Back to Authors

Umpierrez, Guillermo E.

0000-0002-3252-5026

Mayo Clinic

Emory University

Citations 29

Glucagon Prescribing and Costs Among U.S. Adults With Diabetes, 2011–2021
Herges, Joseph R. , Galindo, Rodolfo J. , Neumiller, Joshua J. , Heien, Herbert C., Umpierrez, Guillermo E. , McCoy, Rozalina G. , Umpierrez, Guillermo E. , McCoy, Rozalina Grubina , Galindo, Rodolfo J , Neumiller, Joshua J.

Diabetes Care | January 11, 2023 | Volume: 46 | Issue: 3 | Pages: 620-627

10.2337/dc22-1564 Get It

OBJECTIVETo characterize contemporary trends in glucagon fill rates and expenditures in a nationwide cohort of adults with diabetes overall and by key demographic and clinical characteristics.RESEARCH DESIGN AND METHODSIn this retrospective cohort study, we examined 1) glucagon fill rates per 1,000 person-years and 2) patient out-of-pocket and health plan costs per filled glucagon dose among adults with diabetes included in OptumLabs Data Warehouse between 1 January 2011 and 31 March 2021.RESULTSThe study population comprised 2,814,464 adults with diabetes with a mean age of 62.8 (SD 13.2) years. The overall glucagon fill rate decreased from 2.91 to 2.28 per 1,000 person-years (−22%) over the study period. In groups at high risk for severe hypoglycemia, glucagon fill rates increased from 22.46 to 36.76 per 1,000 person-years (64%) among patients with type 1 diabetes, 11.64 to 16.63 per 1,000 person-years (43%) among those treated with short-acting insulin, and 16.08 to 20.12 per 1,000 person-years (25%) among those with a history of severe hypoglycemia. White patients, women, individuals with high income, and commercially insured patients had higher glucagon fill rates compared with minority patients, males, individuals with low income, and Medicare Advantage patients, respectively. Total cost per dosing unit increased from $157.97 to $275.32 (74%) among commercial insurance beneficiaries and from $150.37 to $293.57 (95%) among Medicare Advantage beneficiaries.CONCLUSIONSGlucagon fill rates are concerningly low and declined between 2011 and 2021 but increased in appropriate subgroups with type 1 diabetes, using short-acting insulin, or with a history of severe hypoglycemia. Fill rates were disproportionately low among minority patients and individuals with low income.
Rates of Hypoglycemic and Hyperglycemic Emergencies Among U.S. Adults With Diabetes, 2011–2020
McCoy, Rozalina G. , Galindo, Rodolfo J. , Swarna, Kavya, McCoy, Rozalina Grubina , Galindo, Rodolfo J , Herrin, Jeph , Umpierrez, Guillermo E. , Golden, Sherita Hill , O’Connor, Patrick J.

Diabetes Care | December 15, 2022 | Volume: 46 | Issue: 2 | Pages: e69-e71

10.2337/dc22-1673 Get It

Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline
Korytkowski, Mary T. , Antinori-Lent, Kellie, Donihi, Amy C. , Drincic, Andjela, Luger, Anton, Nielsen, Craig , Pegg, Claire, Rushakoff, Robert J , McDonnell, Marie E , Rushakoff, Robert J , Muniyappa, Ranganath , Hirsch, Irl B. , McDonnell, Marie E. , Murad, M. Hassan , Santesso, Nancy A. , Umpierrez, Guillermo E.

The Journal of Clinical Endocrinology & Metabolism | June 12, 2022 | Volume: 107 | Issue: 8 | Pages: 2101-2128

10.1210/clinem/dgac278 Get It

Abstract Background Adult patients with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. These patients are at increased risk for adverse clinical outcomes in the absence of defined approaches to glycemic management. Objective To review and update the 2012 Management of Hyperglycemia in Hospitalized Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline and to address emerging areas specific to the target population of noncritically ill hospitalized patients with diabetes or newly recognized or stress-induced hyperglycemia. Methods A multidisciplinary panel of clinician experts, together with a patient representative and experts in systematic reviews and guideline development, identified and prioritized 10 clinical questions related to inpatient management of patients with diabetes and/or hyperglycemia. The systematic reviews queried electronic databases for studies relevant to the selected questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. Results The panel agreed on 10 frequently encountered areas specific to glycemic management in the hospital for which 15 recommendations were made. The guideline includes conditional recommendations for hospital use of emerging diabetes technologies including continuous glucose monitoring and insulin pump therapy; insulin regimens for prandial insulin dosing, glucocorticoid, and enteral nutrition–associated hyperglycemia; and use of noninsulin therapies. Recommendations were also made for issues relating to preoperative glycemic measures, appropriate use of correctional insulin, and diabetes self-management education in the hospital. A conditional recommendation was made against preoperative use of caloric beverages in patients with diabetes. Conclusion The recommendations are based on the consideration of important outcomes, practicality, feasibility, and patient values and preferences. These recommendations can be used to inform system improvement and clinical practice for this frequently encountered inpatient population.
A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings
Klonoff, David C. , Wang, Jing , Rodbard, David , Kohn, Michael A. , Li, Chengdong , Liepmann, Dorian , Kerr, David , Ahn, David , Peters, Anne L. , Umpierrez, Guillermo E. , Xu, Nicole Y. , Nguyen, Kevin T. , Simonson, Gregg D. , Agus, Michael S. D. , Armaiz-Peña, Gustavo , Basu, Ananda , Battelino, Tadej , Yeshiwas, Sewagegn , Bequette, B. Wayne , Blevins, Thomas , Breton, Marc D. , Castle, Jessica R. , Close, Kelly L. , Drincic, Angela, Dungan, Kathleen , Ejskjær, Niels , Espinoza, Juan , Fleming, G. Alexander , Forlenza, Gregory P. , Freckmann, Guido , Galindo, Rodolfo J. , Gómez, Ana María , Gutow, Hanna A. , Hovorka, Roman , Ji, Linong , Joubert, Michaël , Koliwad, Suneil K. , Lal, Rayhan , Lansang, M. Cecilia , Lee, Wei-An , Leelarathna, Lalantha , Lind, Marcus , Mahoney, Katherine , Mankovsky, Boris , Masharani, Umesh , Mathioudakis, Nestoras , Mayorov, Alexander Yur'evich , Messler, Jordan , Mohan, Viswanathan , Nichols, James H. , O’Neal, David N. , Pasquel, Francisco J. , Philis‐Tsimikas, Athena , Phillip, Moshe , Rayman, Gerry , Russell, Steven J. , Spanakis, Elias K. , Waki, Kayo , Wallia, Amisha , Weinberg, Melissa E. , Wolpert, Howard , Zilbermint, Mihail , Kovatchev, Boris , Seley, Jane Jeffrie , Xu, Nicole Y , Nguyen, Kevin T , Simonson, Gregg , Agus, Michael S D , Al-Sofiani, Mohammed E , Armaiz-Pena, Gustavo , Bailey, Timothy S , Basu, Ananda , Battelino, Tadej , Bekele, Sewagegn Yeshiwas , Benhamou, Pierre-Yves , Bequette, B Wayne , Blevins, Thomas , Breton, Marc D , Castle, Jessica R , Chase, James Geoffrey , Chen, Kong , Choudhary, Pratik , Clements, Mark A , Close, Kelly L , Cook, Curtiss B , Doyle, Francis J , Drincic, Angela , Dungan, Kathleen M , Edelman, Steven V , Ejskjaer, Niels , Espinoza, Juan , Fleming, G Alexander , Forlenza, Gregory P , Freckmann, Guido , Galindo, Rodolfo J , Gomez, Ana Maria , Gutow, Hanna A , Heinemann, Lutz , Hirsch, Irl B , Hoang, Thanh D , Hovorka, Roman , Jendle, Johan H , Ji, Linong , Joshi, Shashank R , Joubert, Michael , Koliwad, Suneil K , Lal, Rayhan A , Lansang, M Cecilia , Lee, Wei-An Andy , Leelarathna, Lalantha , Leiter, Lawrence A , Lind, Marcus , Litchman, Michelle L , Mader, Julia K , Mahoney, Katherine M , Mankovsky, Boris , Masharani, Umesh , Mathioudakis, Nestoras N , Mayorov, Alexander , Messler, Jordan , Miller, Joshua D , Mohan, Viswanathan , Nichols, James H , Nørgaard, Kirsten , O'Neal, David N , Pasquel, Francisco J , Philis-Tsimikas, Athena , Pieber, Thomas , Phillip, Moshe , Polonsky, William H , Pop-Busui, Rodica , Rayman, Gerry , Rhee, Eun-Jung , Russell, Steven J , Shah, Viral N , Sherr, Jennifer L , Sode, Koji , Spanakis, Elias K , Wake, Deborah J , Waki, Kayo , Wallia, Amisha , Weinberg, Melissa E , Wolpert, Howard , Wright, Eugene E , Zilbermint, Mihail , Kovatchev, Boris , Kohn, Michael , Umpierrez, Guillermo E. , Peters, Anne L , Ahn, David T , Liepmann, Dorian , Bailey, Timothy S. , Chen, Kong Y. , Choudhary, Pratik , Cook, Curtiss B. , Danne, Thomas , Doyle, Francis J. , Heinemann, Lutz , Hirsch, Irl B. , Leiter, Lawrence A. , Mader, Julia K. , Pop‐Busui, Rodica , Shah, Viral N. , Sode, Koji , Wright, Eugene E.

Journal of Diabetes Science and Technology | March 29, 2022 | Volume: 17 | Issue: 5 | Pages: 1226-1242

10.1177/19322968221085273 Get It

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.
Hypoglycemic and Hyperglycemic Crises Among U.S. Adults With Diabetes and End-stage Kidney Disease: Population-Based Study, 2013–2017
Galindo, Rodolfo J. , Ali, Mohammed K. , Funni, Shealeigh A., Dodge, Andrew , Kurani, Shaheen , Shah, Nilay D. , Kurani, Shaheen S, Galindo, Rodolfo J , Ali, Mohammed K , Umpierrez, Guillermo E. , McCoy, Rozalina G.

Diabetes Care | November 5, 2021 | Volume: 45 | Issue: 1 | Pages: 100-107

10.2337/dc21-1579 Get It

OBJECTIVE We characterized annual trends of severe hypoglycemic and hyperglycemic crises (diabetic ketoacidosis/hyperglycemic hyperosmolar state) in patients with diabetes and end-stage kidney disease (ESKD). RESEARCH DESIGN AND METHODS This was a nationwide, retrospective study of adults (≥18 years old) with diabetes/ESKD, from the United States Renal Data System registry, between 2013 and 2017. Primary outcome was annual rates of emergency department visits or hospitalizations for hypoglycemic and hyperglycemic crises, reported as number of events/1,000 person-years. Event rates and risk factors were adjusted for patient age, sex, race/ethnicity, dialysis modality, comorbidities, treatment regimen, and U.S. region. RESULTS Among 521,789 adults with diabetes/ESKD (median age 65 years [interquartile range 57–73], 56.1% male, and 46% White), overall adjusted rates of hypoglycemic and hyperglycemic crises were 53.64 and 18.24 per 1,000 person-years, respectively. For both hypoglycemia and hyperglycemia crises, respectively, the risks decreased with age and were lowest in older patients (≥75 vs. 18–44 years old: incidence rate ratio 0.35, 95% CI 0.33–0.37, and 0.03, 0.02–0.03), women (1.09, 1.06–1.12, and 1.44, 1.35–1.54), and those with smoking (1.36, 1.28–1.43, and 1.71, 1.53–1.91), substance abuse (1.27, 1.15–1.42, and 1.53, 1.23–1.9), retinopathy (1.10, 1.06–1.15, and 1.36, 1.26–1.47), and insulin therapy (vs. no therapy; 0.60, 0.59–0.63, and 0.44, 0.39–0.48). For hypoglycemia, specifically, additional risk was conferred by Black race (1.11, 1.08–1.15) and amputation history (1.20, 1.13–1.27). CONCLUSIONS In this nationwide study of patients with diabetes/ESKD, hypoglycemic crises were threefold more common than hyperglycemic crises, greatly exceeding national reports in nondialysis patients with chronic kidney disease. Young, Black, and female patients were disproportionately affected.
Sociodemographic, Clinical, and Treatment-Related Factors Associated With Hyperglycemic Crises Among Adults With Type 1 or Type 2 Diabetes in the US From 2014 to 2020
Galindo, Rodolfo J. , Swarna, Kavya, Houten, Holly K. Van , Shah, Nilay D. , Galindo, Rodolfo J , McCoy, Rozalina G. , O’Connor, Patrick J. , Umpierrez, Guillermo E.

JAMA Network Open | September 1, 2021 | Volume: 4 | Issue: 9 | Pages: e2123471

10.1001/jamanetworkopen.2021.23471 Get It

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline
Galindo, Rodolfo J. , Rushakoff, Robert J , Basu, Ananda , Lohnes, Suzanne, Nichols, James H. , Spanakis, Elias K. , Espinoza, Juan , Palermo, Nadine E. , Awadjie, Dessa Garnett, Bak, Leigh B., Buckingham, Bruce A. , Freckmann, Guido , Hovorka, Roman , Mathioudakis, Nestoras , Newman, Tonya, O’Neal, David N. , Rickert, Michaela , Wallia, Amisha , Shang, Trisha , Zhang, Jennifer Y. , Han, Julia , Klonoff, David C. , Nichols, James H , Spanakis, Elias K , Espinoza, Juan , Cook, Curtiss B. , Freckmann, Guido , Heinemann, Lutz , O'Neal, David N , Sacks, David B , Shang, Trisha , Zhang, Jennifer Y , Klonoff, David C , Galindo, Rodolfo J , Hovorka, Roman , Mathioudakis, Nestoras N , Buckingham, Bruce , Umpierrez, Guillermo E. , Heinemann, Lutz , Seley, Jane Jeffrie

Journal of Diabetes Science and Technology | September 28, 2020 | Volume: 14 | Issue: 6 | Pages: 1035-1064

10.1177/1932296820954163 Get It

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.
Consensus Statement on Inpatient Use of Continuous Glucose Monitoring
Wallia, Amisha , Rushakoff, Robert J , Klonoff, David C. , Rubin, Daniel J. , Thompson, Bithika , Cook, Curtiss B. , Umpierrez, Guillermo E. , Golden, Sherita Hill

Journal of Diabetes Science and Technology | April 21, 2017 | Volume: 11 | Issue: 5 | Pages: 1036-1044

10.1177/1932296817706151 Get It

In June 2016, Diabetes Technology Society convened a panel of US experts in inpatient diabetes management to discuss the current and potential role of continuous glucose monitoring (CGM) in the hospital. This discussion combined with a literature review was a follow-up to a meeting, which took place in May 2015. The panel reviewed evidence on use of CGM in 3 potential inpatient scenarios: (1) the intensive care unit (ICU), (2) non-ICU, and (3) transitioning outpatient CGM use into the hospital setting. Panel members agreed that data from limited studies and theoretical considerations suggested that use of CGM in the hospital had the potential to improve patient clinical outcomes, and in particular reduction of hypoglycemia. Panel members discussed barriers to widespread adoption of CGM, which patients would benefit most from use of this technology, and what type of outcome studies are needed to guide use of CGM in the inpatient setting.
Hyperglycemic Crises in Adult Patients With Diabetes
Kitabchi, Abbas E., Miles, John M., Fisher, Joseph N., Umpierrez, Guillermo E. , Miles, John M.

Diabetes Care | June 29, 2009 | Volume: 32 | Issue: 7 | Pages: 1335-1343

10.2337/dc09-9032 Get It