Does the number of abnormal values in the oral glucose tolerance test impact pregnancy outcomes?

doi:10.21203/rs.3.rs-4927003/v1

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Research Article

Does the number of abnormal values in the oral glucose tolerance test impact pregnancy outcomes?

https://doi.org/10.21203/rs.3.rs-4927003/v1

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Background:

Gestational diabetes mellitus (GDM) affects over 10% of pregnancies worldwide, leading to various maternal and neonatal complications. The American College of Obstetricians and Gynecologists (ACOG) recommends a two-step diagnostic approach using the Glucose Challenge Test (GCT) and the oral glucose tolerance test (OGTT), which can yield between 0 to 4 abnormal values (AbVs).The primary objective of this study was to evaluate the association between the number of AbVs in the oral glucose tolerance test (OGTT) and the risk of GDMA2, which requires pharmacological intervention for glycemic control. Secondary outcomes included assessing the relationship between the number of AbVs and adverse maternal and neonatal outcomes, considering its impact on the course of pregnancy, delivery, maternal health, and neonatal outcomes.

Methods

This retrospective cohort study included all pregnant women who underwent OGTT between the years 2015 and 2022, and diagnosed with GDM, at our department. The study cohort was divided into four groups based on the number of AbVs in the OGTT: one AbV, two AbVs, three AbVs and four AbVs group. Maternal characteristics and pregnancy outcomes were compared between these groups.

Results

A total of 1821 women diagnosed with GDM following were included in the analysis. The distribution of abnormal OGTT AbVs was as follows: one AbV (36.95%), two AbVs (43.71%), three AbVs (16.09%), and four AbVs (3.24%). Presence of GDMA2 varied significantly among groups (p < 0.001), with higher occurrence correlating with increased AbVs. Maternal outcomes differed in induction of labor (p < 0.001), episiotomy (p = 0.006), and maternal composite outcomes (p = 0.011). Neonatal outcomes showed differences in gestational age at delivery (p = 0.007) and Apgar score < 7 (p = 0.021). Logistic regression adjusted for confounders revealed that the number of AbVs (aOR 1.2, 95% CI 1.01–1.42) and maternal BMI (aOR 1.07, 95% CI 1.05–1.1) were significantly associated with GDMA2.

Conclusions

An elevated number AbVs indicates challenges in glycemic control through dietary measures alone, necessitating potential medical interventions. An increased occurrence of AbVs in OGTT correlates with heightened probabilities of GDMA2, labor induction, episiotomy, and neonatal Apgar scores below 7. From the study results we can infer that OGTT serves not only as a diagnostic tool for GDM but also enables healthcare practitioners to enhance their awareness of potential adverse outcomes for both the mother and neonate through meticulous analysis of abnormal values.

Gestetional Diabetes

Oral glucose challange test

Gestational diabetes mellitus (GDM) is a prevalent complication affecting over 10% of pregnancies worldwide, presenting significant challenges for patient management and impacting pregnancy, delivery, maternal health, and neonatal outcomes [1–5]. Adverse short-term neonatal outcomes linked to GDM include polyhydramnios, macrosomia, neonatal hypoglycemia, shoulder dystocia, and intra-uterine fetal death, alongside long-term health implications such as metabolic syndrome and behavioral disorders [2, 6–8]. Maternal health is also affected, with associations observed between GDM and preeclampsia, operative vaginal delivery, cesarean section, perineal injuries, and future health complications like diabetes mellitus and cardiovascular impairments [7, 9–11].

While the diagnosis of GDM can be performed in many forms [6], The American College of Obstetricians and Gynecologists (ACOG) recommends the two-step approach as the preferred method for diagnosing GDM, comprising the Glucose Challenge Test (GCT) followed by the oral glucose tolerance test (OGTT) [12–13]. This test is usually performed at 24 to 28 weeks of gestational and is composed of the GCT as the first step, with an oral load of 50-gram glucose, and measurements of glucose serum levels after one hour. Parturitions who scored ≥140 mg/dL are then referred to the second step which is the OGTT with an oral load of 100-gram glucose. The OGTT score is composed of 4 measurements of blood glucose levels: fasting (cut-off ≥ 95), one hour after drinking 100 gr, glucose (cut-off ≥ 180), 2 hours (cut-off ≥ 155), and 3 hours (cut-off ≥ 140) [14]. Results may vary from one abnormal value (AbV) and up to four AbVs.

Given the significance of strict glucose control in reducing maternal and neonatal complications [15–16], understanding the implications of various OGTT results is essential for clinicians. This study aimed to investigate the relationship between the number of AbVs in OGTT and adverse maternal and neonatal outcomes in women diagnosed with GDM.

This retrospective cohort study, conducted at a tertiary university-affiliated hospital, aimed to investigate the relationship between the number of abnormal values (AbVs) in OGTT and maternal and neonatal outcomes in pregnant women diagnosed with GDM. GDM was diagnosed by using the ACOG’s two step approach, as previously discussed [14]. Women initially started glycemic control through diet and lifestyle changes. Those who had more than 20% abnormal glucose values during daily monitoring over approximately two weeks were transitioned to pharmacological treatment.

Data were collected from pregnant women who underwent OGTT between 2015 and 2022 and gave birth at the hospital's department. The study was approved by the local Review Board (MMC-0244-22), with patient informed consent waived due to the retrospective nature of data collection. Demographic and medical information was extracted from electronic medical records.

Data Collection:

All pregnant women diagnosed with GDM who were admitted to the department and underwent a 100g OGTT were identified and included in the study. Maternal demographics, obstetric history, pregnancy surveillance, labor and delivery information, and short term maternal and neonatal outcomes were all retrieved from each woman’s electronic medical records.

Women were stratified into one of 4 groups according to the number of abnormal values in OGTT: 1 AbVs, 2 AbVs, 3 AbVs, or 4 AbVs.

Outcomes:

The primary outcome was the rates of GDMA2 based on the classification of GDM, with GDMA1 manageable through diet alone and GDMA2 requiring medical intervention. Secondary outcomes included maternal composite outcomes (induction of labor, episiotomy, emergency cesarean section, vacuum-assisted delivery, and obstetric anal sphincter injuries) and fetal composite outcomes (shoulder dystocia, Apgar scores < 7, hypoglycemia, jaundice, nursery stays > 2 days following vaginal delivery or > 3 days post-cesarean section, and NICU admissions).

Data analysis:

Comparative analyses of demographic characteristics and outcomes were performed across the four groups categorized by abnormal OGTT values. Chi-square or Fisher’s exact tests were utilized for categorical variables (The selection of each test was made according to the accepted standards based on the sample size.), while continuous variables were first assessed for normal distribution using the Shapiro-Wilk test. Normally distributed variables were then compared using ANOVA, whereas the Kruskal-Wallis test was applied for those not normally distributed.

Subsequently, for the primary outcome GDMA2, pairwise Fisher's Exact Tests were conducted between each unique pair of AbV groups. This step was crucial for pinpointing which specific groups exhibited significant differences in GDMA type. Given the multiple comparisons inherent in this pairwise approach, p-values were adjusted using the Bonferroni correction method to control for the increased risk of Type I errors.

Logistic regression analyses were conducted for both primary and secondary outcomes. Initially, an unadjusted logistic regression model was established to examine each variable independently. Subsequently, a multivariable logistic regression was employed to evaluate the association between the number of abnormal OGTT values and its significance, adjusting for potential confounding variables such as age, Body-Mass-Index (BMI), gravidity, parity, and gestational week at delivery. Data was analyzed using R software, R version 4.0.3 (2020-10-10).

Between 2015 and 2022, our institution recorded a total of 42,180 births. Among these, 5,700 women underwent an OGTT for the diagnosis of GDM, with 1,903 women showing at least one AbV. Following the exclusion of 82 women due to incomplete clinical information in the records, 1,821 women were confirmed to have GDM and were subsequently included in the final analysis (Fig. 1). Of them, 673 (36.95%) had one AbV in OGTT, 796 (43.71%) had two AbVs, 293 (16.09%) had three AbVs and 59 (3.24%) had four AbVs.

ANOVA revealed significant differences between the groups in terms of weight gain during pregnancy (p < 0.001), gravidity (p = 0.046), parity (p = 0.012), BMI > 30 (p = 0.013) and nulliparity (p = 0.003). Maternal age at gestation, multiple gestation and fetal gender did not differ between the groups. All demographic and basic obstetrics characteristics are presented in Table 1.

Table 1

Maternal characteristics and clinical measurements stratified by number of AbVs^@ in OGTT^:
Characteristics	Number of Abnormal OGTT^ Values				P-value
Characteristics	1 (N = 673)	2 (N = 796)	3 (N = 293)	4 (N = 59)
Maternal age, years	32.4 ± 5.24	32.9 ± 5.27	32.4 ± 5.45	33.7 ± 5.26	0.093
BMI* > 30	117 17.4%)	141 (17.7%)	57 (19.5%)	17 (28.8%)	0.0125	*
Gravidity (G)	2.85 ± 1.74	2.65 ± 1.68	2.61 ± 1.75	2.81 ± 2.06	0.0457	*
Parity (P)	1.28 ± 1.24	1.15 ± 1.28	1.06 ± 1.19	1.22 ± 1.33	0.0119	*
Nulliparity	211 (31.4%)	314 (39.4%)	123 (42.0%)	24 (40.7%)	0.0025	**
Weight gain during pregnancy, Kg	10.8 ± 7.41	9.53 ± 5.85	9.57 ± 6.22	7.02 ± 4.83	< 0.001	**
Multiple Gestation	17 (2.5%)	32 (4.0%)	6 (2.0%)	0 (0%)	0.148
Male fetus	349 (51.9%)	433 (54.4%)	157 (53.6%)	30 (50.8%)	0.78
For categorical variables results are presented as value (%) and for continuous variables as value ± standard deviation (SD). Significant p values (< 0.05) are in bold.
^@AbV – Abnormal Values ; ^OGTT – oral glucose tolerance test ; *BMI – body mass index

Primary Outcome:

GDMA2 presence was significantly different between the groups (p < 0.001). In most cases, as the number of AbVs was higher, the presence of GDMA2 was higher (Table 2a), except for the differences between one AbV and two AbVs. In this case, Fischer’s pairwise analysis did not reveal significant differences (p = 1.000). All other comparisons between AVs number group were significant, as presented in Table 2b.

Table 2

a: Maternal outcomes stratified by number of AbVs* in OGTT^:
Characteristics	Number of OGTT Pathological values				P-value
Characteristics	1 (N = 673)	2 (N = 796)	3 (N = 293)	4 (N = 59)
GDMA2**	187 (27.8%)	202 (25.4%)	111 (37.9%)	36 (61.0%)	< 0.001	***
Induction of Labor	318 (47.3%)	318 (39.9%)	149 (50.9%)	35 (59.3%)	< 0.001	***
Vaginal Delivery	541 (80.4%)	644 (80.9%)	225 (76.8%)	44 (74.6%)	0.342
Vacuum extraction	49 (7.3%)	77 (9.7%)	29 (9.9%)	7 (11.9%)	0.293
Emergency CS^#	77 (11.4%)	90 (11.3%)	39 (13.3%)	9 (15.3%)	0.685
Elective CS^#	55 (8.2%)	62 (7.8%)	29 (9.9%)	6 (10.2%)	0.662
Episiotomy	83 (12.3%)	143 (18.0%)	61 (20.8%)	11 (18.6%)	0.006	**
Perineal Lacerations Grade 1 or 2	222 (33.0%)	262 (32.9%)	89 (30.4%)	12 (20.3%)	0.195
OASIS^$	5 (0.7%)	6 (0.8%)	1 (0.3%)	0 (0%)	0.905
Maternal Composite Outcome^&	363 (53.9%)	404 (50.8%)	177 (60.4%)	39 (66.1%)	0.011	*
For categorical variables results are presented as value (%) and for continuous variables as value ± standard deviation (SD). Significant p values (< 0.05) are in bold.
AbVs – abnormal values; ^OGTT – oral glucose tolerance test; *GDMA2 –gestational diabetes type 2; # CS – cesarian section; $ OASIS – obstetrical anal sphincter injury; & Maternal composite outcome - need for induction of labor, vacuum extraction, emergency CS and OASIS

Table 2

b: Fischer’s test pairwise analysis for GDMA2, comparing number of abnormal values in OGTT^:
Groups of GDMA2* comparison	P-value	Adjusted P-value
1 abnormal value vs 2 abnormal values	0.313	1.000
1 abnormal value vs 3 abnormal values	0.002	0.014	*
1 abnormal value vs 4 abnormal values	< 0.001	< 0.001	***
2 abnormal values vs 3 abnormal values	< 0.001	< 0.001	***
2 abnormal values vs 4 abnormal values	< 0.001	< 0.001	***
3 abnormal values vs 4 abnormal values	0.001	0.008	**
*GDMA2 –gestational diabetes type 2 ; ^OGTT – oral glucose tolerance test

Secondary outcomes: Maternal Outcomes:

Differences were found between the groups in the prevalence of induction of labor (p < 0.001), episiotomy (p = 0.006) and in Maternal Composite Outcomes (which included the need for induction of labor, vacuum extraction, emergency CS, and OASIS) (p = 0.011). The groups did not differ in mode of delivery and the presence of perineal lacerations at any grade, including OASIS. These comparisons are presented in Table 2a.

Secondary Outcomes: Neonatal Outcomes:

Significant differences between the groups were found in the gestational age at delivery (p = 0.007) and Apgar score (p = 0.021). Shoulder dystocia, neonatal hypoglycemia or jaundice, macrosomia, neonatal hospitalization days, and NICU admission did not significantly differ between the groups. Neonatal composite outcome (which included shoulder dystocia, Apgar < 7, neonatal hypoglycemia, neonatal jaundice, NICU admission, nursery hospitalization > 2 days after vaginal delivery or > 3 days after CS) also did not differ between the groups. All comparisons are presented in Table 3.

Table 3

Neonatal outcomes stratified by number of AbVs* in OGTT^:
Characteristics	Number of OGTT^ Pathological values				P-value
Characteristics	1 (N = 673)	2 (N = 796)	3 (N = 293)	4 (N = 59)	P-value
Gestational age at delivery, weeks	39.1 ± 1.27	39.1 ± 1.43	38.8 ± 1.71	38.8 ± 1.20	0.007	**
Cases with Apgar < 7	20 (3.0%)	15 (1.9%)	16 (5.5%)	2 (3.4%)	0.021	*
Shoulder Dystocia	11 (1.6%)	8 (1.0%)	4 (1.4%)	2 (3.4%)	0.299
Neonatal Hypoglycemia	23 (3.4%)	21 (2.6%)	15 (5.1%)	4 (6.8%)	0.080
Neonatal Jaundice	184 (27.3%)	212 (26.6%)	90 (30.7%)	21 (35.6%)	0.210
Neonate’s birth weight, gr.	3370 ± 460	3300 ± 484	3320 ± 504	3380 ± 620	0.135
Macrosomia (> 4 kg.)	55 (8.2%)	49 (6.2%)	24 (8.2%)	8 (13.6%)	0.120
NICU** Admission	18 (2.7%)	27 (3.4%)	18 (6.1%)	2 (3.4%)	0.071
Neonatal Hospitalization days	3.31 (1.42)	3.28 (1.08)	3.31 (2.00)	3.49 (1.09)	0.679
Neonatal Composite Outcome	623 (92.6%)	728 (91.5%)	275 (93.9%)	55 (93.2%)	0.619
For categorical variables results are presented as value (%) and for continuous variables as value ± standard deviation (SD). Significant p values (< 0.05) are in bold.
AbVs – abnormal values; ^OGTT – oral glucose tolerance test ; *NICU– neonatal intensive care unite

Furthermore, we found that the gestational week at the time of the delivery decreased significantly with the increased number of AbV in OGTT.

Logistic Regression for GDMA2:

Following adjustment to confounders (number of abnormal OGTT values, maternal BMI, maternal age, gravidity and parity), the most important factor that correlated with the presence of GDMA2 was the number of AbVs (aOR 1.2, 95% CI 1.01–1.42), following by maternal BMI (aOR 1.07, 95% 1.05–1.1) (Table 4).

Table 4

Logistic regression analysis of GDMA2^ :
Outcome	Unadjusted OR (95% CI)	Adjusted OR (95% CI)	Estimate	P-value
AbVs*	1.35 (1.01, 1.42)	1.2 (1.01, 1.42)	0.179	0.039	*
BMI^$	1.08 (1.05, 1.1)	1.07 (1.05, 1.1)	0.068	< 0.001	***
Maternal age, years	1.04 (0.97, 1.03)	1 (0.97, 1.03)	-0.001	0.967
Gravidity	1.13 (0.9, 1.19)	1.03 (0.9, 1.19)	0.031	0.670
Parity	1.17 (0.9, 1.33)	1.09 (0.9, 1.33)	0.087	0.381
^GDMA2 – gestational diabetes type 2; *AbVs – abnormal values; $ BMI – body mass index

This was a retrospective analysis that aimed to determine the relations between the number of AbV in OGTT and the presence of GDMA2. Our study demonstrated that GDMA2 was more prevalent as the number of AbVs in OGTT increased.

The differences between one or two AbVs was less significant, but beyond two AbVs, the risk of GDMA2 has increased significantly. Conversely, upon conducting pairwise comparisons across all AbVs groups, discernible distinctions emerged among each. It should be noted that the absence of significant differences in the likelihood of GDMA2 between one AbV and two AbVs strengths the approach of considering a single AbV in OGTT as indicative of GDM.

The robustness of our primary outcome is reinforced through logistic regression analysis, conducted to identify potential confounders, which revealed that the most influential factor correlated with GDMA2 is the number of AbVs in OGTT.

Hence, it is empirically valid to assert that the increased prevalence of pathological values correlates positively with the likelihood of diagnosing GDMA2 over GDMA1.

Based on these disparities, which have not been previously described in the literature, it can be inferred that the cohort of women with the elevated number of AbVs in OGTT likely represents a population for whom GDM management with diet alone may pose challenges in achieving glycemic control. Consequently, these women may eventually necessitate pharmacological intervention in pursuit of glycemic balance.

Following this fundamental premise, we attempt to explicate the additional findings arising from our research results: We found that the prevalence of maternal composite outcomes was higher with an increased occurrence of AbVs in OGTT. As mentioned above, poorly controlled gestational diabetes raises the overall risk of maternal complications [7, 9–11]. Therefore, our results align with what is known in the professional obstetric literature and previous studies.

We found that a higher prevalence of AbVs correlates with an increased necessity for labor induction. This observation is consistent with the notion that a greater occurrence of AbVs in OGTT is associated with a higher probability of glycemic imbalance and the presence of GDMA2. In gestational diabetes, labor induction is frequently performed to prevent complications such as stillbirth, excessive fetal growth leading to difficult vaginal delivery, or other complications associated with poorly controlled diabetes, as it is known that the risk of complications increases with poorer glycemic control and later gestational age [17]. Furthermore, if we extrapolate that an increased number of AbVs in OGTT corresponds to a heightened likelihood of GDMA2, and as we demonstrated, there is a higher prevalence of induction of labor, it follows logically that gestational week at birth will decrease as the number of AbVs increase- a finding that was observed in our study.

Concerning neonatal outcomes, we found that as the number of AbVs in OGTT increases, the gestational week at delivery decreases. This may be attributed to the higher frequency of labor inductions observed in groups with more AbVs, indicating that as the prevalence of pathological values rises, there are more cases of GDMA2 and presumably fewer instances of good glycemic balance, leading to increased intervention for delivery induction and earlier gestational weeks at birth.

Another finding emerging from our research results is that women with higher occurrences of AbVs in OGTT had a higher presence of episiotomies performed. Previous studies have found that gestational diabetes is a risk factor for episiotomy during childbirth [18–19]. In some international childbirth management guidelines for women with suspected poor glycemic control or high fetal estimated weight, it is recommended to selectively consider performing an episiotomy to prevent OASIS or shoulder dystocia. Therefore, based on the assumption that more abnormal values in OGTT imply higher risk of GDMA2 and poorer glycemic control, it is clear why there is a higher prevalence of episiotomy during childbirth in cohorts with more AbVs.

Our study reveals that women with a heightened occurrence of AbVs in OGTT are at an increased likelihood of requiring pharmacological intervention for glycemic management. This finding can assist clinicians in interpreting OGTT results, promoting heightened vigilance and awareness of potential risks among women demonstrating a higher number of AbVs in the test. Moreover, it can help educate and motivate individuals to follpw proper dietary practices. However, our findings also indicate no significant differences in mode of delivery, incidence of OASIS, or perineal lacerations of grade 1 or 2 between the studied groups.

The differences found between the groups in the neonatal outcomes were specifically concerning gestational age at delivery and Apgar score and did not encompass the majority of neonatal outcomes. Such results may serve as reassuring tools for patients diagnosed with gestational diabetes, even in instances where the number of AbVs is elevated.

OGTT serves not only as a diagnostic tool for GDM but also enables healthcare practitioners to enhance their awareness of potential adverse outcomes for both the mother and neonate through meticulous analysis of abnormal values.

Although previous studies have examined OGTT results and their correlation with obstetric outcomes, to the best of our knowledge, our study is the first to evaluate the relationship between the numbers of AbVs in OGTT to GDMA1/2 and other maternal and neonatal outcomes, in a large cohort. The study by Mor et al. investigated the relationship between the additive OGTT score and neonatal outcomes, finding that a higher additive OGTT score is associated with an increased risk of GDMA2, greater insulin use, and more maternal and neonatal complications [20]. A systematic review and meta-analysis by Chatzakis et al. explored different phenotypes of GDM based on OGTT, comparing women with pathological fasting glucose values to those with pathological post-load glucose values, and to those with combined pathological values [21].. Another study published on a much smaller cohort addressed the relationship between the number of AbVs in the OGTT and neonatal weight only [22], while another study examined the relationship between a single abnormal value in OGTT and the likelihood of developing type 2 diabetes [23].

These studies underscore the importance of carefully examining OGTT results and their association with adverse obstetric outcome, however, no study has specifically examined the number of AbVs in OGTT and their association with adverse obstetric outcomes.

Additionally, our study benefits from the substantial cohort size and the high quality of gathered data. All participants delivered at our medical facility, guaranteeing thorough documentation of pregnancy progression, labor dynamics, and delivery outcomes for each participant. Other studies that attempted to examine the relationship between the number of AbVs in the OGTT and obstetrics outcomes had a much smaller sample size compared to that presented in our study [22,24].

Nevertheless, our study is not free of limitations, largely attributable to its retrospective design. A notable absence of data concerns the extent of glycemic control for each participant during the pregnancy. It is conceivable that some individuals classified under GDMA1 may not have achieved optimal glycemic balance, and there could be variability in clinical glycemic control within the GDMA2 cohort. Also, the level of glycemic control may influence maternal and especially neonatal outcomes, and the lack of such information could obscure some results, necessitating further investigation. However, given the stringent and comprehensive prenatal monitoring and care provided by obstetricians to the majority of pregnant women in our country, it is reasonable to infer that women who maintained glycemic balance through dietary measures without requiring pharmacological intervention were included in the study. It is important to note that the OGTT was originally developed by O'Sullivan and Mahan in the 1960s to predict the onset of type 2 diabetes after pregnancy, and not specifically to identify perinatal morbidities [25]. Unfortunately, we are unable to follow all the women in our cohort to determine whether they developed type 2 diabetes later in life. However, several publications have shown a correlation between the number of pathological values in the OGTT and the likelihood of developing type 2 diabetes during one's lifetime [26–27].

GDM - Gestational Diabetes Mellitus
ACOG - College of Obstetricians and Gynecologists
GCT - Glucose Challenge Test
OGTT - Oral Glucose Tolerance Test
AbVs - Abnormal Values
BMI – Body Mass Index
OASIS - Obstetric Anal Sphincter Injuries
NICU – Neonatal Intensive Care Unit
CS – Cesarian Section

Declaration of Interest- The authors declare no conflicts of interests.

Ethics approval and consent to participate - The study was approved by the local Review Board (MMC-0244-22), with patient informed consent waived due to the retrospective nature of data collection.
Consent for publication- Not Applicable
Availability of data and materials - The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Competing interests- Not Applicable
Funding- None.
Authors' contributions –

HG – Conception and design of the study and manuscript, critical revision of the manuscript for important intellectual content.
YY – Critical revision of the manuscript for important intellectual content, Supervision

SM – Acquisition of data, Data Analysis
KS – Acquisition of data
EP – Acquisition of data

GSM – Critical revision of the manuscript for important intellectual content, Supervision
TBS – Critical revision of the manuscript for important intellectual content, Supervision
MK- Critical revision of the manuscript for important intellectual content, Supervision
OW – Conception and design of the study and manuscript, statistical analysis, critical revision of the manuscript for important intellectual content.

Acknowledgements- Not Applicable

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No competing interests reported.

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Does the number of abnormal values in the oral glucose tolerance test impact pregnancy outcomes?

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Logistic Regression for GDMA2:

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