To examine the association between a history of periodontitis (PD) and incident systemic lupus erythematosus (SLE) We used 2003–2012 claims data from the Taiwanese National Health Insurance Database to identify 7,204 incident SLE patients during 2007–2012 as the study group, along with randomly selecting 72,040 non-SLE patients matched (1:10) for age, gender, and first diagnosis date (index date) as the control group. The correlation between PD and SLE risk was estimated using conditional logistic regression analysis, after making adjustments for confounders (including a history of diabetes and number of non-PD related dental visits before the index date). To evaluate the effects of PD severity and the lag time which occurred since the last PD visit on SLE development, odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for subgroups of patients with PD according to their number of visits, cumulative cost and also the time gaps between their last PD-related visit and the index date. A statistically significant association between a history of PD and newly diagnosed SLE was observed (OR, 1.21; 95% CI, 1.14–1.28; p-value, <0.001). The association was both dose- and time-dependent and was found to be strongest when the interval between the last PD-related visit and the index date was less than three months (OR, 1.83; 95% CI, 1.61–2.09; p-value, <0.001). The association between PD exposure and SLE risk was consistently significant among subgroups stratified based on age, gender, or DM status. The results of this nationwide, population-based, case-control study suggest that there is a significant association between a history of PD and incident SLE in Taiwan. This weak association is limited to lack of information on individual smoking status in the database.

The implications of boosting Omalizumab treatment (OT) in patients with severe allergic asthma (SAA) remain unclear. The study aimed to explore and compare the 12-month effectiveness between continuous, at least 10-month OT (continuation group) and four-month boost of Omalizumab (boost group) in adult patients with SAA. In this retrospective cohort study, clinical data were collected for further analysis. Of all participants (n = 124), a significant reduction in annual exacerbations (baseline = 0.8 ± 1.5, follow-up = 0.5 ± 1.0, p = 0.047 *) and improvement in small airway ventilation as evaluated by forced expiratory flow at 25–75% (baseline = 55.1 ± 11.1%, follow-up = 59.4 ± 8.4%, p < 0.001 *) were found in the continuation group (n = 110). By contrast, the boost group (n = 14) had significantly increased annual exacerbations (baseline = 0.7 ± 1.4, follow-up = 2.9 ± 3.6, p = 0.031 *) and impaired small airway function (baseline = 55.3 ± 12.9, follow-up = 52.1 ± 12.5, p = 0.026 *). Furthermore, the continuation group rather than the boost group had significant decreases in the frequency of oral corticosteroid (OCS) use as controllers (baseline = 32.7%, follow-up = 20.0%, p = 0.047 *; baseline = 50.0%, follow-up = 21.4%, p = 0.237, respectively) and OCS maintenance dose (mg/month) (baseline = 85.9 ± 180.8, follow-up = 45.8 ± 106.6, p = 0.020 *; baseline = 171.4 ± 221.5, follow-up = 50.0 ± 104.3, p = 0.064, respectively), and increases in asthma control test scores (baseline = 16.0 ± 3.0, follow-up = 19.8 ± 4.4, p < 0.001 *; baseline = 14.6 ± 3.8, follow-up = 19.7 ± 4.7, p = 0.050, respectively). Continuous OT would be beneficial for adult patients with SAA, while boost of Omalizumab would worsen their long-term outcomes.

Background: Antinuclear antibody pattern recognition is vital for autoimmune disease diagnosis but labor-intensive for manual interpretation. To develop an automated pattern recognition system, we established machine learning models based on the International Consensus on Antinuclear Antibody Patterns (ICAP) at a competent level, mixed patterns recognition, and evaluated their consistency with human reading. Methods: 51,694 human epithelial cells (HEp-2) cell images with patterns assigned by experienced medical technologists collected in a medical center were used to train six machine learning algorithms and were compared by their performance. Next, we choose the best performing model to test the consistency with five experienced readers and two beginners. Results: The mean F1 score in each classification of the best performing model was 0.86 evaluated by Testing Data 1. For the inter-observer agreement test on Testing Data 2, the average agreement was 0.849 (κ) among five experienced readers, 0.844 between the best performing model and experienced readers, 0.528 between experienced readers and beginners. The results indicate that the proposed model outperformed beginners and achieved an excellent agreement with experienced readers. Conclusions: This study demonstrated that the developed model could reach an excellent agreement with experienced human readers using machine learning methods.

This study aimed to compare the test results of anti-double-stranded DNA (anti-dsDNA) antibodies obtained using chemiluminescent immunoassay (CIA) and enzyme-linked immunosorbent assay (ELISA), and investigate predictors of inconsistent results. This retrospective study included 502 patients who underwent CIA and ELISA to determine their anti-dsDNA antibody values within a year. We compared the diagnostic power for SLE, disease activity, and predictive power for lupus nephritis (LN). A multivariate analysis was performed to determine the predictors of inconsistencies. CIA and ELISA were moderately correlated in terms of their consistency (Cronbach’s α = 0.571), and yielded comparably favorable results in terms of SLE diagnostic power and SLE disease activity. However, if the patient had LN, CIA displayed higher predictive power than ELISA (0.620 vs. 0.555, p = 0.026). Compared with the CIA/ELISA double-positive group, the inconsistent group had lower anti-C1q circulating immune complexes (CIC) antibody values (OR: 0.42, 95% CI: 0.18–0.94, p = 0.036), and lower SLEDAI scores (≥4) (OR: 0.33, 95% CI: 0.14–0.79, p = 0.013). Anti-dsDNA antibody detection with CIA exhibited higher predictability for diagnosing LN than did ELISA. In the event of inconsistencies between anti-dsDNA methods, SLE disease activity and CIC test values should be considered simultaneously.

Background: Lupus nephritis (LN) often lead to end-stage renal disease in systemic lupus erythematosus patients. This study aimed to investigate the clinical application of renal gallium-67 scans for determining renal histological parameters in LN patients. Methods: Between 2006 and 2018, 237 biopsy-proven and 35 repeat biopsies LN patients who underwent renal gallium scans before or after biopsy were included for analysis. The classification and scoring of LN were assessed according to the International Society of Nephrology/Renal Pathology Society. A delayed 48-h gallium scan was performed and interpreted by semiquantitative methods using left kidney/spine (K/S) ratio. The renal histological results were compared with gallium uptake. Results: Out of 237 participants, 180 (76%) had proliferative LN. Baseline gallium left K/S ratio was significantly higher in class IV LN as compared to class III (median (interquartile range, IQR): 1.16 (1.0–1.3), 0.95 (0.9–1.1), respectively, p < 0.001). Furthermore, changes in gallium uptake between two biopsies were positively correlated with changes activity index (r = 0.357, p = 0.035), endocapillary hypercellularity (r = 0.385, p = 0.032), and neutrophils infiltration (r = 0.390, p = 0.030) in renal pathology. Conclusions: Renal gallium uptake is associated with active inflammation in LN. Changes in renal gallium uptake positively correlated with changes in activity index in renal pathology.