Side effects and treatment initiation barriers of sodium-glucose cotransporter 2 inhibitors in heart failure: a systematic review and meta-analysis

Aims Physicians are sometimes reluctant to initiate guideline-directed therapy in patients with heart failure and reduced ejection fraction (HFrEF) due to concerns of adverse events. We explored the risk of hypotension, volume depletion, and acute kidney injury (AKI) on sodium–glucose cotransporter 2 (SGLT2) inhibitors in HFrEF populations. Methods and results We determined summary risk ratios (RRs) by conducting a meta-analysis on reported aforementioned adverse events on SGLT2 inhibitors from randomized controlled trials. We explored robustness of meta-analyses by computing fragility and/or reverse fragility index (FI or RFI) and its corresponding fragility quotient (FQ or RFQ) for each outcome. A total of 10 050 patients with HFrEF entered the final meta-analysis. Hypotension was reported in 4.5% (219/4836) on SGLT2 inhibitors and in 4.1% (202/4846) on placebo (RR 1.09, 95% confidence interval [CI] 0.91–1.31, p = 0.36). An RFI of 21 and RFQ of 0.002 suggest robust findings for hypotension. Volume depletion occurred in 9.4% (473/5019) on SGLT2 inhibitors and in 8.7% (438/5031) on placebo (RR 1.07, 95% CI 0.95–1.21, p = 0.25), respectively. RFI of 19 and RFQ of 0.001 suggest moderately robust findings for volume depletion. AKI was reported in fewer patients (1.9% [95/4888]) on SGLT2 inhibitors than on placebo (2.8% [140/4899]) providing lower incidence of AKI (RR 0.69, 95% CI 0.51–0.93, p = 0.02). FI of 14 and RFQ of 0.001 suggest moderately robust findings for AKI. Conclusion Sodium–glucose cotransporter 2 inhibitor therapy is not associated with a clinically relevant risk of hypotension and volume depletion. Its use reduces the risk of AKI. This analysis supports current guideline recommendations on early use of SGLT2 inhibitors

Characterization of maximally random jammed sphere packings: Voronoi correlation functions

We characterize the structure of maximally random jammed (MRJ) sphere packings by computing the Minkowski functionals (volume, surface area, and integrated mean curvature) of their associated Voronoi cells. The probability distribution functions of these functionals of Voronoi cells in MRJ sphere packings are qualitatively similar to those of an equilibrium hard-sphere liquid and partly even to the uncorrelated Poisson point process, implying that such local statistics are relatively structurally insensitive. This is not surprising because the Minkowski functionals of a single Voronoi cell incorporate only local information and are insensitive to global structural information. To improve upon this, we introduce descriptors that incorporate nonlocal information via the correlation functions of the Minkowski functionals of two cells at a given distance as well as certain cell-cell probability density functions. We evaluate these higher-order functions for our MRJ packings as well as equilibrium hard spheres and the Poisson point process. We find strong anticorrelations in the Voronoi volumes for the hyperuniform MRJ packings, consistent with previous findings for other pair correlations [A. Donev et al., Phys. Rev. Lett. 95, 090604 (2005)], indicating that large-scale volume fluctuations are suppressed by accompanying large Voronoi cells with small cells, and vice versa. In contrast to the aforementioned local Voronoi statistics, the correlation functions of the Voronoi cells qualitatively distinguish the structure of MRJ sphere packings (prototypical glasses) from that of the correlated equilibrium hard-sphere liquids. Moreover, while we did not find any perfect icosahedra (the locally densest possible structure in which a central sphere contacts 12 neighbors) in the MRJ packings, a preliminary Voronoi topology analysis indicates the presence of strongly distorted icosahedra.Comment: 13 pages, 10 figure

Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.

PurposeTo assess feasibility of training a convolutional neural network (CNN) to automate liver segmentation across different imaging modalities and techniques used in clinical practice and apply this to enable automation of liver biometry.MethodsWe trained a 2D U-Net CNN for liver segmentation in two stages using 330 abdominal MRI and CT exams acquired at our institution. First, we trained the neural network with non-contrast multi-echo spoiled-gradient-echo (SGPR)images with 300 MRI exams to provide multiple signal-weightings. Then, we used transfer learning to generalize the CNN with additional images from 30 contrast-enhanced MRI and CT exams.We assessed the performance of the CNN using a distinct multi-institutional data set curated from multiple sources (n = 498 subjects). Segmentation accuracy was evaluated by computing Dice scores. Utilizing these segmentations, we computed liver volume from CT and T1-weighted (T1w) MRI exams, and estimated hepatic proton- density-fat-fraction (PDFF) from multi-echo T2*w MRI exams. We compared quantitative volumetry and PDFF estimates between automated and manual segmentation using Pearson correlation and Bland-Altman statistics.ResultsDice scores were 0.94 ± 0.06 for CT (n = 230), 0.95 ± 0.03 (n = 100) for T1w MR, and 0.92 ± 0.05 for T2*w MR (n = 169). Liver volume measured by manual and automated segmentation agreed closely for CT (95% limit-of-agreement (LoA) = [-298 mL, 180 mL]) and T1w MR (LoA = [-358 mL, 180 mL]). Hepatic PDFF measured by the two segmentations also agreed closely (LoA = [-0.62%, 0.80%]).ConclusionsUtilizing a transfer-learning strategy, we have demonstrated the feasibility of a CNN to be generalized to perform liver segmentations across different imaging techniques and modalities. With further refinement and validation, CNNs may have broad applicability for multimodal liver volumetry and hepatic tissue characterization

Evaluation of an anthropomorphic user interface in a travel reservation context and affordances

This paper describes an experiment and its results concerning research that has been going on for a number ofyears in the area of anthropomorphic user interface feedback. The main aims of the research have been to examine theeffectiveness and user satisfaction of anthropomorphic feedback in various domains. The results are of use to all interactivesystems designers, particularly when dealing with issues of user interface feedback design. There is currently somedisagreement amongst computer scientists concerning the suitability of such types of feedback. This research is working toresolve this disagreement. The experiment detailed, concerns the specific software domain of Online Factual Delivery in thespecific context of online hotel bookings. Anthropomorphic feedback was compared against an equivalent non-anthropomorphicfeedback. Statistically significant results were obtained suggesting that the non-anthropomorphic feedback was more effective.The results for user satisfaction were however less clear. The results obtained are compared with previous research. Thissuggests that the observed results could be due to the issue of differing domains yielding different results. However the resultsmay also be due to the affordances at the interface being more facilitated in the non-anthropomorphic feedback

The Efficacy of Proclarix to Select Appropriate Candidates for Magnetic Resonance Imaging and Derived Prostate Biopsies in Men with Suspected Prostate Cancer

Diagnosis; Proclarix; Prostate cancerDiagnóstico; Proclarix; Cáncer de próstataDiagnòstic; Proclarix; Càncer de pròstataPurpose To analyze how Proclarix is valuable to appropriately select candidates for multiparametric magnetic resonance imaging (mpMRI) and derived biopsies, among men with suspected prostate cancer (PCa). Proclarix is a new marker computing the clinically significant PCa (csPCa) risk, based on serum thosmbospondin-1, cathepsin D, prostate-specific antigen (PSA) and percent free PSA, in addition to age, that has been developed in men with serum PSA 2 to 10 ng/mL, prostate volume ≥35 mL, and normal digital rectal examination (DRE). Materials and Methods Proclarix score (0%–100%) is analyzed in a prospective frozen serum collection of 517 correlative men scheduled for guided and/or systematic biopsies after mpMRI. Outcome variables were csPCa detection (grade group ≥2), insignificant PCa (iPCa) overdetection and avoided mpMRIs. Results The area under the curve of Proclarix was 0.701 (95% CI 0.637–0.765) among 281 men with serum PSA 2 to 10 ng/mL, prostate volume ≥35 mL, and -normal DRE, and 0.754 (95% CI 0.701–0.807) in the others, p=0.038. Net benefit of Proclarix existed in all men. After selecting 10% threshold, Proclarix was integrated in an algorithm which also used the serum PSA level and DRE. A reduction of 25.4% of mpMRIs request was observed and 17.7% of prostate biopsies. Overdetection of iPCa was reduced in 18.2% and 2.6% of csPCa were misdiagnosed. Conclusions Proclarix is valuable in all men with suspected PCa. An algorithm integrating Proclarix score, serum PSA, and DRE can avoid mpMRI requests, unnecessary prostate biopsies and iPCa overdetection, with minimal loss of csPCa detection

Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm