Priya Prahalad, MD

Abstract

Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N=1309) to children with (N=6545) and without (N=6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls.We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise.Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes.We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

View details for DOI 10.1093/jamiaopen/ooad016

View details for PubMedID 36926600

View details for PubMedCentralID PMC10013630

View details for DOI 10.1089/dia.2023.2508

View details for PubMedID 36802194

View details for DOI 10.1007/s11892-023-01500-8

View details for PubMedID 36708445

Abstract

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.

View details for DOI 10.1177/19322968221148743

View details for PubMedID 36704821

Abstract

PURPOSE OF REVIEW: Although advances in diabetes technology and pharmacology have significantly and positively impacted diabetes management and health outcomes for some, diabetes care remains burdensome and can be challenging to balance with other life priorities. The purpose of this article is to review the rationale for assessment of psychosocial domains in diabetes care settings and strategies for the implementation of psychosocial screening into routine practice. Survey data from the Type 1 Diabetes Exchange Quality Improvement Network is highlighted.RECENT FINDINGS: Implementation of psychosocial screening requires identifying the population; selecting validated tools to assess target domains; determining frequency of screening and mode of survey delivery; and scoring, interpreting, documenting, and facilitating referrals such that these processes are part of clinical workflows. Recognizing the influence of psychosocial factors for people with diabetes (PWD), professional society guidelines for comprehensive diabetes care recommend the integration of psychosocial screening into routine care.

View details for DOI 10.1007/s11892-022-01497-6

View details for PubMedID 36538250

Abstract

AIMS: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D.METHODS: We analyzed electronic health record data from the Cerner Real-World DataTM (CRWD) de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection.RESULTS: In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m2), increased BMI (>25.0-29.9 kg/m2), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c).CONCLUSIONS: The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes.

View details for DOI 10.1016/j.diabres.2022.110156

View details for PubMedID 36400172

Abstract

Population-level algorithm-enabled remote patient monitoring (RPM) based on continuous glucose monitor (CGM) data review has been shown to improve clinical outcomes in diabetes patients, especially children. However, existing reimbursement models are geared towards the direct provision of clinic care, not population health management. We developed a financial model to assist pediatric type 1 diabetes (T1D) clinics design financially sustainable RPM programs based on algorithm-enabled review of CGM data.Data were gathered from a weekly RPM program for 302 pediatric patients with T1D at Lucile Packard Children's Hospital. We created a customizable financial model to calculate the yearly marginal costs and revenues of providing diabetes education. We consider a baseline or status quo scenario and compare it to two different care delivery scenarios, in which routine appointments are supplemented with algorithm-enabled, flexible, message-based contacts delivered according to patient need. We use the model to estimate the minimum reimbursement rate needed for telemedicine contacts to maintain revenue-neutrality and not suffer an adverse impact to the bottom line.The financial model estimates that in both scenarios, an average reimbursement rate of roughly $10.00 USD per telehealth interaction would be sufficient to maintain revenue-neutrality. Algorithm-enabled RPM could potentially be billed for using existing RPM CPT codes and lead to margin expansion.We designed a model which evaluates the financial impact of adopting algorithm-enabled RPM in a pediatric endocrinology clinic serving T1D patients. This model establishes a clear threshold reimbursement value for maintaining revenue-neutrality, as well as an estimate of potential RPM reimbursement revenue which could be billed for. It may serve as a useful financial-planning tool for a pediatric T1D clinic seeking to leverage algorithm-enabled RPM to provide flexible, more timely interventions to its patients.

View details for DOI 10.3389/fendo.2022.1021982

View details for PubMedID 36440201

View details for PubMedCentralID PMC9691757

Abstract

To analyze whether the coronavirus disease 2019 (COVID-19) pandemic increased the number of cases or impacted seasonality of new-onset type 1 diabetes (T1D) in large pediatric diabetes centers globally.We analyzed data on 17,280 cases of T1D diagnosed during 2018-2021 from 92 worldwide centers participating in the SWEET registry using hierarchic linear regression models.The average number of new-onset T1D cases per center adjusted for the total number of patients treated at the center per year and stratified by age-groups increased from 11.2 (95% CI 10.1-12.2) in 2018 to 21.7 (20.6-22.8) in 2021 for the youngest age-group, <6 years; from 13.1 (12.2-14.0) in 2018 to 26.7 (25.7-27.7) in 2021 for children ages 6 to <12 years; and from 12.2 (11.5-12.9) to 24.7 (24.0-25.5) for adolescents ages 12-18 years (all P < 0.001). These increases remained within the expected increase with the 95% CI of the regression line. However, in Europe and North America following the lockdown early in 2020, the typical seasonality of more cases during winter season was delayed, with a peak during the summer and autumn months. While the seasonal pattern in Europe returned to prepandemic times in 2021, this was not the case in North America. Compared with 2018-2019 (HbA1c 7.7%), higher average HbA1c levels (2020, 8.1%; 2021, 8.6%; P < 0.001) were present within the first year of T1D during the pandemic.The slope of the rise in pediatric new-onset T1D in SWEET centers remained unchanged during the COVID-19 pandemic, but a change in the seasonality at onset became apparent.

View details for DOI 10.2337/dc22-0278

View details for PubMedID 36166593

Abstract

Initiating continuous glucose monitoring (CGM) shortly after Type 1 diabetes diagnosis has glycemic and quality of life benefits for youth with Type 1 diabetes and their families. The SARS-CoV-2 pandemic led to a rapid shift to virtual delivery of CGM initiation visits. We aimed to understand parents' experiences receiving virtual care to initiate CGM within 30days of diagnosis.We held focus groups and interviews using a semi-structured interview guide with parents of youth who initiated CGM over telehealth within 30days of diagnosis during the SARS-CoV-2 pandemic. Questions aimed to explore experiences of starting CGM virtually. Groups and interviews were audio-recorded, transcribed, and analyzed using thematic analysis.Participants were 16 English-speaking parents (age 436years; 63% female) of 15 youth (age 94years; 47% female; 47% non-Hispanic White, 20% Hispanic, 13% Asian, 7% Black, 13% other). They described multiple benefits of the virtual visit including convenient access to high-quality care; integrating Type 1 diabetes care into daily life; and being in the comfort of home. A minority experienced challenges with virtual care delivery; most preferred the virtual format. Participants expressed that clinics should offer a choice of virtual or in-person to families initiating CGM in the future.Most parents appreciated receiving CGM initiation education via telehealth and felt it should be an option offered to all families. Further efforts can continue to enhance CGM initiation teaching virtually to address identified barriers.

View details for DOI 10.1111/dme.14923

View details for PubMedID 35899591

Abstract

PURPOSE OF REVIEW: To synthesize findings from studies published within the last 5 to 10years and recruiting families of children with new-onset type 1 diabetes (T1D).RECENT FINDINGS: Children can establish glycated hemoglobin (HbA1c) trajectories in the new-onset period that may persist for up to a decade. Demographic factors, family conflict, and diabetic ketoacidosis at the time of diagnosis may be risk factors for sub-optimal child HbA1c, while new immune modulating therapies and a treatment approach that combines advanced technologies and remote patient monitoring may improve child HbA1c. Nonetheless, recent trials in the new-onset period have largely overlooked how treatments may impact families' psychosocial functioning and longitudinal observational studies have been limited. The new-onset period of T1D is an important time for research and clinical intervention, though gaps exist specific to families' psychosocial needs. Filling these gaps is essential to inform clinical management and standard of care guidelines and improve outcomes.

View details for DOI 10.1007/s11892-022-01479-8

View details for PubMedID 35727439

Abstract

BACKGROUND: The use of continuous glucose monitors (CGMs) is recommended as the standard of care by the American Diabetes Association for individuals with type 1 diabetes (T1D). Few hardware-agnostic, open-source, whole-population tools are available to facilitate the use of CGM data by clinicians such as physicians and certified diabetes educators.OBJECTIVE: This study aimed to develop a tool that identifies patients appropriate for contact using an asynchronous message through electronic medical records while minimizing the number of patients reviewed by a certified diabetes educator or physician using the tool.METHODS: We used consensus guidelines to develop timely interventions for diabetes excellence (TIDE), an open-source hardware-agnostic tool to analyze CGM data to identify patients with deteriorating glucose control by generating generic flags (eg, mean glucose [MG] >170 mg/dL) and personalized flags (eg, MG increased by >10 mg/dL). In a prospective 7-week study in a pediatric T1D clinic, we measured the sensitivity of TIDE in identifying patients appropriate for contact and the number of patients reviewed. We simulated measures of the workload generated by TIDE, including the average number of time in range (TIR) flags per patient per review period, on a convenience sample of eight external data sets, 6 from clinical trials and 2 donated by research foundations.RESULTS: Over the 7 weeks of evaluation, the clinical population increased from 56 to 64 patients. The mean sensitivity was 99% (242/245; SD 2.5%), and the mean reduction in the number of patients reviewed was 42.6% (182/427; SD 10.9%). The 8 external data sets contained 1365 patients with 30,017 weeks of data collected by 7 types of CGMs. The rates of generic and personalized TIR flags per patient per review period were, respectively, 0.15 and 0.12 in the data set with the lowest average MG (141 mg/dL) and 0.95 and 0.22 in the data set with the highest average MG (207 mg/dL).CONCLUSIONS: TIDE is an open-source hardware-agnostic tool for personalized analysis of CGM data at the clinical population scale. In a pediatric T1D clinic, TIDE identified 99% of patients appropriate for contact using an asynchronous message through electronic medical records while reducing the number of patients reviewed by certified diabetes care and education specialists by 43%. For each of the 8 external data sets, simulation of the use of TIDE produced fewer than 0.25 personalized TIR flags per patient per review period. The use of TIDE to support telemedicine-based T1D care may facilitate sensitive and efficient guideline-based population health management.

View details for DOI 10.2196/27284

View details for PubMedID 35666570

Abstract

In July 2018, pediatric type 1 diabetes (T1D) care at Stanford suffered many of the problems that plague U.S. health care. Patient outcomes lagged behind those of peer European nations, care was delivered primarily on a fixed cadence rather than as needed, continuous glucose monitors (CGMs) were largely unavailable for individuals with public insurance, and providers' primary access to CGM data was through long printouts. Stanford developed a new technology-enabled, telemedicine-based care model for patients with newly diagnosed T1D. They developed and deployed Timely Interventions for Diabetes Excellence (TIDE) to facilitate as-needed patient contact with the partially automated analysis of CGM data and used philanthropic funding to facilitate full access to CGM technology for publicly insured patients, for whom CGM is not readily available in California. A study of the use of CGM for patients with new-onset T1D (pilot Teamwork, Targets, and Technology for Tight Control [4T] study), which incorporated the use of TIDE, was associated with a 0.5%-point reduction in hemoglobin A1c compared with historical controls and an 86% reduction in screen time for providers reviewing patient data. Based on this initial success, Stanford expanded the use of TIDE to a total of 300 patients, including many outside the pilot 4T study, and made TIDE freely available as open-source software. Next steps include expanding the use of TIDE to support the care of approximately 1,000 patients, improving TIDE and the associated workflows to scale their use to more patients, incorporating data from additional sensors, and partnering with other institutions to facilitate their deployment of this care model.

View details for DOI 10.1056/CAT.21.0438

View details for PubMedID 36544715

View details for Web of Science ID 000791212200153

View details for Web of Science ID 000791212200128

Abstract

BACKGROUND: Millions of people have limited access to specialty care. The problem is exacerbated by ineffective specialty visits due to incomplete prereferral workup, leading to delays in diagnosis and treatment. Existing processes to guide prereferral diagnostic workup are labor-intensive (ie, building a consensus guideline between primary care doctors and specialists) and require the availability of the specialists (ie, electronic consultation).OBJECTIVE: Using pediatric endocrinology as an example, we develop a recommender algorithm to anticipate patients' initial workup needs at the time of specialty referral and compare it to a reference benchmark using the most common workup orders. We also evaluate the clinical appropriateness of the algorithm recommendations.METHODS: Electronic health record data were extracted from 3424 pediatric patients with new outpatient endocrinology referrals at an academic institution from 2015 to 2020. Using item co-occurrence statistics, we predicted the initial workup orders that would be entered by specialists and assessed the recommender's performance in a holdout data set based on what the specialists actually ordered. We surveyed endocrinologists to assess the clinical appropriateness of the predicted orders and to understand the initial workup process.RESULTS: Specialists (n=12) indicated that <50% of new patient referrals arrive with complete initial workup for common referral reasons. The algorithm achieved an area under the receiver operating characteristic curve of 0.95 (95% CI 0.95-0.96). Compared to a reference benchmark using the most common orders, precision and recall improved from 37% to 48% (P<.001) and from 27% to 39% (P<.001) for the top 4 recommendations, respectively. The top 4 recommendations generated for common referral conditions (abnormal thyroid studies, obesity, amenorrhea) were considered clinically appropriate the majority of the time by specialists surveyed and practice guidelines reviewed.CONCLUSIONS: An item association-based recommender algorithm can predict appropriate specialists' workup orders with high discriminatory accuracy. This could support future clinical decision support tools to increase effectiveness and access to specialty referrals. Our study demonstrates important first steps toward a data-driven paradigm for outpatient specialty consultation with a tier of automated recommendations that proactively enable initial workup that would otherwise be delayed by awaiting an in-person visit.

View details for DOI 10.2196/30104

View details for PubMedID 35238788

View details for DOI 10.2337/dc22-Sdis

View details for Web of Science ID 000905201100021

View details for PubMedID 34964863

Abstract

Advancements in diabetes technology such as continuous glucose monitoring (CGM), insulin pumps, and automated insulin delivery provide opportunities to improve glycemic control for youth with type 1 diabetes (T1D). However, diabetes technology use is lower in youth on public insurance, and this technology use gap is widening in the US. There is a significant need to develop effective interventions and policies to promote equitable care. The dual purpose of this case series is as follows: (1) describe success stories of the CGM Time in Range Program (CGM TIPs), which removed barriers for initiating CGM and provided asynchronous remote glucose monitoring for youth on public insurance, and (2) advocate for improving CGM coverage by public insurance. We describe a series of six youths with T1D and public insurance who obtained and sustained use of CGM with assistance from the program. Three youths had improved engagement with the care team while on CGM and the remote monitoring protocol, and three youths were able to leverage sustained CGM wear to obtain insurance coverage for automated insulin delivery systems. CGM TIPs helped these youths achieve lower hemoglobin A1c and improved time in range (TIR). Despite the successes, expansion of CGM TIPs is limited by stringent barriers for CGM approval and difficult postapproval patient workflows to receive shipments. These cases highlight the potential for combining diabetes technology and asynchronous remote monitoring to support continued use and provide education to improve glycemic control for youth with T1D on public insurance and the need to reduce barriers for obtaining CGM coverage by public insurance.

View details for DOI 10.1155/2022/9911736

View details for PubMedID 35273814

Abstract

Algorithm-enabled patient prioritization and remote patient monitoring (RPM) have been used to improve clinical workflows at Stanford and have been associated with improved glucose time-in-range in newly diagnosed youth with type 1 diabetes (T1D). This novel algorithm-enabled care model currently integrates continuous glucose monitoring (CGM) data to prioritize patients for weekly reviews by the clinical diabetes team. The use of additional data may help clinical teams make more informed decisions around T1D management. Regular exercise and physical activity are essential to increasing cardiovascular fitness, increasing insulin sensitivity, and improving overall well-being of youth and adults with T1D. However, exercise can lead to fluctuations in glycemia during and after the activity. Future iterations of the care model will integrate physical activity metrics (e.g., heart rate and step count) and physical activity flags to help identify patients whose needs are not fully captured by CGM data. Our aim is to help healthcare professionals improve patient care with a better integration of CGM and physical activity data. We hypothesize that incorporating exercise data into the current CGM-based care model will produce specific, clinically relevant information such as identifying whether patients are meeting exercise guidelines. This work provides an overview of the essential steps of integrating exercise data into an RPM program and the most promising opportunities for the use of these data.

View details for DOI 10.3389/fendo.2022.1096325

View details for PubMedID 36714600

Abstract

Pathogenic INS gene mutations are causative for Mutant INS-gene-induced Diabetes of Youth (MIDY). We characterize a novel de novo heterozygous INS gene mutation (c.289A>C, p.T97P) that presented in an autoantibody-negative 5-month-old male infant with severe diabetic ketoacidosis. In silico pathogenicity prediction tools provided contradictory interpretations, while structural modeling indicated a deleterious effect on proinsulin folding. Transfection of wildtype and INS p.T97P expression and luciferase reporter constructs demonstrated elevated intracellular mutant proinsulin levels and dramatically impaired proinsulin/insulin and luciferase secretion. Notably, proteasome inhibition partially and selectively rescued INS p.T97P-derived luciferase secretion. Additionally, expression of INS p.T97P caused increased intracellular proinsulin aggregate formation and XBP-1s protein levels, consistent with induction of endoplasmic reticulum stress. We conclude that INS p.T97P is a newly identified pathogenic A-chain variant that is causative for MIDY via disruption of proinsulin folding and processing with induction of the endoplasmic reticulum stress response.

View details for DOI 10.1210/endocr/bqab246

View details for PubMedID 34888628

View details for DOI 10.1111/1753-0407.13235

View details for PubMedID 34874109

Abstract

This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.

View details for DOI 10.1177/19322968211042656

View details for PubMedID 34605694

View details for DOI 10.2337/cd21-0032

View details for PubMedID 34421199

Abstract

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.

View details for DOI 10.2337/cd21-0026

View details for PubMedID 34421201

View details for Web of Science ID 000656638700350

View details for Web of Science ID 000656638700121

Abstract

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

View details for DOI 10.1016/j.jdiacomp.2021.107950

View details for PubMedID 34127370

Abstract

BACKGROUND: We describe the utilization of telemedicine visits (video or telephone) across the T1D Exchange Quality Improvement Collaborative (T1DX-QI) during the COVID-19 pandemic. Metrics, site-level survey results, and examples of interventions conducted to support telemedicine in type 1 diabetes (T1D) are shown.METHODS: Thirteen clinics (11 pediatric, 2 adult) provided monthly telemedicine metrics between December 2019-August 2020 and 21 clinics completed a survey about their telemedicine practices.RESULTS: The proportion of telemedicine visits in T1DX-QI before the pandemic was less than 1%, rising to an average of 95.2% in April 2020 (range 52.3% to 99.5). Three sites initially used mostly telephone visits before converting to video visits. By August 2020, the proportion of telemedicine visits decreased to an average of 45% across T1DX-QI (range 10% to 86.6%). The majority of clinics (62%) performed both video and telephone visits; Zoom was the most popular video platform used. Over 95% of clinics reported using CareLink, Clarity, Glooko and/or t:connect to view device data, with only one center reporting automated data upload into the electronic medical record. The majority of centers had multidisciplinary teams participating in the video visits. All sites reported reimbursement for video visits, and 95% of sites reported coverage for telephone visits early on in the pandemic.CONCLUSIONS: There was rapid adoption of telemedicine in T1DX-QI during the COVID-19 pandemic. Future insurance reimbursement for telemedicine visits and the ideal ratio of telemedicine to in-person visits in T1D care remain to be determined.

View details for DOI 10.1089/dia.2021.0080

View details for PubMedID 33851873

Abstract

Previous studies have suggested that clear HbA1c target setting by the diabetes team is associated with HbA1c outcomes in adolescents. The aim of this study was to evaluate whether this finding is consistent in a larger cohort of children from centers participating in the SWEET international diabetes registry. A questionnaire was sent out to 76 SWEET centers, of which responses from 53 pediatric centers were included (70%). Descriptive outcomes were presented as median with lower and upper quartile. The association between the centers' target HbA1c and mean outcome HbA1c was calculated using linear regression adjusted for age, diabetes duration, sex, and gross domestic product. Median age of the children in the studied centers (n = 35,483) was 13.3 [12.6-14.6] years (49% female). Of the 53 centers, 13.2% reported an HbA1c target between 6.0 and 6.5%, 32.1% had a target between 6.0 and 7.0%, 18.9% between 7.0 and 7.5%, and 3.8% between 7.5 and 8.5%. No specific target value was reported by 32.1% of all centers. Median HbA1c across all centers was 7.9 [7.6-8.3] %. Adjusted regression analysis showed a positive association between HbA1c outcome and target HbA1c (p = 0.005).Conclusions: This international study demonstrated that a lower target for HbA1c was associated with better metabolic control. It is unclear whether low target values result in better metabolic control, or lower HbA1c values actually result in more ambitious target values. This target setting could contribute to the differences in HbA1c values between centers and could be an approach for improving metabolic outcomes. What is Known: Target setting of HbA1c is important in children and adolescents with type 1 diabetes. The optimal therapeutic approach of children with type 1 diabetes requires a trained multidisciplinary team. What is New: Lower HbA1c targets are associated with better metabolic control. No associations between the composition of the diabetes teams and metabolic control could be demonstrated.

View details for DOI 10.1007/s00431-020-03891-2

View details for PubMedID 33415466

Abstract

A majority of youth with type 1 diabetes do not meet recommended hemoglobin A1c (HbA1c) targets. The SWEET diabetes registry is a multi-national registry of youth with diabetes. We used data from this registry to identify characteristics associated with glycemic control.Patients in the SWEET diabetes registry with at least one HbA1c value within 10days of diagnosis and 3 follow up measurements in the first 18months of diagnosis were included (~10% of the SWEET diabetes registry). Locally weighted scatterplot smoothing was used to generate curves of HbA1c. Wilcoxon, Kruskal-Wallis, or 2-tests were used to calculate differences between groups.The mean HbA1c of youth in the SWEET diabetes registry is highest at diagnosis and lowest between months 4 and 5 post-diabetes diagnosis. HbA1c continues to increase steadily through the first 18months of diagnosis. There are no differences in HbA1c trajectories based on sex or use of diabetes technology. Youth in North America/Australia/New Zealand had the highest HbA1c throughout the first 18months of diagnosis. The trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. Youth from countries with the highest gross domestic product (GDP) had the highest HbA1c throughout the first 18months of diagnosis.In this subset of patients, the trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. High GDP and high use of technology did not seem to protect from a higher trajectory. This article is protected by copyright. All rights reserved.

View details for DOI 10.1111/pedi.13278

View details for PubMedID 34779090

Abstract

Early initiation of continuous glucose monitoring (CGM) is advocated for youth with type 1 diabetes (T1D). Data to guide CGM use on time-in-range (TIR), hypoglycemia, and the role of partial clinical remission (PCR) are limited. Our aims were to assess whether: 1) an association between increased TIR and hypoglycemia exists, and 2) how time in hypoglycemia varies by PCR status.We analyzed 80 youth who were started on CGM shortly after T1D diagnosis and were followed for up to 1-year post-diagnosis. TIR and hypoglycemia rates were determined by CGM data and retrospectively analyzed. PCR was defined as (visit-HbA1c)+(4*units/kg/day) <9.Youth were started on CGM 8.0 (IQR 6.0-13.0) days post-diagnosis. Time spent <70mg/dL remained low despite changes in TIR (highest TIR 74.616.7%, 2.42.4% hypoglycemia at 1 month post-diagnosis; lowest TIR 61.320.3%, 2.12.7% hypoglycemia at 12 months post-diagnosis). No events of severe hypoglycemia occurred. Hypoglycemia was rare and there was minimal difference for PCR versus non-PCR youth (54-70mg/dL: 1.8% vs 1.2%, p=0.04; <54mg/dL: 0.3% vs 0.3%, p=0.55). Approximately 50% of the time spent in hypoglycemia was in the 65-70mg/dL range.As TIR gradually decreased over 12 months post-diagnosis, hypoglycemia was limited with no episodes of severe hypoglycemia. Hypoglycemia rates did not vary in a clinically meaningful manner by PCR status. With CGM being started earlier, consideration needs to be given to modifying CGM hypoglycemia education, including alarm settings. These data support a trial in the year post-diagnosis to determine alarm thresholds for youth who wear CGM.

View details for DOI 10.1210/clinem/dgab522

View details for PubMedID 34265059

Abstract

Telemedicine has rapidly expanded in many aspects of pediatric care as a result of the COVID-19 pandemic. However, little is known about what factors may make pediatric subspeciality care more apt to long-term adoption of telemedicine. To better delineate the potential patient, provider, and subspecialty factors which may influence subspecialty adoption of telemedicine, we reviewed our institutional experience. The top 36 pediatric subspecialties at Stanford Children's Health were classified into high telemedicine adopters, low telemedicine adopters, and telemedicine reverters. Distance from the patient's home, primary language, insurance type, institutional factors such as wait times, and subspecialty-specific clinical differences correlated with differing patterns of telemedicine adoption. With greater awareness of these factors, institutions and providers can better guide patients in determining which care may be best suited for telemedicine and develop sustainable long-term telemedicine programming.

View details for DOI 10.3389/fped.2021.648631

View details for PubMedID 33928058

Abstract

To capture the experience of parents of youth with recent onset Type 1 diabetes who initiated use of continuous glucose monitoring (CGM) technology soon after diagnosis, which is a new practice.Focus groups and individual interviews were conducted with parents of youth with Type 1 diabetes who had early initiation of CGM as part of a new clinical protocol. Interviewers used a semi-structured interview guide to elicit feedback and experiences with starting CGM within 30 days of diagnosis, and the benefits and barriers they experienced when adjusting to this technology. Groups and interviews were audio-recorded, transcribed, and analyzed using content analysis.Participants were 16 parents (age 44.138.43 years; 75% female; 56.25% non-Hispanic White) of youth (age 12.384.15 years; 50% female; 50% non-Hispanic White; diabetes duration 10.353.89 months) who initiated CGM 11.317.33 days after diabetes diagnosis. Overall, parents reported high levels of satisfaction with starting CGM within a month of diagnosis and described a high level of reliance on the technology to help manage their child's diabetes. All participants recommended early CGM initiation for future families and were committed to continue using the technology for the foreseeable future, provided that insurance covered it.Parents experienced CGM initiation shortly after their child's Type 1 diabetes diagnosis as a highly beneficial and essential part of adjusting to living with diabetes.

View details for DOI 10.1111/dme.14567

View details for PubMedID 33772862

Abstract

OBJECTIVES: To describe clinical presentation and long-term outcomes in a large cohort of children diagnosed with thiamine-responsive megaloblastic anemia (TRMA)-related diabetes.METHODS: Data from the Diabetes Patienten Verlaufsdokumentation (DPV) and Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference (SWEET) registries were used to identify cases. Complementary information was collected through a chart review of each case. Descriptive analyses with medians and interquartile ranges and numbers (proportions) were tabulated.RESULTS: We identified 23 cases (52% male) in the 2 registries. Eighteen (78%) had genetic confirmation of TRMA. Median age at diabetes onset was 1.4 (quartiles 0.8 to 3.6) years and median age at initiation of thiamine treatment was 5.9 (2.4 to 12.4) years. At their most recent visit, patients' median age was 14.3 (8.1 to 17.5) years, glycated hemoglobin level was 6.9% (6.1% to 7.9%), insulin dose was 0.9 (0.4 to 1.2) units/kg per day and thiamine dose was 200 (100 to 300) mg/day. Three patients were not treated with insulin or antidiabetic drugs. There was no difference in diabetes outcomes in patients with initiation of thiamine 1 year after diabetes onset compared to patients with initiation of thiamine >1 year after diabetes onset.CONCLUSIONS: This is the longest case series of pediatric TRMA-related diabetes reported to date. Diabetes onset often occurs several years before initiation of thiamine supplementation. Early initiation of thiamine (within 1 year of diabetes onset) was not linked to improved diabetes outcome. However, the role of thiamine in pancreatic function needs further assessment. Patients with TRMA-related diabetes maintained good glycemic control even after 9 years (median) of follow up.

View details for DOI 10.1016/j.jcjd.2020.11.006

View details for PubMedID 33388275

Abstract

INTRODUCTION: Population-level and individual-level analyses have strengths and limitations as do 'blackbox' machine learning (ML) and traditional, interpretable models. Diabetes mellitus (DM) is a leading cause of morbidity and mortality with complex sociodemographic dynamics that have not been analyzed in a way that leverages population-level and individual-level data as well as traditional epidemiological and ML models. We analyzed complementary individual-level and county-level datasets with both regression and ML methods to study the association between sociodemographic factors and DM.RESEARCH DESIGN AND METHODS: County-level DM prevalence, demographics, and socioeconomic status (SES) factors were extracted from the 2018 Robert Wood Johnson Foundation County Health Rankings and merged with US Census data. Analogous individual-level data were extracted from 2007 to 2016 National Health and Nutrition Examination Survey studies and corrected for oversampling with survey weights. We used multivariate linear (logistic) regression and ML regression (classification) models for county (individual) data. Regression and ML models were compared using measures of explained variation (area under the receiver operating characteristic curve (AUC) and R2).RESULTS: Among the 3138 counties assessed, the mean DM prevalence was 11.4% (range: 3.0%-21.1%). Among the 12824 individuals assessed, 1688 met DM criteria (13.2% unweighted; 10.2% weighted). Age, gender, race/ethnicity, income, and education were associated with DM at the county and individual levels. Higher county Hispanic ethnic density was negatively associated with county DM prevalence, while Hispanic ethnicity was positively associated with individual DM. ML outperformed regression in both datasets (mean R2 of 0.679 vs 0.610, respectively (p<0.001) for county-level data; mean AUC of 0.737 vs 0.727 (p<0.0427) for individual-level data).CONCLUSIONS: Hispanic individuals are at higher risk of DM, while counties with larger Hispanic populations have lower DM prevalence. Analyses of population-level and individual-level data with multiple methods may afford more confidence in results and identify areas for further study.

View details for DOI 10.1136/bmjdrc-2020-001725

View details for PubMedID 33229378

View details for DOI 10.2337/db20-1294-P

View details for Web of Science ID 000554509803068

View details for DOI 10.2337/db20-1289-P

View details for Web of Science ID 000554509803063

View details for DOI 10.2337/db20-1185-P

View details for Web of Science ID 000554509802428

View details for DOI 10.2337/db20-159-LB

View details for Web of Science ID 000554509800310

View details for DOI 10.2337/db20-1801-P

View details for Web of Science ID 000554509804067

View details for DOI 10.2337/db20-1295-P

View details for Web of Science ID 000554509803069

View details for DOI 10.2337/db20-1297-P

View details for Web of Science ID 000554509803071

View details for Web of Science ID 000514025300046

View details for Web of Science ID 000514025300602

View details for DOI 10.2337/dc19-1214

View details for PubMedID 31672703

View details for DOI 10.1111/pedi.12832

View details for Web of Science ID 000468283100001

Abstract

Background Neonatal severe hyperparathyroidism (NSHPT) is commonly treated with either parathyroidectomy or pharmacologic agents with varying efficacy and numerous side effects. Reports of using cinacalcet for NSHPT have increased, however, the effective dose for pediatric patients from the onset of symptoms through infancy has not been established. Case presentation We describe the clinical course of a newborn with a de novo R185Q mutation in the calcium-sensing receptor (CASR) gene, causing NSHPT. The infant received cinacalcet from the first days of life until 1 year of age. Conclusions Cinacalcet therapy effectively controlled the patient's serum calcium, phosphorus, and parathyroid hormone (PTH) levels without side effects.

View details for PubMedID 30730839

View details for DOI 10.2337/dc19-1205

View details for PubMedID 31558548

Abstract

Diabetes Technology Society (DTS) convened a meeting about the US Food and Drug Administration (FDA) Digital Health Software Precertification Program on August 28, 2018. Forty-eight attendees participated from clinical and academic endocrinology (both adult and pediatric), nursing, behavioral health, engineering, and law, as well as representatives of FDA, National Institutes of Health (NIH), National Telecommunications and Information Administration (NTIA), and industry. The meeting was intended to provide ideas to FDA about their plan to launch a Digital Health Software Precertification Program. Attendees discussed the four components of the plan: (1) excellence appraisal and certification, (2) review pathway determination, (3) streamlined premarket review process, and (4) real-world performance. The format included (1) introductory remarks, (2) a program overview presentation from FDA, (3) roundtable working sessions focused on each of the Software Precertification Program's four components, (4) presentations reflecting the discussions, (5) questions to and answers from FDA, and (6) concluding remarks. The meeting provided useful information to the diabetes technology community and thoughtful feedback to FDA.

View details for PubMedID 30394807

View details for PubMedID 30020810

Abstract

With the evolution of diabetes technology, those living with Type 1 diabetes are given a wider arsenal of tools with which to achieve glycaemic control and improve patient-reported outcomes. Furthermore, the use of these technologies may help reduce the risk of acute complications, such as severe hypoglycaemia and diabetic ketoacidosis, as well as long-term macro- and microvascular complications. In addition, diabetes technology can have a beneficial impact on psychosocial health by reducing the burden of diabetes. Unfortunately, diabetes goals are often unmet and people with Type 1 diabetes too frequently experience acute and long-term complications of this condition, in addition to often having less than ideal psychosocial outcomes. Increasing realization of the importance of patient-reported outcomes is leading to diabetes care delivery becoming more patient-centred. Diabetes technology in the form of medical devices, digital health and big data analytics have the potential to improve clinical care and psychosocial support, resulting in lower rates of acute and chronic complications, decreased burden of diabetes care, and improved quality of life. This article is protected by copyright. All rights reserved.

View details for PubMedID 29356074

Abstract

This article reviews mobile medical applications that are commercially available in the United States or European Union (EU) and are (1) associated with published data of clinical outcomes in the peer-reviewed literature during the past 5 years, (2) cleared by the US Food and Drug Administration (FDA) in the United States, or (3) a recipient of a CE (Conformit Europenne) mark by the EU. Many of these applications have been shown to positively affect outcomes in the short term, but long-term studies are needed. Until more data are available, consumers and professionals can consider guidance based on FDA/CE status.

View details for DOI 10.1016/j.ecl.2016.06.001

View details for PubMedID 27823614

Abstract

Cleared blood glucose monitor (BGM) systems do not always perform as accurately for users as they did to become cleared. We performed a literature review of recent publications between 2010 and 2014 that present data about the frequency of inaccurate performance using ISO 15197 2003 and ISO 15197 2013 as target standards. We performed an additional literature review of publications that present data about the clinical and economic risks of inaccurate BGMs for making treatment decisions or calibrating continuous glucose monitors (CGMs). We found 11 publications describing performance of 98 unique BGM systems. 53 of these 98 (54%) systems met ISO 15197 2003 and 31 of the 98 (32%) tested systems met ISO 15197 2013 analytical accuracy standards in all studies in which they were evaluated. Of the tested systems, 33 were identified by us as FDA-cleared. Among these FDA-cleared BGM systems, 24 out of 32 (75%) met ISO 15197 2003 and 15 out of 31 (48.3%) met ISO 15197 2013 in all studies in which they were evaluated. Among the non-FDA-cleared BGM systems, 29 of 65 (45%) met ISO 15197 2003 and 15 out of 65 (23%) met ISO 15197 2013 in all studies in which they were evaluated. It is more likely that an FDA-cleared BGM system, compared to a non-FDA-cleared BGM system, will perform according to ISO 15197 2003 ((2) = 6.2, df = 3, P = 0.04) and ISO 15197 2013 ((2) = 11.4, df = 3, P = 0.003). We identified 7 articles about clinical risks and 3 articles about economic risks of inaccurate BGMs. We conclude that a significant proportion of cleared BGMs do not perform at the level for which they were cleared or according to international standards of accuracy. Such poor performance leads to adverse clinical and economic consequences.

View details for DOI 10.1177/1932296815584797

View details for PubMedID 25990294

Abstract

Tumor development, growth, and metastasis depend on the provision of an adequate vascular supply. This can be due to regulated angiogenesis, recruitment of circulating endothelial progenitors, and/or vascular transdifferentiation. Our previous studies showed that retinoic acid (RA) treatment converts a subset of breast cancer cells into cells with significant endothelial genotypic and phenotypic elements including marked induction of VE-cadherin, which was responsible for some but not all morphological changes. The present study demonstrates that of the endothelial-related genes induced by RA treatment, only a few were affected by knockdown of VE-cadherin, ruling it out as a regulator of the RA-induced endothelial genotypic switch. In contrast, knockdown of the RA-induced gene COUP-TFII prevented the formation of networks in Matrigel but had no effect on VE-cadherin induction or cell fusion. Two pan-kinase inhibitors markedly blocked RA-induced VE-cadherin expression and cell fusion. However, RA treatment resulted in a marked and broad reduction in tyrosine kinase activity. Several genes in the TGFbeta signaling pathway were induced by RA, and specific inhibition of the TGFbeta type I receptor blocked both RA-induced VE-cadherin expression and cell fusion. Together these data indicate a role for the TGFbeta pathway and COUP-TFII in mediating the endothelial transdifferentiating properties of RA.

View details for DOI 10.1371/journal.pone.0010023

View details for PubMedID 20386594

Abstract

Many aspects of development, tumor growth and metastasis depend upon the provision of an adequate vasculature. This can be a result of regulated angiogenesis, recruitment of circulating endothelial progenitors and/or vascular trans-differentiation. The present study demonstrates that treatment of SKBR-3 breast cancer cells with retinoic acid (RA), an important regulator of embryogenesis, cancer and other diseases, stimulates the formation of networks in Matrigel. RA-treatment of SKBR-3 cells co-cultured with human umbilical vein endothelial cells resulted in the formation of mixed structures. RA induces expression of many endothelial genes including vascular endothelial (VE) cadherin. VE-cadherin was also induced by RA in a number of other breast cancer cells. We show that RA-induced VE-cadherin is responsible for the RA-induced morphological changes. RA rapidly induced the expression of Sox-9 and ER81, which in turn form a complex on the VE-cadherin promoter and are required to mediate the transcriptional regulation of VE-cadherin by RA. These data indicate that RA may promote the expression of endothelial genes resulting in endothelial-like differentiation, or provide a mechanism whereby circulating endothelial progenitor cells could be incorporated into a growing organ or tumor.

View details for DOI 10.1371/journal.pone.0002714

View details for Web of Science ID 000264057200057

View details for PubMedID 18628953

Abstract

The attachment of epithelial cells to the extracellular matrix substratum is essential for their differentiation and polarization. Despite this, the precise adhesion mechanism and its regulation are poorly understood. In the kidney, an ischemic insult causes renal tubular epithelial cells to detach from the basement membrane, even though they remain viable. To understand this phenomenon, and to probe the regulation of epithelial cell attachment, we used a model system consisting of newly adherent Madin-Darby canine kidney (MDCK) cells subjected to ATP depletion to mimic ischemic injury. We found that MDCK cells detach from collagen I after 60 min of ATP depletion but reattach when resupplied with glucose. Detachment is not caused by degradation or endocytosis of beta(1)-integrins, which mediate attachment to collagen I. Basal actin filaments and paxillin-containing adhesion complexes are disrupted by ATP depletion and quickly reform on glucose repletion. However, partial preservation of basal actin by overexpression of constitutively active RhoA does not significantly affect cell detachment. Furthermore, Y-27632, an inhibitor of the RhoA effector Rho-kinase, does not prevent reattachment of cells on glucose addition, even though reformation of central stress fibers and large adhesion complexes is blocked. In contrast, reattachment of ATP-depleted cells and detachment of cells not previously subjected to ATP depletion are prevented by ML-7, an inhibitor of myosin light chain kinase (MLCK). We conclude that initial adherence of MDCK cells to a collagen I substratum is mediated by peripheral actin filaments and adhesion complexes regulated by MLCK but not by stress fibers and adhesion complexes controlled by RhoA.

View details for DOI 10.1152/ajpcell.00124.2003

View details for Web of Science ID 000188707600027

View details for PubMedID 14644769