Elevated FPG, not post-load glucose, raises risk for large for gestational age outcomes


Elevated fasting plasma glucose, but not post-load glucose, is associated with increased risk for large for gestational age infants, according to study findings published in Diabetic Medicine.

In a retrospective cohort study of women who had a singleton pregnancy in the province of Alberta, Canada, and oral glucose tolerance test data available from October 2008 to December 2018, large for gestational age rates increased as FPG, 1-hour glucose and 2-hour glucose levels increased. However, only FPG was significantly associated with an increased risk for large for gestational age outcomes, with no increased risk observed for women with only elevated post-load glucose.

Elevated fasting plasma glucose raises risk for large for gestational age infants.
More than 20% of mothers with an FPG between 5.6 and 5.8 mmol/L had large for gestational age infants. Data were derived from Kaul P, et al. Diabet Med. 2022;doi:10.1111/dme.14786.

“Among pregnancies with elevated 1-hour and 2-hour post-load glucose levels, large for gestational age rates differed markedly between pregnancies with and without FPG elevations,” Padma Kaul, PhD, professor of medicine and co-director of the Canadian VIGOUR Centre at the University of Alberta in Edmonton, Canada, and colleagues wrote. “Despite higher rates of pharmaceutical intervention, often introduced when diet and exercise therapy are insufficient, large for gestational age rates in pregnancies with elevated FPG were much higher than those among pregnancies with only post-load glucose elevations.”

Researchers collected data from 84,534 pregnant women (mean age, 31.7 years) with a singleton pregnancy who underwent an OGTT. The cohort was grouped into seven categories based on their level of FPG, 1-hour post-load glucose and 2-hour post-load glucose. The categories for each glucose type were the same as those observed in the Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) study, which examined associations between increasing maternal glucose and adverse pregnancy outcomes. Study data were compared with findings from HAPO.

Large for gestational age risk climbs with glucose

The study cohort had similar FPG levels to the HAPO cohort, but 1-hour post-load glucose (8.8 mmol/L vs. 7.4 mmol/L) and 2-hour post-load glucose (7.4 mmol/L vs. 6.2 mmol/L) were higher than in HAPO.

The rate of large for gestational age increased from 7.6% for women with FPG of less than 4.2 mmol/L to 21.4% for those with an FPG of 5.6 mmol/L to 5.8 mmol/L. Large for gestation age rates increased from 5.7% with a 1-hour glucose level of 5.5 mmol/L or less to 12.5% for with a 1-hour post-load glucose of 11.8 mmol/L or higher. Large for gestational age rates climbed from 7.5% with a 2-hour post-load glucose of 5 mmol/L or less to 9.2% with 2-hour post-load glucose between 9.9 mmol/L and 11.1 mmol/L. All three measures showed a trend of increasing large for gestational age rates with increasing glycemia (P < .01 for all).

FPG predicts large for gestational age

Large for gestational age rates were higher among women with elevated FPG than women who only had elevated post-load glucose. Women with elevated FPG, 1-hour post-load glucose and 2-hour post-load glucose were most likely to have large for gestational age babies (adjusted OR = 2.41; 95% CI, 2.18-2.66) compared with those with normal glucose levels. Researchers wrote that the increased risk was primarily due to elevated FPG. Women who had only elevated post-load glucose had a lower risk for large for gestational age outcomes (aOR = 0.81; 95% CI, 0.77-0.86) than those with normal glucose.

The researchers said there are several possible reasons why FPG more strongly predicts large for gestational age outcomes, all of which should be investigated in future studies.

“First, FPG elevation may be a marker of more severe disease, which requires early identification and treatment,” the researchers wrote. “Second, FPG may be less amenable to treatment. Prospective studies are needed to examine whether more aggressive treatment to lower glucose thresholds would impact large for gestational age rates in pregnancies with elevated FPG. Third, maternal obesity may be an unmeasured confounder of the association between FPG and large for gestational age, and thus not amenable to change by treatment. And lastly, it may be that, along the diabetes spectrum, FPG identifies a different type of diabetes in pregnancy.”

The dangers of being born too small or too soon.


Birth is dangerous, especially for infants born too small or too soon. Although much is known about the mortality risk for such infants in high-income countries, little is known about the risk in poorer countries. In The Lancet, Joanne Katz and colleagues begin to fill in the gap on just how dangerous it is to be born too small or too soon in a low-income or middle-income country.1 The investigators analysed more than 2 million birth outcomes from resource-poor countries in Asia, Africa, and Latin America and calculated the regional risk of neonatal and post-neonatal mortality associated with being born preterm, small-for-gestational age (SGA), or both.

Using data from 20 cohorts in 13 countries, Katz and colleagues show that being born SGA increased the risk of neonatal mortality by two to five times across the three regions, but being born preterm (<37 completed weeks of gestation) raised the risk by six to 26 times. When children were born both SGA and preterm, neonatal mortality was ten to 39 times higher than in otherwise normal neonates. These findings provide the first solid estimates of the excess risk of dying for infants in these categories of births for countries where 135 million babies are born every year.

Katz and colleagues’ findings advance our knowledge by going beyond the use of low birthweight (<2500 g) as a means of identifying infants in danger. The low birthweight category includes both premature and growth-restricted infants. It excludes newborn babies heavier than 2500 g who might also be premature or have restricted growth and therefore still have an increased risk of dying. As a result of these findings, the sources of neonatal mortality are now better known in the regions studied and appropriate interventions to prevent early deaths can be developed.

Katz and colleagues are also the first to document the high proportion of Asian and African newborn babies (21% and 16%, respectively) who are SGA (defined as the lowest tenth percentile of the growth reference) but neither preterm nor low birthweight. In view of the surprisingly high proportion of such infants, it is disappointing that the authors did not provide the associated mortality risk. Term-SGA infants had about three times higher risk of death (across all regions) during the early and late neonatal as well as the postneonatal periods, but these included a high proportion of low-birthweight (LBW) infants. The investigators state that the large group of infants who are SGA but not preterm or LBW have a higher mortality risk than term, appropriate weight-for-gestational-age infants, but we are left to wonder: how much higher?

The high prevalence of term SGA births and their excess risk of death throughout infancy suggest that there is more to know about these babies than just their weight-for-gestational age. They could also be shorter, as documented in Guatemala,2where linear growth failure was detectable as early as 15 weeks of gestation, and infants tend to be born “short and round”.3 Infants of HIV-infected mothers on antiretroviral therapy in Haiti and Zambia were also born small, largely because of shortness at birth rather than thinness.45 There has been much discussion about the causes and consequences of proportional (ie, short and round) versus disproportional (long and thin) phenotypes of SGA babies, with some evidence that thin SGA babies are at higher risk of adverse outcomes.67 Elucidation of the differences in mortality risk among types of SGA infants will require datasets that include infant length at birth, but such data are rare.

Katz and colleagues’ findings present important methodological challenges. The investigators included cohorts on the basis of completeness and quality of their data. Nonetheless, in six of the cohorts, they imputed some birthweights because some data were missing or measured too late. Some of the variability in birthweight might have resulted from the 72 h observation window used (during which breastfed neonates can lose up to 10% of their weight8). Unfortunately, the preferred reference dataset for calculating birthweight-for-gestational age (the Alexander reference9) provides data at only the tenth percentile, so the authors used a different reference dataset to identify infants below the third percentile.10 Both references are from large US populations, with data obtained in 1972—76 and 1991, respectively. The appropriateness of these reference populations, especially for the cohorts from South Asia, is unknown and might be among the factors that account for the high proportions of SGA births seen. Again, not knowing the excess mortality associated with the SGA babies who were term and not LBW, we wonder whether the use of the tenth percentile of the Alexander reference put too many babies in this risk category.

The analysis presented by Katz and colleagues is a substantial contribution, and points the way to further advances. Most of the cohort studies included were not representative of the country where they were done, and the studies included in a given region were also not representative of that region—eg, the vast majority of data from Latin America was from Chile. More representative data are surely needed. Also, many low-income or middle-income countries are in eastern Europe and central Asia, regions not represented in these analyses. The scarcity of data from these regions, however, is because of a dearth of global resources and attention rather than a product of poor study design. We hope that this important study can serve as a catalyst for the development of stronger datasets that require fewer assumptions and include additional essential information, including length at birth.

Source: Lancet

 

Human Brains Outpace Chimp Brains in Womb.


Humans‘ superior brain size in comparison to their chimpanzee cousins traces all the way back to the womb. That’s according to a study reported in the September 25 issue of Current Biology, a Cell Press publication, that is the first to track and compare brain growth in chimpanzee and human fetuses.

“Nobody knew how early these differences between human and chimp brains emerged,” said Satoshi Hirata of Kyoto University.

Hirata and colleagues Tomoko Sakai and Hideko Takeshita now find that human and chimp brains begin to show remarkable differences very early in life. In both primate species, the brain grows increasingly fast in the womb initially. After 22 weeks of gestation, brain growth in chimpanzees starts to level off, while that of humans continues to accelerate for another two months or more. (Human gestation time is only slightly longer than that of chimpanzees, 38 weeks versus 33 or 34 weeks.)

The findings are based on 3D ultrasound imaging of two pregnant chimpanzees from approximately 14 to 34 weeks of gestation and comparison of those fetal images to those of human fetuses. While early brain differences were suspected, no one had previously measured the volume of chimpanzee brains as they develop in the womb until now.

The findings are part of a larger effort by the research team to explore differences in primate brains. In another Current Biology report published last year, they compared brain development in chimps versus humans via magnetic resonance imaging (MRI) scans of three growing chimpanzees from the age of six months to six years.

“Elucidating these differences in the developmental patterns of brain structure between humans and great apes will provide important clues to understand the remarkable enlargement of the modern human brain and humans’ sophisticated behavior,” Sakai said.

The researchers say they now hope to explore fetal development in particular parts of the brain, including the forebrain, which is critical for decision making, self-awareness, and creativity.

Source: http://www.sciencedaily.com

Neonatal Mortality Risk Associated with Preterm Birth in East Africa, Adjusted by Weight for Gestational Age: Individual Participant Level Meta-Analysis.


Low birth weight and prematurity are amongst the strongest predictors of neonatal death. However, the extent to which they act independently is poorly understood. Our objective was to estimate the neonatal mortality risk associated with preterm birth when stratified by weight for gestational age in the high mortality setting of East Africa.

Methods and Findings

Members and collaborators of the Malaria and the MARCH Centers, at the London School of Hygiene & Tropical Medicine, were contacted and protocols reviewed for East African studies that measured (1) birth weight, (2) gestational age at birth using antenatal ultrasound or neonatal assessment, and (3) neonatal mortality. Ten datasets were identified and four met the inclusion criteria. The four datasets (from Uganda, Kenya, and two from Tanzania) contained 5,727 births recorded between 1999–2010. 4,843 births had complete outcome data and were included in an individual participant level meta-analysis. 99% of 445 low birth weight (<2,500 g) babies were either preterm (<37 weeks gestation) or small for gestational age (below tenth percentile of weight for gestational age). 52% of 87 neonatal deaths occurred in preterm or small for gestational age babies. Babies born <34 weeks gestation had the highest odds of death compared to term babies (odds ratio [OR] 58.7 [95% CI 28.4–121.4]), with little difference when stratified by weight for gestational age. Babies born 34–36 weeks gestation with appropriate weight for gestational age had just three times the likelihood of neonatal death compared to babies born term, (OR 3.2 [95% CI 1.0–10.7]), but the likelihood for babies born 34–36 weeks who were also small for gestational age was 20 times higher (OR 19.8 [95% CI 8.3–47.4]). Only 1% of babies were born moderately premature and small for gestational age, but this group suffered 8% of deaths. Individual level data on newborns are scarce in East Africa; potential biases arising due to the non-systematic selection of the individual studies, or due to the methods applied for estimating gestational age, are discussed.

Conclusions

Moderately preterm babies who are also small for gestational age experience a considerably increased likelihood of neonatal death in East Africa.

Source: PLOS