Label of Gestational Diabetes Mellitus Affects Caesarean Section and Neonatal Intensive Care Unit Admission without Conventional Indications

Insulin Use During Gestational and Pre-existing Diabetes in Pregnancy: A Systematic Review of Study Design

INTRODUCTION

Insulin is the first-line pharmacologic therapy for women with diabetes in pregnancy. However, conducting well-designed randomized clinical trials (RCTs) and achieving recommended glycemic targets remains a challenge for this unique population. This systematic literature review (SLR) aimed to understand the evidence for insulin use in pregnancy and the outcome metrics most often used to characterize its effect on glycemic, maternal and fetal outcomes in gestational diabetes mellitus (GDM) and in pregnant women with diabetes.

METHODS

An SLR was conducted using electronic databases in Medline, EMBASE via Ovid platform, evidence-based medicine reviews (2010-2020) and conference proceedings (2018-2019). Studies were included if they assessed the effect of insulin treatment on glycemic, maternal or fetal outcomes in women with diabetes in pregnancy. Studies on any type of diabetes other than gestational or pre-existing diabetes as well as non-human studies were excluded.

RESULTS

In women diagnosed with GDM or pre-existing diabetes, most studies compared treatment of insulin with metformin (n = 35) followed by diet along with lifestyle intervention (n = 24) and glibenclamide (n = 12). Most studies reporting on glycemic outcomes compared insulin with metformin (n = 22) and glibenclamide (n = 4). Fasting blood glucose was the most reported clinical outcome of interest. Among the studies reporting maternal outcomes, method of delivery and delivery complications were most commonly reported. Large for gestational age, stillbirth and perinatal mortality were the most common fetal outcomes reported.

CONCLUSION

This SLR included a total of 108 clinical trials and observational studies with diverse populations and treatment arms. Outcomes varied across the studies, and a lack of consistent outcome measures to manage diabetes in pregnant women was observed. This elucidates a need for global consensus on study design and standardized clinical, maternal and fetal outcomes metrics.

An exploration of differences in infant feeding practices among women with and without diabetes in pregnancy: A mixed-methods study

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.

Developing routinely recorded clinical data from electronic patient records as a national resource to improve neonatal health care: the Medicines for Neonates research programme

Background

Clinical data offer the potential to advance patient care. Neonatal specialised care is a high-cost NHS service received by approximately 80,000 newborn infants each year.

Objectives

(1) To develop the use of routinely recorded operational clinical data from electronic patient records (EPRs), secure national coverage, evaluate and improve the quality of clinical data, and develop their use as a national resource to improve neonatal health care and outcomes. To test the hypotheses that (2) clinical and research data are of comparable quality, (3) routine NHS clinical assessment at the age of 2 years reliably identifies children with neurodevelopmental impairment and (4) trial-based economic evaluations of neonatal interventions can be reliably conducted using clinical data. (5) To test methods to link NHS data sets and (6) to evaluate parent views of personal data in research.

Design

Six inter-related workstreams; quarterly extractions of predefined data from neonatal EPRs; and approvals from the National Research Ethics Service, Health Research Authority Confidentiality Advisory Group, Caldicott Guardians and lead neonatal clinicians of participating NHS trusts.

Setting

NHS neonatal units.

Participants

Neonatal clinical teams; parents of babies admitted to NHS neonatal units.

Interventions

In workstream 3, we employed the Bayley-III scales to evaluate neurodevelopmental status and the Quantitative Checklist of Autism in Toddlers (Q-CHAT) to evaluate social communication skills. In workstream 6, we recruited parents with previous experience of a child in neonatal care to assist in the design of a questionnaire directed at the parents of infants admitted to neonatal units.

Data sources

Data were extracted from the EPR of admissions to NHS neonatal units.

Main outcome measures

We created a National Neonatal Research Database (NNRD) containing a defined extract from real-time, point-of-care, clinician-entered EPRs from all NHS neonatal units in England, Wales and Scotland (n = 200), established a UK Neonatal Collaborative of all NHS trusts providing neonatal specialised care, and created a new NHS information standard: the Neonatal Data Set (ISB 1595) (see http://webarchive.nationalarchives.gov.uk/±/http://www.isb.nhs.uk/documents/isb-1595/amd-32–2012/index_html; accessed 25 June 2018).

Results

We found low discordance between clinical (NNRD) and research data for most important infant and maternal characteristics, and higher prevalence of clinical outcomes. Compared with research assessments, NHS clinical assessment at the age of 2 years has lower sensitivity but higher specificity for identifying children with neurodevelopmental impairment. Completeness and quality are higher for clinical than for administrative NHS data; linkage is feasible and substantially enhances data quality and scope. The majority of hospital resource inputs for economic evaluations of neonatal interventions can be extracted reliably from the NNRD. In general, there is strong parent support for sharing routine clinical data for research purposes.

Limitations

We were only able to include data from all English neonatal units from 2012 onwards and conduct only limited cross validation of NNRD data directly against data in paper case notes. We were unable to conduct qualitative analyses of parent perspectives. We were also only able to assess the utility of trial-based economic evaluations of neonatal interventions using a single trial. We suggest that results should be validated against other trials.

Conclusions

We show that it is possible to obtain research-standard data from neonatal EPRs, and achieve complete population coverage, but we highlight the importance of implementing systematic examination of NHS data quality and completeness and testing methods to improve these measures. Currently available EPR data do not enable ascertainment of neurodevelopmental outcomes reliably in very preterm infants. Measures to maintain high quality and completeness of clinical and administrative data are important health service goals. As parent support for sharing clinical data for research is underpinned by strong altruistic motivation, improving wider public understanding of benefits may enhance informed decision-making.

Future work

We aim to implement a new paradigm for newborn health care in which continuous incremental improvement is achieved efficiently and cost-effectively by close integration of evidence generation with clinical care through the use of high-quality EPR data. In future work, we aim to automate completeness and quality checks and make recording processes more ‘user friendly’ and constructed in ways that minimise the likelihood of missing or erroneous entries. The development of criteria that provide assurance that data conform to prespecified completeness and quality criteria would be an important development. The benefits of EPR data might be extended by testing their use in large pragmatic clinical trials. It would also be of value to develop methods to quality assure EPR data including involving parents, and link the NNRD to other health, social care and educational data sets to facilitate the acquisition of lifelong outcomes across multiple domains.

Study registration

This study is registered as PROSPERO CRD42015017439 (workstream 1) and PROSPERO CRD42012002168 (workstream 3).

Funding

The National Institute for Health Research Programme Grants for Applied Research programme (£1,641,471). Unrestricted donations were supplied by Abbott Laboratories (Maidenhead, UK: £35,000), Nutricia Research Foundation (Schiphol, the Netherlands: £15,000), GE Healthcare (Amersham, UK: £1000). A grant to support the use of routinely collected, standardised, electronic clinical data for audit, management and multidisciplinary feedback in neonatal medicine was received from the Department of Health and Social Care (£135,494).

A systematic review of administrative and clinical databases of infants admitted to neonatal units

OBJECTIVES

High quality information, increasingly captured in clinical databases, is a useful resource for evaluating and improving newborn care. We conducted a systematic review to identify neonatal databases, and define their characteristics.

METHODS

We followed a preregistered protocol using MesH terms to search MEDLINE, EMBASE, CINAHL, Web of Science and OVID Maternity and Infant Care Databases for articles identifying patient level databases covering more than one neonatal unit. Full-text articles were reviewed and information extracted on geographical coverage, criteria for inclusion, data source, and maternal and infant characteristics.

RESULTS

We identified 82 databases from 2037 publications. Of the country-specific databases there were 39 regional and 39 national. Sixty databases restricted entries to neonatal unit admissions by birth characteristic or insurance cover; 22 had no restrictions. Data were captured specifically for 53 databases; 21 administrative sources; 8 clinical sources. Two clinical databases hold the largest range of data on patient characteristics, USA's Pediatrix BabySteps Clinical Data Warehouse and UK's National Neonatal Research Database.

CONCLUSIONS

A number of neonatal databases exist that have potential to contribute to evaluating neonatal care. The majority is created by entering data specifically for the database, duplicating information likely already captured in other administrative and clinical patient records. This repetitive data entry represents an unnecessary burden in an environment where electronic patient records are increasingly used. Standardisation of data items is necessary to facilitate linkage within and between countries.

Establishing consensus in the diagnosis of gestational diabetes following HAPO: where do we stand?

New proposals for the diagnosis of gestational diabetes (GDM), promulgated by the International Association of Diabetes and Pregnancy Study Groups (IADPSG), will substantially increase the number of women diagnosed with GDM. This will have an enormous impact on healthcare resources, diverting attention away from genuinely high risk diabetic pregnancies. Randomized trials in 'mild' GDM indicate that the main effects of treatment are a 2 %-3 % reduction in birth weight, fewer 'big babies', and less shoulder dystocia. However, these studies used different diagnostic criteria, and women diagnosed by the broader IADPSG criteria may not derive the same modest benefit. Modeling indicates a very high cost per QALY, unless later development of type 2 diabetes can be prevented. Far from producing consensus, the IADPSG suggestion has thrown sharply into focus the need to assess critically the risks, costs and benefits of adopting criteria that may pathologize a large number of otherwise normal pregnancies.