CHANGING TO BASAL-BOLUS INSULIN THERAPY FOR THE INPATIENT MANAGEMENT OF HYPERGLYCEMIA-A NATURAL EXPERIMENT.

Objective: Most acute-care hospitals have transitioned from sliding-scale to basal-bolus insulin therapy to manage hyperglycemia during hospitalization, but there is limited scientific evidence demonstrating better short-term clinical outcomes using the latter approach. The present study sought to determine if using basal-bolus insulin therapy favorably affects these outcomes in noncritical care settings and, if so, whether the magnitude of benefit differs in patients with known versus newly diagnosed type 2 diabetes. Methods: This natural experiment compared outcomes in 10,120 non-critically ill adults with type 2 diabetes admitted to an academic teaching hospital before and after hospital-wide implementation of a basal-bolus insulin therapy protocol. A group of 30,271 inpatients without diabetes (type 1 or 2) served as controls. Binomial models were used to compare percentages of patients with type 2 diabetes who were transferred to intensive care, experienced complications, or died in the hospital before and after implementation of the protocol, controlling for changes in the control group. The analysis also evaluated before-after changes in length of stay and glucometric indicators. Results: Implementation of basal-bolus therapy did not reduce intensive care use (the primary outcome), complications, mortality, or median length of stay, except in patients with newly diagnosed diabetes (n = 234), who experienced a statistically significant decline in the incidence of complications (P<.01). The absence of effect in previously diagnosed patients was observed in spite of a 32% decline (from 3.7% to 2.5%) in the proportion of inpatient days with hypoglycemia <70 mg/dL (P<.01) and a 16% decline (from 13.5% to 11.3%) in the proportion of days with hyperglycemia >300 mg/dL (P<.01). Conclusion: Despite achieving significant reductions in both hyperglycemia and hypoglycemia, use of basal-bolus insulin therapy to manage hyperglycemia in non-critically ill hospitalized patients did not improve short-term clinical outcomes, except in the small minority of patients with newly diagnosed diabetes. The optimal management of hyperglycemia for improving these outcomes has yet to be determined. Abbreviation: ICD-9 = International Classification of Diseases-Ninth Revision.

Pitfalls in hemoglobin A1c measurement: when results may be misleading.

Since the beginning of clinical use in the 1970s, hemoglobin A1c (A1c) has become the standard tool for monitoring glycemic control in patients with diabetes. The role of the A1c test was broadened in 2010, when the American Diabetes Association added A1c as a diagnostic criterion for diabetes. Because of hemoglobin A1c's integral role in diagnosis and treatment, it is important to recognize clinical scenarios and interfering factors that yield false results. The purpose of this review is to describe the A1c measurement, outline clinical scenarios or factors that may yield false results, and describe alternative laboratory biomarkers.

Assessing Prevalence of Hypoglycemia in a Medical Transcription Database.

PURPOSE: The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database. PATIENTS AND METHODS: The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018. RESULTS: Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses. CONCLUSION: In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.

ß-Cell death is decreased in women with gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) affects approximately 7-17 % of all pregnancies and has been recognized as a significant risk factor to neonatal and maternal health. Postpartum, GDM significantly increases the likelihood of developing type 2 diabetes (T2D). While it is well established that insulin resistance and impaired ß-cell function contribute to GDM development, the role of active ß-cell loss remains unknown. Differentially methylated circulating free DNA (cfDNA) is a minimally invasive biomarker of ß-cell loss in type 1 diabetes mellitus. Here we use cfDNA to examine the levels of ß-cell death in women with GDM. METHODS: Second to third-trimester pregnant women with GDM were compared with women with normal pregnancy (PRG), women at postpartum (PP), and non-pregnant (NP) women. Fasting glucose levels, insulin, and C-peptide levels were measured. Serum samples were collected and cfDNA purified and bisulfite treated. Methylation-sensitive probes capable of differentiating between ß-cell-derived DNA (demethylated) and non-ß-cell-derived DNA (methylated) were used to measure the presence of ß-cell loss in the blood. RESULTS: GDM was associated with elevated fasting glucose levels (GDM = 185.9 ± 5.0 mg/dL) and reduced fasting insulin and c-peptide levels when compared with NP group. Interestingly, ß-cell derived insulin DNA levels were significantly lower in women with GDM when compared with PRG, NP, and PP groups (demethylation index: PRG = 7.74 × 10(-3) ± 3.09 × 10(-3), GDM = 1.01 × 10(-3) ± 5.86 × 10(-4), p < 0.04; NP = 4.53 × 10(-3) ± 1.62 × 10(-3), PP = 3.24 × 10(-3) ± 1.78 × 10(-3)). CONCLUSIONS: These results demonstrate that ß-cell death is reduced in women with GDM. This reduction is associated with impaired insulin production and hyperglycemia, suggesting that ß-cell death does not contribute to GDM during the 2nd and 3rd trimester of pregnancy.