Remission and low disease activity in Polish patients with systemic lupus erythematosus - real-life, five-year follow-up outcomes.

OBJECTIVE: Remission in systemic lupus erythematosus (SLE) or Lupus Low Disease Activity State (LLDAS) are associated with less organ damage and thus create new perspectives for effective damage-limiting treatment. The aim of this study was to assess the occurrence of remission defined by The Definition of Remission In SLE (DORIS) and of LLDAS as well as their predictors in the Polish SLE cohort. PATIENTS AND METHODS: In this retrospective study data were collected on patients with SLE that achieved at least one year of DORIS remission or LLDAS and were followed up for 5 years. Clinical and demographic data were gathered; DORIS and LLDAS predictors were determined by univariate regression analysis. RESULTS: The full analysis set included 80 patients at baseline and 70 at follow-up. Over half of patients with SLE (39; 55.7%) fulfilled the DORIS remission criteria. In this group, 53.8% (21) of patients were in remission on-treatment and 46.1% (18) in remission off-treatment. LLDAS was fulfilled by a cohort of 43 (61.4%) patients with SLE. Among patients that achieved DORIS or LLDAS at follow-up, 77% were not treated with glucocorticoids (GCs). The most important predictors for DORIS and LLDAS off-treatment were mean SLEDAI-2K score with cut-off of ≤8.0, treatment with mycophenolate mofetil or antimalarials, and the age at disease onset above 43 years. CONCLUSIONS: Remission and LLDAS are achievable goals in treating SLE as over half of study patients fulfilled the DORIS remission and LLDAS criteria. The identified predictors for DORIS and LLDAS indicate the importance of effective therapy leading to reduction of GC use.

Development and validation of COVID-19 Radiological Risk Score (COVID-RRS): a multivariable radiological score to estimate the in-hospital mortality risk in COVID-19 patients.

OBJECTIVE: To develop and validate in-hospital mortality risk score comprising radiological aberrances in chest computed tomography (CT) performed on admission. PATIENTS AND METHODS: Single-center, longitudinal cohort study in adult patients admitted with Coronavirus Disease 2019 (COVID-19) to our ward. Patients were followed-up during hospitalization until discharge or death. Eligibility criteria for the study comprised positive real-time reverse transcription-polymerase chain reaction test (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and ground-glass opacities in chest CT. In-hospital death was the outcome of interest. Radiological, laboratory, and clinical data were analyzed. Radiological determinants of mortality were used as variables in multivariate logistic regression analysis, and results were used to build a radiological risk score. RESULTS: 371 patients were enrolled in development and validation cohorts (181 and 190 respectively), with a total of 47 non-survivors. Univariate analysis data determined 12 predictive factors (nine risk and three protective). In multivariate analysis, we developed COVID-RRS (COVID-19 Radiological Risk Score) - a radiological score predicting in-hospital COVID-19 mortality risk comprising estimated lung involvement percentage, pleural effusion, and domination of consolidation-type changes in chest CT. Our score was superior in the prediction of COVID-19 mortality to the percentage of lung involvement alone, Chest Computed Tomography Severity Score (CTSS), and Total Severity Score (TSS) in both groups with AUC of 0.910 and 0.902, respectively (p <0.001). CONCLUSIONS: Additional imaging features independently contribute to COVID-19 mortality risk. Our model comprising lung involvement estimation, pleural effusion, and domination of consolidations performed significantly better than scores based on the extent of the changes alone. COVID-RRS is a simple, reliable, and ready-to-use tool for clinical practice.

Distinct regional brain atrophy pattern in multiple sclerosis and neuropsychiatric systemic lupus erythematosus patients.

Differentiation of systemic lupus erythematosus (SLE) from multiple sclerosis (MS) can be challenging, especially when neuropsychiatric (NP) symptoms are accompanied by white matter lesions in the brain. Given the lack of discriminative power of currently applied tools for their differentiation, there is an unmet need for other measures that can aid in distinguishing between the two autoimmune disorders. In this study we aimed at exploring whether brain atrophy measures could serve as markers differentiating MS and SLE. Thirty-seven relapsing-remitting MS and 38 SLE patients with nervous system manifestations, matched according to age and disease duration, underwent 1.5 Tesla magnetic resonance imaging (MRI), including volumetric sequences, and clinical assessment. Voxelwise analysis was performed using ANTS-SyN elastic registration protocol, FSL Randomise and Gamma methods. Cortical and subcortical segmentation was performed with Freesurfer 5.3 pipeline using T1-weighted MPRAGE sequence data. Using MRI volumetric markers of general and subcortical gray matter atrophy and clinical variables, we built a stepwise multivariable logistic diagnostic model to identify MRI parameters that best differentiate MS and SLE patients. We found that the best volumetric predictors to distinguish them were: fourth ventricle volume (sensitivity 0.86, specificity 0.57, area under the curve, AUC 0.77), posterior corpus callosum (sensitivity 0.81, specificity 0.57, AUC 0.68), and third ventricle to thalamus ratio (sensitivity 0.42, specificity 0.84, AUC 0.65). The same classifiers were identified in a subgroup analysis that included patients with a short disease duration. In MS brain atrophy and lesion load correlated with clinical disability, while in SLE age was the main determinant of brain volume. This study proposes new imaging parameters for differential diagnosis of MS and SLE with central nervous system involvement. We show there is a different pattern of atrophy in MS and SLE, and the key structural volumes that are differentially affected include fourth ventricle and posterior section of corpus callosum, followed by third ventricle to thalamus ratio. Different correlation patterns between volumetric and clinical data may suggest that while in MS atrophy is driven mainly by disease activity, in SLE it is mostly associated with age. However, these results need further replication in a larger cohort.

Subcortical gray matter atrophy is associated with cognitive deficit in multiple sclerosis but not in systemic lupus erythematosus patients.

Cognitive impairment is a significant clinical problem both in multiple sclerosis (MS) and systemic lupus erythematosus (SLE) patients. In MS cognitive dysfunction has been associated with brain atrophy and total demyelinating lesion volume. In SLE cognitive impairment is much less understood, and its link to structural brain damage remains to be established. The aim of this study was to identify the relationship between subcortical gray matter volume and cognitive impairment in MS and SLE. We recruited 37 MS and 38 SLE patients matched by age, disease duration and educational level. Patients underwent magnetic resonance imaging (MRI) and a battery of psychometric tests. Severity of cognitive impairment was similar in both cohorts despite larger white matter lesion load in MS patients. Psychometric scores were associated with global and subcortical gray matter atrophy measures and lesion load in MS, but not in SLE. In SLE, the lack of a relationship between cognitive impairment and structural damage, defined either as atrophy or white matter lesions, indicates a different causal mechanism of cognitive deficit.

Effect of tumour necrosis factor-α inhibitor on serum level of dickkopf-1 protein and bone morphogenetic protein-7 in ankylosing spondylitis patients with high disease activity.

OBJECTIVES: To examine changes in serum levels of the bone remodelling molecules dickkopf-1 (Dkk-1), sclerostin, wingless-type protein-3a (Wnt-3a), and bone morphogenetic protein-7 (BMP-7) during 6 months of anti-tumour necrosis factor (anti-TNF) treatment in ankylosing spondylitis (AS) patients with high disease activity. METHOD: We included 40 patients with axial AS: 20 patients with high disease activity were assigned to treatment with TNF inhibitor and 20 with low disease activity were assigned to non-steroidal anti-inflammatory drug (NSAID) treatment. Markers of bone remodelling and inflammation were assessed at baseline and after 6 months. RESULTS: In the TNF inhibitor-treated group Dkk-1 decreased significantly from 196.8 pg/mL [95% confidence interval (CI) 94.1-399.0] to 116.3 pg/mL (95% CI 38.0-301.6) and BMP-7 increased significantly from 1.4 pg/mL (95% CI 0-23.0) to 20.3 pg/mL (95% CI 4.9-41.3). There was a significant negative correlation between Dkk-1 and BMP-7 at 6 months (r = -0.64, p = 0.004) in this group. Non-parametric regression analysis adjusted for disease duration, age, sex, baseline modified Stoke's Ankylosing Spondylitis Spine Score (mSASSS), and baseline C-reactive protein (CRP) confirmed a statistically significant effect of treatment on time-related changes of Dkk-1 and BMP-7. Erythrocyte sedimentation rate (ESR), CRP, and also the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) score decreased significantly in the anti-TNF-treated group. CONCLUSIONS: Among the potential biomarkers of bone remodelling in AS, Dkk-1 and BMP-7 displayed significant time alterations and correlative interactions during anti-TNF treatment.