Different insulin types and regimens for pregnant women with pre-existing diabetes

O’Neill, Sinéad M; Kenny, Louise C.; Khashan, Ali S.; West, Helen; Smyth, Rebecca; Kearney, Patricia M.

doi:10.1002/14651858.cd011880.pub2

Cited by 25 publications

(12 citation statements)

References 72 publications

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“…Our findings support those of other studies that maternal adverse emotions, a common morbidity during pregnancy, can lead to poor birth outcomes 38 . Xiaoqiang, Q et al reported that psychological trauma or tension, stimulating the sympathetic adrenomedullin system and pituitary adrenocortical system, will cause a series of physiological changes and increase the risk of teratogenesis 39 .…”

Section: Discussionsupporting

confidence: 92%

A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

Liang

et al. 2020

Int. J. Med. Sci.

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Objective: Based on epidemiological field data, this study was to develop a prediction model which can be used as a preliminary screening tool to identify pregnant women who were at high risk of offspring congenital heart disease (CHD) in Nanchong City, and be beneficial in guiding prenatal management and prevention. Methods: A total of 367 children with CHD and 367 children without congenital malformations aged 0 to 14 years old were recruited from the Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital between March 2016 and November 2018. Using the SPSS 22.0 case-control matching module, the controls were matched to the cases at a rate of 1:1, according to the same gestational age of child (premature delivery or full-term), the maternal age of pregnancy (less than 1 year). 327 matched case-control pairs were analyzed by SPSS 22. Univariate and multivariate analysis were performed to find the important maternal influencing factors of offspring CHD. A logistic regression disease prediction model was constructed as the final predictors, and Hosmer-Lemeshow goodness of fit test and receiver operating characteristic (ROC) curve were used to evaluate the model. Results: 654 subjects (327 cases and 327 controls) were matched. The 25 variables were analysed. The logistic regression model established in this study was as follows: Logit(P)= -2.871+(0.686×respiratory infections)+(1.176×water pollution)+(1.019×adverse emotions during pregnancy) - (0.617×nutrition supplementation). The Hosmer-Lemeshow chi-square value was 7.208 (df = 6), with a nonsignificant p value of 0.302, which indicates that the model was well-fitted. The calibration plot showed good agreement between the bias-corrected prediction and the ideal reference line. Area under the ROC curve was 0.72 (95% CI: 0.681~0.759), which means that the predictive power of the model set fitted the data. Conclusion: In Nanchong city, more attention should be paid to mother who had a history of respiratory infections, exposure to polluted water, adverse emotions during pregnancy and nutritional deficiency. The risk model might be an effective tool for predicting of the risk of CHD in offspring by maternal experience during pregnancy, which can be used for clinical practise in Nanchong area.

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Section: Discussionsupporting

confidence: 92%

A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

Liang

et al. 2020

Int. J. Med. Sci.

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“…Insulin has been used safely in pregnancy for many years as it does not cross the placenta and the FDA has sufficient evidence to classify the risk of insulin use as “low” in pregnancy 37 . A Cochrane review reported limited evidence to support one type of insulin regimen over another 38 however there is growing evidence that insulin analogues are likely to be a safe alternative to human insulin in pregnancy 37 . Although considered safe to use in pregnancy, insulin also has significant disadvantages as it can cause maternal hypoglycaemia, increase weight gain and requires education in administration and the inconvenience of multiple injections 39 .…”

Section: Short‐ and Long‐term Impact Of Treatment Of Gdm On Fetal Devmentioning

confidence: 99%

Short‐ and long‐term outcomes of gestational diabetes and its treatment on fetal development

Murray

Reynolds

2020

Prenatal Diagnosis

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Globally the prevalence of gestational diabetes mellitus (GDM) is rising mainly due to the increase in maternal obesity. A number of different methods to screen for and diagnose GDM have been described although consensus on the preferred methods does not yet exist. GDM has significant short‐ and long‐term health risks for the mother, developing fetus and the children born to mothers with GDM. Short‐term risks for the fetus include macrosomia (excessive birthweight), shoulder dystocia, birth trauma, and hypoglycaemia in the immediate postpartum period. Long‐term risks for offspring born to mothers with GDM include increased rates of childhood and adulthood obesity and an increased cardiometabolic risk. A number of pharmacological treatments for GDM have been identified, these include insulin and oral glucose‐lowering drugs metformin and glibenclamide. Whilst these oral glucose‐lowering drugs show similar short‐term childhood outcomes to insulin there is increasing evidence that these drugs may have adverse long‐term outcomes on children and adults exposed to the drugs in utero. Future research on treatments for GDM should include long‐term follow‐ up of children exposed to glucose lowering medication in utero to determine the long‐term cardiometabolic risk in the offspring born to mothers with GDM.

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“…Both multiple daily insulin injections and continuous subcutaneous insulin infusion are reasonable delivery strategies, and neither has been shown to be superior during pregnancy (59). A recent Cochrane systematic review was not able to recommend any specific insulin regimen over another for the treatment of diabetes in pregnancy (67). has concluded that this approach would reduce morbidity, save lives, and lower health care costs (70).…”

Section: Insulinmentioning

confidence: 99%

14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes—2019

2018

Diabetes Care

235

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The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

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Different insulin types and regimens for pregnant women with pre-existing diabetes

Abstract: Different insulin types and regimens for pregnant women with pre-existing diabetes.

Cited by 25 publications

References 72 publications

A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

A predictive model of offspring congenital heart disease based on maternal risk factors during pregnancy: a hospital based case-control study in Nanchong City

Short‐ and long‐term outcomes of gestational diabetes and its treatment on fetal development

14. Management of Diabetes in Pregnancy: Standards of Medical Care in Diabetes—2019

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