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Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Continuous glucose monitoring (CGM) has led to a paradigm shift in the management of pregnant women with type 1 diabetes (T1D), with improved glycaemic control, less hypoglycaemia and fewer pregnancy complications. Data on CGM use in pregnant women with type 2 diabetes (T2D) are limited. A large randomized controlled trial (RCT) on CGM use in people with T2D in pregnancy is ongoing. Small studies on CGM use in women with gestational diabetes (GDM) have suggested improved glycaemic control and better qualification when insulin is needed. However, none of these studies was powered to evaluate pregnancy outcomes. Several large RCTs are ongoing in women with GDM. In addition to CGM, other technologies, such as advanced hybrid closed‐loop (AHCL) systems have further improved glycaemic management in people with T1D. AHCL therapy adapts insulin delivery via a predictive algorithm integrated with CGM and an insulin pump. A large RCT with the AHCL CamAPS® FX demonstrated a 10% increase in time in range compared to standard insulin therapy in a pregnant population with T1D. Recently, an RCT of an AHCL system not approved for use in pregnancy (780G MiniMed) has also demonstrated additional benefits of AHCL therapy compared to standard insulin therapy, with improved time in range overnight, less hypoglycaemia and improved treatment satisfaction. More evidence is needed on the impact of AHCL therapy on maternal and neonatal outcomes and on which glycaemic targets with CGM should be used in pregnant women with T2D and GDM. We review the current evidence on the use of CGM and AHCL therapy in pregnancy. [ABSTRACT FROM AUTHOR]

A systematic review is a rigorous process that involves identifying, selecting, and synthesizing available evidence pertaining to an a priori–defined research question. The resulting evidence base may be summarized qualitatively or through a quantitative analytic approach known as meta-analysis. Systematic review and meta-analysis (SRMAs) have risen in popularity across the scientific realm including diabetes research. Although well-conducted SRMAs are an indispensable tool in informing evidence-based medicine, the proliferation of SRMAs has led to many reviews of questionable quality and misleading conclusions. The objective of this article is to provide up-to-date knowledge and a comprehensive understanding of strengths and limitations of SRMAs. We first provide an overview of the SRMA process and offer ways to identify common pitfalls at key steps. We then describe best practices as well as evolving approaches to mitigate biases, improve transparency, and enhance rigor. We discuss several recent developments in SRMAs including individual-level meta-analyses, network meta-analyses, umbrella reviews, and prospective meta-analyses. Additionally, we outline several strategies that can be used to enhance quality of SRMAs and present key questions that authors, editors, and readers should consider in preparing or critically reviewing SRMAs. [ABSTRACT FROM AUTHOR]

Background: There is limited information regarding the association between missed appointments and neonatal outcomes for diabetes in pregnancy. Study Methods: This retrospective live birth cohort included pregnant women with Type 1 or 2 diabetes who attended specialized clinics from 2008 to 2020. The association between at least one missed antenatal diabetes appointments and outcomes were assessed using logistic regression and reported as adjusted odds ratios (aOR) (95% confidence interval). Mediation analyses were conducted to examine if above target HbA1c mediated these relationships. Results: The cohort included 407 and 902 women with Type 1 and 2 diabetes, respectively, of whom 25.1% and 34.5% missed at least one appointment. Women with Type 1 diabetes who missed an appointment were more likely to have a caesarean section (aOR 1.95 [1.15, 3.31]) and their babies more likely to be admitted to the neonatal intensive care unit (aOR 2.25 [1.35, 3.75]). Women with Type 2 diabetes who missed an appointment were more likely to have a large‐for‐gestational‐age infant (aOR 1.61 [1.13, 2.28]), and an extreme large‐for‐gestational‐age infant (aOR 1.69 [1.02, 2.81]) compared with women who did not miss appointments. Above target HbA1c mediated the relationship between missed appointments and caesarean delivery in Type 1 diabetes and large‐for‐gestational age and extreme large‐for‐gestational age in Type 2 diabetes. Conclusion: In individuals with Type 1 and 2 diabetes, there are differences in neonatal outcomes between those who missed an appointment compared to those who did not. It remains unclear if missed diabetes appointments are causative or a marker of other health behaviours or risk factors leading to neonatal morbidity. [ABSTRACT FROM AUTHOR]

Aims: (1) To determine the likelihood of full breastfeeding at 3 months postpartum in women with and without diabetes in pregnancy (DiP); (2) to explore the associations between diabetes management practices and infant feeding practices in those who had DiP and (3) to examine women's experiences of feeding their infants after having DiP. Methods: The quantitative study used data from Alberta Pregnancy Outcomes and Nutrition (APrON) cohort study. Participants who had DiP (n = 62) were matched 1:3 to participants without DiP for pre‐pregnancy BMI, parity, mode of delivery and pre‐term birth. Infant feeding questionnaires, prospective breastfeeding diaries and medical chart data were analysed to determine likelihood of fully breastfeeding at 3 months postpartum. For the qualitative study, interviews were conducted with postpartum women who had DiP to explore the experiences of infant feeding. Interviews were thematically analysed, and the results were compared between women who were categorized as 'full breast feeders' or 'mixed feeders'. Results: The odds of fully breastfeeding were 50% lower in women with DiP than women without DiP (OR: 0.50, 95% CI 0.25–0.99, p = 0.04). Qualitative interviews identified that although all women showed resilience in the face of infant feeding challenges, those who were fully breastfeeding reported seeking out external infant feeding supports, for example, classes or Doula's. Mixed Feeders perceived there was a lack of infant feeding information and support given to them prior to giving birth. Conclusion: Women with DiP may require additional prenatal and postnatal infant feeding support to be better prepared to overcome feeding challenges they may face. [ABSTRACT FROM AUTHOR]