EAL

GDM: Abnormal Glucose Tolerance During Pregnancy (2008)

Citation:

Study Design:

Class:

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Quality Rating:

Research Purpose:

To compare the influence of different levels of carbohydrate intolerance on neonatal outcomes.

Inclusion Criteria:

The cohort constituted by the 1,962 pregnant women screened for gestational diabetes who gave birth at the University of Granada (Spain) in the year 1995 was followed retrospectively.

Inclusion Criteria:

Delivery in 1995
Usual residence and health care in the area of reference Hospital Universitario Granada (HUG).
Simple pregnancy
First doctor visit before the 28^th week of gestation
Delivery after 28^th week
2574 fulfilled the inclusion criteria

Three groups of comparisons were established:

diagnosis of GDM (65)
positive screen but non-GDM (231)
negative screen and non-GDM (1666).

Exclusion Criteria:

Diabetes type 1, type 2 or carbohydrate intolerance diagnosed before pregnancy
Pregnancy not under medical control
Pregnancies and deliveries involving a high obstetric risk which, otherwise, would not have been attended at the HUG.

Description of Study Protocol:

Recruitment Method was not detailed

Design Historical Cohort

Blinding used: not applicable

Intervention

All GDM women were tested with diet, 5 of them (7.7%) under treatment of diet plus insulin
In GDM gravidae, the metabolic control was considered “non-optimal” when the woman presented a fasting plasma glucose>105 mg/dl and /or a 2 h postprandial> 120 mg/dl on two or more occasions
Or the patient’s obstetric or endocrinological record specified that the response to treatment was poor.
Thus, metabolic control was considered “non-optimal" in 12 GDM women (18.5%).

Statistical Analysis

The Pearson Chi-square test and Fisher’s exact test were used to compare proportions.
A Chi-square test for trends was performed only if the P value for the Pearson Chi-square test was <0.05.
The difference between means was tested by analysis of variance (ANOVA) for normal variables, and when the results were statistically significant, the Newman-Keuls test was used to compare pairs.
The Kruskal-Wallis test was performed to compare means for non-parametric continuous data.
A value of P<0.05 was considered statistically significant.
A stratified analysis was used to attempt to eliminate the possible bias introduced by GDM risk factors.

Data Collection Summary:

Timing of Measurements

All newborns were examined in the first 24 h by a neonatologist in the HUG.

Dependent Variables

Diagnostic Criteria

GDM streamlining included whether or not GCT was performed, week of screening, and results of glycemia in a fasting state and 1-h after glucose load.
It was noted if there was a confirmatory diagnosis (OGTT), the week of its performance, and the glycemic fasting, and at 1, 2,3 h. Screening for GDM was performed in 1962 subjects who constituted the final study sample.

Neonatal Outcome:

Macrosomia-defined as fetal birth weight over 4000 grams. To adjust the weight for gestational age and sex of the newborn, the Lubchenco tables were used.
LGA-neonates with a weight above the 90^th percentile were considered large for gestational age
Neonatal Hypoglycemia- was defined as glycemia <40 mg/dl.
Neonatal Hypocalcaemia- was defined as calcaemia <8 mg/dl. Only r\early-on set cases of hypocalcaemia were considered ( manifested in the first 4 days of life).
Hyperbilirubinemia- was defined as total bilirubin over 12 mg/dl in full term neonates, and over 14mg/dl in preterm-newborns.
Erythocytosis was checked when the hematocrit was over 60% , the number of erythrocytes over 6,000,000, and the mean concentration of hemoglobin over 20 mg/dl.
RDS
Traumatism at birth

Neonate Anthropometric Variables

Weight at birth
Males
Females
Length (cm)
Thorax circumference (cm)
Head circumferences (cm)
Gestational age at birth
Need for special care
Congenital malformations
Perinatal mortality

Independent Variables

Age > 30 years of age
Weight (kg)
BMI (kg/m² ) over 27
Parity
Family history of diabetes
Antecedents of macrosomia
Previous GDM
Chronic hypertension
Antecedents of malformations
Antecedents of fetal death

Control Variables

Description of Actual Data Sample:

Initial N: 2574 fulfilled the inclusion criteria

Attrition (final N): 1,962 women

Age: See Table 1

Ethnicity: not specified

Other relevant demographics:

Anthropometrics

Location: Department of Preventive Medicine and Public Health, Facultad de Medicina, Universidad de Granada, Granada, Spain

Summary of Results:

Statistically significant differences were found among the three groups analyzed . The pregnant women with GDM showed greater values for age, weight, and parity than in the other groups. There was a significant difference in maternal age between women screening negative and those screening positive (with or without GDM) (see Table 1).

Table I Maternal characteristics ^a

Characteristic	Screened(+),n=1666	Screened(-),n=231	GDM,n=65	P
Age ^e	28.5(4.8)	30.3(4.7)	31.3(4.8)	<0.001
Weight(kg)	60.5 (9.3)	63.8 (11.3)	67.4(15.7)	<0.001
BMI ^b (kg/m² )	23.4 (3.4)	24.9(4.2)	26.9 (5.8)	<0.001
Parity ^c,e	0.8 (0.8)	1.0(0.9)	1.1(0.9)	<0.001
Familial history of diabetes^e	252 [15.1]	61[26.4]	21[32.3]	<0.001
Antecedents of microsomia	82 [4.9]	21[9.1]	12[18.5]	<0.001
Previous GDM	7 [0.4]	6[2.6]	8[12.3]	<0.001
Chronic hypertension	13 [0.8]	2[0.9]	3[4.6]	<0.05
Antecedent of malformations	9[0.5]	0	0	n.s^d
Antecedents of fetal death	18 [1.1]	5[2.2]	0	n.s ^d

^a Quantative variables are expressed as mean (SD). Qualitative variables are expressed as number of cases and [percent].

^b BMI : body mass index

^c Pregnancy in course is not included.

^dn.s: not significant

^e No significant difference in screened(+) and GDM groups

The differences were statistically significant for weight at birth when considered globally (P<0.01). A clear association was seen between the degree of carbohydrate intolerance aqnd the frequency of macrosomia : from 4.0% in the negative screen group to 50% among those diagnosed with GDM and classified under non-optimal metabolic control (Chi-square for trends=28.84; P<0.001)(see Tables 2 and 3).

Table 2 Anthropometric characteristics of the neonate, perinatal mortality and presence of congenital malformations^a

-	Screened(-),n=1666	Screened(+),n=231	GDM, n=65	P
Weight at birth (g)	3253(490)	3367(475)	3384(561)	0.001
Males	856[51.4]	106[45.9]	34[52.3]	-
Females	810[48.6]	125[54.1]	31[47.7]	n.s^b
Length (cm)	50.4(2.4)	50.5(2.3)	50.7(2.1)	n.s^b
Thorax circumference(cm)	33.3(2.0)	33.4 (2.0)	33.4(2.2)	n.s^b
Head circumference(cm)	34.7(1.5)	35.0 (1.4)	34.6 (1.4)	<0.01
Gestational age at birth	39.2(1.8)	39.4 (1.6)	38.8(1.6)	<0.05
Need for special care	223[13.4]	23[10.0]	11[16.9]	n.s^b
Congenital malformations^c	57[3.4]	10[4.3]	0	n.s^b
Perinatal mortality^d	11[0.7]	1[0.4]	0	n.s^b

a Quantative variables are expressed as mean (SD). Qualitative variables are expressed as number of cases and [percent].

^b n.s: not statistically significant (P>0.05)

^c Major and minor congenital malformations

^d Seven anteparum deaths and five postpartum ones (two polymalformative syndrones, one congenital cardiopathy, and two premature (weeks at delivery 29 and 30, weight at birth 1100 and 1050 g, respectively).

Table 3 Complications in the neonate potentially related with GDM

-	Number of cases, n[%]	>	>	>	P
-	Screened (-)^a	Screened ( +)^b	GDM optimal control^c	GDM non-optimal control^d	-
Macrosomia ^h	67[4.0]	17[7.4]	4[7.5]	6[50.0]	<0.001
LGA ^e,h	101[6.1]	27[11.7]	7[13.2]	7[58.3]	<0.001
Hypoglycemia ⁱ	53[3.2]	5[2.2]	4[7.5]	4[33.3]	<0.001
Hypocalcemiaⁱ	5[0.3]	0	2[3.8]	2[16.7]	<0.001
Hyperbilirubinemia	235[14.1]	41[17.7]	3[25.0]	10[18.9]	n.s^f
Erythrocytosis	27[1.6]	5[2.2]	1[1.9]	1[8.3]	n.s^f
RDS^g	88[5.3]	10[4.3]	3[5.7]	1[8.3]	n.s^f
Tramatism at birth	25[1.5]	4[1.7]	1[1.9]	1[8.3]	n.s^f

^a n=1666

^bn=231

^c n=53

^d n=12

^e LGA: large for gestational age (>90th percentile)

^f ns: not statistically significant (P>0.05).

^gRDS: respiratory distress syndrone

^h No significant difference in screened (+) and GDM optimal control groups.

ⁱ No significant difference in screened (-) and screened (+) groups.

Only those pregnant women at risk gave significant differences with regard to the incidence of macrosiminia or any other complication (greater overall in the gravidae with GDM)(see Tbale 4).

Table 4 Complications in neonate according to maternal weight(BMI>27) and advanced maternal age(>30)^ab

-	Number of cases	>	>	>	P
	Screened(-),n[%]^c	Screened (+),n[%]^d	GDM,n[%]^e	Total,n[%]^f	-
Macrosomia	-	-	-	-	-
RF	35[4.4]	13[8.1]	9[17.6]	57[5.7]	<0.005
No RF	32[3.7]	4[5.6]	1[7.1]	37[3.9]	n.s^g
LGA^h	-	-	-	-	-
RF	52[6.6]	22[13.8]	13[25.5]	87[8.7]	<0.005
No RF	49[5.6]	5[7.0]	1[7.1]	55[5.7]	n.s^g
Hypoglycemia	-	-	-	-	-
RF	29[3.7]	3[1.9]	7[13.7]	39[3.9]	<0.005
No RF	24[2.7]	2[2.8]	1[7.1]	27[2.8]	n.s^g
Hypocalcemia	-	-	-	-	-
RF	2[10.3]	0	4 [7.8]	6[0.6]	<0.005
No RF	3[10.3]	0	0	3[0.3]	n.s^g

^a RF: gravidae with BMI>27 and/or age > 30.

^bNo RF: gravidae without GDM risk factors

^cRF=791, no RF=875, n[%]:number of cases and [percent].

^dRF=160, no RF=71, n[%]:number of cases and [percent].

^eRF=51, no RF=14, n[%]:number of cases and [percent].

^f RF=1002, no RF=960, n[%]:number of cases and [percent].

^gn.s. : not statistically significant (P. 0.05).

^hLGA: large for gestational age ( >90th percentile).

Other Findings

Author Conclusion:

Both maternal gestational diabetes risk factors and greater carbohydrate intolerance in gravidae are associated with an increase in adverse newborn outcomes.
Gestational diabetes was associated with a greater incidence of high birth weight, hypoglycemia and hypocalcemia.
Adequate metabolic control of the illness reduced the risk of adverse outcome.
Birth weight traced a positive slope with respect to the degree of carbohydrate intolerance. Regardless of carbohydrate intolerance , macrosomia was always higher among gravidas with gestational diabetes risk factors than among women without them.

Limitations

Other factors commonly associated with the development of a macrosomic fetus are advanced maternal age, obesity, weight gain during pregnancy, prolonged gestation and multiparity; some of these are known to be associated with GDM as well. The researchers attempted to eliminate the possible bias introduced by these risk factors by stratifying data as the presence or absence of advanced maternal age (30 years or older) and obesity (BMI >27)

Funding Source:

Reviewer Comments:

In a historical cohort study, data on exposure and occurrence of disease are collected after the events have taken place—the cohorts of exposed and non-exposed subjects are assembled from existing records, or health care registries. Studies of this kind provide a better opportunity than one time cross sectional studies to examine whether certain behaviors do in fact lead to (or cause) the disease.

The limitations and critique of the study, as stated by the authors appear to be very appropriate.

Quality Criteria Checklist: Primary Research
Relevance Questions
	1.	Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies)	Yes
	2.	Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about?	Yes
	3.	Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice?	Yes
	4.	Is the intervention or procedure feasible? (NA for some epidemiological studies)	Yes

Validity Questions
1.	Was the research question clearly stated?		Yes
	1.1.	Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified?	Yes
	1.2.	Was (were) the outcome(s) [dependent variable(s)] clearly indicated?	Yes
	1.3.	Were the target population and setting specified?	Yes
2.	Was the selection of study subjects/patients free from bias?		Yes
	2.1.	Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study?	Yes
	2.2.	Were criteria applied equally to all study groups?	Yes
	2.3.	Were health, demographics, and other characteristics of subjects described?	Yes
	2.4.	Were the subjects/patients a representative sample of the relevant population?	Yes
3.	Were study groups comparable?		Yes
	3.1.	Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT)	N/A
	3.2.	Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline?	Yes
	3.3.	Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.)	Yes
	3.4.	If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis?	Yes
	3.5.	If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.)	N/A
	3.6.	If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")?	N/A
4.	Was method of handling withdrawals described?		N/A
	4.1.	Were follow-up methods described and the same for all groups?	N/A
	4.2.	Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.)	N/A
	4.3.	Were all enrolled subjects/patients (in the original sample) accounted for?	N/A
	4.4.	Were reasons for withdrawals similar across groups?	N/A
	4.5.	If diagnostic test, was decision to perform reference test not dependent on results of test under study?	N/A
5.	Was blinding used to prevent introduction of bias?		N/A
	5.1.	In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate?	N/A
	5.2.	Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.)	N/A
	5.3.	In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded?	N/A
	5.4.	In case control study, was case definition explicit and case ascertainment not influenced by exposure status?	N/A
	5.5.	In diagnostic study, were test results blinded to patient history and other test results?	N/A
6.	Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described?		Yes
	6.1.	In RCT or other intervention trial, were protocols described for all regimens studied?	N/A
	6.2.	In observational study, were interventions, study settings, and clinicians/provider described?	Yes
	6.3.	Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect?	N/A
	6.4.	Was the amount of exposure and, if relevant, subject/patient compliance measured?	N/A
	6.5.	Were co-interventions (e.g., ancillary treatments, other therapies) described?	N/A
	6.6.	Were extra or unplanned treatments described?	N/A
	6.7.	Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups?	N/A
	6.8.	In diagnostic study, were details of test administration and replication sufficient?	N/A
7.	Were outcomes clearly defined and the measurements valid and reliable?		Yes
	7.1.	Were primary and secondary endpoints described and relevant to the question?	Yes
	7.2.	Were nutrition measures appropriate to question and outcomes of concern?	Yes
	7.3.	Was the period of follow-up long enough for important outcome(s) to occur?	Yes
	7.4.	Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures?	Yes
	7.5.	Was the measurement of effect at an appropriate level of precision?	Yes
	7.6.	Were other factors accounted for (measured) that could affect outcomes?	Yes
	7.7.	Were the measurements conducted consistently across groups?	Yes
8.	Was the statistical analysis appropriate for the study design and type of outcome indicators?		Yes
	8.1.	Were statistical analyses adequately described and the results reported appropriately?	Yes
	8.2.	Were correct statistical tests used and assumptions of test not violated?	Yes
	8.3.	Were statistics reported with levels of significance and/or confidence intervals?	Yes
	8.4.	Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)?	N/A
	8.5.	Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)?	Yes
	8.6.	Was clinical significance as well as statistical significance reported?	Yes
	8.7.	If negative findings, was a power calculation reported to address type 2 error?	Yes
9.	Are conclusions supported by results with biases and limitations taken into consideration?		Yes
	9.1.	Is there a discussion of findings?	Yes
	9.2.	Are biases and study limitations identified and discussed?	Yes
10.	Is bias due to study's funding or sponsorship unlikely?		Yes
	10.1.	Were sources of funding and investigators' affiliations described?	Yes
	10.2.	Was the study free from apparent conflict of interest?	Yes