Bi-directional association between depression and HF: An electronic health records-based cohort study.

To determine whether a bi-directional relationship exists between depression and HF within a single population of individuals receiving primary care services, using longitudinal electronic health records (EHRs). This retrospective cohort study utilized EHRs for adults who received primary care services within a large healthcare system in 2006. Validated EHR-based algorithms identified 10,649 people with depression (depression cohort) and 5,911 people with HF (HF cohort) between January 1, 2006 and December 31, 2018. Each person with depression or HF was matched 1:1 with an unaffected referent on age, sex, and outpatient service use. Each cohort (with their matched referents) was followed up electronically to identify newly diagnosed HF (in the depression cohort) and depression (in the HF cohort) that occurred after the index diagnosis of depression or HF, respectively. The risks of these outcomes were compared (vs. referents) using marginal Cox proportional hazard models adjusted for 16 comorbid chronic conditions. 2,024 occurrences of newly diagnosed HF were observed in the depression cohort and 944 occurrences of newly diagnosed depression were observed in the HF cohort over approximately 4-6 years of follow-up. People with depression had significantly increased risk for developing newly diagnosed HF (HR 2.08, 95% CI 1.89-2.28) and people with HF had a significantly increased risk of newly diagnosed depression (HR 1.34, 95% CI 1.17-1.54) after adjusting for all 16 comorbid chronic conditions. These results provide evidence of a bi-directional relationship between depression and HF independently of age, sex, and multimorbidity from chronic illnesses

Recommendations for cardiovascular health and disease surveillance for 2030 and beyond: A policy statement from the american heart association

The release of the American Heart Association's 2030 Impact Goal and associated metrics for success underscores the importance of cardiovascular health and cardiovascular disease surveillance systems for the acquisition of information sufficient to support implementation and evaluation. The aim of this policy statement is to review and comment on existing recommendations for and current approaches to cardiovascular surveillance, identify gaps, and formulate policy implications and pragmatic recommendations for transforming surveillance of cardiovascular disease and cardiovascular health in the United States. The development of community platforms coupled with widespread use of digital technologies, electronic health records, and mobile health has created new opportunities that could greatly modernize surveillance if coordinated in a pragmatic matter. However, technology and public health and scientific mandates must be merged into action. We describe the action and components necessary to create the cardiovascular health and cardiovascular disease surveillance system of the future, steps in development, and challenges that federal, state, and local governments will need to address. Development of robust policies and commitment to collaboration among professional organizations, community partners, and policy makers are critical to ultimately reduce the burden of cardiovascular disease and improve cardiovascular health and to evaluate whether national health goals are achieved

Randomized controlled trial of a lay-facilitated angina management programme

AIMS: This article reports a randomized controlled trial of lay-facilitated angina management (registered trial acronym: LAMP). BACKGROUND: Previously, a nurse-facilitated angina programme was shown to reduce angina while increasing physical activity, however most people with angina do not receive a cardiac rehabilitation or self-management programme. Lay people are increasingly being trained to facilitate self-management programmes. DESIGN: A randomized controlled trial comparing a lay-facilitated angina management programme with routine care from an angina nurse specialist. METHODS: Participants with new stable angina were randomized to the angina management programme (intervention: 70 participants) or advice from an angina nurse specialist (control: 72 participants). Primary outcome was angina frequency at 6 months; secondary outcomes at 3 and 6 months included: risk factors, physical functioning, anxiety, depression, angina misconceptions and cost utility. Follow-up was complete in March 2009. Analysis was by intention-to-treat; blind to group allocation. RESULTS: There was no important difference in angina frequency at 6 months. Secondary outcomes, assessed by either linear or logistic regression models, demonstrated important differences favouring the intervention group, at 3 months for: Anxiety, angina misconceptions and for exercise report; and at 6 months for: Anxiety; Depression; and angina misconceptions. The intervention was considered cost-effective. CONCLUSION: The angina management programme produced some superior benefits when compared to advice from a specialist nurse

Biology, Fishery, Conservation and Management of Indian Ocean Tuna Fisheries

The focus of the study is to explore the recent trend of the world tuna fishery with special reference to the Indian Ocean tuna fisheries and its conservation and sustainable management. In the Indian Ocean, tuna catches have increased rapidly from about 179959 t in 1980 to about 832246 t in 1995. They have continued to increase up to 2005; the catch that year was 1201465 t, forming about 26% of the world catch. Since 2006 onwards there has been a decline in the volume of catches and in 2008 the catch was only 913625 t. The Principal species caught in the Indian Ocean are skipjack and yellowfin. Western Indian Ocean contributed 78.2% and eastern Indian Ocean 21.8% of the total tuna production from the Indian Ocean. The Indian Ocean stock is currently overfished and IOTC has made some recommendations for management regulations aimed at sustaining the tuna stock. Fishing operations can cause ecological impacts of different types: by catches, damage of the habitat, mortalities caused by lost or discarded gear, pollution, generation of marine debris, etc. Periodic reassessment of the tuna potential is also required with adequate inputs from exploratory surveys as well as commercial landings and this may prevent any unsustainable trends in the development of the tuna fishing industry in the Indian Ocean

Stress testing and non-invasive coronary angiography in patients with suspected coronary artery disease: time for a new paradigm

Diagnosis and management of coronary artery disease represents major challenges to our health care system, affecting millions of patients each year. Until recently, the diagnosis of coronary artery disease was possible only through cardiac catheterization and invasive coronary angiography. To avoid the risks of an invasive procedure, stress testing is often employed for an initial assessment of patients with suspected coronary artery disease, serving as a gatekeeper for cardiac catheterization. With the emergence of non-invasive coronary angiography, the question arises if such a strategy is still sensible, particularly, in view of only a modest agreement between stress testing results and the presence of coronary artery disease established by cardiac catheterization. Much data in support of the diagnostic accuracy and prognostic value of non-invasive coronary angiography by computed tomography have emerged within the last few years. These data challenge the role of stress testing as the initial imaging modality in patients with suspected coronary artery disease. This article reviews the clinical utility, limitations, as well as the hazards of stress testing compared with non-invasive coronary artery imaging by computed tomography. Finally, the implications of this review are discussed in relation to clinical practice

Taxonomy based on science is necessary for global conservation

Peer reviewe

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories