Herpes simplex virus type 1 U(L)34 gene product is required for viral envelopment

The herpes simplex virus type 1 U(L)34 gene encodes a protein that is conserved in all human herpesviruses. The association of the U(L)34 protein with membranes in the infected cell and its expression as a gamma-1 gene suggest a role in maturation or egress of the virus particle from the cell. To determine the function of this gene product, we have constructed a recombinant virus that fails to express the U(L)34 protein. This recombinant virus, in which the U(L)34 protein coding sequence has been replaced by green fluorescent protein, forms minute plaques and replicates in single-step growth experiments to titers 3 to 5 log orders of magnitude lower than wild-type or repair viruses. On Vero cells, the deletion virus synthesizes proteins of all kinetic classes in normal amounts. Electron microscopic and biochemical analyses show that morphogenesis of the deletion virus proceeds normally to the point of formation of DNA-containing nuclear capsids, but electron micrographs show no enveloped virus particles in the cytoplasm or at the surface of infected cells, suggesting that the U(L)34 protein is essential for efficient envelopment of capsids.

Home use of a bihormonal bionic pancreas versus insulin pump therapy in adults with type 1 diabetes: a multicentre randomised crossover trial

BACKGROUND

The safety and effectiveness of a continuous, day-and-night automated glycaemic control system using insulin and glucagon has not been shown in a free-living, home-use setting. We aimed to assess whether bihormonal bionic pancreas initialised only with body mass can safely reduce mean glycaemia and hypoglycaemia in adults with type 1 diabetes who were living at home and participating in their normal daily routines without restrictions on diet or physical activity.

METHODS

We did a random-order crossover study in volunteers at least 18 years old who had type 1 diabetes and lived within a 30 min drive of four sites in the USA. Participants were randomly assigned (1:1) in blocks of two using sequentially numbered sealed envelopes to glycaemic regulation with a bihormonal bionic pancreas or usual care (conventional or sensor-augmented insulin pump therapy) first, followed by the opposite intervention. Both study periods were 11 days in length, during which time participants continued all normal activities, including athletics and driving. The bionic pancreas was initialised with only the participant's body mass. Autonomously adaptive dosing algorithms used data from a continuous glucose monitor to control subcutaneous delivery of insulin and glucagon. The coprimary outcomes were the mean glucose concentration and time with continuous glucose monitoring (CGM) glucose concentration less than 3·3 mmol/L, analysed over days 2-11 in participants who completed both periods of the study. This trial is registered with ClinicalTrials.gov, number NCT02092220.

FINDINGS

We randomly assigned 43 participants between May 6, 2014, and July 3, 2015, 39 of whom completed the study: 20 who were assigned to bionic pancreas first and 19 who were assigned to the comparator first. The mean CGM glucose concentration was 7·8 mmol/L (SD 0·6) in the bionic pancreas period versus 9·0 mmol/L (1·6) in the comparator period (difference 1·1 mmol/L, 95% CI 0·7-1·6; p<0·0001), and the mean time with CGM glucose concentration less than 3·3 mmol/L was 0·6% (0·6) in the bionic pancreas period versus 1·9% (1·7) in the comparator period (difference 1·3%, 95% CI 0·8-1·8; p<0·0001). The mean nausea score on the Visual Analogue Scale (score 0-10) was greater during the bionic pancreas period (0·52 [SD 0·83]) than in the comparator period (0·05 [0·17]; difference 0·47, 95% CI 0·21-0·73; p=0·0024). Body mass and laboratory parameters did not differ between periods. There were no serious or unexpected adverse events in the bionic pancreas period of the study.

INTERPRETATION

Relative to conventional and sensor-augmented insulin pump therapy, the bihormonal bionic pancreas, initialised only with participant weight, was able to achieve superior glycaemic regulation without the need for carbohydrate counting. Larger and longer studies are needed to establish the long-term benefits and risks of automated glycaemic management with a bihormonal bionic pancreas.

FUNDING

National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health, and National Center for Advancing Translational Sciences.

Inequities in Diabetic Ketoacidosis Among Patients With Type 1 Diabetes and COVID-19: Data From 52 US Clinical Centers

OBJECTIVE

We examined whether diabetic ketoacidosis (DKA), a serious complication of type 1 diabetes (T1D) was more prevalent among Non-Hispanic (NH) Black and Hispanic patients with T1D and laboratory-confirmed coronavirus disease 2019 (COVID-19) compared with NH Whites.

METHOD

This is a cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 52 clinical sites in the United States, data were collected from April to August 2020. We examined the distribution of patient factors and DKA events across NH White, NH Black, and Hispanic race/ethnicity groups. Multivariable logistic regression analysis was performed to examine the odds of DKA among NH Black and Hispanic patients with T1D as compared with NH White patients, adjusting for potential confounders, such as age, sex, insurance, and last glycated hemoglobin A1c (HbA1c) level.

RESULTS

We included 180 patients with T1D and laboratory-confirmed COVID-19 in the analysis. Forty-four percent (n = 79) were NH White, 31% (n = 55) NH Black, 26% (n = 46) Hispanic. NH Blacks and Hispanics had higher median HbA1c than Whites (%-points [IQR]: 11.7 [4.7], P < 0.001, and 9.7 [3.1] vs 8.3 [2.4], P = 0.01, respectively). We found that more NH Black and Hispanic presented with DKA compared to Whites (55% and 33% vs 13%, P < 0.001 and P = 0.008, respectively). After adjusting for potential confounders, NH Black patients continued to have greater odds of presenting with DKA compared with NH Whites (OR [95% CI]: 3.7 [1.4, 10.6]).

CONCLUSION

We found that among T1D patients with COVID-19 infection, NH Black patients were more likely to present in DKA compared with NH White patients. Our findings demonstrate additional risk among NH Black patients with T1D and COVID-19.

Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI)

The T1D Exchange established a learning platform by evaluating the current state of care and engaging 10 diabetes clinics in collaborative quality improvement (QI) activities. Participating clinics are sharing data and best practices to improve care delivery for people with type 1 diabetes. This article describes the design and initial implementation of this platform, known as the T1D Exchange Quality Improvement Collaborative. This effort has laid a foundation for learning from variation in type 1 diabetes care delivery via QI methodology and has demonstrated success in improving processes through iterative testing cycles and transparent sharing of data.

Continuous glucose monitoring: current use and future directions

Continuous glucose monitoring (CGM) is an emerging technology that provides a continuous measure of interstitial glucose levels. In addition to providing a more complete pattern of glucose excursions, CGMs utilize real-time alarms for thresholds and predictions of hypo- and hyperglycemia, as well as rate of change alarms for rapid glycemic excursions. CGM users have been able to improve glycemic control without increasing their risk of hypoglycemia. Sensor accuracy, reliability, and wearability are important challenges to CGM success and are critical to the development of an artificial pancreas (or closed-loop system).

Multi-Clinic Quality Improvement Initiative Increases Continuous Glucose Monitoring Use Among Adolescents and Young Adults With Type 1 Diabetes

Continuous glucose monitoring (CGM) use is associated with improved A1C outcomes and quality of life in adolescents and young adults with diabetes; however, CGM uptake is low. This article reports on a quality improvement (QI) initiative of the T1D Exchange Quality Improvement Collaborative to increase CGM use among patients in this age-group. Ten centers participated in developing a key driver diagram and center-specific interventions that resulted in an increase in CGM use from 34 to 55% in adolescents and young adults over 19-22 months. Sites that performed QI tests of change and documented their interventions had the highest increases in CGM uptake, demonstrating that QI methodology and sharing of learnings can increase CGM uptake.

Improved Low-Glucose Predictive Alerts Based on Sustained Hypoglycemia: Model Development and Validation Study

BACKGROUND

Predictive alerts for impending hypoglycemic events enable persons with type 1 diabetes to take preventive actions and avoid serious consequences.

OBJECTIVE

This study aimed to develop a prediction model for hypoglycemic events with a low false alert rate, high sensitivity and specificity, and good generalizability to new patients and time periods.

METHODS

Performance improvement by focusing on sustained hypoglycemic events, defined as glucose values less than 70 mg/dL for at least 15 minutes, was explored. Two different modeling approaches were considered: (1) a classification-based method to directly predict sustained hypoglycemic events, and (2) a regression-based prediction of glucose at multiple time points in the prediction horizon and subsequent inference of sustained hypoglycemia. To address the generalizability and robustness of the model, two different validation mechanisms were considered: (1) patient-based validation (model performance was evaluated on new patients), and (2) time-based validation (model performance was evaluated on new time periods).

RESULTS

This study utilized data from 110 patients over 30-90 days comprising 1.6 million continuous glucose monitoring values under normal living conditions. The model accurately predicted sustained events with >97% sensitivity and specificity for both 30- and 60-minute prediction horizons. The false alert rate was kept to <25%. The results were consistent across patient- and time-based validation strategies.

CONCLUSIONS

Providing alerts focused on sustained events instead of all hypoglycemic events reduces the false alert rate and improves sensitivity and specificity. It also results in models that have better generalizability to new patients and time periods.

Medical and Psychological Considerations for Carbohydrate-Restricted Diets in Youth With Type 1 Diabetes

PURPOSE OF REVIEW

Given the challenges achieving recommended glycemic targets in youth with type 1 diabetes (T1D), providers may consider recommending carbohydrate-restricted diets (CRDs) to optimize glycemic control. The goal of the present review is to describe relevant literature on the potential medical and psychosocial benefits and risks of CRDs in youth with T1D.

RECENT FINDINGS

Limited data exist on the effects of CRDs in pediatric populations. Findings from studies with youth and adults are mixed; some indicate that CRDs may be associated with desirable medical outcomes, such as improved glycemic control and reduced HbA1c, which may contribute to positive psychological outcomes such as reduced diabetes distress and depressive symptoms. Others suggest that CRDs may also be associated with detrimental outcomes, including mineral deficiencies and suboptimal growth, and dietary restriction has been linked to greater diabetes distress, disordered eating, and diabetes management. More research is needed to evaluate benefits and risks of CRDs in youth. Providers should exercise caution when discussing CRDs with youth and families, particularly when considering CRDs for youth at elevated risk for eating disordered behavior.

Camp for Youth With Type 1 Diabetes

Camps for youth with type 1 diabetes (T1D) have grown in size and scope since they first emerged in the 1920s. Anecdotal evidence suggests that attending camp with other youth with T1D is beneficial, largely attributed to sharing fun, active experiences and removing the isolation of living with diabetes. However, few studies have evaluated the psychosocial and medical impacts of T1D camp attendance during and after camp sessions. In addition, T1D camps have been a setting for numerous studies on a variety of T1D-related research questions not related to camp itself, such as testing novel diabetes management technologies in an active, non-laboratory setting. This paper reviews the evidence of psychosocial and medical outcomes associated with T1D camp attendance across the globe, provides an overview of other research conducted at camp, and offers recommendations for future research conducted at T1D camp.

Dyslipidemia in adolescents and young adults with type 1 and type 2 diabetes: a retrospective analysis

Background

Youth onset type 1 diabetes (T1D) and type 2 diabetes (T2D) is increasing and associated with earlier vascular complications and mortality. Dyslipidemia is an important modifiable cardiovascular (CVD) risk factor that is under-recognized and undertreated in youth with T1D and T2D. Given this, we evaluated the prevalence and associations between lipid concentrations and clinical CVD risk factors in youth with T1D compared to T2D at our large ethnically diverse diabetes center.

Methods

A retrospective chart review was performed, evaluating patients with T1D or T2D seen at least once in clinic from 2015 to 2017, age 10–22 years of age, duration of diabetes at least 6 months on the date of most recent LDL-cholesterol (LDL-C) concentration, and not on statin therapy. We performed independent and multivariable linear regressions of LDL-C and HDL-cholesterol (HDL-C) concentrations.

Results

There were 32.7% with T1D (n = 1701) and 47.7% with T2D (n = 298) with LDL-C above recommend goal (> 100 mg/dL/2.6 mmol/L). Furthermore, there were 9% with T1D and 16.4% with T2D with LDL > 130 mg/dL (> 3.4 mmol/L), who likely met criteria for starting statin therapy. Higher LDL-C and/or lower HDL-C were associated with increased age, diabetes duration, higher HbA1C, female sex, Hispanic ethnicity, obesity, and T2D. After adjusting for these risk factors in a multivariable linear regression model, the association of higher LDL-C and lower HDL-C was higher with T2D than T1D.

Conclusions

This highlights the need for more aggressive dyslipidemia screening and treatment in youth with diabetes, especially T2D. At our institution we have created and instituted quality improvement algorithms to try to address this need.

Diabetes Curriculum for Pediatric Endocrine Fellowship Utilizing Modified Team-Based Learning

INTRODUCTION

While type 1 diabetes is frequently encountered clinically in pediatric endocrinology fellowship training, other types of diabetes may only be encountered in educational settings. Adult learners learn best through knowledge application, but to date there are no published curricula utilizing application educational strategies for all forms of diabetes.

METHODS

We utilized a team-based learning (TBL) approach to create four modules on different types of diabetes: type 1 diabetes, type 2 diabetes, neonatal diabetes, and maturity-onset diabetes of the young. We divided our fellows (all training years, n = 11) into two teams and delivered four separate, 90-minute sessions. To emphasize the application of knowledge, we modified the format to combine the readiness assurance test (RAT) with application problem (APP) questions. The combined RAT/APP questions were answered by individuals and teams. We analyzed scores from individual and team tests and evaluated each module. Additionally, we acquired subjective data from the fellows regarding their experiences.

RESULTS

Teams outperformed individuals on the tests, as expected (94% vs. 76% correct questions, respectively). All the fellows agreed that the sessions should be included permanently. Additionally, all agreed the sessions helped them apply knowledge. Subjectively, the fellows were very engaged and lively during the sessions and felt the sessions were feasible as implemented.

DISCUSSION

TBL can be a valuable educational strategy to increase the application of knowledge for diabetes in pediatric endocrinology fellows. Future studies examining the use of this strategy to increase critical thinking skills and knowledge retention in the long-term would be useful.

Erratum. Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Clinical Diabetes 2020;38:141-151 (DOI: 10.2337/cd19-0032)

[This corrects the article on p. 141 in vol. 38, PMID: 32327886.].

Hypoglycemia Prediction in Type 1 Diabetes With Electrocardiography Beat Ensembles

INTRODUCTION

Current methods to detect hypoglycemia in type 1 diabetes (T1D) require invasive sensors (ie, continuous glucose monitors, CGMs) that generally have low accuracy in the hypoglycemic range. A forward-looking alternative is to monitor physiological changes induced by hypoglycemia that can be measured non-invasively using, eg, electrocardiography (ECG). However, current methods require extraction of fiduciary points in the ECG signal (eg, to estimate QT interval), which is challenging in ambulatory settings.

METHODS

To address this issue, we present a machine-learning model that uses (1) convolutional neural networks (CNNs) to extract morphological information from raw ECG signals without the need to identify fiduciary points and (2) ensemble learning to aggregate predictions from multiple ECG beats. We evaluate the model on an experimental data set that contains ECG and CGM recordings over a period of 14 days from ten participants with T1D. We consider two testing scenarios, one that divides ECG data according to CGM readings (CGM-split) and another that divides ECG data on a day-to-day basis (day-split).

RESULTS

We find that models trained using CGM-splits tend to produce overly optimistic estimates of hypoglycemia prediction, whereas day-splits provide more realistic estimates, which are consistent with the intrinsic accuracy of CGM devices. More importantly, we find that aggregating predictions from multiple ECG beats using ensemble learning significantly improves predictions at the beat level, though these improvements have large inter-individual differences.

CONCLUSION

Deep learning models and ensemble learning can extract and aggregate morphological information in ECG signals that is predictive of hypoglycemia. Using two validation procedures, we estimate an upper bound on the accuracy of ECG hypoglycemia prediction of 81% equal error rate and a lower bound of 60%. Further improvements may be achieved using big-data approaches that require longitudinal data from a large cohort of participants.

Diabetic ketoacidosis in youth with diabetes mellitus during the COVID-19 pandemic

OBJECTIVES

We sought to determine if the early months of the coronavirus disease 2019 (COVID-19) pandemic influenced pediatric diabetic ketoacidosis (DKA) hospitalization characteristics.

METHODS

This is a cross-sectional study of youth with laboratory-confirmed DKA admitted to a large tertiary children's hospital in the USA. Data were collected from admissions in March through July 2019 and March through July 2020, respectively. We evaluated the clinical characteristics of hospitalization, including demographic data and DKA severity. We used univariable ordinal logistic regression followed by multiple ordinal logistic regression to adjust for potential confounders.

RESULTS

We included 137 children with diabetes admitted for DKA in the relevant period in 2019 and 173 patients admitted for DKA in the same period in 2020. Hemoglobin A1C (HbA1c) upon admission was higher in 2020 (median=12.2 %) than in 2019 (11.5 %, p=0.018). Children who were admitted with DKA in 2020 were less likely to be autoantibody positive than those in 2019 (83 vs. 91 %, p=0.028). In the univariable model, being admitted in 2020 was significantly associated with more severe DKA (p=0.038), as was HbA1c (p=0.001). After adjusting for HbA1c upon admission, admission year was no longer significantly associated with more severe DKA.

CONCLUSIONS

In this study of pediatric diabetes of any type and duration of diabetes, youth admitted for DKA at the start of the COVID-19 pandemic, compared with those admitted during the year before, were more likely to have autoantibody-negative diabetes and had significantly higher HbA1c. Additionally, higher HbA1c seemed to mediate more severe DKA during the pandemic.