Objective To assess the accuracy of expert neurosonography (two-and three-dimensional NSG)

Objectives

Qualitative and quantitative QC monitoring was feasible and highly reproducible in a large multicenter research study, which facilitated the production of high-quality ultrasound images. We recommend that the QC system we developed is implemented in future research studies and clinical practice. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

BackgroundThe independent prognostic impact of diabetes mellitus (DM) and prediabetes mellitus (pre‐DM) on survival outcomes in patients with chronic heart failure has been investigated in observational registries and randomized, clinical trials, but the results have been often inconclusive or conflicting. We examined the independent prognostic impact of DM and pre‐DM on survival outcomes in the GISSI‐HF (Gruppo Italiano per lo Studio della Sopravvivenza nella Insufficienza Cardiaca‐Heart Failure) trial.Methods and ResultsWe assessed the risk of all‐cause death and the composite of all‐cause death or cardiovascular hospitalization over a median follow‐up period of 3.9 years among the 6935 chronic heart failure participants of the GISSI‐HF trial, who were stratified by presence of DM (n=2852), pre‐DM (n=2013), and non‐DM (n=2070) at baseline. Compared with non‐DM patients, those with DM had remarkably higher incidence rates of all‐cause death (34.5% versus 24.6%) and the composite end point (63.6% versus 54.7%). Conversely, both event rates were similar between non‐DM patients and those with pre‐DM. Cox regression analysis showed that DM, but not pre‐DM, was associated with an increased risk of all‐cause death (adjusted hazard ratio, 1.43; 95% CI, 1.28–1.60) and of the composite end point (adjusted hazard ratio, 1.23; 95% CI, 1.13–1.32), independently of established risk factors. In the DM subgroup, higher hemoglobin A1c was also independently associated with increased risk of both study outcomes (all‐cause death: adjusted hazard ratio, 1.21; 95% CI, 1.02–1.43; and composite end point: adjusted hazard ratio, 1.14; 95% CI, 1.01–1.29, respectively).ConclusionsPresence of DM was independently associated with poor long‐term survival outcomes in patients with chronic heart failure.Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00336336.

The findings of this study suggest that protocol-based management of SGA babies may improve outcome, and that identification of moderate SGA should not in isolation prompt delivery. Larger numbers are required to assess any impact on perinatal mortality. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

No abstract

The first trimester fetal ultrasound scan is important to confirm fetal viability, to estimate the gestational age of the fetus, and to detect fetal anomalies early in pregnancy. First trimester ultrasound images have a different appearance than for the second trimester scan, reflecting the different stage of fetal development. There is limited literature on automation of image-based assessment for this earlier trimester, and most of the literature is focused on one specific fetal anatomy. In this paper, we consider automation to support first trimester fetal assessment of multiple fetal anatomies including both visualization and the measurements from a single 3-D ultrasound scan. We present a deep learning and image processing solution i) to perform semantic segmentation of the whole fetus, ii) to estimate plane orientation for standard biometry views, iii) to localize and automatically estimate biometry, and iv) to detect fetal limbs from a 3-D first trimester volume. Computational analysis methods were built using a real-world dataset (n=44 volumes). An evaluation on a further independent clinical dataset (n=21 volumes) showed that the automated methods approached human expert assessment of a 3D volume.

CondensationAfter first-and second-trimester screening, during routine third-trimester growth scans, a previously undiagnosed fetal malformation is incidentally identified in approximately 1 in 300 women. Short title Third-trimester malformations AJOG at a GlanceA. Why was the study conducted ?• Third-trimester growth scans are increasingly offered. Incidental fetal malformations detected during routine third-trimester growth scan are rarely discussed B. What are the key findings?• After first-and second-trimester screening, during routine third-trimester growth scans performed by sonographers, a previously undiagnosed fetal malformation is incidentally identified in approximately 1 in 300 women • The majority of malformations detected at routine third-trimester growth scans are renal, and these are most likely to present spontaneous postnatal resolution C. What does this study add to what is already known?• Unexpected diagnosed of a fetal malformation at the third-trimester is infrequent • Management changing malformations are rarely identified at a routine third-trimester growth scan