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Record W4383058427 · doi:10.1097/jcma.0000000000000954

Diabetes mellitus in pregnancy increases the risk of birth defects of newborns

2023· article· en· W4383058427 on OpenAlexaboutno aff
Wen-Ling Lee, Fa‐Kung Lee, Peng‐Hui Wang

Bibliographic record

VenueJournal of the Chinese Medical Association · 2023
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersTaipei Veterans General Hospital
KeywordsMedicinePregnancyGestational diabetesObstetricsDiabetes mellitusAnxietyType 2 Diabetes MellitusReproductive healthGestationPopulationPsychiatryEndocrinologyEnvironmental health

Abstract

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Gestational diabetes mellitus (GDM) and overt diabetes mellitus (DM), including type I DM (T1DM) and type 2 DM (T2DM), belonging to one type of metabolic syndromes/diseases are complex but common diseases, with a continuously and rapidly growing prevalence worldwide, involving not only in general health of women themselves but also in association with worse outcomes of their offsprings.1–6 Despite much understanding of the pathophysiology of DM or GDM, availability of significantly effective and powerful screening tests, and awareness of modified health behaviors and continuously far-advanced development of antidiabetes agents (ADAs), management of women with DM or GDM during reproductive age is still a biggest challenge in modern obstetrics, partly because many women are unaware of their DM status until their first antenatal medical examination and partly because fewer than one-third of reproductive-aged women have been successfully or actively receive adequate and appropriate preconception care.2,3,5 Preconception counseling is highly recommended by the obstetric experts and academic societies to avoid unintended pregnancy with abnormal glucose levels (particular abnormal glycosylated hemoglobin [hemoglobin A1c, HbA1c] levels), based on the facts observing the high possibility of severe damage of early embryonic development and significant increase of hazards to fetus and pregnancy outcomes secondary to hyperglycemia during pregnancy.5 All of them not only result in national and financial embarrassment but also influence the willingness and anxiety about the next pregnancy in reproductive-age women.6 The recent publication in the June issue of the Journal of the Chinese Medical Association entitled “Maternal diabetes mellitus and birth defects in Taiwan: A 5-year nationwide population-based cohort study” attempted to investigate the association between maternal DM and GDM and the risk of birth defects (BDs) in Taiwan, since BDs are the main causes of morbidity and mortality of fetus and newborns.7 The authors conducted a 5-year nationwide population-based cohort study, including 24 204 newborns with BDs, and 854 519 newborns without BDs to compare their maternal background, which focused on the presence and absence of DM and GDM.7 Additionally, time course of T2DM was also included for analysis to evaluate the association between the duration of T2DM and the risk of BDs.7 The authors found that T2DM mothers had a high risk of cardiovascular system-related BDs compared to non-DM mothers with adjusted odd ratio (aOR) of 1.30 (T2DM for < 2 years), 1.39 (T2DM for 2–5 years), and 1.62 (T2DM for > 5 years), respectively compared to non-DM mothers.7 Additionally, musculoskeletal system-related BDs are also increased in T2DM mothers with aOR of 1.44 (T2DM for < 2 years), and 1.54 (T2DM for 2–5 years), respectively.7 Moreover, in term of eyes-, ears-, face-, and neck (skull and neck)-related BDs, T2DM mothers increased at lease 1.9-fold risks with aOR of 1.90 (T2DM for 2–5 years), and 2.59 (T2DM for > 5 years), respectively.7 For T1DM mothers, they have a particularly higher risk of delivering skull- and neck-related BDs and respiratory system-related BDs newborns with aOR of 8.70 and 3.35, respectively, than non-DM mothers.7 For GDM mothers, it is interesting to find that GDM mothers may have a higher risk of delivery of genitourinary system-related BDs newborns (aOR of 1.08) and musculoskeletal system-related BDs newborns (aOR of 1.12), respectively, than non-DM mothers.7 The current article is interesting and worthy of further discussion. The present study evaluating the pregnant women between 2010 and 2014 showed the incidence of T2DM pregnant women is significantly higher than T1DM pregnant women, with an estimated incidence of 2.23% (19 590/878 723) in T2DM mothers and 0.04% (367/878 723) in T1DM mothers, respectively, contributing to the incidence of preexisting DM in pregnancy at least as 2.27% (19 957/878 723) supporting the fact that the DM incidence in reproductive-age women have been dramatically increased in recent years, since the previous report from Chen’s study between 2005 and 2014 showed the incidence of preexisting DM in pregnancy was only 1.1%.8 Since no prospective national population-based data in Taiwan are available regarding women with pregestational DM identified before pregnancy, it is hard to explain the incidence of preexisting DM in pregnancy is at least 2-fold increase in the recent 5 years (between 2010 and 2014) compared to that in the early 5 years (between 2005 and 2009). Knowledge of the true prevalence or incidence may depend on the inclusion of women with early pregnancy losses, which are not available in birth certificate or hospital discharge data.6 Although the authors using the National Birth Defects Surveillance Program (NBDSP) data to identify all births, including live and stillbirths conducted the present cohort study, the authors excluded the stillbirth, unknown status of offspring and missing data, and incidence or prevalence of preexisting DM in pregnancy may be underestimated, contributing to the high possibility of underestimated risk of BDs in pregnant women with DM. Kitzmiller et al have suggested that population-based data are needed to track conception, miscarriage, major malformations, and livebirth and stillbirth frequencies among women with preexisting DM.6 By contrast, compared to the data from the western countries (Canada as an example), the incidence or prevalence of preexisting DM in pregnant women in domestic data of the present study seemed to be unexpectedly higher than the average ranging from 0.46% to 1.51% in the population-based study in Canada between 1996 and 2013 and reach the similar incidence in the United States.6 Furthermore, increasing maternal age at conception is likely to further increase the risk of poor pregnancy outcomes.6 As shown in the present study, the pregnant women with DM were older than the mothers without DM (32.1 ± 5.6 [T1DM] and 32.9 ± 5.0 [T2DM] vs 31.1 ± 5.1 [non-DM] using the presentation by mean ± standard deviation of maternal age,7 suggesting that elder mothers have a higher risk of diagnosed DM. The US National studies between 1993 and 2010 supported that the incidence of DM in pregnancy is proportionally increased with an increasing age from 0.41 in age between 15 and 19 years to 2.14 in age between 40 and 44 years in 2010.6 However, the present study did not show the incidence of DM in different-age pregnant women. By contrast, the present study only showed the maternal age may be related to worse perinatal outcomes indirectly since the authors found that the maternal age has a significantly negative impact on the newborns based on its association with an increased risk of BDs.7 Maternal age in the present study, as expected, contributes to the key and determinate independent risk factors for BDs, regardless whether pregnant women had or did not have a diagnosed DM with aOR of 1.072 (age between 30 and 44 years) and 1.753 (age ≥ 45 years).7 The association between maternal age and the risk of BDs is more stronger than DM and the risk BDs (aOR of 1.748 in T1DM, 1.175 in T2DM for < 2 years, 1.331 in T2DM for 2–5 years, and 1.391 T2DM for >5 years, respectively).7 Therefore, the real impact of DM on the risk of BDs needs further validation, particularly the risk estimation should be corrected by age factor. Moreover, elder mothers (≥34 years of age) in Taiwan are often suggested to undergo the amniocentesis procedure to exclude the chromosomal abnormalities,9–11 and the high-resolution ultrasound and Down’s screening test (noninvasive prenatal testing) are also popular in Taiwan, regardless whether maternal age was ≥34 or <34 years. Additionally, although the present data did not mention who could be enrolled into the NBDSP, based on our limited knowledge, the data of live and stillbirths in the NBDSP are limited to ≥24 gestational-week fetus. According to the aforementioned background, it is not surprising to find that chromosomal abnormalities did not increase in pregnant women with diagnosed DM compared to non-DM pregnant mothers.7 All suggest the present study may be at potential risk of underestimating or overestimating their data because they are frequently noted in the literature review.12–15 In fact, we supposed the possibility of underestimating the risk of BDs will occur in elder mothers and by contrast, overestimating the risk of BDs may occur in younger pregnant women. It is well established that major congenital malformations are associated with poor glycemic control of T1DM and T2DM.6 The authors also mentioned the aforementioned limitation, since they did not provide the first trimester HbA1c in the present study.7 It is believed that first trimester HbA1c levels >7.0% are associated with increased risks of BDs, but the association between the risk of BDs and first trimester HbA1c levels <7.0% is still worthy of further investigation. Fortunately, the authors provided the association between the risk of BDs and GDM in pregnant women, who are often believed to have HbA1c levels <7.0%. However, as shown in the present study, GDM pregnant women seemed to have a certain degree association between certain organs-related BDs, including genitourinary system-related and musculoskeletal system-related BDs newborns (aOR of 1.12), respectively.7 That is why we concern about the association between BDs and DM pregnant women since without the aforementioned data, it is hard to establish the risk of BDs in DM mothers. Additionally, the hyperglycemia-related teratogenic effects may be confounded by obesity, smoking, alcohol use, and/or unhealthy styles, such as deficiency of essential minerals, or adequate nutrition support,6 and all of the above are frequently found in DM mothers. Unfortunately, the present study also failed to provide these essential data. The authors have tried their best to present that T2DM mothers have increased to deliver the BD infants than non-DM mothers, particularly showing the malformation of cardiovascular, musculoskeletal and eyes, ears, face, and neck systems or organs are dramatically increased.7 Although some discrepancies are present to describe the most frequently involved organs in the different studies, there is no doubt that the most common major congenital malformations are in the cardiovascular system.7 For the adequate stabilization of blood sugar before and during pregnancy, an urgent consultation and antenatal care is of critical importance. However, it is still controversial whether the use of ADAs common among reproductive-age women with DM contributes to the risk of malformations, although evidence has shown insulin and ADAs may not appear to do so.6 Unfortunately, the authors also failed to provide these confounders in their present study. Taken together, although there are many uncertainties about the real correlation between DM pregnant women and BDs of their offspring, we should applaud that the authors have followed the general principle,6 such as nonchromosomal, nonsyndromic major malformations (single or multiple in the same infant) that cause death or seriously affect the health of the child to define major congenital malformations (BDs) in their study. We believe that much understanding and awareness of DM-related negative impact on pregnancy outcomes is needed not only in health providers but also in women during the reproductive age. To clarify the relationship between DM and BDs, there is a long way to go. We are looking forward to seeing more and more studies focusing on this challenge issue. ACKNOWLEDGMENTS This article was supported by grants from the Taiwan Ministry of Science and Technology, Executive Yuan, Taiwan (MOST 110-2314-B-075-016-MY3 and MOST 111-2314-B-075-045), and Taipei Veterans General Hospital (V112C-154 and V112D64-001-MY2-1). The authors appreciate the support from Female Cancer Foundation, Taipei, Taiwan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.272
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
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