Telemedicine for Disparity Patients With Diabetes: The Feasibility of Utilizing Telehealth in the Management of Uncontrolled Type 2 Diabetes in Black and Hispanic Disparity Patients; A Pilot Study.

BACKGROUND: Non-Hispanic Black (NHB) and Hispanic/Latinx (H/L) patients bear a disproportionate burden of type 2 diabetes and associated complications. Regular visits to a primary care doctor or diabetes specialist are warranted to maintain glycemic control, but for a myriad of reasons disparity populations may have difficulties receiving diabetes care. We seek to determine the feasibility of telehealth added to care as usual and secondarily to improve health outcomes (hemoglobin A1c [HbA1c]) in NHB and H/L with uncontrolled type 2 diabetes managed with two or three noninsulin agents. METHODS: Twenty-nine patients were randomized to monthly phone calls or weekly to biweekly telehealth visits. Feasibility outcomes were summarized descriptively for the telehealth arm. Differences scores for A1C level and surveys were computed between baseline and three months and compared across arms using a two-sample t test or Mann-Whitney U test. RESULTS: Patients in the telehealth arm completed a median of eight visits (IQR: 5, 8), and 53% of those in the telephone arm completed 100% of their calls. Change in HbA1c was greater for those in the telephone arm (-2.57 vs -2.07%, P = .70) but the mean baseline HbA1c was higher in the telephone group (11.1% vs 10.3%). Although the change in HbA1c was not statistically different across arms, it was clinically significant. CONCLUSIONS: Augmenting care as usual with telehealth provided by telephone or tablet can be of benefit in improving glycemic control in NHB and H/L with type 2 diabetes. Larger studies need to explore this further.

Multidisciplinary management of endocrinopathies and treatment-related toxicities in patients with Bloom syndrome and cancer.

The treatment of malignancy in cancer predisposition syndromes that also confer exquisite sensitivity to standard chemotherapy and radiation regimens remains a challenge. Bloom syndrome is one such disorder that is caused by a defect in DNA repair, predisposing to the development of early-onset age-related medical conditions and malignancies. We report on two patients with Bloom syndrome who responded well to chemotherapy despite significant alterations to standard protocols necessitated by hypersensitivity. Both patients experienced severe toxicities and exacerbation of endocrine comorbidities during chemotherapy. A multidisciplinary team of oncologists and endocrinologists is best suited to care for this patient population.

Hypoglycemia in Patients with Type 2 Diabetes Mellitus and Chronic Kidney Disease: A Prospective Observational Study.

Background: Glycemic management in patients with type 2 diabetes mellitus (T2DM) and CKD can become complicated. One factor that may affect treatment is hypoglycemia. Hypoglycemia risk may be increased by several biologic processes in CKD. The objective of this study was to determine the frequency, severity, and risk factors for hypoglycemia in patients with T2DM and CKD. Methods: The design was a prospective observational study. A continuous glucose monitor (CGM) was worn by 80 patients for up to 14 days; glucose was measured every 15 minutes. Patients with T2DM and eGFR <45 ml/min were enrolled. Patients on dialysis were excluded. The primary outcome was to assess the frequency of hypoglycemic episodes during the study period. Hypoglycemic episodes were defined as a reduced glucose concentration (<70 mg/dl) lasting ≥15 minutes. Secondary outcomes included assessment of severity of hypoglycemia and risk factors for its development. Results: A total of 80 patients wore the CGM for a mean of 12.7±2.9 days. Hypoglycemic events occurred in 61 of 80 patients (76%) with glucose <70 mg/dl, and 49 of 80 (61%) with glucose <60 mg/dl. Prolonged hypoglycemic events (CGM glucose <54 mg/dl for ≥120 consecutive minutes) occurred in 31 patients (39%) with 118 total events. Most hypoglycemic episodes occurred overnight, from 1:00 am to 9:00 am. By multivariate analysis, lower hemoglobin A1c and treatment with insulin were two modifiable risk factors for hypoglycemic events. Conclusions: Patients with T2DM and CKD have frequent periods of hypoglycemia that can be severe and prolonged. Hemoglobin A1c does not portray the full scope of hypoglycemia risk. This study illustrates the need for careful monitoring of glucose levels in patients with T2DM and CKD.

Continuous Glucose Monitoring and Glycemic Control in Patients With Type 2 Diabetes Mellitus and CKD.

RATIONALE & OBJECTIVE: The accuracy of glycated hemoglobin (HbA1c) level for assessment of glycemic control in patients with chronic kidney disease (CKD) is uncertain. This study assessed the accuracy of HbA1c level using continuous glucose monitoring. STUDY DESIGN: Diagnostic test study of HbA1c and serum fructosamine. The continuous glucose monitor was worn for 14 days. Glucose was measured every 15 minutes (up to 1,344 measurements). Average glucose concentration was calculated for each patient from the patient's continuous glucose monitor measurements. Linear regression was applied to estimate the relationship between average glucose concentration and HbA1c and serum fructosamine levels. The influence of patient characteristics on the relationship between HbA1c and average glucose concentrations was examined in a multivariate regression model. SETTING & PARTICIPANTS: Patients with type 2 diabetes and CKD (estimated glomerular filtration rate, 7-45 mL/min, not receiving dialysis) seen in an academic nephrology clinic. TESTS ANALYZED: The accuracy of HbA1c level for assessment of chronic glycemia. A secondary objective was to study serum fructosamine levels. OUTCOMES: The degree of correlation between continuous glucose monitoring-derived average glucose concentration and HbA1c level; serum fructosamine level was studied as a secondary outcome. RESULTS: 80 patients wore the continuous glucose monitor for a mean of 12.7 ± 2.9 days. Average glucose concentration of all patients was 151.5 ± 55.7 mg/dL. Mean HbA1c level was 7.2% ± 1.5%. HbA1c level was highly correlated with average glucose concentration, described by the equation: average glucose concentration = 30.48 × HbA1c - 68.48; r = 0.82; P < 0.001. Serum fructosamine level was also significantly correlated with average glucose concentration; r = 0.55; P < 0.001. The strong correlation between average glucose concentration and HbA1c level was not affected by the severity of CKD, whereas the performance of serum fructosamine level, in contrast, degraded among patients with more severe CKD. LIMITATIONS: Relatively small sample size. CONCLUSIONS: HbA1c is an accurate measure of glycemic status among patients with CKD and type 2 diabetes. This relationship appears to hold true among patients with more severe CKD.

What to do after basal insulin: 3 Tx strategies for type 2 diabetes.

These strategies can help you optimize glucose control in your patient with type 2 diabetes when basal insulin alone isn't sufficient.

Lipodystrophy: Syndrome of severe insulin resistance.

CONTEXT: Lipodystrophy (LD) is a relatively rare complex collection of diseases that can be congenital or acquired. It is commonly missed in the clinical setting. Thus, the spectrum of disease presentation mandates clinician expertise in the pathophysiology and management of all forms of LD, obesity, and insulin resistance. METHODS AND MATERIALS: An extensive literature search of clinical trials, systematic reviews, and narrative reviews was completed in PubMed for the years 1970 to 2013. The search terms were lipodystrophy, congenital LD, acquired LD, HIV-associated LD, severe insulin resistance, adiposity, obesity, and dyslipidemia. EVIDENCE SYNTHESIS: Lipodystrophies are a heterogeneous group of disorders with abnormal adipose tissue distribution, utilization, and metabolism. Adipose tissue can undergo significant changes in composition (hypertrophy and atrophy) in response to a nutritional state. Paradoxically, both excess and deficient adipose tissue is associated with insulin resistance and the metabolic syndrome. Bone density scan (DEXA) for body fat composition analysis or magnetic resonance imaging are optimal modalities for the assessment of abnormal adipose tissue distribution. Ongoing clinical studies suggest thiazolidinediones, insulin like growth factor-1, leptin, and growth hormone-releasing hormone as possible treatment for LPD; however, none of them is approved to reverse fat loss or treat severe insulin resistance due to LPD. CONCLUSION: The underlying mechanisms for LPD causing insulin resistance may be lipotoxicity and derangements in adipose tissue-derived proteins (adipocytokines). However, the lack of evidence to support this model means that clinicians are on their own as they navigate through the phenotypic presentation of lipodystrophies, obesity, insulin resistance, and the metabolic syndrome.