART. Shortest survival was seen in subjects who were both HBV- and HCV-positive.
CONCLUSION: In this Asian cohort of HIV-infected patients, HCV co-infection, but not HBV co-infection, was associated with lower CD4 cell recovery after ART and increased mortality.
METHODS: We used the 2003-2013 Taiwanese National Health Insurance Research Database to identify RA patients who started any RA-related medical therapy from 2008 to 2012. Those who initiated etanercept or adalimumab therapy during 2008-2012 were selected as the TNFi group and those who never received biologic disease-modifying anti-rheumatic drug therapy were identified as the comparison group after excluding the patients who had a history of TB or human immunodeficiency virus infection/acquired immune deficiency syndrome. We used propensity score matching (1:6) for age, sex, and the year of the drug index date to re-select the TNFi group and the non-TNFi controls. After adjusting for potential confounders, hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to examine the 1-year TB risk in the TNFi group compared with the non-TNFi controls. Subgroup analyses according to the year of treatment initiation and specific TNFi therapy were conducted to assess the trend of 1-year TB risk in TNFi users from 2008 to 2012.
RESULTS: This study identified 5,349 TNFi-treated RA patients and 32,064 matched non-TNFi-treated controls. The 1-year incidence rates of TB were 1,513 per 105 years among the TNFi group and 235 per 105 years among the non-TNFi controls (incidence rate ratio, 6.44; 95% CI, 4.69-8.33). After adjusting for age, gender, disease duration, comoridities, history of TB, and concomitant medications, TNFi users had an increased 1-year TB risk (HR, 7.19; 95% CI, 4.18-12.34) compared with the non-TNFi-treated controls. The 1-year TB risk in TNFi users increased from 2008 to 2011 and deceased in 2012 when the Food and Drug Administration in Taiwan announced the Risk Management Plan for patients scheduled to receive TNFi therapy.
CONCLUSION: This study showed that the 1-year TB risk in RA patients starting TNFi therapy was significantly higher than that in non-TNFi controls in Taiwan from 2008 to 2012.