Predictive value of erythrocyte sedimentation rate and C-reactive protein in Behcet's disease activity and manifestations: a cross-sectional study.

BACKGROUND: Behcet's disease (BD) as a chronic inflammatory condition that affects the eyes, skin, central nervous system, gastrointestinal tract and vessels. According to the literature, the exact value of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) in predicting active manifestations of BD remains controversial. In this study, we aim to assess and compare values of ESR and CRP between BD patients with active/inactive BD and active/inactive manifestations of the disease. Moreover, we try to determine the predictive value of ESR and CRP for disease activity. METHODS: Participants (n = 514) were drug-naïve BD patients; Based on last two visits, ESR and CRP values, disease activity, and active manifestations were recorded. The Man-Whitney U test measured the associations, and the binomial logistic regression evaluated the predictive value of ESR and CRP for active disease and each active manifestation. The sensitivity and specificity and the area under the curve (AUC) for each model were determined using receiver operating characteristic curves (ROC). Multiple regressions were run to predict BD activity score from ESR and CRP. RESULT: Patients with active oral, genital, joint and dermal manifestations had higher ESR and CRP values (Mann-Whitney U test, p < 0.05 for all). Binomial logistic regressions showed that ESR had valuable predictive value for active BD (OR = 1.09 [1.04-1.13], AUC = 0.79 [0.74-0.83], p < 0.001) and active vascular manifestations (1.03 [1.01-1.05], AUC = 0.85 [0.79-0.92], p < 0.001). CRP had good predictive value for active vascular manifestations (OR 1.98 [1.45-2.72], AUC = 0.86 [0.8-0.91], p < 0.001). The optimal value of ESR ≥ 10.5 and ESR ≥ 42.5 could predict active BD and active vascular manifestations with sensitivity, specificity = 71%, 75% and = 81%, 83% respectively. CONCLUSIONS: ESR and CRP are both associated with active BD and most manifestations of the diseases. They can be used for the prediction of active BD and active vascular manifestations in BD patients. Further studies can help to confirm the findings of the current research.

Sex differences in microstructural white matter alterations of mathematics anxiety based on diffusion MRI connectometry.

BACKGROUND: Mathematics Anxiety (MA) is a feeling of stress, tension, and fear in situations engaging with math-related tasks. Herein, we utilized Diffusion Magnetic Resonance Imaging (DMRI) connectometry approach to tracking white matter (WM) fibers with a significant correlation with the severity of MA. METHODS: A total of 77 healthy adult participants (50 males, mean age ± SD = 26.00 ± 3.54) were included from the Leipzig Study for Mind-Body-Emotion Interactions (LEMON) database. Abbreviated Math Anxiety Scale (AMAS) questionnaire was used for assessing the participant's feelings when facing a math-related activity. DMRI data were prepared and analyzed with the connectometry approach. Multiple regression models were then carried out to examine the correlation of WM microstructural connectivity with AMAS score. RESULTS: DMRI connectometry showed a significant association between AMAS score and increased microstructural connectivity in left arcuate fasciculus (AF), the body of corpus callosum (CC), right cingulum, and left inferior longitudinal fasciculus (ILF) in male participants with moderate effect size false discovery rate (FDR = 0.040). Furthermore, DMRI connectometry in females identified a positive correlation between AMAS score and microstructural connectivity in the genu of CC, right ILF, and bilateral fornices with small-to-moderate effect size (FDR = 0.012) and a negative correlation between AMAS score and microstructural connectivity in the bilateral cingulum with small-to-moderate effect size (FDR = 0.032) Conclusion: Our findings support that structures with functional relation to language processing areas (e.g., AF) or limbic system (cingulum, CC, fornix, and ILF) play a significant role in MA. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Biofluid Biomarkers in Traumatic Brain Injury: A Systematic Scoping Review.

Emerging evidence suggests that biofluid-based biomarkers have diagnostic and prognostic potential in traumatic brain injuries (TBI). However, owing to the lack of a conceptual framework or comprehensive review, it is difficult to visualize the breadth of materials that might be available. We conducted a systematic scoping review to map and categorize the evidence regarding biofluid-based biochemical markers of TBI. A comprehensive search was undertaken in January 2019. Of 25,354 records identified through the literature search, 1036 original human studies were included. Five hundred forty biofluid biomarkers were extracted from included studies and classified into 19 distinct categories. Three categories of biomarkers including cytokines, coagulation tests, and nerve tissue proteins were investigated more than others and assessed in almost half of the studies (560, 515, and 502 from 1036 studies, respectively). S100 beta as the most common biomarker for TBI was tested in 21.2% of studies (220 articles). Cortisol was the only biomarker measured in blood, cerebrospinal fluid, urine, and saliva. The most common sampling time was at admission and within 24 h of injury. The included studies focused mainly on biomarkers from blood and central nervous system sources, the adult population, and severe and blunt injuries. The most common outcome measures used in studies were changes in biomarker concentration level, Glasgow coma scale, Glasgow outcome scale, brain computed tomography scan, and mortality rate. Biofluid biomarkers could be clinically helpful in the diagnosis and prognosis of TBI. However, there was no single definitive biomarker with accurate characteristics. The present categorization would be a road map to investigate the biomarkers of the brain injury cascade separately and detect the most representative biomarker of each category. Also, this comprehensive categorization could provide a guiding framework to design combined panels of multiple biomarkers.