Plasma levels of D-dimer and fibrin degradation products correlate with bullous pemphigoid severity: a cross-sectional study.

Bullous pemphigoid (BP), the most frequent blistering dermatosis in the elderly, is associated with increased mortality. The severity of BP can be assessed by detecting the anti-BP180 immunoglobulin G (IgG) concentration, but the lab test is not available in many community clinics. BP patients are usually in a hypercoagulable state with increased levels of D-dimer and fibrin degradation products (FDPs). We aimed to evaluate the use of D-dimer and FDPs in assessing BP severity. We compared the levels of plasma D-dimer, plasma FDPs, eosinophil counts, eosinophil cationic protein, and serum anti-BP180 IgG concentration between 48 typical BP patients and 33 Herpes zoster (HZ) patients (control group). Correlational analyses were conducted to determine the relationships between the lab values and common BP severity markers. The plasma D-dimer and FDP levels were higher in BP patients than in HZ controls (D-dimer: 3297 ± 2517 µg/L vs. 569.70 ± 412.40 µg/L; FDP: 9.74 ± 5.88 mg/L vs. 2.02 ± 1.69 mg/L, respectively, P < 0.0001). Significant positive correlations were found between D-dimer/FDP levels and BP severity markers (i.e. anti-BP180 IgG concentration [D-dimer: r = 0.3928, P = 0.0058; FDP: r = 0.4379, P = 0.0019] and eosinophil counts [D-dimer: r = 0.3625, P = 0.0013; FDP: r = 0.2880, P = 0.0472]) in BP patients. We also found an association between FDP and urticaria/erythema lesions (r = 0.3016, P = 0.0372), but no other BPDAI components. In 19 BP patients with complete remission after systemic glucocorticoid treatment, D-dimer and FDP levels decreased post-therapy (D-dimer: 5559 ± 7492 µg/L vs. 1738 ± 1478 µg/L; P < 0.0001; FDP: 11.20 ± 5.88 mg/L vs. 5.13 ± 3.44 mg/L; P = 0.0003), whereas they did not in BP patients with treatment resistant. Plasma D-dimer and FDP are convenient markers to evaluate BP severity assistant on BPDAI and eosinophil counts. FDP is also helpful for inflammatory lesions in BP patients.

Remote Ischemic Postconditioning for Ischemic Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Remote ischemic postconditioning (RIPostC) appears to protect distant organs from ischemia-reperfusion injury (IRI). However, cerebral protection results have remained inconclusive. In the present study, a meta-analysis was performed to compare stroke patients with and without RIPostC. METHODS: CNKI, WanFang, VIP, CBM, PubMed, and Cochrane Library databases were searched up to July 2016. Data were analyzed using both fixed-effects and random-effects models by Review Manager. For each outcome, risk ratio (RR) and mean difference (MD) with 95% confidence interval (CI) were calculated. RESULTS: A total of 13 randomized controlled trials that enrolled a total of 794 study participants who suffered from or are at risk for brain IRI were selected. Compared with controls, RIPostC significantly reduced the recurrence of stroke or transient ischemic attacks (RR = 0.37; 95% CI: 0.26-0.55; P < 0.00001). Moreover, it can reduce the levels of the National Institutes of Health Stroke Scale score (MD: 1.96; 95% CI: 2.18-1.75; P < 0.00001), modified Rankin Scale score (MD: 0.73; 95% CI: 1.20-0.25; P = 0.00300), and high-sensitivity C-reactive protein (MD: 4.17; 95% CI: 4.71-3.62; P < 0.00001) between the two groups. There was no side effect of RIPostC using tourniquet cuff around the limb on ischemic stroke treating based on different intervention duration. CONCLUSION: The present meta-analysis suggests that RIPostC might offer cerebral protection for stroke patients suffering from or are at risk of brain IRI.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.