Assessment of Angiography-Based Renal Quantitative Flow Ratio Measurement in Patients with Atherosclerotic Renal Artery Stenosis.

Background: Quantitative flow ratio (QFR) is an angiography-based fractional flow reserve measurement without pressure wire or induction of hyperemia. A recent innovation that uses combined geometrical data and hemodynamic boundary conditions to measure QFR from a single angiographic view has shown the potential to measure QFR of the renal artery-renal QFR (rQFR). Objective: The aim of this pilot study was to assess the feasibility of rQFR measurement and the contribution of rQFR in selecting patients with atherosclerotic renal artery stenosis (ARAS) undergoing revascularization. Methods: This retrospective trial enrolled patients who had ARAS (50-90%) and hypertension. The enrolled patients were treated by optimal antihypertensive medication or revascularization, respectively, and the therapeutic strategies were based on rFFR measurement and/or clinical feature. Results: A total of 55 patients underwent rQFR measurement. Among the enrolled patients, 18 underwent optimal antihypertensive medication and 37 underwent revascularization, 19 patients in whom rQFR and rFFR were both assessed. During the 180-day follow-up, 25 patients saw an improvement in their blood pressure among the 37 patients that underwent revascularization. ROC analysis revealed that rQFR had a high diagnostic accuracy for predicting blood pressure improvement (AUCrQFR = 0.932, 95% CI 0.798-0.998). The ideal cut-off value of rQFR for predicting blood pressure improvement after revascularization is ≤0.72 (sensitivity: 72.00%, specificity: 100%). The paired t test and Bland-Altman analyses demonstrated good agreement between rQFR and rFFR (t = 1.887, 95% CI -0.021 to 0.001, 95% limits of agreement: -0.035 to 0.055, p = 0.075). The Spearman correlation test reveals that there was a significant positive correlation between rQFR and rFFR (r = 0.952, 95% CI 0.874 to 0.982, p < 0.001). Conclusion: The rQFR has the potential to enhance the ability of angiography to detect functionally significant renal artery stenosis during angiography and to produce results that are comparable to invasive hemodynamic assessment.

Assessment of anti-desmoglein antibodies levels and other laboratory indexes as objective comprehensive indicators of patients with pemphigus vulgaris of different severity: a single-center retrospective study.

The aim of this study is to assess the utility of anti-desmoglein (Dsg) antibodies levels, hematological biomarkers levels, the albumin to globulin (A/G) ratio, blood lipids levels, and lymphocyte subpopulation percentages as objective laboratory indicators of disease severity of pemphigus vulgaris (PV). A retrospective study of 187 PV patients with 256 medical records between January 2013 and December 2020. PV patients were divided into three groups by disease severity according to the pemphigus disease area index (PDAI) score: mild (0-8), moderate (9-24), and severe (≥ 25). The levels of anti-Dsg antibodies, hematological biomarkers, A/G ratio, blood lipids, and the percentage of lymphocyte subpopulations were measured. We assessed the correlations of quantitative variables by Pearson correlation (r). Multivariable linear regression was used to identify the variables associated with the disease severity of PV (PDAI score). The results show that the levels of Dsg1 (r = 0.294, P < 0.001) and Dsg3 (r = 0.206, P = 0.011), monocyte count (r = 0.210, P = 0.001), neutrophil-to-lymphocyte ratio (NLR) (r = 0.123, P = 0.049), and platelet-to-lymphocyte ratio (PLR) (r = 0.170, P = 0.006) were positively correlated with the PDAI score. However, the A/G ratio (r = - 0.399, P < 0.001), and the levels of total serum cholesterol (r = - 0.140, P = 0.026) and HDL (r = - 0.143, P = 0.023) were negatively correlated with the PDAI score. Multiple linear regression showed that the factors associated with the PDAI score were higher level of anti-Dsg1 antibody (P = 0.001), a higher NLR (P = 0.005), and a lower A/G ratio (P < 0.001). The linear regression equation was Y(PDAI) = 32.798 + 0.058X(Dsg1) + 0.846 X(NLR)-16.472 X(A/G) (R2 = 0.586). Therefore, high levels of anti-Dsg1 antibody and NLR combined with a low A/G ratio could explain the PDAI score. These findings might provide a more comprehensive and objective evaluation system for reflecting the disease severity of PV based on laboratory indicators.

Comparison of a Virtual Older Driver Assessment with an On-Road Driving Test.

OBJECTIVES: To design a low-cost simulator-based driving assessment for older adults and to compare its validity with that of an on-road driving assessment and other measures of older driver risk. DESIGN: Cross-sectional observational study. SETTING: Canberra, Australia. PARTICIPANTS: Older adult drivers (N = 47; aged 65-88, mean age 75.2). MEASUREMENTS: Error rate on a simulated drive with environment and scoring procedure matched to those of an on-road test. Other measures included participant age, simulator sickness severity, neuropsychological measures, and driver screening measures. Outcome variables included occupational therapist (OT)-rated on-road errors, on-road safety rating, and safety category. RESULTS: Participants' error rate on the simulated drive was significantly correlated with their OT-rated driving safety (correlation coefficient (r) = -0.398, P = .006), even after adjustment for age and simulator sickness (P = .009). The simulator error rate was a significant predictor of categorization as unsafe on the road (P = .02, sensitivity 69.2%, specificity 100%), with 13 (27%) drivers assessed as unsafe. Simulator error was also associated with other older driver safety screening measures such as useful field of view (r = 0.341, P = .02), DriveSafe (r = -0.455, P < .01), and visual motion sensitivity (r = 0.368, P = .01) but was not associated with memory (delayed word recall) or global cognition (Mini-Mental State Examination). Drivers made twice as many errors on the simulated assessment as during the on-road assessment (P < .001), with significant differences in the rate and type of errors between the two mediums. CONCLUSION: A low-cost simulator-based assessment is valid as a screening instrument for identifying at-risk older drivers but not as an alternative to on-road evaluation when accurate data on competence or pattern of impairment is required for licensing decisions and training programs.