March 5, 2019 e1 WRITING GROUP MEMBERS Emelia J. Benjamin, MD, ScM, FAHA, Chair Paul Muntner, PhD, MHS, FAHA, Vice Chair Alvaro Alonso, MD, PhD, FAHA Marcio S. Bittencourt, MD, PhD, MPH Clifton W. Callaway, MD, FAHA April P. Carson, PhD, MSPH, FAHA Alanna M. Chamberlain, PhD Alexander R. Chang, MD, MS Susan Cheng, MD, MMSc, MPH, FAHA Sandeep R. Das, MD, MPH, MBA, FAHA Francesca N. Delling, MD, MPH Luc Djousse, MD, ScD, MPH Mitchell S.V. Elkind, MD, MS, FAHA Jane F. Ferguson, PhD, FAHA Myriam Fornage, PhD, FAHA Lori Chaffin Jordan, MD, PhD, FAHA Sadiya S. Khan, MD, MSc Brett M. Kissela, MD, MS Kristen L. Knutson, PhD Tak W. Kwan, MD, FAHA Daniel T. Lackland, DrPH, FAHA Tené T. Lewis, PhD Judith H. Lichtman, PhD, MPH, FAHA Chris T. Longenecker, MD Matthew Shane Loop, PhD Pamela L. Lutsey, PhD, MPH, FAHA Seth S. Martin, MD, MHS, FAHA Kunihiro Matsushita, MD, PhD, FAHA Andrew E. Moran, MD, MPH, FAHA Michael E. Mussolino, PhD, FAHA Martin O’Flaherty, MD, MSc, PhD Ambarish Pandey, MD, MSCS Amanda M. Perak, MD, MS Wayne D. Rosamond, PhD, MS, FAHA Gregory A. Roth, MD, MPH, FAHA Uchechukwu K.A. Sampson, MD, MBA, MPH, FAHA Gary M. Satou, MD, FAHA Emily B. Schroeder, MD, PhD, FAHA Svati H. Shah, MD, MHS, FAHA Nicole L. Spartano, PhD Andrew Stokes, PhD David L. Tirschwell, MD, MS, MSc, FAHA Connie W. Tsao, MD, MPH, Vice Chair Elect Mintu P. Turakhia, MD, MAS, FAHA Lisa B. VanWagner, MD, MSc, FAST John T. Wilkins, MD, MS, FAHA Sally S. Wong, PhD, RD, CDN, FAHA Salim S. Virani, MD, PhD, FAHA, Chair Elect On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association

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Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in a single document the most up-to-date statistics related to heart disease, stroke, and the cardiovascular risk factors listed in the AHA’s My Life Check - Life’s Simple 7 (Figure1), which include core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure [BP], and glucose control) that contribute to cardiovascular health. The Statistical Update represents …

Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association.

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovas...

Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascul...

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association.

A reply to: Challen K. " Early warnings? Please include the ED in your ViEWS"

A reaction indistinguishable from the early dumping syndrome was induced in four of nine normal volunteers by intraduodenal instillation of a hypertonic glucose meal. Tachycardia and marked peripheral vasodilatation were demonstrated in 'dumpers' by Doppler ultrasound measurements of the arterial blood flow signal. The dumping reaction was not detectably altered by the addition of guar to the meal. Plasma VIP concentration rose and plasma volume fell to a similar degree in 'dumpers' and 'non-dumpers', suggesting that neither event is an integral component of the dumping mechanism. In contrast, the rates of rise of blood glucose and enteroglucagon concentration were markedly greater in 'dumpers'. The results are inconsistent with the conventional explanation that the early dumping syndrome is caused by a large osmotic fluid shift, but are compatible with a mechanism involving an initial period of intestinal hypermotility.

Studies on thepathogenesis oftheearly dumping syndrome induced byintraduodenal instillation of hypertonic glucose

Reply to: Performance of the National Early Warning Score in hospitalised patients infected by Covid-19.

citing two inappropriate references. However, Morgan et al. published the first early warning score (EWS) in 1997 and Stenhouse et al. described the first ‘modified’ version (i.e. MEWS) in 2000. Since then, a confusing array of different EWS – many named MEWS (modified EWS) – has been introduced into clinical practice. In 2012, the Royal College of Physicians of London (RCP) developed NEWS, which was based on a minor modification of the VitalPAC EWS (ViEWS). NEWS has greater discrimination for predicting patients at risk an adverse outcome within 24 h than other published EWS systems including the Gardner-Thorpe MEWS used in Garland et al.’s study (c-statistic: NEWS 0.87, Gardner-Thorpe MEWS 0.83). Garland et al. also suggest MEWS has been ‘‘. . . renamed as the National Early Warning Score (NEWS) by NHS England . . .,’’ although this is not supported by the references they cite. We are unaware of any such act. Moreover, as NEWS and the many different versions of MEWS vary in their composition and performance, this would be inappropriate. Garland et al. also state ‘‘. . .Current care pathways for patients in the MEWS systems recommend escalation, if the MEWS rises above 5 . . .,’’ citing the RCP report. It is important to note that different early warning systems vary substantially in terms of how the aggregate score maps to the risk of mortality or other adverse events (e.g. unanticipated ICU admission). Consequently, the score threshold of 55 used to trigger a prompt clinical review of patients recommended by the RCP applies only if NEWS is used. It is also worth noting that the score thresholds suggested for NEWS by the RCP working group were arrived at pragmatically, based on the associated risk of adverse outcomes and the expected workload generated in a single hospital. A balance must always be achieved between the benefits of the early clinical assessment of patients with high/rising EWS values and the disadvantages of ‘‘alarm fatigue.’’ The RCP working group also notes: ‘‘. . . the most effective way to formally evaluate the effectiveness of NEWS at improving clinical outcomes was to implement it into practice and evaluate its performance on a large scale . . .’’ Unfortunately, there are no large-scale evaluations of the impact of using different thresholds to trigger a clinical response.

/pdf/response-to-inpatient-illness-severity-surveys-provide-4rtuvwzc5r.pdf

Response to Inpatient illness severity surveys provide essential data for planning capacity and managing patient flow in the acute hospital setting (J Intensive Care Soc 2016; 17: 196-201).

• LDT-EWS: 0.743 (0.718 to 0.768) (Q10) to 0.799 (0.773 to 0.825) (Q9) • NEWS: 0.704 (0.675 to 0.733) (Q7) to 0.759 (0.732 to 0.786) (Q8) • Combined EWS: 0.799 (0.776 to 0.822) (Q10) to 0.836 (0.813 to 0.861) (Q21) The combined EWS also offered better performance than LDT-EWS or NEWS as measured by an

Combining the National Early Warning Score with an early warning score based on Combining the National Early Warning Score with an early warning score based on common laboratory test results better discriminates patients at risk of hospital common laboratory test results better discriminates patients at risk of hospital mortality mortality

David Prytherch

Papers

A reply to: Challen K. " Early warnings? Please include the ED in your ViEWS"

Studies on thepathogenesis oftheearly dumping syndrome induced byintraduodenal instillation of hypertonic glucose

Reply to: Performance of the National Early Warning Score in hospitalised patients infected by Covid-19.

Response to Inpatient illness severity surveys provide essential data for planning capacity and managing patient flow in the acute hospital setting (J Intensive Care Soc 2016; 17: 196-201).