Daniel Einhorn
University of California, San Diego
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Endocrine Practice | 2009
Helena W. Rodbard; Paul S. Jellinger; Jaime A. Davidson; Daniel Einhorn; Alan J. Garber; George Grunberger; Yehuda Handelsman; Edward S. Horton; Harold E. Lebovitz; Philip Levy; Etie S. Moghissi; Stanley Schwartz
This report presents an algorithm to assist primary care physicians, endocrinologists, and others in the management of adult, nonpregnant patients with type 2 diabetes mellitus. In order to minimize the risk of diabetes-related complications, the goal of therapy is to achieve a hemoglobin A1c (A1C) of 6.5% or less, with recognition of the need for individualization to minimize the risks of hypoglycemia. We provide therapeutic pathways stratified on the basis of current levels of A1C, whether the patient is receiving treatment or is drug naïve. We consider monotherapy, dual therapy, and triple therapy, including 8 major classes of medications (biguanides, dipeptidyl-peptidase-4 inhibitors, incretin mimetics, thiazolidinediones, alpha-glucosidase inhibitors, sulfonylureas, meglitinides, and bile acid sequestrants) and insulin therapy (basal, premixed, and multiple daily injections), with or without orally administered medications. We prioritize choices of medications according to safety, risk of hypoglycemia, efficacy, simplicity, anticipated degree of patient adherence, and cost of medications. We recommend only combinations of medications approved by the US Food and Drug Administration that provide complementary mechanisms of action. It is essential to monitor therapy with A1C and self-monitoring of blood glucose and to adjust or advance therapy frequently (every 2 to 3 months) if the appropriate goal for each patient has not been achieved. We provide a flow-chart and table summarizing the major considerations. This algorithm represents a consensus of 14 highly experienced clinicians, clinical researchers, practitioners, and academicians and is based on the American Association of Clinical Endocrinologists/American College of Endocrinology Diabetes Guidelines and the recent medical literature.
The New England Journal of Medicine | 2010
John J.V. McMurray; R R Holman; Steven M. Haffner; M. Angelyn Bethel; Björn Holzhauer; Tsushung A Hua; Yuri N. Belenkov; Mitradev Boolell; John B. Buse; Brendan M. Buckley; Antonio Roberto Chacra; Fu-Tien Chiang; Bernard Charbonnel; Chun -Chung Chow; Melanie J. Davies; Prakash Deedwania; Peter Diem; Daniel Einhorn; Vivian Fonseca; Gregory R. Fulcher; Zbigniew Gaciong; Sonia Gaztambide; Thomas D. Giles; Edward S. Horton; Hasan Ilkova; Trond Jenssen; Steven E. Kahn; Henry Krum; Markku Laakso; Lawrence A. Leiter
BACKGROUND It is not known whether drugs that block the renin-angiotensin system reduce the risk of diabetes and cardiovascular events in patients with impaired glucose tolerance. METHODS In this double-blind, randomized clinical trial with a 2-by-2 factorial design, we assigned 9306 patients with impaired glucose tolerance and established cardiovascular disease or cardiovascular risk factors to receive valsartan (up to 160 mg daily) or placebo (and nateglinide or placebo) in addition to lifestyle modification. We then followed the patients for a median of 5.0 years for the development of diabetes (6.5 years for vital status). We studied the effects of valsartan on the occurrence of three coprimary outcomes: the development of diabetes; an extended composite outcome of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, arterial revascularization, or hospitalization for unstable angina; and a core composite outcome that excluded unstable angina and revascularization. RESULTS The cumulative incidence of diabetes was 33.1% in the valsartan group, as compared with 36.8% in the placebo group (hazard ratio in the valsartan group, 0.86; 95% confidence interval [CI], 0.80 to 0.92; P<0.001). Valsartan, as compared with placebo, did not significantly reduce the incidence of either the extended cardiovascular outcome (14.5% vs. 14.8%; hazard ratio, 0.96; 95% CI, 0.86 to 1.07; P=0.43) or the core cardiovascular outcome (8.1% vs. 8.1%; hazard ratio, 0.99; 95% CI, 0.86 to 1.14; P=0.85). CONCLUSIONS Among patients with impaired glucose tolerance and cardiovascular disease or risk factors, the use of valsartan for 5 years, along with lifestyle modification, led to a relative reduction of 14% in the incidence of diabetes but did not reduce the rate of cardiovascular events. (ClinicalTrials.gov number, NCT00097786.)
Endocrine Practice | 2016
Alan J. Garber; Martin J. Abrahamson; Joshua I. Barzilay; Lawrence Blonde; Zachary T. Bloomgarden; Michael A. Bush; Samuel Dagogo-Jack; Ralph A. DeFronzo; Daniel Einhorn; Vivian Fonseca; Jeffrey R. Garber; W. Timothy Garvey; George Grunberger; Yehuda Handelsman; Robert R. Henry; Irl B. Hirsch; Paul S. Jellinger; Janet B. McGill; Jeffrey I. Mechanick; Paul D. Rosenblit; Guillermo E. Umpierrez
Abbreviations: A1C = hemoglobin A1C AACE = American Association of Clinical Endocrinologists ACCORD = Action to Control Cardiovascular Risk in Diabetes ACCORD BP = Action to Control Cardiovascular Risk in Diabetes Blood Pressure ACEI = angiotensinconverting enzyme inhibitor AGI = alpha-glucosidase inhibitor apo B = apolipoprotein B ARB = angiotensin II receptor blocker ASCVD = atherosclerotic cardiovascular disease BAS = bile acid sequestrant BMI = body mass index BP = blood pressure CHD = coronary heart disease CKD = chronic kidney disease CVD = cardiovascular disease DKA = diabetic ketoacidosis DPP-4 = dipeptidyl peptidase 4 EPA = eicosapentaenoic acid FDA = Food and Drug Administration GLP-1 = glucagon-like peptide 1 HDL-C = high-density-lipoprotein cholesterol LDL-C = low-densitylipoprotein cholesterol LDL-P = low-density-lipoprotein particle Look AHEAD = Look Action for Health in Diabetes NPH = neutral protamine Hagedorn OSA = obstructive sleep apnea SFU = sulfonylurea SGLT-2 = sodium glucose cotrans...
Endocrine Practice | 2009
Etie S. Moghissi; Mary T. Korytkowski; Monica DiNardo; Daniel Einhorn; Richard Hellman; Irl B. Hirsch; Silvio E. Inzucchi; Faramarz Ismail-Beigi; M. Sue Kirkman; Guillermo E. Umpierrez
This report is being published concurrently in 2009 in Endocrine Practice and Diabetes Care by the American Association of Clinical Endocrinologists and the American Diabetes Association. From the 1Department of Medicine, University of California Los Angeles, Los Angeles, California, 2Department of Medicine, Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, Pennsylvania, 3Division of Endocrinology and Metabolism, Veterans Affairs Pittsburgh Health Center and University of Pittsburgh School of Nursing PhD Program, Pittsburgh, Pennsylvania, 4Scripps Whittier Diabetes Institute, La Jolla, California, University of California San Diego School of Medicine, San Diego, California, and Diabetes and Endocrine Associates, La Jolla, California, 5Department of Medicine, University of Missouri-Kansas City School of Medicine and Hellman and Rosen Endocrine Associates, North Kansas City, Missouri, 6Department of Medicine, University of Washington School of Medicine, Seattle, Washington, 7Department of Medicine, Section of Endocrinology, Yale University School of Medicine and the Yale Diabetes Center, Yale-New Haven Hospital, New Haven, Connecticut, 8Department of Medicine, Physiology and Biophysics, Division of Clinical and Molecular Endocrinology, Case Western Reserve University, Cleveland, Ohio, 9Clinical Affairs, American Diabetes Association, Alexandria, Virginia, and 10Department of Medicine/Endocrinology, Emory University, Atlanta, Georgia. Address correspondence and reprint requests to Dr. Etie S. Moghissi, 4644 Lincoln Boulevard, Suite 409, Marina del Rey, CA 90292.
The New England Journal of Medicine | 2010
R R Holman; Steven M. Haffner; John J.V. McMurray; M. Angelyn Bethel; Björn Holzhauer; Tsushung A Hua; Yuri N. Belenkov; Mitradev Boolell; John B. Buse; Brendan M. Buckley; Antonio Roberto Chacra; Fu-Tien Chiang; Bernard Charbonnel; Chun -Chung Chow; Melanie J. Davies; Prakash Deedwania; Peter Diem; Daniel Einhorn; Vivian Fonseca; Gregory R. Fulcher; Zbigniew Gaciong; Sonia Gaztambide; Thomas D. Giles; Edward S. Horton; Hasan Ilkova; Trond Jenssen; Steven E. Kahn; Henry Krum; Markku Laakso; Lawrence A. Leiter
BACKGROUND The ability of short-acting insulin secretagogues to reduce the risk of diabetes or cardiovascular events in people with impaired glucose tolerance is unknown. METHODS In a double-blind, randomized clinical trial, we assigned 9306 participants with impaired glucose tolerance and either cardiovascular disease or cardiovascular risk factors to receive nateglinide (up to 60 mg three times daily) or placebo, in a 2-by-2 factorial design with valsartan or placebo, in addition to participation in a lifestyle modification program. We followed the participants for a median of 5.0 years for incident diabetes (and a median of 6.5 years for vital status). We evaluated the effect of nateglinide on the occurrence of three coprimary outcomes: the development of diabetes; a core cardiovascular outcome that was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure; and an extended cardiovascular outcome that was a composite of the individual components of the core composite cardiovascular outcome, hospitalization for unstable angina, or arterial revascularization. RESULTS After adjustment for multiple testing, nateglinide, as compared with placebo, did not significantly reduce the cumulative incidence of diabetes (36% and 34%, respectively; hazard ratio, 1.07; 95% confidence interval [CI], 1.00 to 1.15; P=0.05), the core composite cardiovascular outcome (7.9% and 8.3%, respectively; hazard ratio, 0.94, 95% CI, 0.82 to 1.09; P=0.43), or the extended composite cardiovascular outcome (14.2% and 15.2%, respectively; hazard ratio, 0.93, 95% CI, 0.83 to 1.03; P=0.16). Nateglinide did, however, increase the risk of hypoglycemia. CONCLUSIONS Among persons with impaired glucose tolerance and established cardiovascular disease or cardiovascular risk factors, assignment to nateglinide for 5 years did not reduce the incidence of diabetes or the coprimary composite cardiovascular outcomes. (ClinicalTrials.gov number, NCT00097786.)
Endocrine Practice | 2013
Alan M. Garber; Martin J. Abrahamson; Joshua I. Barzilay; Lawrence Blonde; Zachary T. Bloomgarden; Michael A. Bush; Samuel Dagogo-Jack; Michael Davidson; Daniel Einhorn; W. Garvey; George Grunberger; Yehuda Handelsman; Irl B. Hirsch; Paul S. Jellinger; Janet B. McGill; Jeffrey I. Mechanick; Paul D. Rosenblit; Guillermo E. Umpierrez
Alan J. Garber, MD, PhD, FACE; Martin J. Abrahamson, MD; Joshua I. Barzilay, MD, FACE; Lawrence Blonde, MD, FACP, FACE; Zachary T. Bloomgarden, MD, MACE; Michael A. Bush, MD; Samuel Dagogo-Jack, MD, FACE; Michael B. Davidson, DO, FACE; Daniel Einhorn, MD, FACP, FACE; W. Timothy Garvey, MD; George Grunberger, MD, FACP, FACE; Yehuda Handelsman, MD, FACP, FACE, FNLA; Irl B. Hirsch, MD; Paul S. Jellinger, MD, MACE; Janet B. McGill, MD, FACE; Jeffrey I. Mechanick, MD, FACE, ECNU, FACN, FACP; Paul D. Rosenblit, MD, PhD, FACE, FNLA; Guillermo E. Umpierrez, MD, FACE; Michael H. Davidson, MD, FACC, FACP, FNLA
Endocrine Practice | 2015
Yehuda Handelsman; Zachary T. Bloomgarden; George Grunberger; Guillermo Umpierrez; Robert S. Zimmerman; Timothy S. Bailey; Lawrence Blonde; George A. Bray; A. Jay Cohen; Samuel Dagogo-Jack; Jaime A. Davidson; Daniel Einhorn; Om P. Ganda; Alan J. Garber; W. Timothy Garvey; Robert R. Henry; Irl B. Hirsch; Edward S. Horton; Daniel L. Hurley; Paul S. Jellinger; Lois Jovanovič; Harold E. Lebovitz; Derek LeRoith; Philip Levy; Janet B. McGill; Jeffrey I. Mechanick; Jorge H. Mestman; Etie S. Moghissi; Eric A. Orzeck; Rachel Pessah-Pollack
The American Association of Clinical Endocrinologists/American College of Endocrinology Medical Guidelines for Clinical Practice are systematically developed statements to assist healthcare professionals in medical decision making for specific clinical conditions. Most of the content herein is based on literature reviews. In areas of uncertainty, professional judgment was applied. These guidelines are a working document that reflects the state of the field at the time of publication. Because rapid changes in this area are expected, periodic revisions are inevitable. We encourage medical professionals to use this information in conjunction with their best clinical judgment. The presented recommendations may not be appropriate in all situations. Any decision by practitioners to apply these guidelines must be made in light of local resources and individual patient circumstances. Abbreviations: A1C = hemoglobin A1c AACE = American Association of Clinical Endocrinologists ACCORD = Action to Control Cardiovascu...
Endocrine Practice | 2008
Alan J. Garber; Yehuda Handelsman; Daniel Einhorn; Donald Bergman; Zachary T. Bloomgarden; Vivian Fonseca; W. Timothy Garvey; James R. Gavin; George Grunberger; Edward S. Horton; Paul S. Jellinger; Kenneth L. Jones; Harold E. Lebovitz; Philip Levy; Darren K. McGuire; Etie S. Moghissi; Richard W. Nesto
Alan J. Garber, MD, PhD, FACE, Yehuda Handelsman, MD, FACP, FACE, Daniel Einhorn, MD, FACP, FACE, Donald A. Bergman, MD, FACE, Zachary T. Bloomgarden, MD, FACE, Vivian Fonseca, MD, FACE, W. Timothy Garvey, MD, James R. Gavin III, MD, PhD, George Grunberger, MD, FACP, FACE, Edward S. Horton, MD, FACE, Paul S. Jellinger, MD, MACE, Kenneth L. Jones, MD, Harold Lebovitz, MD, FACE, Philip Levy, MD, MACE, Darren K. McGuire, MD, MHSc, FACC, Etie S. Moghissi, MD, FACP, FACE, and Richard W. Nesto, MD, FACC, FAHA
Endocrine Practice | 2007
Daniel Einhorn; Deirdre Stewart; Milton K. Erman; Nancy Gordon; Athena Philis-Tsimikas; Eileen Casal
OBJECTIVE To assess the prevalence of sleep apnea (SA) in adults with type 2 diabetes mellitus (T2DM) and examine whether demographics and comorbid factors were associated with SA in this population. METHODS This study enrolled 330 consecutive adults with T2DM referred to a diabetes clinic, 279 of whom completed the study. Evaluation of the presence of SA was performed with use of a single-channel recording device that measures disordered breathing events from a nasal cannula airflow signal. The device was worn by the study participants in their home, after instruction in appropriate use by clinical staff at the diabetes center. The presence and severity of SA were determined by use of an apnea-hypopnea index (AHI), reflecting periods of diminished and absent breathing. Demographic and medical information data were collected to detect factors associated with SA in this study population. In addition, a time and cost analysis was conducted regarding the screening process for SA by clinical staff at the diabetes center. RESULTS The results show a high prevalence of SA in adults with T2DM, ranging from 48% (AHI level of >or=10 events/h) to 29% (AHI level of >or=20 events/h). At an AHI cutoff value of >or=15 events/h, the overall prevalence rate was 36% (49% in male and 21% in female participants). The following variables were associated with SA: age >or=62 years, male sex, body mass index >or=30 kg/m2, snoring, and reports of stopping breathing during sleep. The time and cost analysis showed that the screening device involved minimal setup time, was simple to use, and was a cost-effective method to screen for SA. CONCLUSION SA is a common disorder associated with major morbid conditions, including hypertension, obesity, cardiovascular disease, and insulin resistance. Predisposing factors for SA and T2DM are similar. This study showed that SA has a high prevalence in adults with T2DM and identified factors that may be associated with its presence in this population. Assessment for SA can be easily performed in an outpatient setting with a portable recording device such as the one used in this study. Screening for SA should be considered in the T2DM population.
Endocrine Practice | 2013
Alan M. Garber; Martin J. Abrahamson; Joshua I. Barzilay; Lawrence Blonde; Zachary T. Bloomgarden; Michael A. Bush; Samuel Dagogo-Jack; Michael Davidson; Daniel Einhorn; W. Garvey; George Grunberger; Yehuda Handelsman; Irl B. Hirsch; Paul S. Jellinger; Janet B. McGill; Jeffrey I. Mechanick; Paul D. Rosenblit; Guillermo E. Umpierrez; Michael Devidson
Alan J. Garber, MD, PhD, FACE; Martin J. Abrahamson, MD; Joshua I. Barzilay, MD, FACE; Lawrence Blonde, MD, FACP, FACE; Zachary T. Bloomgarden, MD, MACE; Michael A. Bush, MD; Samuel Dagogo-Jack, MD, FACE; Michael B. Davidson, DO, FACE; Daniel Einhorn, MD, FACP, FACE; W. Timothy Garvey, MD; George Grunberger, MD, FACP, FACE; Yehuda Handelsman, MD, FACP, FACE, FNLA; Irl B. Hirsch, MD; Paul S. Jellinger, MD, MACE; Janet B. McGill, MD, FACE; Jeffrey I. Mechanick, MD, FACE, ECNU, FACN, FACP; Paul D. Rosenblit, MD, PhD, FACE, FNLA; Guillermo E. Umpierrez, MD, FACE; Michael H. Davidson, MD, FACC, FACP, FNLA