128 research outputs found

    Protein Diet Restriction Slows Chronic Kidney Disease Progression in Non-Diabetic and in Type 1 Diabetic Patients, but Not in Type 2 Diabetic Patients: A Meta-Analysis of Randomized Controlled Trials Using Glomerular Filtration Rate as a Surrogate

    No full text
    <div><p>Background/ Objective</p><p>Studies, including various meta-analyses, on the effect of Protein Diet Restriction on Glomerular Filtration Rate (GFR) in Chronic Kidney Disease (CKD) have reported conflicting results. In this paper, we have provided an update on the evidence available on this topic. We have investigated the reasons why the effect has been inconsistent across studies. We have also compared the effect on GFR in various subgroups including type 1 diabetics, type 2 diabetics and non-diabetics.</p><p>Method</p><p>We searched for Randomized Controlled Trials on this intervention from MEDLINE, EMBASE, and other information sources. The PRISMA guidelines, as well as recommended meta-analysis practices were followed in the selection process, analysis and reporting of our findings. The effect estimate used was the change in mean GFR. Heterogeneity across the considered studies was explored using both subgroup analyses and meta-regression. Quality assessment was done using the Cochrane risk of bias tool and sensitivity analyses.</p><p>Results</p><p>15 randomized controlled trials, including 1965 subjects, were analyzed. The pooled effect size, as assessed using random-effects model, for all the 15 studies was -0.95 ml/min/1.73m<sup>2</sup>/year (95% CI: -1.79, -0.11), with a significant p value of 0.03. The combined effect estimate for the non-diabetic and type 1 diabetic studies was -1.50 ml/min/1.73m<sup>2</sup>/year (95% CI: -2.73, -0.26) with p value of 0.02. The effect estimate for the type 2 diabetic group was -0.17 ml/min/1.73m<sup>2</sup>/year (95% CI: -1.88, 1.55) with p value of 0.85. There was significant heterogeneity across the included studies (I<sup>2</sup> = 74%, p value for Q < 0.0001), explained by major variations in the percentage of type 2 diabetic subjects, the number of subjects and overall compliance level to diet prescribed.</p><p>Conclusion</p><p>Our findings suggest that protein diet restriction slows chronic renal disease progression in non-diabetic and in type 1 diabetic patients, but not in type 2 diabetic patients.</p></div

    The PRISMA flow diagram for the study selection process.

    No full text
    <p>From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(6): e1000097. doi:<a href="http://dx.doi.org/10.1371/journal.pmed1000097" target="_blank">10.1371/journal.pmed1000097</a>.</p

    Forest Plot of all the included studies <sup>a</sup>.

    No full text
    <p>The forest plot for all included studies pooled together using a random-effects model. <sup>a</sup> em, mean decline in experimental group; es, standard deviation in experimental group; en, number of subjects in experimental group; cm, mean decline in control group; cs, standard deviation in control group; cn, number of subjects in control group, MD, mean difference; I2, variability due to heterogeneity; Q, chi-square test; K, number of included studies.</p

    Non-volatile Reconfigurable Digital Optical Diffractive Neural Network Based on Phase Change Material

    No full text
    Optical diffractive neural networks have triggered extensive research with their low power consumption and high speed in image processing. In this work, we propose a reconfigurable digital all-optical diffractive neural network (R-ODNN) structure. The optical neurons are built with Sb2Se3 phase-change material, making our network reconfigurable, digital, and non-volatile. Using three digital diffractive layers with 14,400 neurons on each and 10 photodetectors connected to a resistor network, our model achieves 94.46% accuracy for handwritten digit recognition. We also performed full-vector simulations and discussed the impact of errors to demonstrate the feasibility and robustness of the R-ODNN

    S1 Appendix -

    No full text
    With the advancement of touch screen technology, the application of touch screens in civil aircraft cockpits has become increasingly popular. However, further analysis and research are required to fully promote its applications. The paper researched the usability of touch screens in aircraft cockpit considering the operation performance and subjective NASA-TLX workload evaluation, conducted experimental research on three touch gestures: click, drag, and zoom. Additionally, a comparative analysis was conducted on the touch performance under different layouts, positions, touch sizes, dragging direction angles, and zoom multiples. The touch performance indicators include operation time, error rate, operation speed, and workload. The experimental results show that the 21 mm size has the minimum operation time and workload, and 18 mm size has the lowest error rate in the clicking tasks. Additionally, the performance and workload of the captain’s layout are better than those of the co-pilot’s layout, and the performance of the center console position is best. The operation speed of the dragging tasks is faster when performed at position R3 compared to other positions. The dragging moving angles with better operation speed are 80°-190° and 250°-290°. The operation performance and workload of the zooming tasks vary depending on the zoom multiples. As the multiple increases, the operation time and workload also increase. There is no difference in operation performance or workload between zooming in and zooming out. The paper provides experimental support and suggestions based on human operation and subjective NASA-TLX workload evaluation for the application of touch screens in civil aircraft cockpits.</div

    Additional file 7 of Serum cystatin C is associated with the prognosis in acute myocardial infarction patients after coronary revascularization: a systematic review and meta-analysis

    No full text
    Additional file 7. Fig. S5: The forest plot of subgroup analysis according to the study size for serum cystatin C contributes for the MACE risk of AMI patients after coronary revascularization
    corecore