Development of automated neural network prediction for echocardiographic left ventricular ejection fraction

Introduction: The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification of patients with heart failure (HF).Methods: This paper aimed to quantify LVEF automatically and accurately with the proposed pipeline method based on deep neural networks and ensemble learning. Within the pipeline, an Atrous Convolutional Neural Network (ACNN) was first trained to segment the left ventricle (LV), before employing the area-length formulation based on the ellipsoid single-plane model to calculate LVEF values. This formulation required inputs of LV area, derived from segmentation using an improved Jeffrey’s method, as well as LV length, derived from a novel ensemble learning model. To further improve the pipeline’s accuracy, an automated peak detection algorithm was used to identify end-diastolic and end-systolic frames, avoiding issues with human error. Subsequently, single-beat LVEF values were averaged across all cardiac cycles to obtain the final LVEF.Results: This method was developed and internally validated in an open-source dataset containing 10,030 echocardiograms. The Pearson’s correlation coefficient was 0.83 for LVEF prediction compared to expert human analysis (p < 0.001), with a subsequent area under the receiver operator curve (AUROC) of 0.98 (95% confidence interval 0.97 to 0.99) for categorisation of HF with reduced ejection (HFrEF; LVEF<40%). In an external dataset with 200 echocardiograms, this method achieved an AUC of 0.90 (95% confidence interval 0.88 to 0.91) for HFrEF assessment.Conclusion: The automated neural network-based calculation of LVEF is comparable to expert clinicians performing time-consuming, frame-by-frame manual evaluations of cardiac systolic function

Glycine supplementation extends lifespan of male and female mice.

Diets low in methionine extend lifespan of rodents, though through unknown mechanisms. Glycine can mitigate methionine toxicity, and a small prior study has suggested that supplemental glycine could extend lifespan of Fischer 344 rats. We therefore evaluated the effects of an 8% glycine diet on lifespan and pathology of genetically heterogeneous mice in the context of the Interventions Testing Program. Elevated glycine led to a small (4%-6%) but statistically significant lifespan increase, as well as an increase in maximum lifespan, in both males (p = 0.002) and females (p \u3c 0.001). Pooling across sex, glycine increased lifespan at each of the three independent sites, with significance at p = 0.01, 0.053, and 0.03, respectively. Glycine-supplemented females were lighter than controls, but there was no effect on weight in males. End-of-life necropsies suggested that glycine-treated mice were less likely than controls to die of pulmonary adenocarcinoma (p = 0.03). Of the 40 varieties of incidental pathology evaluated in these mice, none were increased to a significant degree by the glycine-supplemented diet. In parallel analyses of the same cohort, we found no benefits from TM5441 (an inhibitor of PAI-1, the primary inhibitor of tissue and urokinase plasminogen activators), inulin (a source of soluble fiber), or aspirin at either of two doses. Our glycine results strengthen the idea that modulation of dietary amino acid levels can increase healthy lifespan in mice, and provide a foundation for further investigation of dietary effects on aging and late-life diseases

Glycine supplementation extends lifespan of male and female mice.

Diets low in methionine extend lifespan of rodents, though through unknown mechanisms. Glycine can mitigate methionine toxicity, and a small prior study has suggested that supplemental glycine could extend lifespan of Fischer 344 rats. We therefore evaluated the effects of an 8% glycine diet on lifespan and pathology of genetically heterogeneous mice in the context of the Interventions Testing Program. Elevated glycine led to a small (4%-6%) but statistically significant lifespan increase, as well as an increase in maximum lifespan, in both males (p = 0.002) and females (p \u3c 0.001). Pooling across sex, glycine increased lifespan at each of the three independent sites, with significance at p = 0.01, 0.053, and 0.03, respectively. Glycine-supplemented females were lighter than controls, but there was no effect on weight in males. End-of-life necropsies suggested that glycine-treated mice were less likely than controls to die of pulmonary adenocarcinoma (p = 0.03). Of the 40 varieties of incidental pathology evaluated in these mice, none were increased to a significant degree by the glycine-supplemented diet. In parallel analyses of the same cohort, we found no benefits from TM5441 (an inhibitor of PAI-1, the primary inhibitor of tissue and urokinase plasminogen activators), inulin (a source of soluble fiber), or aspirin at either of two doses. Our glycine results strengthen the idea that modulation of dietary amino acid levels can increase healthy lifespan in mice, and provide a foundation for further investigation of dietary effects on aging and late-life diseases

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

Abstract: Objective: To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust. Design: Data resource comprising linked person level records from national healthcare settings for the English population, accessible within NHS Digital’s new trusted research environment. Setting: EHRs from primary care, hospital episodes, death registry, covid-19 laboratory test results, and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular, and covid-19 vaccination data. Participants: 54.4 million people alive on 1 January 2020 and registered with an NHS general practitioner in England. Main measures of interest: Confirmed and suspected covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack and incident myocardial infarction) and all cause mortality between 1 January and 31 October 2020. Results: The linked cohort includes more than 96% of the English population. By combining person level data across national healthcare settings, data on age, sex, and ethnicity are complete for around 95% of the population. Among 53.3 million people with no previous diagnosis of stroke or transient ischaemic attack, 98 721 had a first ever incident stroke or transient ischaemic attack between 1 January and 31 October 2020, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.2 million people with no previous diagnosis of myocardial infarction, 62 966 had an incident myocardial infarction during follow-up, of which 8% were recorded only in primary care and 12% only in death registry records. A total of 959 470 people had a confirmed or suspected covid-19 diagnosis (714 162 in primary care data, 126 349 in hospital admission records, 776 503 in covid-19 laboratory test data, and 50 504 in death registry records). Although 58% of these were recorded in both primary care and covid-19 laboratory test data, 15% and 18%, respectively, were recorded in only one. Conclusions: This population-wide resource shows the importance of linking person level data across health settings to maximise completeness of key characteristics and to ascertain cardiovascular events and covid-19 diagnoses. Although this resource was initially established to support research on covid-19 and cardiovascular disease to benefit clinical care and public health and to inform healthcare policy, it can broaden further to enable a wide range of research

Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource

Abstract: Objective: To describe a novel England-wide electronic health record (EHR) resource enabling whole population research on covid-19 and cardiovascular disease while ensuring data security and privacy and maintaining public trust. Design: Data resource comprising linked person level records from national healthcare settings for the English population, accessible within NHS Digital’s new trusted research environment. Setting: EHRs from primary care, hospital episodes, death registry, covid-19 laboratory test results, and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular, and covid-19 vaccination data. Participants: 54.4 million people alive on 1 January 2020 and registered with an NHS general practitioner in England. Main measures of interest: Confirmed and suspected covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack and incident myocardial infarction) and all cause mortality between 1 January and 31 October 2020. Results: The linked cohort includes more than 96% of the English population. By combining person level data across national healthcare settings, data on age, sex, and ethnicity are complete for around 95% of the population. Among 53.3 million people with no previous diagnosis of stroke or transient ischaemic attack, 98 721 had a first ever incident stroke or transient ischaemic attack between 1 January and 31 October 2020, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.2 million people with no previous diagnosis of myocardial infarction, 62 966 had an incident myocardial infarction during follow-up, of which 8% were recorded only in primary care and 12% only in death registry records. A total of 959 470 people had a confirmed or suspected covid-19 diagnosis (714 162 in primary care data, 126 349 in hospital admission records, 776 503 in covid-19 laboratory test data, and 50 504 in death registry records). Although 58% of these were recorded in both primary care and covid-19 laboratory test data, 15% and 18%, respectively, were recorded in only one. Conclusions: This population-wide resource shows the importance of linking person level data across health settings to maximise completeness of key characteristics and to ascertain cardiovascular events and covid-19 diagnoses. Although this resource was initially established to support research on covid-19 and cardiovascular disease to benefit clinical care and public health and to inform healthcare policy, it can broaden further to enable a wide range of research

Drs. David and Es Nash Awards Ceremony.

Various Jefferson learners who demonstrated innovation and dedication to improving the safety and quality of care were recognized with the Drs. David and Es Nash Safety and Quality awards. In addition, the very first Ira Brind Platinum Glove Award was also given to Jefferson Health employees who demonstrated their commitment to making our patient’s lives safer everyday through the OnPoint Great Catch Program

Live-Action Role-Playing Games

© 2018 Taylor & Francis Group. All rights reserved. This is the accepted manuscript version of a book chapter which has been published in final form at https://www.routledge.com/Role-Playing-Game-Studies-Transmedia-Foundations/Deterding-Zagal/p/book/9780815369202Peer reviewe