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      Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study : Associations of maternal A1C and glucose with pregnancy outcomes

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          Abstract

          OBJECTIVE

          To compare associations of maternal glucose and A1C with adverse outcomes in the multinational Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and determine, based on those comparisons, if A1C measurement can provide an alternative to an oral glucose tolerance test (OGTT) in pregnant women.

          RESEARCH DESIGN AND METHODS

          Eligible pregnant women underwent a 75-g OGTT at 24–32 weeks’ gestation. A sample for A1C was also collected. Neonatal anthropometrics and cord serum C-peptide were measured. Associations with outcomes were assessed using multiple logistic regression with adjustment for potential confounders.

          RESULTS

          Among 23,316 HAPO Study participants with glucose levels blinded to caregivers, 21,064 had a nonvariant A1C result. The mean ± SD A1C was 4.79 ± 0.40%. Associations were significantly stronger with glucose measures than with A1C for birth weight, sum of skinfolds, and percent body fat >90th percentile and for fasting and 1-h glucose for cord C-peptide (all P < 0.01). For example, in fully adjusted models, odds ratios (ORs) for birth weight >90th percentile for each measure higher by 1 SD were 1.39, 1.45, and 1.38, respectively, for fasting, 1-, and 2-h plasma glucose and 1.15 for A1C. ORs for cord C-peptide >90th percentile were 1.56, 1.45, and 1.35 for glucose, respectively, and 1.32 for A1C. ORs were similar for glucose and A1C for primary cesarean section, preeclampsia, and preterm delivery.

          CONCLUSIONS

          On the basis of associations with adverse outcomes, these findings suggest that A1C measurement is not a useful alternative to an OGTT in pregnant women.

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          Most cited references12

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          The classification and diagnosis of the hypertensive disorders of pregnancy: statement from the International Society for the Study of Hypertension in Pregnancy (ISSHP).

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            Anthropometric estimation of neonatal body composition.

            (1995)
            Estimation of neonatal body composition can be useful in the understanding of fetal growth. However, body composition methods such as total body water and total body electric conductivity are expensive and not readily available. Our primary purpose was to develop an anthropometric model to estimate neonatal body composition and prospectively validate the model against total body electric conductivity and secondarily to compare our anthropometric model and a previously published anthropometric formula with total body electric conductivity. A total of 194 neonates had estimates of body composition according to total body electric conductivity (group 1). Parental morphometrics, gestational age, race, sex, parity, and neonatal measurements including birth weight, length, head circumference, and skinfolds (triceps, subscapular, flank, and thigh) were correlated with body fat by use of stepwise regression analysis. The model was validated in a second group of 65 neonates (group 2). There were no significant differences in any of the parental or neonatal measurements between groups 1 and 2. In group 1, 78% of the variance in body fat with the use of total body electric conductivity was explained by birth weight, length, and flank skinfold (R2 = 0.78, p = 0.0001). When prospectively validated by the subjects in group 2, the model had significant and stronger correlation (R2 = 0.84, p = 0.0001) with body fat estimated by total body electric conductivity as compared with the other anthropometric model (R2 = 0.54, p = 0.0001). There was no significant (p = 0.11) difference between our anthropometric estimate of body fat and total body electric conductivity. The anthropometric model developed can be used to reasonably predict neonatal body fat mass at birth.
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              Diagnosing gestational diabetes

              E. Ryan (2011)
              The newly proposed criteria for diagnosing gestational diabetes will result in a gestational diabetes prevalence of 17.8%, doubling the numbers of pregnant women currently diagnosed. These new diagnostic criteria are based primarily on the levels of glucose associated with a 1.75-fold increased risk of giving birth to large-for-gestational age infants (LGA) in the Hyperglycemia Adverse Pregnancy Outcome (HAPO) study; they use a single OGTT. Thus, of 23,316 pregnancies, gestational diabetes would be diagnosed in 4,150 women rather than in 2,448 women if a twofold increased risk of LGA were used. It should be recognised that the majority of women with LGA have normal glucose levels during pregnancy by these proposed criteria and that maternal obesity is a stronger predictor of LGA. The expected benefit of a diagnosis of gestational diabetes in these 1,702 additional women would be the prevention of 140 cases of LGA, 21 cases of shoulder dystocia and 16 cases of birth injury. The reproducibility of an OGTT for diagnosing mild hyperglycaemia is poor. Given that (1) glucose is a weak predictor of LGA, (2) treating these extra numbers has a modest outcome benefit and (3) the diagnosis may be based on a single raised OGTT value, further debate should occur before resources are allocated to implementing this change. Electronic supplementary material The online version of this article (doi:10.1007/s00125-010-2005-4) contains supplementary material, which is available to authorised users.
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                Author and article information

                Journal
                Diabetes Care
                diacare
                dcare
                Diabetes Care
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                March 2012
                10 February 2012
                : 35
                : 3
                : 574-580
                Affiliations
                [1] 1Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
                [2] 2Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
                [3] 3Department of Endocrinology, John Hunter Hospital, Newcastle, Australia
                [4] 4Regional Centre for Endocrinology and Diabetes, Royal Victoria Hospital Belfast, Belfast, Northern Ireland, U.K.
                [5] 5Department of Haematology, Queen’s University Belfast, Belfast, Northern Ireland, U.K.
                [6] 6Department of Clinical Biochemistry, Queen’s University Belfast, Belfast, Northern Ireland, U.K.
                [7] 7Division of Maternal Fetal Medicine, Warren Alpert Medical School, Brown University, Women & Infants Hospital of Rhode Island, Providence, Rhode Island
                [8] 8Department of Obstetrics and Gynecology, Helen Schneider Hospital for Women, Rabin Medical Center–Sackler Faculty of Medicine, Tel-Aviv University, Petah-Tiqva, Israel
                [9] 9Department of Obstetric Medicine, Mater Misericordiae Mothers’ Hospital–University of Queensland, Brisbane, Australia
                [10] 10Department of Pediatrics, Karolinska Institute, Stockholm, Sweden
                Author notes
                Corresponding author: Lynn P. Lowe, lplowe@ 123456northwestern.edu .
                Article
                1687
                10.2337/dc11-1687
                3322718
                22301123
                31d3bc55-e330-4a58-9410-7e3e57d95209
                © 2012 by the American Diabetes Association.

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

                History
                : 31 August 2011
                : 4 December 2011
                Categories
                Original Research
                Epidemiology/Health Services Research

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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