Preadmission predictors of severe COVID-19 in patients with diabetes mellitus.

OBJECTIVE: To explore predictors of severe COVID-19 disease in patients with diabetes hospitalized for COVID-19. METHODS: This is a retrospective observational study of adults with diabetes admitted for COVID-19. Bivariate tests and multivariable Cox regression were used to identify risk factors for severe COVID-19, defined as a composite endpoint of intensive care unit admission/intubation or in-hospital death. RESULTS: In 1134 patients with diabetes admitted for COVID-19, more severe disease was associated with older age (HR 1.02, p<0.001), male sex (HR 1.28, p=0.017), Asian race (HR 1.34, p=0.029 [reference: white]), and greater obesity (moderate obesity HR 1.59, p=0.015; severe obesity HR 2.07, p=0.002 [reference: normal body mass index]). Outpatient diabetes medications were not associated with outcomes. CONCLUSIONS: Age, male sex, Asian race, and obesity were associated with increased risk of severe COVID-19 disease in adults with type 2 diabetes hospitalized for COVID-19. SUMMARY: In patients with type 2 diabetes hospitalized for COVID-19 disease, we observed that age, male sex, Asian race, and obesity predicted severe COVID-19 outcomes of intensive care unit admission, intubation, or in-hospital death. The risk conferred by obesity increased with worsening obesity. Outpatient diabetes medications were not observed to be significant predictors of study outcomes.

The Independent Risk of Obesity and Diabetes and Their Interaction in COVID-19: A Retrospective Cohort Study.

OBJECTIVE: This study aimed to assess whether diabetes mellitus (DM) or obesity is an independent risk factor for severe coronavirus disease 2019 (COVID-19) outcomes and to explore whether the risk conferred by one condition is modified by the other. METHODS: This retrospective cohort study of inpatient adults with COVID-19 used multivariable Cox regression to determine the independent effects of DM and obesity on the composite outcome of intubation, intensive care unit admission, or in-hospital mortality. Effect modification between DM and obesity was assessed with a statistical interaction term and an exploration of stratum-specific effects. RESULTS: Out of 3,533 patients, a total of 1,134 (32%) had DM, 1,256 (36%) had obesity, and 430 (12%) had both. DM and obesity were independently associated with the composite outcome (hazard ratio [HR] 1.14 [95% CI: 1.01-1.30] and HR 1.22 [95% CI: 1.05-1.43], respectively). A statistical trend for potential interaction between DM and obesity was observed (P = 0.20). Stratified analyses showed potential increased risk with obesity compared with normal weight among patients with DM (HR 1.34 [95% CI: 1.04-1.74]) and patients without DM (HR 1.18 [95% CI: 0.96-1.43]). CONCLUSIONS: DM and obesity are independent risk factors associated with COVID-19 severity. Stratified analyses suggest that obesity may confer greater risk to patients with DM compared with patients without DM, and this relationship requires further exploration.

Strategies to Prevent Readmission in High-Risk Patients with Diabetes: the Importance of an Interdisciplinary Approach.

PURPOSE OF REVIEW: Patients with diabetes are known to have higher 30-day readmission rates compared to the general inpatient population. A number of strategies have been shown to be effective in lowering readmission rates. RECENT FINDINGS: A review of the current literature revealed several strategies that have been associated with a decreased risk of readmission in high-risk patients with diabetes. These strategies include inpatient diabetes survival skills education and medication reconciliation prior to discharge to send the patient home with the "right" medications. Other key strategies include scheduling a follow-up phone call soon after discharge and an office visit to adjust the diabetes regimen. The authors identified the most successful strategies to reduce readmissions as well as some institutional barriers to following a transitional care program. Recent studies have identified risk factors in the diabetes population that are associated with an increased risk of readmission as well as interventions to lower this risk. A standardized transitional care program that focuses on providing interventions while reducing barriers to implementation can contribute to a decreased risk of readmission.

Using multiple measures of glycemia to support individualized diabetes management: recommendations for clinicians, patients, and payers.

By the year 2030, the diabetes pandemic will likely affect more than 10% of the world's population. The personal, public health, and economic crises implicit in this trend call for decisive action. Yet, escalating dilemmas thwart full realization of current therapies. First, controversial studies, such as the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Trial, have amplified calls to individualize glycated hemoglobin (A1C) targets in the absence of adequate infrastructures for supporting personalized care. Second, costlier medications and technologies addressing more nuanced aspects of metabolic dysfunction are expanding options for diabetes management amidst growing disparities between "affordable" and "best" care. Third, common clinical quandaries, such as discrepancies between A1C and self-monitoring of blood glucose data, as well as misconceptions about long-term glycemic assessment, compound entrenched cycles of inadequate self-care, delayed intervention, and suboptimal glycemic outcomes. Because individual, clinical, and public policy responses to these conflicting forces are based largely on methodologies for glucose measurement, a panel of clinical experts from Europe and North America was convened to reexamine our glucose measuring tools and determine ways in which they can be better applied toward more purposeful processes of glycemic management. Among the main issues addressed were the need for caution in interpreting A1C for individual patients, the role of alternative biomarkers in identifying aspects of glycemic dysregulation not captured by A1C, and the value of using patients' own glucose data to consolidate therapeutic, educational, and behavior-change objectives.

Management of hyperglycemia in hospitalized patients in non-critical care setting: an endocrine society clinical practice guideline.

OBJECTIVE: The aim was to formulate practice guidelines on the management of hyperglycemia in hospitalized patients in the non-critical care setting. PARTICIPANTS: The Task Force was composed of a chair, selected by the Clinical Guidelines Subcommittee of The Endocrine Society, six additional experts, and a methodologist. EVIDENCE: This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence. CONSENSUS PROCESS: One group meeting, several conference calls, and e-mail communications enabled consensus. Endocrine Society members, American Diabetes Association, American Heart Association, American Association of Diabetes Educators, European Society of Endocrinology, and the Society of Hospital Medicine reviewed and commented on preliminary drafts of this guideline. CONCLUSIONS: Hyperglycemia is a common, serious, and costly health care problem in hospitalized patients. Observational and randomized controlled studies indicate that improvement in glycemic control results in lower rates of hospital complications in general medicine and surgery patients. Implementing a standardized sc insulin order set promoting the use of scheduled basal and nutritional insulin therapy is a key intervention in the inpatient management of diabetes. We provide recommendations for practical, achievable, and safe glycemic targets and describe protocols, procedures, and system improvements required to facilitate the achievement of glycemic goals in patients with hyperglycemia and diabetes admitted in non-critical care settings.