Uptake of guideline-recommended postpartum diabetes screening among diverse women with gestational diabetes: associations with patient factors in an integrated health system in USA

Digital health outreach to promote postpartum screening after gestational diabetes: A randomized factorial pilot study

Objective

We examined the acceptability and feasibility of a multi-component digital health outreach intervention to promote uptake of guideline-recommended postpartum screening for type 2 diabetes among patients with gestational diabetes (GDM).

Methods

We conducted a 24 randomized factorial experiment as part of the Multiphase Optimization Strategy (MOST) preparation phase for developing behavioral interventions. Participants with current or recent GDM in an integrated healthcare system were randomized to receive an outreach message with up to four intervention components, designed to be self-administered in about 10 min and efficiently delivered online via REDCap: a streamlined values affirmation, personalized information on diabetes risk, an interactive motivational interviewing-based component, and an interactive action planning component. Patient-reported acceptability and feasibility outcomes were assessed via survey.

Results

Among 162 participants, 72% self-identified with a racial/ethnic minority group. Across components, acceptability scores averaged 3.9/5; ≥91% of participants read most or all of the outreach message; ≥89% perceived the amount of information as "about right"; and ≥ 87% completed ≥1 interactive prompt.

Conclusion

Each intervention component was acceptable to diverse patients and feasible to deliver in a brief, self-directed, online format.

Innovation

These novel components target unaddressed barriers to patient engagement in guideline-recommended postpartum diabetes screening and adapt theory-based behavior change techniques for large-scale use.

Opportunities in the Postpartum Period to Reduce Cardiovascular Disease Risk After Adverse Pregnancy Outcomes: A Scientific Statement From the American Heart Association

Adverse pregnancy outcomes are common among pregnant individuals and are associated with long-term risk of cardiovascular disease. Individuals with adverse pregnancy outcomes also have an increased incidence of cardiovascular disease risk factors after delivery. Despite this, evidence-based approaches to managing these patients after pregnancy to reduce cardiovascular disease risk are lacking. In this scientific statement, we review the current evidence on interpregnancy and postpartum preventive strategies, blood pressure management, and lifestyle interventions for optimizing cardiovascular disease using the American Heart Association Life's Essential 8 framework. Clinical, health system, and community-level interventions can be used to engage postpartum individuals and to reach populations who experience the highest burden of adverse pregnancy outcomes and cardiovascular disease. Future trials are needed to improve screening of subclinical cardiovascular disease in individuals with a history of adverse pregnancy outcomes, before the onset of symptomatic disease. Interventions in the fourth trimester, defined as the 12 weeks after delivery, have great potential to improve cardiovascular health across the life course.

Models Predicting Postpartum Glucose Intolerance Among Women with a History of Gestational Diabetes Mellitus: a Systematic Review

PURPOSE OF REVIEW

Despite the crucial role that prediction models play in guiding early risk stratification and timely intervention to prevent type 2 diabetes after gestational diabetes mellitus (GDM), their use is not widespread in clinical practice. The purpose of this review is to examine the methodological characteristics and quality of existing prognostic models predicting postpartum glucose intolerance following GDM.

RECENT FINDINGS

A systematic review was conducted on relevant risk prediction models, resulting in 15 eligible publications from research groups in various countries. Our review found that traditional statistical models were more common than machine learning models, and only two were assessed to have a low risk of bias. Seven were internally validated, but none were externally validated. Model discrimination and calibration were done in 13 and four studies, respectively. Various predictors were identified, including body mass index, fasting glucose concentration during pregnancy, maternal age, family history of diabetes, biochemical variables, oral glucose tolerance test, use of insulin in pregnancy, postnatal fasting glucose level, genetic risk factors, hemoglobin A1c, and weight. The existing prognostic models for glucose intolerance following GDM have various methodological shortcomings, with only a few models being assessed to have low risk of bias and validated internally. Future research should prioritize the development of robust, high-quality risk prediction models that follow appropriate guidelines, in order to advance this area and improve early risk stratification and intervention for glucose intolerance and type 2 diabetes among women who have had GDM.

Diabetes detection in women with gestational diabetes and polycystic ovarian syndrome

Gestational diabetes mellitus (GDM) and polycystic ovarian syndrome (PCOS) represent two of the highest risk factors for development of type 2 diabetes mellitus in young women. As these increasingly common conditions generally affect younger women, early detection of dysglycemia is key if preventative measures are to be effective. While international guidance recommends screening for type 2 diabetes, current screening strategies suffer from significant challenges.First, guidance lacks consensus in defining which tests to use and frequency of monitoring, thereby sending mixed messages to healthcare professionals.Second, conformity to guidance is poor, with only a minority of women having tests at the recommended frequency (where specified). Approaches to improve conformity have focused on healthcare related factors (largely technology driven reminder systems), but patient factors such as convenience and clear messaging around risk have been neglected.Third, and most critically, current screening strategies are too generic and rely on tests that become abnormal far too late in the trajectory towards dysglycemia to offer opportunities for effective preventative measures. Risk factors show wide interindividual variation, and insulin sensitivity and β cell function are often abnormal during pre-diabetes stage, well before frank diabetes.New, consistent, targeted screening strategies are required that incorporate early, prevention focused testing and personalised risk stratification.

Pregnancy as an Early Cardiovascular Moment: Peripartum Cardiovascular Health

Pregnancy is commonly referred to as a window into future CVH (cardiovascular health). During pregnancy, physiological adaptations occur to promote the optimal growth and development of the fetus. However, in approximately 20% of pregnant individuals, these perturbations result in cardiovascular and metabolic complications, which include hypertensive disorders of pregnancy, gestational diabetes, preterm birth, and small-for-gestational age infant. The biological processes that lead to adverse pregnancy outcomes begin before pregnancy with higher risk of adverse pregnancy outcomes observed among those with poor prepregnancy CVH. Individuals who experience adverse pregnancy outcomes are also at higher risk of subsequent development of cardiovascular disease, which is largely explained by the interim development of traditional risk factors, such as hypertension and diabetes. Therefore, the peripartum period, which includes the period before (prepregnancy), during, and after pregnancy (postpartum), represents an early cardiovascular moment or window of opportunity when CVH should be measured, monitored, and modified (if needed). However, it remains unclear whether adverse pregnancy outcomes reflect latent risk for cardiovascular disease that is unmasked in pregnancy or if adverse pregnancy outcomes are themselves an independent and causal risk factor for future cardiovascular disease. Understanding the pathophysiologic mechanisms and pathways linking prepregnancy CVH, adverse pregnancy outcomes, and cardiovascular disease are necessary to develop strategies tailored for each stage in the peripartum period. Emerging evidence suggests the utility of subclinical cardiovascular disease screening with biomarkers (eg, natriuretic peptides) or imaging (eg, computed tomography for coronary artery calcium or echocardiography for adverse cardiac remodeling) to identify risk-enriched postpartum populations and target for more intensive strategies with health behavior interventions or pharmacological treatments. However, evidence-based guidelines focused on adults with a history of adverse pregnancy outcomes are needed to prioritize the prevention of cardiovascular disease during the reproductive years and beyond.

Barriers to and enablers of type 2 diabetes screening among women with prior gestational diabetes: A qualitative study applying the Theoretical Domains Framework

Introduction

Women with previous gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes (T2D). Guidelines recommend postnatal diabetes screening (oral glucose tolerance test or HbA1c) typically 6-12 weeks after birth, with screening maintained at regular intervals thereafter. Despite this, around half of women are not screened, representing a critical missed opportunity for early identification of prediabetes or type 2 diabetes. While policy and practice-level recommendations are comprehensive, those at the personal-level primarily focus on increasing screening knowledge and risk perception, potentially missing other influential behavioral determinants. We aimed to identify modifiable, personal-level factors impacting postpartum type 2 diabetes screening among Australian women with prior gestational diabetes and recommend intervention functions and behavior change techniques to underpin intervention content.

Research design and methods

Semi-structured interviews with participants recruited via Australia's National Gestational Diabetes Register, using a guide based on the Theoretical Domains Framework (TDF). Using an inductive-deductive approach, we coded data to TDF domains. We used established criteria to identify 'important' domains which we then mapped to the Capability, Opportunity, Motivation-Behavior (COM-B) model.

Results

Nineteen women participated: 34 ± 4 years, 19 ± 4 months postpartum, 63% Australian-born, 90% metropolitan, 58% screened for T2D according to guidelines. Eight TDF domains were identified: 'knowledge', 'memory, attention, and decision-making processes', 'environmental context and resources', 'social influences', 'emotion', 'beliefs about consequences', 'social role and identity', and 'beliefs about capabilities'. Study strengths include a methodologically rigorous design; limitations include low recruitment and homogenous sample.

Conclusions

This study identified numerous modifiable barriers and enablers to postpartum T2D screening for women with prior GDM. By mapping to the COM-B, we identified intervention functions and behavior change techniques to underpin intervention content. These findings provide a valuable evidence base for developing messaging and interventions that target the behavioral determinants most likely to optimize T2D screening uptake among women with prior GDM. .

Meta-Analysis of the Effect of Nursing Intervention on Children with Type 2 Diabetes

Objective

To systematically evaluate the effect of nursing intervention on children with type 2 diabetes.

Methods

The randomized controlled trials (RCTs) on nursing intervention in children with type 2 diabetes in CNKI, VIP, WanFang, Chinese Biomedical Database (CBM), PubMed, The Cochrane Library, Embase, and Science were searched by the computer until July 2022. Two evaluators reviewed the articles, selected the information, and assessed their quality according to the inclusion criteria and exclusion criteria and then carried out meta-analysis with RevMan 5.3.

Results

A total of 5 RCT studies were kept, including 319 patients with type 2 diabetes (≤21 years old), where 162 patients were in the nursing group and 157 patients were in the control group. Meta-analysis revealed that, compared with routine nursing, nursing intervention could effectively control children's fasting blood glucose (FBG) (MD = -1.68, 95% CI (-2.19, -1.17), P < 0.00001), 2 h postprandial blood glucose (2hPG) (MD = -4.01, 95% CI (-4.70, -3.33), P < 0.00001), fasting insulin (FINS) (MD = -7.42, 95% CI (-10.63, -4.20), P < 0.00001), 2 h postprandial insulin (2hINS) (MD = -58.18, 95% CI (-103.24, -13.11), P = 0.01), triglycerides (TG) (MD = -0.41, 95% CI (-0.56, -0.25), P < 0.00001), and systolic blood pressure (SBP) (MD = -8.85, 95% CI (-14.67, -3.03), P = 0.003) and effectively maintain patients' blood glucose at a normal level (MD = -8.85, 95% CI (-14.67, -3.03), P = 0.003), where all the differences were statistically significant.

Conclusion

The existing evidence showed that nursing intervention has a significant effect in controlling normal blood glucose and improving insulin utilization in children with type 2 diabetes, which can effectively improve the therapeutic effect on children.

The Impact of Ethnicity on Fetal and Maternal Outcomes of Gestational Diabetes

Background and Objectives: The prevalence of gestational diabetes mellitus (GDM) significantly varies across different ethnic groups. In particular, Africans, Latinos, Asians and Pacific Islanders are the ethnic groups with the highest risk of GDM. The aim of this study was to evaluate the impact of ethnicity on pregnancy outcomes in GDM. Patients and Methods: n = 399 patients with GDM were enrolled, n = 76 patients of high-risk ethnicity (HR-GDM), and n = 323 of low-risk ethnicity (LR-GDM). Clinical and biochemical parameters were collected during pregnancy until delivery. Fetal and maternal short-term outcomes were evaluated. Results: HR-GDM had significantly higher values of glycosylated hemoglobin checked at 26−29 weeks of gestation (p < 0.001). Gestational age at delivery was significantly lower in HR-GDM (p = 0.03). The prevalence of impaired fetal growth was significantly higher in HR-GDM than LR-GDM (p = 0.009). In logistic regression analysis, the likelihood of impaired fetal growth was seven times higher in HR-GDM than in LR-GDM, after adjustment for pre-pregnancy BMI and gestational weight gain (OR = 7.1 [2.0−25.7] 95% CI, p = 0.003). Conclusions: HR-GDM had worse pregnancy outcomes compared with LR-GDM. An ethnicity-tailored clinical approach might be effective in reducing adverse outcomes in GDM.