Factors predicting poor glycemic control in the first two years of childhood onset type 1 diabetes in a cohort from East London, UK: Analyses using mixed effects fractional polynomial models

Risk predictors of glycaemic control in children and adolescents with type 1 diabetes: A systematic review and meta-analysis

OBJECTIVES

To conduct systematic evaluation of the risk predictors of glycaemic control in children and adolescents with type 1 diabetes mellitus.

METHODS

Cohort studies on risk predictors of glycaemic control in children and adolescents with type 1 diabetes were retrieved from CNKI, PubMed, Web of Science, Embase databases, etc. from the construction of the repository to 3 February 2023. Literature screening was conducted according to inclusion and exclusion criteria, then data extraction of region, sample size, age, follow-up time, risk predictors, outcome indicators, etc., and quality evaluation of The Newcastle-Ottawa Scale were conducted by two researchers while the third researcher makes decisions if there are disagreements. Finally, Revman5.4 and StataMP17 were used for meta-analysis.

RESULTS

A total of 29 studies were included, and the results showed that insulin pump [Weighed mean difference (WMD) = -.48, 95% CI (-.73, -.24), p < .01], high-frequency sensor monitoring, early use of insulin pumps, prospective follow-up male, white race, large body mass index-standardised scoring, conscientiousness, agreeableness of mothers, eicosapentaenoic acid, leucine and protein (p < .05) were beneficial for reducing HbA1c levels in children and adolescents with diabetes. Ketoacidosis [WMD = .39, 95% CI (.28, .50), p < .01], selective admission, higher HbA1c level at one time (p < .01), higher glutamate decarboxylase antibody at 1 month after diagnosis, lower socio-economic status, non-living with biological parents, non-two-parent family, family disorder, family history of diabetes and high carbohydrate intake (p < .05) increased HbA1c levels in children and adolescents with diabetes.

CONCLUSION

For children and adolescents with type 1 diabetes mellitus, the use of insulin pump, high-frequency sensor monitoring, prospective follow-up, good family support and reasonable diet are conducive to blood glucose control, while selective admission and DKA are not. Disease characteristics and demographic characteristics of children are closely related to subsequent blood glucose control, and the relationship between diagnosis age and blood glucose control needs to be further explored.

Predictors of glycemic control in children and adolescents with type 1 diabetes at 12 months after diagnosis

Identifying risk factors for suboptimal glycemic control during the first year after diagnosis with type 1 diabetes (T1D) may provide early appropriate and individualized management. Our aim was to study possible predictors of early glycemic control during the first year after diagnosis with T1D in children and adolescents in Jordan. This is a retrospective study conducted through a review of medical records at Jordan University Hospital and the National Centre for Diabetes, Endocrinology and Genetics. Children and adolescents diagnosed with T1D at age younger than 16 years and with diabetes duration of at least 2 years were included. Demographic, clinical and socioeconomic factors were collected, in addition to glycosylated hemoglobin (HbA1c) values during the first year after diagnosis. Average age at diagnosis of the 337 patients who were enrolled in the study was 7.7 ± 3.8 years. HbA1c at diagnosis was 10.9 ± 1.9% (95.64 ± 20.76 mmol/mol). Factors such as the involvement of children's mothers in deciding insulin doses, higher mother's educational level and higher family monthly income were associated with better early glycemic control. HbA1c at 6 months after diagnosis, parental marital status and compliance to counting carbohydrates were significant predictors of glycemic control at 12 months after diagnosis. Many clinical and socioeconomic factors were associated with early glycemic control at 12 months after diagnosis. Modifiable risk factors must be addressed as early as possible to decrease future complications. Children with nonmodifiable risk factors should be identified early for closer observation and providing individualized diabetes care plan.

Trajectory and predictors of HbA1c in children and adolescents with type 1 diabetes-A Danish nationwide cohort study

OBJECTIVES

Poor glycemic control in type 1 diabetes increases the risk of chronic complications and it is essential to identify life periods and predictors associated with deteriorating HbA_1c . The aim was to describe specific HbA_1c trajectories in Danish children and adolescents with type 1 diabetes and study associations with clinical and sociodemographic factors.

RESEARCH DESIGN AND METHODS

5889 children with type 1 diabetes were included from the nationwide Danish Registry of Childhood and Adolescent Diabetes with annual visits during 1996-2019. Trajectories of HbA_1c were modeled with linear mixed-effects models (using age as time scale, included as cubic spline) and with an individual-specific random intercept and slope. The following cofactors were included stepwise into the model: sex, age at diagnosis, calendar year, parental education, immigrant status, health care region, blood glucose monitoring (BGM) frequency, treatment modalities: continuous subcutaneous insulin infusion (pump) versus multiple daily insulin injection therapy (pen) and continuous glucose monitoring.

RESULTS

HbA_1c overall increased during age while there was a significant decreasing secular trend. Older age at diagnosis was associated with a steeper trajectory, and non-Danish origin and shorter parental education were each associated with higher levels of HbA_1c across age. A lower BGM frequency was associated with a markedly poorer HbA_1c trajectory, while no significant differences were shown for different treatment modalities.

CONCLUSIONS

Glycemic outcome worsened with age during childhood and adolescence, which is of clinical concern. Important predictors for a poorer glycemic trajectory were later age at diabetes diagnosis, shorter parental education, non-Danish origin and, in particular low BGM frequency.

Resilience and Diabetes Distress at 3 Months Following Diagnosis Predict A1C Trajectories in Youth With Type 1 Diabetes: An Argument for Early Intervention

OBJECTIVE

Youth and adolescents with type 1 diabetes (T1D) are at risk for poor health outcomes. Understanding if psychological factors shortly following diagnosis, such as diabetes distress and resilience, predict glycated hemoglobin (A1C) trajectories may help inform both optimal timing and content of psychosocial interventions for youth with T1D.

METHODS

Youth and adolescents (N = 34) with newly diagnosed T1D completed distress and resilience measures at baseline and 3 months following diagnosis. Using multilevel modeling, we predicted A1C trajectories up to 3 years following diagnosis.

RESULTS

We found that in separate models, higher 3-month diabetes distress and lower 3-month resilience predicted larger increases in A1C years 1-3 following diagnosis.

CONCLUSIONS

Our findings suggest that targeting resilience and diabetes distress within 3 months following diagnosis has implications for the yearly rate of A1C increase up to 3 years later.

Glycaemic control and factors affecting it in type 1 diabetes in children: experience from a tertiary care centre in India

INTRODUCTION

Optimal glycaemic control is essential for the prevention of future micro- and macrovascular complications in type 1 diabetes (T1D). The type of insulin, the type of insulin delivery device, the caregiver's knowledge, the patient's age, duration of diabetes, and self-monitoring of blood glucose affect glycaemic control in type 1 diabetes. In the present study, we analysed glycaemic control and factors affecting it at a tertiary care centre in northern India.

MATERIAL AND METHODS

A retrospective review of records of patients registered between 2015 and 2018 was done. The data on demographic and disease-related factors were collected from the records. The different groups were compared with the t-test, one-way ANOVA, or Kruskal-Wallis test.

RESULTS

The mean age at the time of evaluation was 10.43 ±4.04 years (2-21 years), and the mean disease duration was 46.61 ±28.49 months (16-141 months). Most of the patients were prepubertal and using a basal-bolus regimen. The mean glycated haemoglobin (HbA1c ) was 7.96 ±1.46%, but only 24% had HbA1c below the International Society of Paediatric and Adolescent Diabetes (ISPAD) recommended desirable level of below 7%. Forty-six patients suffered one or more micro-macrovascular complications, and dyslipidaemia was the most common complication. Children with a longer duration of disease (8.39 ±1.42% vs. 7.59 ±1.65%), an episode of DKA (diabetes ketoacidosis) within a year of evaluation (9.19 ±2.54% vs. 7.93 ±1.39%), lower maternal (8.22 ±1.37% vs. 7.56 ±1.45%) and paternal education (8.26 ±1.67% vs. 7.78 ±1.30%), and hyperthyroid state (9.43 ±2.28% vs. 7.91 ±1.45%) had higher HbA1c.

CONCLUSIONS

Better diabetes education focusing on parents with lower education strata and children with longer disease duration and poor compliance can help improve glycaemic control in developing countries like India.

Factors predicting poor glycemic control in the first two years of childhood onset type 1 diabetes in a cohort from East London, UK: Analyses using mixed effects fractional polynomial models

BACKGROUND/OBJECTIVE

Poor early glycemic control in childhood onset type 1 diabetes (T1D) is associated with future risk of acute and chronic complications. Our aim was to identify the predictors of higher glycated hemoglobin (HbA1c) within 24 months of T1D diagnosis in children and adolescents.

METHODS

Mixed effects models with fractional polynomials were used to analyze longitudinal data of patients <19 years of age, followed from T1D diagnosis for up to 2 years, at three diabetes clinics in East London, United Kingdom.

RESULTS

A total of 2209 HbA1c observations were available for 356 patients (52.5% female; 64.4% non-white), followed from within 3 months of diagnosis during years 2005 to 2015, with a mean ± SD of 6.2 ± 2.5 HbA1c observations/participant. The mean age and HbA1c at diagnosis were 8.9 ± 4.3 years and 10.7% ±4.3% (or expressed as mmol/mol HbA1c mean ± SD 92.9 ± 23.10 mmol/mol) respectively. Over the 2 years following T1D diagnosis, HbA1c levels were mostly above the National Institute for Health, Care and Excellence (NICE), UK recommendations of 7.5% (<58 mmol/mol). Significant (P < .05) predictors of poorer glycemic control were: Age at diagnosis (12-18 years), higher HbA1c at baseline (>9.5%, ie, >80 mmol/mol), clinic site, non-white ethnicity, and period (pre-year 2011) of diagnosis. Additionally in univariable analyses, frequency of clinic visits, HbA1c at diagnosis, and type of insulin treatment regimen showed association with poor glycemic control (P < .05).

CONCLUSIONS

Major risk factors of poorer glycemic control during 3-24 months following childhood onset T1D are: diagnosis prior to 2011, higher HbA1c levels at baseline, age at diagnosis, non-white ethnicity, and clinic site.