Identification of self-management patterns in pediatric type 1 diabetes using cluster analysis

Neonatal outcomes of preterm infants with pulmonary hypertension: clustering based on prenatal risk factors

BACKGROUND

To investigate association of prenatal risk factors and neonatal outcomes of preterm infants with pulmonary hypertension (PH).

METHODS

A prospective cohort study of very-low-birth-weight infants born at 22-29 weeks' gestation who received PH-specific treatment during hospitalization. Infants were classified using a two-step cluster analysis based on gestational age (GA), small-for-gestational-age (SGA), exposure to antenatal corticosteroids (ACS), histologic chorioamnionitis (HCA), and oligohydramnios.

RESULTS

Among 910 infants, six clusters were identified: cluster A (HCA, n = 240), cluster B (oligohydramnios, n = 79), cluster C (SGA, n = 74), cluster D (no-ACS, n = 109), cluster E (no dominant parameter, n = 287), and cluster F (HCA and oligohydroamnios, n = 121). Cluster A was used as a reference group for comparisons among clusters. Compared to cluster A, cluster C (aHR: 1.63 [95% CI: 1.17-2.26]) had higher risk of overall in-hospital mortality. Clusters B (aHR: 1.52 [95% CI: 1.09-2.11]), D (aHR: 1.71 [95% CI: 1.28-2.30]), and F (aHR: 1.51 [95% CI: 1.12-2.03]) had higher risks of receiving PH-specific treatment within the first week of birth compared to cluster A.

CONCLUSION

These findings may provide a better understanding of prenatal risk factors contributing to the development of PH.

IMPACT

Pulmonary hypertension (PH), presenting as hypoxic respiratory failure, has complex etiologies in preterm infants. Although multifactorial risks for the development of PH in preterm infants are known, few studies have classified infants with similar etiologies for PH. Each cluster has distinct patterns of prenatal condition and neonatal outcome.

Forty Years of Behavioral Diabetes Research: A Personal Journey

This article was adapted from the address Dr. Delamater delivered as the recipient of the American Diabetes Association's Richard R. Rubin Award for 2022. This award recognizes a behavioral researcher who has made outstanding, innovative contributions to the study and understanding of the behavioral aspects of diabetes in diverse populations. Dr. Delamater delivered the address in June 2022 at the Association's virtual 82nd Scientific Sessions. A webcast of this speech is available for viewing on the DiabetesPro website (https://professional.diabetes.org/webcast/stigma-diabetes-care%E2%80%94evidence-and-solutions-richard-r-rubin-award-lecture).

Identification of four patterns for self-management behaviors in clients with schizophrenia: A cross-sectional study

This study aimed to describe different patterns of self-management behaviors among clients with schizophrenia in China. Two hundred twenty-eight clients with schizophrenia living in eight communities of Beijing were investigated using the Self-Management Instrument for Persons with Schizophrenia and a Demographic and Clinical Characteristics Questionnaire. Cluster analysis was performed to categorize the data. Four distinct self-management behavior patterns and variables of clients associated with non-adherent self-management were identified. The self-management behaviors and demographic characteristics were similar in each pattern but different among patterns. These findings could guide the development of more personalized and cost-effective self-management interventions for different patterns of clients in the future.

Evaluating the relationship between clinical and demographic characteristics of insulin-using people with diabetes and their health outcomes: a cluster analysis application

Background

The aim of this study was to determine how clusters or subgroups of insulin-treated people with diabetes, based upon healthcare resource utilization, select social demographic and clinical characteristics, and diabetes management parameters, are related to health outcomes including acute care visits and hospital admissions.

Methods

This was a non-experimental, retrospective cluster analysis. We utilized Aetna administrative claims data to identify insulin-using people with diabetes with service dates from 01 January 2015 to 30 June 2018. The study included adults over the age of 18 years who had a diagnosis of type 1 (T1DM) or type 2 diabetes mellitus (T2DM) on insulin therapy and had Aetna medical and pharmacy coverage for at least 18 months (6 months prior and 12 months after their index date, defined as either their first insulin prescription fill date or their earliest date allowing for 6 months’ prior coverage). We used K-means clustering methods to identify relevant subgroups of people with diabetes based on 13 primary outcome variables.

Results

A total of 100,650 insulin-using people with diabetes were identified in the Aetna administrative claims database and met study criteria, including 11,826 (11.7%) with T1DM and 88,824 (88.3%) with T2DM. Of these 79,053 (78.5%) people were existing insulin users. Seven distinct clusters were identified with different characteristics and potential risks of diabetes complications. Overall, clusters were significantly associated with differences in healthcare utilization (emergency room visits, inpatient admissions, and total inpatient days) after multivariable adjustment.

Conclusions

This analysis of healthcare claims data using clustering methodologies identified meaningful subgroups of patients with diabetes using insulin. The subgroups differed in comorbidity burden, healthcare utilization, and demographic factors which could be used to identify higher risk patients and/or guide the management and treatment of diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06603-0.

Patterns and associated factors of diabetes self-management: Results of a latent class analysis in a German population-based study

OBJECTIVE

Few studies on diabetes self-management considered the patterns and relationships of different self-management behaviours (SMB). The aims of the present study are 1) to identify patterns of SMB among persons with diabetes, 2) to identify sociodemographic and disease-related predictors of SMB among persons with diabetes.

RESEARCH DESIGN AND METHODS

The present analysis includes data of 1,466 persons (age 18 to 99 years; 44.0% female; 56.0% male) with diabetes (type I and II) from the population-based study German Health Update 2014/2015 (GEDA 2014/2015-EHIS). We used latent class analysis in order to distinguish different patterns of self-management behaviours among persons with diabetes. The assessment of SMB was based on seven self-reported activities by respondents (dietary plan, diabetes-diary, diabetes health pass, self-assessment of blood glucose, self-examination of feet, retinopathy-screenings and assessment of HbA1c). Subsequent multinomial latent variable regressions identified factors that were associated with self-management behaviour.

RESULTS

Latent class analysis suggested a distinction between three patterns of SMB. Based on modal posterior probabilities 42.8% of respondents showed an adherent pattern of diabetes self-management with above-average frequency in all seven indicators of SMB. 32.1% showed a nonadherent pattern with a below-average commitment in all seven forms of SMB. Another 25.1% were assigned to an ambivalent type, which showed to be adherent with regard to retinopathy screenings, foot examinations, and the assessment of HbA1c, yet nonadherent with regard to all other forms of SMB. In multivariable regression analyses, participation in Diabetes Self-Management Education programs (DSME) was the most important predictor of good self-management behaviour (marginal effect = 51.7 percentage points), followed by attentiveness towards one's personal health (31.0 percentage points). Respondents with a duration of illness of less than 10 years (19.5 percentage points), employed respondents (7.5 percentage points), as well as respondents with a high socioeconomic status (24.7 percentage points) were more likely to show suboptimal forms of diabetes self-management.

DISCUSSION

In the present nationwide population-based study, a large proportion of persons with diabetes showed suboptimal self-management behaviour. Participation in a DSME program was the strongest predictor of good self-management. Results underline the need for continual and consistent health education for patients with diabetes.

The Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations

There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities—foreign-born, immigrant, refugee, and culturally marginalized—are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, several factors may predispose AI to ethnoracial bias. To better understand whether diabetes AI interventions are being designed in an ethnoracially equitable manner, we conducted a secondary analysis of 141 articles included in a 2018 review by Contreras and Vehi entitled “Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.” Two members of our research team independently reviewed each article and selected those reporting ethnoracial data for further analysis. Only 10 articles (7.1%) were ultimately selected for secondary analysis in our case study. Of the 131 excluded articles, 118 (90.1%) failed to mention participants’ ethnic or racial backgrounds. The included articles reported ethnoracial data under various categories, including race (n=6), ethnicity (n=2), race/ethnicity (n=3), and percentage of Caucasian participants (n=1). Among articles specifically reporting race, the average distribution was 69.5% White, 17.1% Black, and 3.7% Asian. Only 2 articles reported inclusion of Native American participants. Given the clear ethnic and racial differences in diabetes biomarkers, prevalence, and outcomes, the inclusion of ethnoracial training data is likely to improve the accuracy of predictive models. Such considerations are imperative in AI-based tools, which are predisposed to negative biases due to their black-box nature and proneness to distributional shift. Based on our findings, we propose a short questionnaire to assess ethnoracial equity in research describing AI-based diabetes interventions. At this unprecedented time in history, AI can either mitigate or exacerbate disparities in health care. Future accounts of the infancy of diabetes AI must reflect our early and decisive action to confront ethnoracial inequities before they are coded into our systems and perpetuate the very biases we aim to eliminate. If we take deliberate and meaningful steps now toward training our algorithms to be ethnoracially inclusive, we can architect innovations in diabetes care that are bound by the diverse fabric of our society.

Mealtime insulin bolus adherence and glycemic control in adolescents on insulin pump therapy

Poor self-management contributes to insufficient glycemic control in adolescents with type 1 diabetes (T1DM). We assessed the effects on glycemic control of adherence to self-measurement of blood glucose (SMBG) and insulin boluses in 90 adolescents with T1DM on insulin pump therapy over a 2-month period. We compared the number of insulin boluses and SMBGs around main meals to the "gold standard" of optimal diabetes management (SMBGs and a bolus before each main meal and SMBG before bedtime). The mean (95% CI) HbA1c levels were 2.9(1.7 to 4.0) mmol/mol lower for every additional insulin bolus and 3.1(1.6 to 4.5) mmol/mol lower for every additional SMBG. Patients performing SMBG and bolusing around each main meal had considerably lower HbA1c levels than those unable to do (95% CI for difference 4.3 to 10.4 mmol/mol and 11.5 to 20.1 mmol/mol respectively). For each additional mealtime bolus/day, the odds ratio of achieving target HbA1c levels of <58 mmol/mol was 6.73 (95% CI 2.94-15.38), after adjustment for gender, age, diabetes duration, and affective responses to SMBG in a multiple logistic regression model.Conclusion: Glycemic control in adolescents with T1DM on insulin pump therapy is strongly dependent on adherence to insulin boluses around mealtimes. What is Known: • In mixed groups of children and adolescents, insulin bolus frequency and self-monitoring of blood glucose (SMBG) frequency were determinants of HbA1c levels. • Adherence to insulin boluses and SMBG is particularly challenging in adolescents. What is New: • In adolescents on insulin pump therapy, each additional insulin bolus, particularly around mealtime, was significantly associated with approximately 3 mmol/mol lower HbA1c levels. • This beneficial effect of mealtime bolusing was strongest for the evening meal.

Psychological Flexibility Among Youth with Type 1 Diabetes: Relating Patterns of Acceptance, Adherence, and Stress to Adaptation

Psychological flexibility, a complex concept encompassing both acceptance and action related factors, has been identified as a target for intervention for diabetes management. Research suggests acceptance, self-management, and stress, all factors that influence psychological flexibility, have an impact on adaptation to type 1 diabetes (T1D) by youth independently. However, yet to be explored is individually varying patterns of these variables and how they may relate to diabetes adaptation outcomes. The present study aimed to establish individual variations of patterns of these factors to derive profiles of psychological flexibility, and examine their relations to the adaptation outcomes of glycemic control and health-related quality of life. Youth (N = 162, aged 12-17 years) with T1D completed the Acceptance and Action Diabetes Questionnaire, Diabetes Stress Questionnaire, Self-Care Inventory, and Pediatric Quality of Life-Diabetes Module. Hemoglobin A_1c values were abstracted from medical records. Latent profile analysis yielded three profiles: High Acceptance & Adherence/Low Stress, Low Acceptance/Moderate Adherence & Stress, and Low Acceptance & Adherence/High Stress. The High Acceptance & Adherence/Low Stress group displayed significantly higher health-related quality of life and lower HbA_1c compared to other groups. Fluid psychological variables, such as acceptance and diabetes stress, and adherence behaviors may be salient targets to increase psychological flexibility for individual psychosocial interventions aimed at improving adaptation to type 1 diabetes in youth.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Background

Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis.

Objective

The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges.

Methods

A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review.

Results

We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results.

Conclusions

We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life.

Age at diagnosis predicts deterioration in glycaemic control among children and adolescents with type 1 diabetes

BACKGROUND

Poor glycemic control early in the course of type 1 diabetes mellitus (T1DM) increases the risk for microvascular complications. However, predictors of deteriorating control after diagnosis have not been described, making it difficult to identify high-risk patients and proactively provide aggressive interventions.

OBJECTIVE

We examined whether diagnostic age, gender, and race were associated with deteriorating glycemic control during the first 5 years after diagnosis.

PARTICIPANTS

2218 pediatric patients with T1DM.

METHODS

We conducted a longitudinal cohort study of pediatric patients with T1DM from the Midwest USA, 1993-2009, evaluating within-patient glycated hemoglobin (HbA1c) trajectories constructed from all available HbA1c values within 5 years of diagnosis.

RESULTS

52.6% of patients were male; 86.1% were non-Hispanic Caucasian. The mean diagnostic age was 9.0±4.1 years. The mean number of HbA1c values/year/participant was 2.4±0.9. HbA1c trajectories differed markedly across age groups, with older patients experiencing greater deterioration than their younger counterparts (p<0.001). HbA1c trajectories, stratified by age, varied markedly by race (p for race×diagnostic age <0.001). Non-Hispanic African-American patients experienced higher initial HbA1c (8.7% vs 7.6% (71.6 vs 59.6 mmol/mol); p<0.001), and greater deterioration in HbA1c than non-Hispanic Caucasian patients across diagnostic ages (rise of 2.04% vs 0.99% per year (22.3 vs 10.8 mmol/mol/year); p<0.0001).

CONCLUSIONS

Older diagnostic age and black race are major risk factors for deterioration in glycemic control early in the course of T1DM. These findings can inform efforts to explore the reasons behind these differences and develop preventive interventions for high-risk patients.

Identification and prediction of group-based glycemic control trajectories during the transition to adolescence

OBJECTIVE

To identify trajectories of glycemic control over a period of 3 years in a pediatric sample of youth diagnosed with Type 1 diabetes transitioning to adolescence. A second aim was to examine a set of modifiable individual and family level baseline predictors of glycemic control group membership.

METHODS

This multisite, prospective study included 239 children and adolescents (ages 9-11 years at baseline) diagnosed with Type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c (HbA1c) collected at 6-month intervals over a period of 3 years. Predictors of glycemic control membership included baseline global executive functioning, diabetes self-management, diabetes-specific family conflict, blood glucose monitoring frequency, and relevant individual and family level covariates.

RESULTS

Group-based trajectory analyses were used to describe patterns of glycemic control from baseline to 36 months and 3 trajectories were identified: low risk (42.9%), elevated risk (44.6%), and high risk (12.1%) subgroups. Baseline maternal-reported family conflict, blood glucose monitoring frequency, and gender were significant predictors of glycemic control group membership. Higher levels of baseline family conflict, lower frequency of blood glucose monitoring, and female gender were associated with elevated and high-risk group membership.

CONCLUSIONS

These findings underscore the importance of examining trajectories of HbA1c across time. These results suggest that problematic trajectories of glycemic control are evident during the transition to adolescence. Furthermore, there are modifiable individual and family level characteristics that predict group membership and hence could be targeted in interventions to ensure adequate glycemic control is maintained over time and that risks for diabetes-related complications are reduced.

Patterns of family management of childhood chronic conditions and their relationship to child and family functioning

Understanding patterns of family response to childhood chronic conditions provides a more comprehensive understanding of their influence on family and child functioning. In this paper, we report the results of a cluster analysis based on the six scales comprising the Family Management Measure (FaMM) and the resulting typology of family management. The sample of 575 parents (414 families) of children with diverse chronic conditions fell into four patterns of response (Family Focused, Somewhat Family Focused, Somewhat Condition Focused, Condition Focused) that differed in the extent family life was focused on usual family routines or the demands of condition management. Most (57%) families were in either the Family Focused or Somewhat Family Focused pattern. Patterns of family management were related significantly to family and child functioning, with families in the Family Focused and Somewhat Family Focused patterns demonstrating significantly better family and child functioning than families in the other two patterns.

Patterns of self-management in pediatric type 1 diabetes predict level of glycemic control 2 years later

OBJECTIVE

To determine if 3 distinct self-management patterns (i.e., maladaptive, moderate/mixed, and adaptive) observed at baseline, 1 year, and 2 years in a sample of youth with type 1 diabetes and their caregivers predicted mean differences in adolescent's subsequent glycemic control.

METHODS

This study is a descriptive, multisite, prospective study that examined a sample of youth diagnosed with type 1 diabetes (ages 9-11 years at baseline). Youth and their maternal and paternal caregivers provided information about the youth's self-management patterns at baseline, 1 year, and 2 years using the Diabetes Self-Management Profile structured interview. Glycemic control (hemoglobin A1c: HbA1c) was examined at baseline and 6, 12, 18, and 24 months.

RESULTS

Three distinct self-management patterns were observed at 1 year and 2 years, which were conceptually consistent with previously reported baseline self-management patterns. Youth identified by their maternal caregivers as having adaptive self-management patterns at baseline had better glycemic control across 2 years compared with those in the maladaptive and mixed self-management groups. Similarly, maternal reports suggested that youth with less adaptive self-management patterns generally had worse glycemic control over time and HbA1c values above the American Diabetes Association recommendations. Youth and paternal caregiver reports yielded more variable findings.

CONCLUSIONS

Findings underscore the stability of self-management patterns in pediatric type 1 diabetes and the need for preventive interventions that are tailored to specific patterns of self-management associated with risk for problematic glycemic control.

Predictors of deteriorations in diabetes management and control in adolescents with type 1 diabetes

PURPOSE

Deteriorating type 1 diabetes management and control are common among adolescents; however, clinical evidence suggests that individual trajectories can vary. The aim of this study was to examine patterns and predictors of blood glucose monitoring (BGM) frequency and glycemic control (hemoglobin A1c).

METHODS

Prospective data analysis spanning 18-24 months was conducted with 150 adolescent-parent pairs. Latent group-based trajectory modeling identified subgroups and determined medical, demographic, psychological, and family predictors of subgroup membership.

RESULTS

Three subgroups emerged, representing diabetes management and control that are "meeting treatment targets" (40%; A1c at baseline = 7.4%, BGM frequency at baseline = 4.8 checks/day) and two levels "not meeting targets":"normatively similar" youth (40%; A1c = 9.2%, BGM frequency = 2.8 checks/day), and "high-risk" youth (20%; A1c = 11.2%, BGM frequency = 2.9 checks/day). Subgroup membership was maintained over 18-24 months. There was minimal change across time, although only one-third of adolescents met treatment targets. Older age, longer diabetes duration, ethnic minority status, unmarried caregiver status, insulin delivery via injections versus continuous subcutaneous insulin infusion, greater depressive symptoms, negative affect about BGM, and diabetes-specific family conflict each predicted membership in a subgroup with poorer diabetes management and control.

CONCLUSIONS

Among the nearly two-thirds of adolescents with management and control that do not meet treatment targets, modifiable and nonmodifiable factors may signal the need for prevention or intervention. Demographic and medical factors may call for proactive efforts to prevent deterioration, and psychological symptoms and family conflict signal opportunities for clinical intervention to promote improved diabetes management and control in adolescence.

Diabetes resilience: a model of risk and protection in type 1 diabetes

Declining diabetes management and control are common as children progress through adolescence, yet many youths with diabetes do remarkably well. Risk factors for poor diabetes outcomes are well-researched, but fewer data describe processes that lead to positive outcomes such as engaging in effective diabetes self-management, experiencing high quality of life, and achieving in-range glycemic control. Resilience theory posits that protective processes buffer the impact of risk factors on an individual's development and functioning. We review recent conceptualizations of resilience theory in the context of type 1 diabetes management and control and present a theoretical model of pediatric diabetes resilience. Applications to clinical care and research include the development of preventive interventions to build or strengthen protective skills and processes related to diabetes and its management. The ultimate goal is to equip youths with diabetes and their families with the tools to promote both behavioral and health-related resilience in diabetes.

Mother-father informant discrepancies regarding diabetes management: associations with diabetes-specific family conflict and glycemic control

OBJECTIVE

To examine the relationship of mother-father informant discrepancies regarding diabetes management to diabetes-specific family conflict and glycemic control.

METHODS

One hundred thirty-six mothers and fathers of youth with Type 1 diabetes reported on the youth's diabetes management, diabetes-specific family conflict, and amount of paternal involvement in diabetes care. Glycosylated hemoglobin A1c (HbA1c) was used to measure glycemic control.

RESULTS

As hypothesized, mother-father discrepancies regarding diabetes management were positively associated with frequency of diabetes-specific family conflict. Contrary to hypotheses, mother-father discrepancies regarding diabetes management predicted poorer glycemic control for youth with less involved fathers only.

CONCLUSIONS

Results highlight the importance of caregivers being consistent about pediatric illness management and support the idea that informant discrepancies represent an important window into the functioning of the family system.

Changes in treatment adherence and glycemic control during the transition to adolescence in type 1 diabetes

OBJECTIVE

To test models of unidirectional and bidirectional change between treatment adherence and glycemic control in youth with type 1 diabetes.

RESEARCH DESIGN AND METHODS

We conducted a 2-year longitudinal, multisite study of 225 youth with type 1 diabetes recruited at the cusp of adolescence (aged 9-11 years) to describe the mutual influences of glycemic control as measured by HbA(1c) and treatment adherence as measured by blood glucose monitoring frequency (BGMF) during the transition to adolescence.

RESULTS

HbA(1c) increased from 8.2 to 8.6% (P < 0.001) and BGMF decreased from 4.9 to 4.5 checks per day (P < 0.02) during the 2-year period. Changes in the BGMF slope predicted changes in HbA(1c). A change (increase) in HbA(1c) was associated with a change (decrease) in BGMF of 1.26 (P < 0.001) after controlling for covariates.

CONCLUSIONS

The magnitude of the effect of declining treatment adherence (BGMF) on glycemic control in young adolescents may be even greater than declines observed among older adolescents. BGMF offers a powerful tool for targeted management of glycemic control for type 1 diabetes during the critical transition to adolescence.

Diabetes management and glycemic control in youth with type 1 diabetes: test of a predictive model

The objective of this study was to test a comprehensive model of biologic (pubertal status), family (communication and conflict), and psychological influences (behavioral autonomy) on diabetes management and glycemic control in a sample of youth (N = 226) with type 1 diabetes recruited during late childhood/early adolescence (ages 9-11 years). The study design was a prospective, multisite, multi-method study involving prediction of diabetes management and glycemic control 1 year post-baseline. The primary outcome measures included diabetes management behaviors based on the Diabetes Self-Management Profile (DSMP) administered separately to mothers and youth and glycemic control measured by glycated hemoglobin (HbA1c) obtained by blood samples and analyzed by a central laboratory to ensure standardization. Our hypothesized predictive model received partial support based on structural equation modeling analyses. Family conflict predicted less adequate glycemic control 1 year later (p < 0.05). Higher conflict predicted less adequate diabetes management and less adequate glycemic control. More advanced pubertal status also predicted less adequate glycemic control, but behavioral autonomy did not. Family conflict is an important, potentially clinically significant influence on glycemic control that should be considered in primary and secondary prevention in the management of type 1 diabetes in youth.