Synchronous Health Care Delivery for the Optimization of Cardiovascular and Renal Care in Patients with Type 2 Diabetes

PURPOSE OF REVIEW

The current care model of type 2 diabetes (T2D) and its complications appears to be "asynchronous" with patient care divided by specialty. This model is associated with low use of guideline-directed medical therapies.

RECENT FINDINGS

The use of integrated care models has been well described in the management of patients with T2D; this usually includes an endocrinologist coupled with a nutritionist and nurse. However, physician-based care models are largely "asynchronous," whereby the patient requires multiple different siloed specialties to manage their health care. To date, there has been limited exploration of synchronous care delivery, i.e., whereby multi-comorbid patients with T2D are seen simultaneously by health care providers from endocrinology, cardiology, and nephrology to optimize use of guideline-directed medical therapies (GDMT). Given the rising complexity of patients with T2D, further research is needed on the role of synchronous health care delivery in optimizing the use of GDMT and improving patient outcomes.

Clinical Prediction Models for Heart Failure Hospitalization in Type 2 Diabetes: A Systematic Review and Meta-Analysis

Background Clinical prediction models have been developed for hospitalization for heart failure in type 2 diabetes. However, a systematic evaluation of these models' performance, applicability, and clinical impact is absent. Methods and Results We searched Embase, MEDLINE, Web of Science, Google Scholar, and Tufts' clinical prediction registry through February 2021. Studies needed to report the development, validation, clinical impact, or update of a prediction model for hospitalization for heart failure in type 2 diabetes with measures of model performance and sufficient information for clinical use. Model assessment was done with the Prediction Model Risk of Bias Assessment Tool, and meta-analyses of model discrimination were performed. We included 15 model development and 3 external validation studies with data from 999 167 people with type 2 diabetes. Of the 15 models, 6 had undergone external validation and only 1 had low concern for risk of bias and applicability (Risk Equations for Complications of Type 2 Diabetes). Seven models were presented in a clinically useful manner (eg, risk score, online calculator) and 2 models were classified as the most suitable for clinical use based on study design, external validity, and point-of-care usability. These were Risk Equations for Complications of Type 2 Diabetes (meta-analyzed c-statistic, 0.76) and the Thrombolysis in Myocardial Infarction Risk Score for Heart Failure in Diabetes (meta-analyzed c-statistic, 0.78), which was the simplest model with only 5 variables. No studies reported clinical impact. Conclusions Most prediction models for hospitalization for heart failure in patients with type 2 diabetes have potential concerns with risk of bias or applicability, and uncertain external validity and clinical impact. Future research is needed to address these knowledge gaps.

Clinical Phenotypes in Patients With Type 2 Diabetes Mellitus: Characteristics, Cardiovascular Outcomes and Treatment Strategies

PURPOSE OF REVIEW

With recent advances in the pharmacological management of type 2 diabetes mellitus (T2DM), there is a growing need to understand which patients optimally benefit from these novel therapies. Various clinical clustering methodologies have emerged that utilise data-agnostic strategies to categorise patients that have similar clinical characteristics and outcomes; broadly, this characterisation is termed phenotyping. In patients with T2DM, we aimed to describe patient characteristics from phenotype studies, their cardiovascular risk profiles and the impact of antihyperglycemic treatment.

RECENT FINDINGS

Numerous phenotypic studies have been undertaken that have utilised a combination of clinical, biochemical, imaging and genetic variables. Each of these has produced phenotypes that display a spectrum of cardiovascular risk. Studies that aimed to describe pathophysiological phenotypes generally identified five phenotypes: autoimmune phenotype, insulin-related phenotypes (including permutations of insulin deficiency and resistance), obesity phenotype, ageing phenotype, and a sex-related phenotype. Studies examining risk profiles have demonstrated that across such phenotypes there is a spectrum of risk for diabetic complications. Few studies have examined treatment effects across these phenotypes, and thus provide little insights towards making phenotype-guided treatment decisions Clustering analyses in patients with T2DM have identified distinct phenotypes with unique risk profiles. Further studies are needed that harness the use of clinical, biochemical, imaging and genetic data to explore therapeutic heterogeneity and response to antihyperglycemic treatment across the spectrum of patient phenotypes.

MON-154 Inhaled Corticosteroids and Adrenal Insufficiency: A Meta-Analysis and Systematic Review

Inhaled corticosteroids have been associated with adrenal insufficiency in adult and pediatric populations¹,². When inhaled corticosteroids are absorbed orally, they can have a systemic effect. Corticosteroid type, particle size, delivery method, liver metabolism via CYP 3A4, protein binding, and half-life all impact the magnitude of the systemic effect of inhaled corticosteroids³. We conducted a systematic review and meta-analysis in order to establish the prevalence of adrenal insufficiency among adult patients taking inhaled corticosteroids. We searched the PubMed, Embase and Cochrane databases for “adrenal insufficiency” AND “inhaled corticosteroids”, yielding 318 search results. We also hand-searched the references of relevant articles. In total, 30 studies were included in our meta-analysis. Amongst these, 15 studies were RCTs and 13 studies were cross-sectional studies. All of these studies used ACTH stimulation testing to diagnose adrenal insufficiency. Risk of bias assessment was completed for all studies using the Cochrane risk of bias assessment tool. Patients with asthma were the population examined in 90% of the included studies. Prevalence of adrenal insufficiency demonstrated by ACTH stimulation testing varied from under 5% to up to 55% among different studies. We recommend that further studies carefully examine and report the clinical impact of abnormal ACTH stimulation testing results, the concomitant use of oral corticosteroids, and the impact of the inhaled corticosteroid delivery method, the corticosteroid type, the corticosteroid dosage, and the duration of therapy.

References:

1. Lapi F, Kezouh A, Suissa S, Ernst P. The use of inhaled corticosteroids and the risk of adrenal insufficiency. Eur Respir J. 2013;42(1)-79-86.

2. Goldbloom EB, Mokashi A, Cummings EA, et al. Symptomatic adrenal suppression among children in Canada. Arch Dis Child. 2017;102(4)-338-339.

3. Ahmet A, Kim H, Spier S. Adrenal suppression- A practical guide to the screening and management of this under-recognized complication of inhaled corticosteroid therapy. Allergy Asthma Clin Immunol. 2011;7-13.

Accuracy of FreeStyle Libre in Adults with Type 1 Diabetes: The Effect of Sensor Age

Background: FreeStyle Libre is a factory-calibrated continuous 14-day glucose sensor. Little is known about the accuracy of FreeStyle Libre as a function of sensor age. Methods: We assessed the accuracy of FreeStyle Libre in 14 adults with type 1 diabetes. Each study participant attended our research facility for two or three 24-h visits, during which they wore a FreeStyle Libre aged 0-1 day, 5-7 days, or 13-14 days. Plasma glucose levels were measured every 10-30 min using YSI2300 STAT Plus Analyser. Participants also wore Dexcom G5^® glucose sensor aged 1-2 days. We assessed sensors' accuracy using mean absolute relative difference (MARD) between FreeStyle Libre, the Dexcom G5 sensor, and plasma glucose. Results: We had 1930 pairs of FreeStyle Libre sensor-plasma glucose measurements, collected from 36 FreeStyle Libre sensors, 18 of which were sensors aged 0-1 day, 9 were sensors aged 5-7 days, and 9 were sensors aged 13-14 days. The mean and median MARD for FreeStyle Libre sensors aged 0-1 days were 14.5% and 11.2%, respectively, and for sensors aged 13-14 days were 14.7% and 11.2%, respectively, but for sensors aged 5-7 days were 7.8% and 6.6%, respectively (P = 0.03 vs. sensors aged 0-1 days, and P = 0.06 vs. sensors aged 13-14 days). The percentage of points falling in the potentially dangerous zones C, D, or E in Clarke's error grid analysis were 1.9% for FreeStyle Libre sensors aged 0-1 day, 0.2% for sensors aged 5-7 days, and 0.4% for sensors aged 13-14 days. The overall accuracy of FreeStyle Libre and Dexcom G5 sensor was the same (mean MARD 12.8% and 12.5%, respectively; P = 0.57). Conclusions: FreeStyle Libre's accuracy is adequate during its entire lifetime but is least accurate during its first and last days. ClinicalTrials.gov Identifier: NCT02814123.

Posttraumatic stress disorder, alone or additively with early life adversity, is associated with obesity and cardiometabolic risk

BACKGROUND AND AIMS

There is some evidence that posttraumatic stress disorder (PTSD) and early life adversity may influence metabolic outcomes such as obesity, diabetes, and cardiovascular disease. However, whether and how these interact is not clear.

METHODS

We analyzed data from a cross-sectional and longitudinal study to determine how PTSD severity influences obesity, insulin sensitivity, and key measures and biomarkers of cardiovascular risk. We then looked at how PTSD and early life adversity may interact to impact these same outcomes.

RESULTS

PTSD severity is associated with increasing risk of obesity, diabetes, and cardiovascular disease, with higher symptoms correlating with higher values of BMI, leptin, fibrinogen, and blood pressure, and lower values of insulin sensitivity. PTSD and early life adversity have an additive effect on these metabolic outcomes. The longitudinal study confirmed findings from the cross sectional study and showed that fat mass, leptin, CRP, sICAM-1, and sTNFRII were significantly increased with higher PTSD severity during a 2.5 year follow-up period.

CONCLUSIONS

Individuals with early life adversity and PTSD are at high risk and should be monitored carefully for obesity, insulin resistance, and cardiometabolic risk.

Accelerated healing of pyoderma gangrenosum treated with bioengineered skin and concomitant immunosuppression

Pyoderma gangrenosum is a rare, destructive, neutrophilic dermatosis, the origin of which remains largely obscure. The ulcerative variant of this inflammatory disorder causes painful, necrotic, rapidly enlarging ulcers. Because of pathergy, many clinicians avoid managing these nonhealing ulcers with aggressive surgical debridement and autologous grafts. This article proposes that the application of an allogeneic cultured human skin equivalent (Graftskin) not only circumvents this problem, but also hastens re-epithelialization of the ulcer bed. An added benefit of the possible improvement of the cosmetic appearance of the final scar by preventing severe wound contracture is also postulated. We report a newly diagnosed case of ulcerative pyoderma gangrenosum; the use of bioengineered skin as an adjunct to concurrent immunosuppressive therapy with cyclosporine hastened the healing and diminished pain in a rapidly enlarging leg ulcer. Within 2 weeks, the ulcer was 30% to 40% healed, achieving 100% re-epithelialization within 6 weeks.