Inadequate postpartum screening for type 2 diabetes in women with previous gestation diabetes mellitus: A retrospective audit of practice over 17 years

Predicting Unfavorable Pregnancy Outcomes in Polycystic Ovary Syndrome (PCOS) Patients Using Machine Learning Algorithms

Background and Objectives: Polycystic ovary syndrome (PCOS) is a complex disorder that can negatively impact the obstetrical outcomes. The aim of this study was to determine the predictive performance of four machine learning (ML)-based algorithms for the prediction of adverse pregnancy outcomes in pregnant patients diagnosed with PCOS. Materials and Methods: A total of 174 patients equally divided into 2 groups depending on the PCOS diagnosis were included in this prospective study. We used the Mantel-Haenszel test to evaluate the risk of adverse pregnancy outcomes for the PCOS patients and reported the results as a crude and adjusted odds ratio (OR) with a 95% confidence interval (CI). A generalized linear model was used to identify the predictors of adverse pregnancy outcomes in PCOS patients, quantifying their impact as risk ratios (RR) with 95% CIs. Significant predictors were included in four machine learning-based algorithms and a sensitivity analysis was employed to quantify their performance. Results: Our crude estimates suggested that PCOS patients had a higher risk of developing gestational diabetes and had a higher chance of giving birth prematurely or through cesarean section in comparison to patients without PCOS. When adjusting for confounders, only the odds of delivery via cesarean section remained significantly higher for PCOS patients. Obesity was outlined as a significant predictor for gestational diabetes and fetal macrosomia, while a personal history of diabetes demonstrated a significant impact on the occurrence of all evaluated outcomes. Random forest (RF) performed the best when used to predict the occurrence of gestational diabetes (area under the curve, AUC value: 0.782), fetal macrosomia (AUC value: 0.897), and preterm birth (AUC value: 0.901) in PCOS patients. Conclusions: Complex ML algorithms could be used to predict adverse obstetrical outcomes in PCOS patients, but larger datasets should be analyzed for their validation.

Prevalence of Hypertensive Disorders of Pregnancy and Gestational Diabetes Mellitus by Race and Ethnicity in Illinois, 2018 to 2020

PURPOSE

Use administrative discharge data from 2018 to 2020 to determine if there are differences in the prevalence of hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) by race and ethnicity in Illinois.

STUDY DESIGN AND METHODS

This retrospective cross-sectional study used administrative discharge records from all patients who had live births in Illinois over a 3-year period; 2018, 2019, 2020. Multivariate analyses were performed to control for covariates and determine if associations vary by race and ethnicity for HDP and GDM.

RESULTS

A total of 287,250 discharge records were included. Multivariate analyses showed that after adjusting for covariates, non-Hispanic Black women had 1.60 increased odds of HDP compared to non-Hispanic White women (OR, 1.60; 95% CI, 1.55-1.65). Hispanic women (OR, 1.45; 95% CI, 1.40-1.50), Asian/Pacific Islander women (OR, 2.07; 95% CI, 1.97-2.17), and American Indian/Alaska Native women (OR, 1.43; 95% CI, 1.17-1.74) had an increased odds of GDM compared to non-Hispanic White women.

CLINICAL IMPLICATIONS

Women of color were at increased odds for HDP and GDM in Illinois. To eliminate poor maternal outcomes in women of color at risk for HDP and GDM, more culturally congruent health equity practices, policies, and comprehensive care interventions must be adopted.

Perceptions of Chinese women with a history of gestational diabetes regarding health behaviors and related factors: a directed qualitative content analysis

BACKGROUND

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders during pregnancy and is associated with adverse outcomes in both mothers and their children. After delivery, women who experience GDM are also at higher risk of both subsequent GDM and type 2 diabetes mellitus (T2DM) than those who do not. Therefore, healthcare providers and public health practitioners need to develop targeted and effective interventions for GDM. In this study, we aimed to explore the perceptions regarding health behaviors and related factors during the inter-pregnancy period among Chinese women with a history of GDM through the lens of the theory of planned behavior (TPB).

METHODS

Between December 2021 and September 2022, 16 pregnant Chinese women with a history of GDM were purposively recruited from a tertiary maternity hospital in Shanghai for face-to-face semi-structured interviews. They were asked questions regarding their health behaviors and related factors. The transcribed data were analyzed using a directed qualitative content analysis method based on the theory of TPB.

RESULTS

The health-related behaviors of the women varied substantially. We identified five domains that influenced women's behaviors according to TPB constructs and based on the data collected: behavioral attitude (perceived benefits of healthy behaviors and the relationship between experience and attitude towards the oral glucose tolerance testing); subjective norms (influences of significant others and traditional cultural beliefs); perceived behavior control (knowledge of the disease, multiple-role conflict, the impact of COVID-19, an unfriendly external environment and difficulty adhering to healthy diets), incentive mechanisms (self-reward and external incentives); preferences of professional and institutional support (making full use of social media platform and providing continuous health management).

CONCLUSIONS

The health-related behaviors of women with a history of GDM were found to be affected by multiple factors. Healthcare professionals are recommended to provide women with sufficient information regarding the disease and to take advantage of the power of the family and other social support networks to improve women's subjective norms and to promote the adoption of a healthy lifestyle.

Evaluation of thyroid function monitoring in people treated with lithium: Advice based on real-world data

INTRODUCTION

Blood test monitoring is essential for the management of lithium treatment and National Institute for Health and Care Excellence guidance recommends 6-monthly serum testing of thyroid function. We examined conformity to these guidelines and the impact of monitoring outside these intervals.

METHODS

We extracted serum lithium and thyroid hormone results at one centre between January 2009 and December 2020. We identified 266 patients who started lithium during this period with no history of thyroid abnormality within the previous 2 years and were at risk of developing thyroid abnormalities. We examined the interval between tests, time between onset of lithium testing and first thyroid-stimulating hormone (TSH) outside the laboratory reference range and assessed impact of testing outside recommended 6-monthly intervals.

RESULTS

The most common testing frequency was 3 months (±1 month), accounting for 17.3% of test intervals. Kaplan-Meier analysis showed that most thyroid dysfunction manifests within 3 years (proportion with abnormal TSH at 3 years = 91.4%, 19.9% of total patients). In the first 3 months after commencing lithium therapy, eight patients developed subclinical hypothyroidism and had clinical follow-up data available. Of these, half spontaneously normalized without clinical intervention. In the remaining patients, thyroxine replacement was only initiated after multiple occasions of subclinical hypothyroidism (median = 2 years after initiating lithium, range: 6 months to 3 years).

CONCLUSION

The peak interval at 3 months suggests that thyroid function is frequently checked at the same time as serum lithium, indicating too frequent testing. Our data support the recommended 6-monthly testing interval and highlight poor adherence to it.

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.

Studies are needed to support optimal insulin dose titration in gestational diabetes mellitus: A systematic review

BACKGROUND AND AIMS

We aimed to summarise the existing literature on insulin dose titration in gestation diabetes.

METHODS

Databases: Medline, EMBASE, CENTRAL and CINAHL were systematically searched for trials and observational studies comparing insulin titration strategies in gestational diabetes.

RESULTS

No trials comparing insulin dose titration strategies were identified. Only one small (n = 111) observational study was included. In this study, patient-led daily basal insulin titration was associated with higher insulin doses, tighter glycaemic control, and lower birthweight, vs weekly clinician-led titration.

CONCLUSIONS

There is a paucity of evidence to support optimal insulin titration in gestational diabetes. Randomized trials are required.

Gestational Diabetes Mellitus in a Multi-Ethnic, High-Risk Population: Adequacy of Screening for Diabetes Mellitus 6 Weeks after Delivery

Gestational diabetes mellitus (GDM) during pregnancy is a marker for future type 2 diabetes mellitus (T2DM); therefore, a meticulous follow-up after delivery can help identify women at risk for T2DM. In a cohort of 5504 pregnant women, the postpartum follow-up of all 1043 women with GDM for hyperglycemia in a multi-ethnic, high-risk Arab population was investigated. The prevalence of GDM was 18.9%. A total of 265 (25.4%) women returned for an oral glucose tolerance test (OGTT) 4-6 weeks after delivery, with more South Asian than Arab women (p < 0.01). The other factors associated with return were (a) family history of T2DM, (b) lower basic metabolic index, (c) higher abortions and (d) lower gravida (p < 0.05), all with minimal effect. An abnormal postpartum OGTT was statistically associated with previous GDM history and hypoglycemic drug treatment, although these effects were small. Overall, the follow-up of women with GDM postpartum was dismal, ethnicity being the major factor influencing return. Urgent public measures are needed to educate women with GDM about follow-up highlighting (a) risk awareness for T2DM and (b) a healthy lifestyle after childbirth-if we are to turn the tide on the epidemic of T2DM plaguing the Arab world.

Development of type 2 diabetes in women with comorbid gestational diabetes and common mental disorders in the Born in Bradford cohort

OBJECTIVES

To compare, in a population of women with gestational diabetes mellitus (GDM), the time to diagnosis of Type 2 diabetes in those with and without common mental disorder (CMD) (depression and/or anxiety) during pregnancy.

DESIGN AND SETTING

prospective study of the Born in Bradford cohort in Bradford, UK.

PARTICIPANTS

909 women diagnosed with GDM between 2007 and 2010, with linkage to their primary care records until 2017. The exposed population were women with an indicator of CMD during pregnancy in primary care records. The unexposed were those without an indicator.

OUTCOME MEASURES

Time to diagnosis of type 2 diabetes as indicated by a diagnosis in primary care records.

ANALYSIS

time to event analysis using Cox regression was employed. Multiple imputation by chained equations was implemented to handle missing data. Models were adjusted for maternal age, ethnicity, education, preconception CMD and tobacco smoking during pregnancy.

RESULTS

165 women (18%) were diagnosed with type 2 diabetes over a follow-up period of around 10 years. There was no evidence of an effect of antenatal CMD on the development of type 2 diabetes following GDM (adjusted HR 0.95; 95% CI 0.57 to 1.57).

CONCLUSIONS

Women with CMD were not at an increased risk of type 2 diabetes following GDM. This is reassuring for women with these co-morbidities but requires replication in other study populations.