Macroergonomic components of the patient work system shaping dyadic care management during adolescence: a case study of type 1 diabetes.

The role of the social, physical, and organisational environments in shaping how patients and their caregivers perform work remains largely unexplored in human factors/ergonomics literature. This study recruited 19 dyads consisting of a parent and their child with type 1 diabetes to be interviewed individually and analysed using a macroergonomic framework. Our findings aligned with the macroergonomic factors as presented in previous models, while highlighting the need to expand upon certain components to gain a more comprehensive representation of the patient work system as relevant to dyadic management. Examples of design efforts that should follow from these findings include expanding existing data sharing options to include information from the external environment and capitalising on the capabilities of artificial intelligence as a decision support system. Future research should focus on longitudinally assessing patient work systems throughout transition periods in addition to more explicitly exploring the roles of social network members.

Work performed by patients and their caregivers is shaped by the social, physical, and organisational contexts they are embedded within. This paper explored how adolescents with type 1 diabetes managed their health alongside their parents in the context of these macroergonomic factors. These findings have implications for research and design.

Academic performance in moderately and late preterm children in the United States: are they catching up?

OBJECTIVE: To determine whether preterm birth of 32-36 6/7 weeks gestation affected school performance from kindergarten through fifth grade. STUDY DESIGN: We assessed 14350 term infants and 1195 32-36 6/7 weeks gestation infants followed in the Early Childhood Longitudinal Study Kindergarten 2011 cohort for classroom performance in kindergarten-fifth grade. Multivariable regression was performed for comparisons, and data were weighted to be representative of the US population. RESULTS: Children born 35-36 6/7 weeks gestation had no significant difference in their academic scores or performance, while 32-34 6/7 weeks' children had lower academic scores and teacher performance scores when compared to term children. Children born between 32 and 36 6/7 weeks gestation had higher odds of individualized education plan needs and had learning disability diagnoses compared to term children. CONCLUSIONS: Children born between 32 and 34 6/7 weeks gestation have poor school performance compared to term children. Children born between 32 and 36 6/7 weeks gestation are at risk for learning disabilities and likely benefit from continued support and services to improve achievement throughout school.

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm.

BACKGROUND: Automated Insulin Delivery (AID) is now integral to the clinical practice of Type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm - a Neural-Net Artificial Pancreas (NAP) - an encoding of an AID algorithm into a neural network that approximates its action, and assess NAP vs the original AID algorithm. METHODS: The UVA model-predictive control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-hour hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were: ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline HbA1c 5.4-8.1%. RESULTS: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% vs 1.8% and coefficients of variation of 29.3% (NAP) vs 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 units/hour. There were no serious adverse events on either controller. NAP had 6-fold lower computational demands than UMPC. CONCLUSION: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine learning methods to enter the AID field.

Patient reported outcomes (PROs) and user experiences of young children with type 1 diabetes using t:slim X2 insulin pump with control-IQ technology.

OBJECTIVE: Examine patient-reported outcomes (PROs) after the use of t:slim X2 insulin pump with Control-IQ technology (CIQ) in young children with type 1 diabetes. METHODS: Children with type 1 diabetes, ages 2 to < 6 years (n = 102), were randomly assigned 2:1 to either CIQ or standard care (SC) with pump or multiple daily injections (MDI) plus continuous glucose monitoring (CGM) for 13 weeks. Both groups were offered to use CIQ for an additional 13 weeks after the randomized control trial's (RCT) completion. Guardians completed PRO questionnaires at baseline, 13-, and 26-weeks examining hypoglycemia concerns, quality of life, parenting stress, and sleep. At 26 weeks, 28 families participated in user-experience interviews. Repeated measures analyses compared PRO scores between systems used. RESULT: Comparing CIQ vs SC, responses on all 5 PRO surveys favored the CIQ group, showing that CIQ was superior to SC at 26 weeks (p values < 0.05). User-experience interviews indicated significant benefits in optimized glycemic control overall and nighttime control (28 of 28 families endorsed). All but 2/28 families noted substantial reduction in management burden resulting in less mental burden and all but 4 stated that they wanted their children to continue using CIQ. CONCLUSIONS: Families utilizing CIQ experienced glycemic benefits coupled with substantial benefits in PROs, documented in surveys and interviews. Families utilizing CIQ had reduced hypoglycemia concerns and parenting stress, and improved quality of life and sleep. These findings demonstrate the benefit of CIQ in young children with type 1 diabetes that goes beyond documented glycemic benefit.

Predicting the Risk of Developing Type 1 Diabetes Using a One-Week Continuous Glucose Monitoring Home Test With Classification Enhanced by Machine Learning: An Exploratory Study.

BACKGROUND: Detection of two or more autoantibodies (Ab) in the blood might describe those individuals at increased risk of developing type 1 diabetes (T1D) during the following years. The aim of this exploratory study is to propose a high versus low T1D risk classifier using machine learning technology based on continuous glucose monitoring (CGM) home data. METHODS: Forty-two healthy relatives of people with T1D with mean ± SD age of 23.8 ± 10.5 years, HbA1c (glycated hemoglobin) of 5.3% ± 0.3%, and BMI (body mass index) of 23.2 ± 5.2 kg/m2 with zero (low risk; N = 21), and ≥2 (high risk; N = 21) Ab, were enrolled in an NIH (National Institutes of Health)-funded TrialNet ancillary study. Participants wore a CGM for a week and consumed three standardized liquid mixed meals (SLMM) instead of three breakfasts. Glycemic features were extracted from two-hour post-SLMM CGM traces, compared across groups, and used in four supervised machine learning Ab risk status classifiers. Recursive Feature Elimination (RFE) algorithm was used for feature selection; classifiers were evaluated through 10-fold cross-validation, using the receiver operating characteristic area under the curve (AUC-ROC) to select the best classification model. RESULTS: The percent time of glucose >180 mg/dL (T180), glucose range, and glucose CV (coefficient of variation) were the only significant differences between the glycemic features in the two groups with P values of .040, .035, and .028 respectively. The linear SVM (Support Vector Machine) model with RFE features achieved the best performance of classifying low-risk versus high-risk individuals with AUC-ROC = 0.88. CONCLUSIONS: A machine learning technology, combining a potentially self-administered one-week CGM home test, has the potential to reliably assess the T1D risk.

Impact of azithromycin and nitazoxanide on the enteric infections and child growth: Findings from the Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT) trial.

BACKGROUND: Early childhood enteric infection with Shigella/EIEC, enteroaggregative E. coli (EAEC), Campylobacter, and Giardia has been associated with reduced child growth, yet a recent randomized trial of antimicrobial therapy to reduce these infections did not improve growth outcomes. To interrogate this discrepancy, we measured the enteric infections from this study. METHODS: We leveraged the Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT) trial, a randomized double-blind placebo-controlled trial of antimicrobial therapy with azithromycin and nitazoxanide provided quarterly to infants from 6 to 15 months of age. We tested 5,479 stool samples at time points across the study for 34 enteropathogens using quantitative PCR. RESULTS: There was substantial carriage of enteropathogens in stool. Azithromycin administration led to reductions in Campylobacter jejuni/coli, enteroaggregative E. coli, and Shigella/EIEC (absolute risk difference ranged from -0.06 to 0.24) 2 weeks after treatment however there was no effect after 3 months. There was no difference in Giardia after nitazoxanide administration (ARR 0.03 at the 12 month administration). When examining the effect of azithromycin versus placebo on the subset of children infected with specific pathogens at the time of treatment, a small increase in weight-for-age Z score was seen only in those infected with Campylobacter jejuni/coli (0.10 Z score, 95% CI -0.01-0.20; length-for-age Z score 0.07, 95% CI -0.06-0.20). CONCLUSION: The antimicrobial intervention of quarterly azithromycin plus or minus nitazoxanide led to only transient decreases in enteric infections with Shigella/EIEC, enteroaggregative E. coli (EAEC), Campylobacter, and Giardia. There was a trend towards improved growth in children infected with Campylobacter that received quarterly azithromycin.

Assessment of Meal Anticipation for Improving Fully Automated Insulin Delivery in Adults With Type 1 Diabetes.

OBJECTIVE: Meals are a consistent challenge to glycemic control in type 1 diabetes (T1D). Our objective was to assess the glycemic impact of meal anticipation within a fully automated insulin delivery (AID) system among adults with T1D. RESEARCH DESIGN AND METHODS: We report the results of a randomized crossover clinical trial comparing three modalities of AID systems: hybrid closed loop (HCL), full closed loop (FCL), and full closed loop with meal anticipation (FCL+). Modalities were tested during three supervised 24-h admissions, where breakfast, lunch, and dinner were consumed per participant's home schedule, at a fixed time, and with a 1.5-h delay, respectively. Primary outcome was the percent time in range 70-180 mg/dL (TIR) during the breakfast postprandial period for FCL+ versus FCL. RESULTS: Thirty-five adults with T1D (age 44.5 ± 15.4 years; HbA1c 6.7 ± 0.9%; n = 23 women and n = 12 men) were randomly assigned. TIR for the 5-h period after breakfast was 75 ± 23%, 58 ± 21%, and 63 ± 19% for HCL, FCL, and FCL+, respectively, with no significant difference between FCL+ and FCL. For the 2 h before dinner, time below range (TBR) was similar for FCL and FCL+. For the 5-h period after dinner, TIR was similar for FCL+ and FCL (71 ± 34% vs. 72 ± 29%; P = 1.0), whereas TBR was reduced in FCL+ (median 0% [0-0%] vs. 0% [0-0.8%]; P = 0.03). Overall, 24-h control for HCL, FCL, and FCL+ was 86 ± 10%, 77 ± 11%, and 77 ± 12%, respectively. CONCLUSIONS: Although postprandial control remained optimal with hybrid AID, both fully AID solutions offered overall TIR >70% with similar or lower exposure to hypoglycemia. Anticipation did not significantly improve postprandial control in AID systems but also did not increase hypoglycemic risk when meals were delayed.

Predicting Immunological Risk for Stage 1 and Stage 2 Diabetes Using a 1-Week CGM Home Test, Nocturnal Glucose Increments, and Standardized Liquid Mixed Meal Breakfasts, with Classification Enhanced by Machine Learning.

Background: Predicting the risk for type 1 diabetes (T1D) is a significant challenge. We use a 1-week continuous glucose monitoring (CGM) home test to characterize differences in glycemia in at-risk healthy individuals based on autoantibody presence and develop a machine-learning technology for CGM-based islet autoantibody classification. Methods: Sixty healthy relatives of people with T1D with mean ± standard deviation age of 23.7 ± 10.7 years, HbA1c of 5.3% ± 0.3%, and body mass index of 23.8 ± 5.6 kg/m2 with zero (n = 21), one (n = 18), and ≥2 (n = 21) autoantibodies were enrolled in an National Institutes of Health TrialNet ancillary study. Participants wore a CGM for a week and consumed three standardized liquid mixed meals (SLMM) instead of three breakfasts. Glycemic outcomes were computed from weekly, overnight (12:00-06:00), and post-SLMM CGM traces, compared across groups, and used in four supervised machine-learning autoantibody status classifiers. Classifiers were evaluated through 10-fold cross-validation using the receiver operating characteristic area under the curve (AUC-ROC) to select the best classification model. Results: Among all computed glycemia metrics, only three were different across the autoantibodies groups: percent time >180 mg/dL (T180) weekly (P = 0.04), overnight CGM incremental AUC (P = 0.005), and T180 for 75 min post-SLMM CGM traces (P = 0.004). Once overnight and post-SLMM features are incorporated in machine-learning classifiers, a linear support vector machine model achieved the best performance of classifying autoantibody positive versus autoantibody negative participants with AUC-ROC ≥0.81. Conclusion: A new technology combining machine learning with a potentially self-administered 1-week CGM home test can help improve T1D risk detection without the need to visit a hospital or use a medical laboratory. Trial registration: ClinicalTrials.gov registration no. NCT02663661.

Effect of an Automated Advice Algorithm (CloudConnect) on Adolescent-Parent Diabetes-Specific Communication and Glycemic Management: A Randomized Trial.

INTRODUCTION: Because adolescence is a time of difficult management of Type 1 diabetes (T1D) in part from adolescent-parent shared responsibility of T1D management, our objective was to assess the effects of a decision support system (DSS) CloudConnect on T1D-related communication between adolescents and their parents and on glycemic management. METHODS: We followed 86 participants including 43 adolescents with T1D (not on automated insulin delivery systems, AID) and their parents/care-giver for a 12-week intervention of UsualCare + CGM or CloudConnect, which included a Weekly Report of automated T1D advice, including insulin dose adjustments, based on data from continuous glucose monitors (CGM), Fitbit and insulin use. Primary outcome was T1D-specific communication and secondary outcomes were hemoglobin A1c, time-in-target range (TIR) 70-180 mg/dl, and additional psychosocial scales. RESULTS: Adolescents and parents reported a similar amount of T1D-related communication in both the UsualCare + CGM or CloudConnect groups and had similar levels of final HbA1c. Overall blood glucose time in range 70-180 mg/dl and time below 70 mg/dl were not different between groups. Parents but not children in the CloudConnect group reported less T1D-related conflict; however, compared to the UsualCare + CGM group, adolescents and parents in the CloudConnect reported a more negative tone of T1D-related communication. Adolescent-parent pairs in the CloudConnect group reported more frequent changes in insulin dose. There were no differences in T1D quality of life between groups. CONCLUSIONS: While feasible, the CloudConnect DSS system did not increase T1D communication or provide improvements in glycemic management. Further efforts are needed to improve T1D management in adolescents with T1D not on AID systems.

Association of Circulating Biomarkers with Growth and Cognitive Development in Rural Tanzania: A Secondary Analysis of the Early Life Interventions in Childhood Growth and Development In Tanzania (ELICIT) Study.

BACKGROUND: Children in low-resource areas experience nutritional and infection challenges delaying growth and cognitive development. OBJECTIVES: Our goal was to assess for associations of circulating biomarkers related to nutrition and inflammation, with growth and developmental outcomes among children in a birth cohort in a resource-poor area in rural Tanzania. METHODS: We assessed data from 1,120 children participating in the Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT) study. At age 12 and 18 mo, participants had blood tests performed for hemoglobin, collagen-X, insulin-like growth factor-1 (IGF-1), fibroblast growth factor-21 (FGF21), thyroglobulin, ferritin, soluble transferrin receptor (sTFR), retinol binding protein-4 (RBP4), C-reactive protein (CRP), α1-acid glycoprotein (AGP), and CD14. At 18 mo, participants had anthropometry measured and converted to z-scores for length-for-age (LAZ), weight-for-age (WAZ) and head-circumference-for-age (HCZ) and had the Malawi Developmental Assessment Tool (MDAT) performed to evaluate cognitive development. We performed linear regression assessing biomarkers (predictor variable) on anthropometry and MDAT scores (dependent variables), adjusted for sex, socioeconomic status, and baseline values. RESULTS: There was a high degree of intrafactor correlation between 12 and 18 mo and interfactor correlation between biomarkers. IGF-1 and sTFR were positively and FGF21 and ferritin negatively associated with LAZ at 18 mo, whereas collagen-X and CD14 were additionally associated with recent linear growth. Only markers predominantly related to nutrition were consistently linked with WAZ at 18 mo, while RBP4 and AGP were additionally associated with recent change in WAZ. IGF-1 was positively and thyroglobulin, RBP4, and CD14 negatively linked to MDAT scores. IGF-1 was the only factor linked to both 18-mo LAZ and MDAT. CONCLUSIONS: Individual biomarkers were consistently linked to growth and cognitive outcomes, providing support for relationships between nutrition and inflammation in early child development. Further research is needed to assess overlaps in how biomarker-related processes interact with both growth and learning. REGISTERED AT CLINICALTRIALS.GOV: NCT03268902.

Trial of Hybrid Closed-Loop Control in Young Children with Type 1 Diabetes.

BACKGROUND: Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes. The efficacy and safety of initiating a closed-loop system virtually are unclear. METHODS: In this 13-week, multicenter trial, we randomly assigned, in a 2:1 ratio, children who were at least 2 years of age but younger than 6 years of age who had type 1 diabetes to receive treatment with a closed-loop system of insulin delivery or standard care that included either an insulin pump or multiple daily injections of insulin plus a continuous glucose monitor. The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring. Secondary outcomes included the percentage of time that the glucose level was above 250 mg per deciliter or below 70 mg per deciliter, the mean glucose level, the glycated hemoglobin level, and safety outcomes. RESULTS: A total of 102 children underwent randomization (68 to the closed-loop group and 34 to the standard-care group); the glycated hemoglobin levels at baseline ranged from 5.2 to 11.5%. Initiation of the closed-loop system was virtual in 55 patients (81%). The mean (±SD) percentage of time that the glucose level was within the target range increased from 56.7±18.0% at baseline to 69.3±11.1% during the 13-week follow-up period in the closed-loop group and from 54.9±14.7% to 55.9±12.6% in the standard-care group (mean adjusted difference, 12.4 percentage points [equivalent to approximately 3 hours per day]; 95% confidence interval, 9.5 to 15.3; P<0.001). We observed similar treatment effects (favoring the closed-loop system) on the percentage of time that the glucose level was above 250 mg per deciliter, on the mean glucose level, and on the glycated hemoglobin level, with no significant between-group difference in the percentage of time that the glucose level was below 70 mg per deciliter. There were two cases of severe hypoglycemia in the closed-loop group and one case in the standard-care group. One case of diabetic ketoacidosis occurred in the closed-loop group. CONCLUSIONS: In this trial involving young children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with a closed-loop system than with standard care. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; PEDAP ClinicalTrials.gov number, NCT04796779.).

Determinants of lung function across childhood in the Severe Asthma Research Program (SARP) 3.

BACKGROUND: Children with asthma are at risk for low lung function extending into adulthood, but understanding of clinical predictors is incomplete. OBJECTIVE: We sought to determine phenotypic factors associated with FEV1 throughout childhood in the Severe Asthma Research Program 3 pediatric cohort. METHODS: Lung function was measured at baseline and annually. Multivariate linear mixed-effects models were constructed to assess the effect of baseline and time-varying predictors of prebronchodilator FEV1 at each assessment for up to 6 years. All models were adjusted for age, predicted FEV1 by Global Lung Function Initiative reference equations, race, sex, and height. Secondary outcomes included postbronchodilator FEV1 and prebronchodilator FEV1/forced vital capacity. RESULTS: A total of 862 spirometry assessments were performed for 188 participants. Factors associated with FEV1 include baseline Feno (B, -49 mL/log2 PPB; 95% CI, -92 to -6), response to a characterizing dose of triamcinolone acetonide (B, -8.4 mL/1% change FEV1 posttriamcinolone; 95% CI, -12.3 to -4.5), and maximal bronchodilator reversibility (B, -27 mL/1% change postbronchodilator FEV1; 95% CI, -37 to -16). Annually assessed time-varying factors of age, obesity, and exacerbation frequency predicted FEV1 over time. Notably, there was a significant age and sex interaction. Among girls, there was no exacerbation effect. For boys, however, moderate (1-2) exacerbation frequency in the previous 12 months was associated with -20 mL (95% CI, -39 to -2) FEV1 at each successive year. High exacerbation frequency (≥3) 12 to 24 months before assessment was associated with -34 mL (95% CI, -61 to -7) FEV1 at each successive year. CONCLUSIONS: In children with severe and nonsevere asthma, several clinically relevant factors predict FEV1 over time. Boys with recurrent exacerbations are at high risk of lower FEV1 through childhood.

Adjusting Therapy Profiles When Switching to Ultra-Rapid Lispro in an Advanced Hybrid Closed-Loop System: An in Silico Study.

BACKGROUND: It has been shown that insulin acceleration by itself might not be sufficient to see clear improvements in glycemic metrics, and insulin therapy may need to be adjusted to fully leverage the extra safety margin provided by faster pharmacokinetic (PK) and pharmacodynamic (PD) profiles. The objective of this work is to explore how to perform such adjustments on a commercially available automated insulin delivery (AID) system. METHODS: Ultra-rapid lispro (URLi) is modeled within the UVA/Padova simulation platform using data from previously published clamp studies. The Control-IQ AID algorithm is selected as it leverages carbohydrate-to-insulin ratio (CR in g/U), correction factor (CF in mg/dL/U), and basal rate (BR in U/h) daily profiles that are fully customizable. An experiment roadmap is proposed to understand how to safely modify these profiles when switching from lispro to URLi. RESULTS: Simulations show that a 7% decrease in CR (approximately an 8% increase in prandial insulin) and a 7.5% increase in BR lead to cumulative improvements in glucose control with URLi. Comparing with baseline metrics using lispro, a clinically significant increase in time in the range of 70 to 180 mg/dL (overall: 70.2%-75.2%, P < .001; 6 am-12 am: 62.4%-68.5%, P < .001) and a reduction in time below 70 mg/dL (overall: 1.8%-1.2%, P < .001; 6 am-12 am: 1.8%-1.3%, P < .001) were observed. CONCLUSION: Properly adjusting therapy parameters allows to fully leverage glucose control benefits provided by faster insulin analogues, opening opportunities to take another step forward into a next generation of more effective AID solutions.

The Impact of Insulin Resistance on Loss of Lung Function and Response to Treatment in Asthma.

Rationale: The role of obesity-associated insulin resistance (IR) in airflow limitation in asthma is uncertain. Objectives: Using data in the Severe Asthma Research Program 3 (SARP-3), we evaluated relationships between homeostatic measure of IR (HOMA-IR), lung function (cross-sectional and longitudinal analyses), and treatment responses to bronchodilators and corticosteroids. Methods: HOMA-IR values were categorized as without (<3.0), moderate (3.0-5.0), or severe (>5.0). Lung function included FEV1 and FVC measured before and after treatment with inhaled albuterol and intramuscular triamcinolone acetonide and yearly for 5 years. Measurements and Main Results: Among 307 participants in SARP-3, 170 (55%) were obese and 140 (46%) had IR. Compared with patients without IR, those with IR had significantly lower values for FEV1 and FVC, and these lower values were not attributable to obesity effects. Compared with patients without IR, those with IR had lower FEV1 responses to ß-adrenergic agonists and systemic corticosteroids. The annualized decline in FEV1 was significantly greater in patients with moderate IR (-41 ml/year) and severe IR (-32 ml/year,) than in patients without IR (-13 ml/year, P < 0.001 for both comparisons). Conclusions: IR is common in asthma and is associated with lower lung function, accelerated loss of lung function, and suboptimal lung function responses to bronchodilator and corticosteroid treatments. Clinical trials in patients with asthma and IR are needed to determine if improving IR might also improve lung function.

Intermittent Fasting and Metabolic Health.

Given the ongoing strain that the obesity epidemic has placed on public health outcomes, new and effective approaches to weight control are needed. One approach to improving weight and metabolic outcomes is intermittent fasting, which consists of multiple different timing schedules for temporary food avoidance, including alternate-day fasting, other similar full-day fasting patterns, and time-restricted feeding (where the day's food is consumed over a 6-h period, allowing for 18 h of fasting). These feeding schedules have favorable metabolic effects by intermittently inducing the metabolism of fatty acids to ketones. The regimens overall lead to a decrease in weight and have been linked to improvements in dyslipidemia and blood pressure. While more research is needed on longer-term outcomes and this approach should be avoided in particular health conditions, intermittent fasting should be considered as an option for individuals who have a pattern of unhealthy weight gain using standard eating patterns.

Sex Differences in Early Childhood Growth in a Resource-Limited Setting: A Secondary Analysis of the Early Life Interventions in Childhood Growth and Development in Tanzania (ELICIT) Study.

BACKGROUND: In population-based growth surveys in sub-Saharan Africa, boys have higher rates of growth failure than girls. OBJECTIVES: Our goal was to assess for the presence, timing, and potential etiology of sex-based differences in length-for-age z score (LAZ), weight-for-age z score (WAZ), and head circumference-for-age z score (HCZ) in a birth cohort in rural Tanzania. METHODS: We performed a secondary analysis of randomized controlled trial data on 1084 children followed from age <2 wk to 18 mo, assessing anthropometry (measured every 3 mo), illness (hospitalization and monthly maternal report of symptoms), and feeding [monthly maternal report of exclusive breastfeeding (EBF) and complementary solids and liquids (CSLs)]. We used linear regression to assess sex differences in LAZ, WAZ, and HCZ over time. RESULTS: Although male and female infants had similar anthropometry measures at study entry, males exhibited poorer growth through 6 mo (e.g., 3-mo mean LAZ: males -0.94, females -0.74, P < 0.01; 3-mo mean WAZ: males -0.63, females -0.48, P < 0.05), without significant worsening from 6 to 18 mo. Males had lower HCZ only at 9 mo. In evaluating possible etiologies, mediation analysis failed to identify illness or hospitalization as mediators of poorer growth among males, although at age 3 mo, males with recently reported illness exhibited greater decline in WAZ than females with illness (ΔWAZ: males -0.24, females 0.03, heterogeneity test P = 0.01). Differences in EBF and introduction of CSL did not explain the sex-based growth outcomes. CONCLUSIONS: In longitudinal analysis, males exhibited more severe growth failure by 3 mo than girls and did not exhibit catchup growth between 6 and 18 mo. Reported symptoms of illness and early introduction of CSL did not appear to be mediators of these sex-based differences, although likely not all sickness was captured by monthly maternal report. Given the early nature of these deficits, LAZ and WAZ measures at 6 mo may be good outcomes for intervention studies targeting improvements in early childhood growth and thriving.

Assessment for Predictors of Rise in Hemoglobin A1c During Extended Use of a Closed-Loop Control System.

We assessed predictors of rising hemoglobin A1c (HbA1c) during long-term use of closed-loop control (CLC) in children aged 6-13 years with type 1 diabetes. Participants used a CLC system during a 16-week randomization phase followed by a 12-week extension phase. We compared an "Increased-HbA1c" group (n = 17, ≥0.5% rise in HbA1c between randomization and extension phases) to a "Maintained-Improvement" group (n = 18, had stable or improved HbA1c). The Increased-HbA1c group had higher pre-CLC HbA1c (8.42% ± 0.80 vs. 7.45% ± 0.93, P = 0.002). Contrary to a-priori hypotheses, there were no differences in Δ-height-for-age z-score, a surrogate for a pubertal growth spurt (+0.16 vs. -0.15, P = 0.113), or number of carbohydrate boluses per day, a surrogate for missed boluses (4.4 ± 2.2 vs. 5.2 ± 2.1, P = 0.263). Both groups maintained high rates in closed-loop. Thus, some children exhibit meaningful rise in HbA1c after initial CLC use, likely from multiple contributing factors, and may benefit from added encouragement during ongoing use.

Prediabetes in Adolescents: Prevalence, Management and Diabetes Prevention Strategies.

The ongoing obesity epidemic in children and adolescents has greatly increased the prevalence of related comorbidities. Prediabetes is defined based on levels of fasting glucose, oral glucose tolerance tests or hemoglobin A1c, that are intermediate between normal levels and thresholds that define type 2 diabetes mellitus (T2DM). As such, prediabetes represents a sign of early pathophysiology preceding T2DM development. Recent analyses of data from US adolescents estimate prediabetes to be present in 4-23% of adolescents, depending on criteria used, with other studies finding an 8% risk of progression from prediabetes to T2DM over a 3-year period. These data support the importance of intervention to avoid long-term sequelae, focusing on reducing degree of obesity and insulin resistance. Lifestyle modification, with increases in physical activity and dietary improvements, remains the first-line approach. Other interventions are based on additional long-term risks and range from metformin treatment for more moderate cases of prediabetes to bariatric surgery for adolescents with severe obesity and comorbidities. As data accumulate regarding sequelae of T2DM in adolescents, there remains a critical need for prevention of obesity and T2DM throughout childhood, and prediabetes should be a trigger for improving this risk profile.

Cognitive Outcomes at 18 Months: Findings from the Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT) Trial.

Micronutrient deficiencies and enteric infections negatively impact child growth and development. We enrolled children shortly after birth in a randomized, placebo-controlled, 2 × 2 factorial interventional trial in Haydom, Tanzania, to assess nicotinamide and/or antimicrobials (azithromycin and nitazoxanide) effect on length at 18 months of age. Cognitive score at 18 months using the Malawi Developmental Assessment Tool (MDAT), which includes gross motor, fine motor, language, and social assessments, was a secondary outcome. Here, we present the MDAT results of 1,032 children. There was no effect of nicotinamide (change in development-for-age Z score [DAZ] -0.08; 95% CI: -0.16, 0) or antimicrobials (change in DAZ 0.04; 95% CI: -0.06, 0.13) on overall MDAT score. The interventions had no effect on cognitive outcomes in subgroups defined by gender, socioeconomic status, birthweight, and birth season or on MDAT subscores. Further analyses are needed to identify targetable risk factors for impaired cognitive development in these settings.