One year of the pandemic - how European endocrinologists responded to the crisis: a statement from the European Society of Endocrinology.

Changes that COVID-19 induced in endocrine daily practice as well as the role of endocrine and metabolic comorbidities in COVID-19 outcomes were among the striking features of this last year. The aim of this statement is to illustrate the major characteristics of the response of European endocrinologists to the pandemic including the disclosure of the endocrine phenotype of COVID-19 with diabetes, obesity and hypovitaminosis D playing a key role in this clinical setting with its huge implication for the prevention and management of the disease. The role of the European Society of Endocrinology (ESE) as a reference point of the endocrine community during the pandemic will also be highlighted, including the refocusing of its educational and advocacy activities.

Diabetes Care Editors' Expert Forum 2018: Managing Big Data for Diabetes Research and Care.

Technological progress in the past half century has greatly increased our ability to collect, store, and transmit vast quantities of information, giving rise to the term "big data." This term refers to very large data sets that can be analyzed to identify patterns, trends, and associations. In medicine-including diabetes care and research-big data come from three main sources: electronic medical records (EMRs), surveys and registries, and randomized controlled trials (RCTs). These systems have evolved in different ways, each with strengths and limitations. EMRs continuously accumulate information about patients and make it readily accessible but are limited by missing data or data that are not quality assured. Because EMRs vary in structure and management, comparisons of data between health systems may be difficult. Registries and surveys provide data that are consistently collected and representative of broad populations but are limited in scope and may be updated only intermittently. RCT databases excel in the specificity, completeness, and accuracy of their data, but rarely include a fully representative sample of the general population. Also, they are costly to build and seldom maintained after a trial's end. To consider these issues, and the challenges and opportunities they present, the editors of Diabetes Care convened a group of experts in management of diabetes-related data on 21 June 2018, in conjunction with the American Diabetes Association's 78th Scientific Sessions in Orlando, FL. This article summarizes the discussion and conclusions of that forum, offering a vision of benefits that might be realized from prospectively designed and unified data-management systems to support the collective needs of clinical, surveillance, and research activities related to diabetes.

AMERICAN ASSOCIATION OF CLINICAL ENDOCRINOLOGISTS AND AMERICAN COLLEGE OF ENDOCRINOLOGY GUIDELINES FOR MANAGEMENT OF DYSLIPIDEMIA AND PREVENTION OF CARDIOVASCULAR DISEASE - EXECUTIVE SUMMARYComplete Appendix to Guidelines available at http://journals.aace.com.

OBJECTIVE: The development of these guidelines is mandated by the American Association of Clinical Endocrinologists (AACE) Board of Directors and American College of Endocrinology (ACE) Board of Trustees and adheres with published AACE protocols for the standardized production of clinical practice guidelines (CPGs). METHODS: Each Recommendation is based on a diligent review of the clinical evidence with transparent incorporation of subjective factors. RESULTS: The Executive Summary of this document contains 87 Recommendations of which 45 are Grade A (51.7%), 18 are Grade B (20.7%), 15 are Grade C (17.2%), and 9 (10.3%) are Grade D. These detailed, evidence-based recommendations allow for nuance-based clinical decision making that addresses multiple aspects of real-world medical care. The evidence base presented in the subsequent Appendix provides relevant supporting information for Executive Summary Recommendations. This update contains 695 citations of which 202 (29.1 %) are evidence level (EL) 1 (strong), 137 (19.7%) are EL 2 (intermediate), 119 (17.1%) are EL 3 (weak), and 237 (34.1%) are EL 4 (no clinical evidence). CONCLUSION: This CPG is a practical tool that endocrinologists, other healthcare professionals, regulatory bodies and health-related organizations can use to reduce the risks and consequences of dyslipidemia. It provides guidance on screening, risk assessment, and treatment recommendations for a range of patients with various lipid disorders. These recommendations emphasize the importance of treating low-density lipoprotein cholesterol (LDL-C) in some individuals to lower goals than previously recommended and support the measurement of coronary artery calcium scores and inflammatory markers to help stratify risk. Special consideration is given to patients with diabetes, familial hypercholesterolemia, women, and pediatric patients with dyslipidemia. Both clinical and cost-effectiveness data are provided to support treatment decisions. ABBREVIATIONS: A1C = hemoglobin A1C ACE = American College of Endocrinology ACS = acute coronary syndrome AHA = American Heart Association ASCVD = atherosclerotic cardiovascular disease ATP = Adult Treatment Panel apo = apolipoprotein BEL = best evidence level CKD = chronic kidney disease CPG = clinical practice guidelines CVA = cerebrovascular accident EL = evidence level FH = familial hypercholesterolemia HDL-C = high-density lipoprotein cholesterol HeFH = heterozygous familial hypercholesterolemia HIV = human immunodeficiency virus HoFH = homozygous familial hypercholesterolemia hsCRP = high-sensitivity C-reactive protein LDL-C = low-density lipoprotein cholesterol Lp-PLA2 = lipoprotein-associated phospholipase A2 MESA = Multi-Ethnic Study of Atherosclerosis MetS = metabolic syndrome MI = myocardial infarction NCEP = National Cholesterol Education Program PCOS = polycystic ovary syndrome PCSK9 = proprotein convertase subtilisin/kexin type 9 T1DM = type 1 diabetes mellitus T2DM = type 2 diabetes mellitus TG = triglycerides VLDL-C = very low-density lipoprotein cholesterol.

eCONSULTS TO ENDOCRINOLOGISTS IMPROVE ACCESS AND CHANGE PRIMARY CARE PROVIDER BEHAVIOR.

OBJECTIVE: To describe the impact of an eConsult service on access to endocrinologists along with its influence on changing primary care provider (PCP) course of action and referral behaviors. METHODS: Established in 2011, the Champlain BASE (Building Access to Specialist Care via eConsult) service allows PCPs to access specialist care in lieu of traditional face-to-face referrals. We conducted a cross-sectional study of eConsult cases submitted to endocrinologists by PCPs between April 15, 2011 and January 31, 2015. Usage data and PCP responses to a mandatory closeout survey were analyzed to determine eConsult response times, PCP practice behavior, referral outcomes, and provider satisfaction. Each eConsult was coded according to clinical topic and question type based on established taxonomies. RESULTS: A total of 180 PCPs submitted 464 eConsults to endocrinology during the study period. Specialist median response time was 7 hours, with 90% of responses occurring within 3 days. PCPs received a new or additional course of action in 62% of submitted cases. An unnecessary face-to-face referral was avoided in 44% of all eConsults and in 67% of cases where the PCP initially contemplated requesting a referral. Over 95% of cases were rated at least 4 out of 5 in value for PCPs and their patients. CONCLUSION: The use of eConsult improves access to endocrinologists by providing timely, highly rated practice-changing clinical advice while reducing the need for patients to attend face-to-face office visits. ABBREVIATIONS: BASE = Building Access to Specialist Advice through eConsult PCP = primary care physician UCSF = University of California San Francisco.