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Research Article
Implementation of the International Association
of Diabetes and Pregnancy Study Groups Criteria:
Not Always a Cause for Concern
Pooja Sibartie1and Julie Quinlivan1,2
1Department of Obstetrics and Gynaecology, Joondalup Health Campus, Joondalup, WA 6027, Australia
2Institute for Health Research, University of Notre Dame Australia, Fremantle, WA 6160, Australia
Correspondence should be addressed to Julie Quinlivan; julie.quinlivan@nd.edu.au
Received October ; Accepted November
Academic Editor: Ellinor Olander
Copyright © P. Sibartie and J. Quinlivan. is is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
Background. Controversy surrounds the decision to adopt the International Association of Diabetes and Pregnancy Study Groups
(IADPSG) criteria for the diagnosis of gestational diabetes mellitus (GDM) as fears that disease prevalence rates will soar have
been raised. Aims. To investigate the prevalence of pregnancy complicated with GDM before and aer the introduction of the
IADPSG diagnostic criteria. Materials and Methods. A prospective audit of all women who delivered from July , , to
June , , in a predened geographic region within the North Metropolitan Health Service of Western Australia. Women were
diagnosed with GDM according to Australian Diabetes in Pregnancy Society (ADIPS ) criteria until December , , and by
the IADPSG criteria aer this date. Incidence of GDM and predened pregnancy outcomes were audited. Results. Of ,
women, antenatal oral glucose tolerance test (OGTT) results and follow-up data were obtained for , women (%), of whom
(.%) were diagnosed with GDM. e rate of GDM utilising ADIPS criteria was .% and the rate of utilising IADPSG criteria
was .% (𝑝 = 0.92). Conclusion. IADPSG diagnostic criteria did not signicantly increase the incidence of GDM in this low
prevalence region.
1. Introduction
Gestational diabetes mellitus (GDM) is a common medical
complication of pregnancy dened as “any degree of glucose
intolerance with onset or rst recognition during pregnancy”
[, ]. e initial criteria for diagnosis were established
more than years ago []; however, these criteria did
not necessarily identify pregnancies with increased risk of
adverse pregnancy outcome [].
e hyperglycaemia and adverse pregnancy outcome
(HAPO) study was conducted to clarify the associations
between maternal hyperglycaemia and adverse outcomes.
e study showed associations between increasing levels
of fasting blood glucose (FBG), -hour and -hour plasma
glucose obtained following an oral glucose tolerance test
(OGTT), and birthweight >th centile and cord-blood
serum C-peptide level >thcentile[].esecondary
outcomes of premature delivery, shoulder dystocia or birth
injury, admission to intensive neonatal care unit, hyperbiliru-
binemia, and preeclampsia were also increased by maternal
hyperglycaemia [].
econsiderationofHAPOdataledtoarecommen-
dation in by the International Association of Diabetes
and Pregnancy Study Groups (IADPSG) for the FBG and h
and h glucose levels to diagnose GDM []. e diagnostic
threshold values were the average glucose values at which
the odds for birthweight >th centile, cord C-peptide >th
centile, and percent body fat >th centile reached . times
theestimatedoddsoftheoutcomesatmeanglucosevalues
[, ].
However, concern has been expressed that adoption of
the new diagnostic criteria would lead to a dramatic increase
in the incidence of GDM. One Australian study reported
that the change in diagnostic criteria from the previously
Hindawi Publishing Corporation
Journal of Pregnancy
Volume 2015, Article ID 754085, 5 pages
http://dx.doi.org/10.1155/2015/754085
Journal of Pregnancy
utilised Australasian Diabetes in Pregnancy Society (ADIPS)
criteria [] to the new IADPSG criteria [] would
increase the prevalence of GDM from .% to .% [].
A NZ study reported that the incidence might rise from
% to % []. National debate continues on the workforce
implications of the revised criteria and their clinical impact
[, ].
eaimofthisstudywastoaudittheimpactofthe
change from the ADIPS criteria [] to the IADPSG
diagnostic criteria [] within a geographically dened
region.
2. Methods
A prospective audit of all pregnancies diagnosed with GDM
commenced from July , , following publication of HAPO
and the IADPSG recommendations. e Institutional Ethics
Committee determined that the project fullled the criteria of
an audit project as pregnancy outcomes were being audited
and no intervention other than routine care according to
existing clinical protocols was planned. erefore, the project
wasexemptedfromformalethicscommitteeapproval.
All pregnant women greater than -week gestation
referred for public maternity care who resided within the
postcodes –, , , , , and within
the North Metropolitan Health Service of the Western Aus-
tralian Department of Health between July , , to June
, , were included in the audit. Women with a history
of preexisting diabetes mellitus (type or ) were specically
excluded from the project.
All women had an OGTT between and weeks of
gestation in accordance with the existing clinical protocol
[].
e ADIPS criteria were used to diagnose GDM in
theperiodfromJuly,,toDecember,[].Women
had a -gram OGTT with glucose samples taken aer an
overnightfastandathrpostprandially.GDMwasdiagnosed
ifthefastingglucosewas≥. mmol/L ( mg/dL) and/or
the h glucose was ≥. mmol/L (∼ mg/dL) [].
From January , , to June , , all patients were
diagnosed with GDM using the IADPSG diagnostic
criteria []. Women had a -gram OGTT with glucose
samples taken aer an overnight fast and at hr and hr
postprandially. One or more abnormal values were needed for
a diagnosis of GDM to be made: FBG >. mmol/L and/or -
hour BSL > mmol/L and/or -hour BSL ≥. mmol/L.
e majority of OGTT in the audit period was performed
at the Western Diagnostics Pathology laboratories. A small
number (.%) was performed at other private accredited
pathology providers.
All patients had their weight (kg) and height (m) recorded
at their booking visit to calculate their body mass index
(BMI). Patients with a BMI greater than had their
antenatal care at the local maternity hospital but were referred
for delivery to the regional tertiary hospital. ese patients
remained within the audit study.
All pregnancies diagnosed with GDM across the audit
period received identical clinical care according to a written
protocol. is involved an initial consultation with a dia-
betic educator, dietician, and obstetric doctor. Patients com-
menced self-monitoring of blood sugar levels and adopted a
diabetic diet. A review visit a fortnight later determined if
medication was required in addition to diet.
Delivery outcomes were entered into a computerized
database called Meditec by attending midwifery sta as part
of routine practice. Delivery outcomes were subsequently
extracted from Meditec, case note audit, and a postnatal
clinical service for all women with GDM conducted by one
author (Julie Quinlivan).
Predened maternal outcomes were audited. ese were
mode of delivery, elective or emergency caesarean section,
estimated blood loss, and rd or th degree perineal tear.
Predened newborn outcomes were audited. ese were
gestational age at birth, birthweight, birthweight >th cen-
tile adjusted for gestational age, Apgar at and minutes,
umbilical artery and vein pH, admission to Special Care
Unit, and serious perinatal complications such as still-
birth, neonatal death, or birth trauma including shoulder
dystocia.
A power calculation assumed that the change in incidence
of GDM would be %, a conservative estimate based on
the previous Australian and New Zealand studies [, ]. e
baseline rate of GDM in the audit region was approximately
.%. Assuming a power of % and alpha error of ., a
sample of , women was required across the audit period
to detect a change in incidence from . to .%.
Data were presented as number and percentage for
the incidence of GDM. Descriptive statistics of predened
clinical outcomes were compared using Student’s 𝑡-test for
continuousvariablesandChiSquaretestorFisherexacttest
for discrete data. A 𝑝value of . was considered signicant.
3. Results
Of , women delivering in the audit period, antenatal
OGTT results could be traced for , women (.%). e
remaining (.%) women did not have an antenatal OGTT,
in violation of national clinical protocol. Of these women,
attempted an OGTT and were unable to complete the test
due to nausea and/or vomiting. ey subsequently declined a
repeattest.eotherwomeneitherpresentedforcaretoo
late for testing or declined testing.
Table summarizes the incidence of GDM under the two
diagnostic criteria. e overall incidence was not signicantly
dierent with .% diagnosed under the ADIPS criteria
and .% under the IADPSG criteria. In the subgroup
of women with a BMI > (representing .% of the
study population) the incidence of GDM was .% using
ADIPS criteria and .% using IADPSG criteria.
is dierence was not statistically signicant (𝑝 = 0.11);
however, the audit was not adequately powered to detect a
dierence in the subgroup of women with high BMI.
Journal of Pregnancy
T : Incidence of GDM under ADIPS and IADPSG
criteria.
ADIPS IADPSG 𝑝value
All women 𝑁=, 𝑁= ,
.
GDM (.%) (.%)
No GDM , (.%) (.%)
Wome n w i t h B M I ≤ 𝑁= 𝑁=
.
GDM (.%) (.%)
No GDM , (.%) , (.%)
Wome n w i t h B M I > 𝑁= 𝑁=
.
GDM (.%) (.%)
No GDM (.%) (.%)
Across the audit period the proportion of women with
GDM who required management with medication (met-
formin or insulin) in addition to diet was not signicantly
dierent (% in women diagnosed by ADIPS criteria
and%inwomendiagnosedbyIADPSGcriteria,
resp.).
Delivery data for , (%) women were available
for audit through Meditec, case note audit, or the postnatal
clinical service.
Table summarizes predened delivery outcomes. Babies
borntowomendiagnosedwithGDMaccordingtothe
IADPSG criteria had signicantly higher umbilical
artery pH (. versus .; 𝑝 = 0.01). ey had a signicant
lower birthweight ( gms versus gms; 𝑝 = 0.02)and
birthweight above the >th centile adjusted for gestational
age (% versus %; 𝑝 = 0.04). Other predened mater-
nal and newborn outcomes were not signicantly dierent
between groups.
4. Discussion
e audit found no signicant dierence in the incidence of
GDM before and aer the introduction of the IADPSG
criteria, with the overall incidence being low at .%. Our
results dier from the previous Australian and New Zealand
studies [, ].
One explanation may be that prevalence of GDM in our
region is low compared to many other sites. Our rate of
.% contrasts higher background rates in the sites involved
in the HAPO trial where incidences ranged from to %
[]. However, HAPO study sites were specically included
because of their high rates of GDM. ey were tertiary
sites where women with high BMI and other pregnancy
complications were referred for antenatal and delivery man-
agement [, ]. Our study was based upon a geographical
region rather than a hospital cohort and thus captured
women of all risk levels, including a majority who were of
“normal” risk, unlike the patient population within a tertiary
centre.
A second explanation for the observed dierence in
outcome between our study and previous ones may be
the racial mix of the population. Although our geographic
maternity cohort reected the wider Australian public mater-
nity cohort in terms of maternal age and parity [],
racial background was overwhelmingly English speaking
Caucasian.
A third explanation may be due to maternal obesity
levels. Our geographic catchment has a low prevalence of
overweight and obese patients compared to many sites. Lower
obesity levels mean that the underlying risk of metabolic
hyperglycaemia is lowered. Of note, in our subgroup of
women with a BMI > the incidence of GDM rose from
.% to .% under the IADPSG criteria, more in line
with studies elsewhere [, ].
As a secondary consideration, the adoption of the
IADPSG criteria did not adversely impact upon our
predened maternal and newborn outcomes. ere was a
signicant improvement in three newborn outcomes, being
an increase in umbilical artery pH and a reduction in
birthweight and birthweight >th centile adjusted for ges-
tational age. ere were no signicant changes in mater-
nal outcomes. is provides reassuring safety data for the
change.
e study had several strengths. Firstly, data were
extracted from a dened geographic region before and aer
implementation of the IADPSG diagnostic criteria.
Secondly, all women received treatment using identical clin-
ical protocols throughout the audit period. irdly, there
was high compliance with screening for GDM (.%) and
ascertainment of outcome (% of women). A study limi-
tation is the low background incidence of GDM that limits
generalizability to regions where incidence rates are higher. A
second limitation is that only .% of women presented with a
BMI >. In this subgroup of women, the incidence of GDM
washigherat.%.Centreswheretheobstetricpopulation
has a higher incidence of obesity may report an increase in
the incidence in GDM utilising the new diagnostic criteria.
However, it is likely that this reects a genuine increase in
metabolicpathology,asobesityisamajorriskfactorforGDM
and adverse pregnancy outcome [].
5. Conclusion
e IADPSG used a consensus process to redene GDM
based on its association with adverse pregnancy outcomes.
ere has been controversy about the adoption of the new
guidelines. However, in our audit study of , women,
we observed no signicant increase in the incidence of
GDM. e adoption of the new criteria was associated with
improvements in three newborn outcomes.
Conflict of Interests
e authors declare that there is no conict of interests
regarding the publication of this paper.
Journal of Pregnancy
T:Deliveryoutcomes.
GDM ADIPS
𝑁 = 121 GDM IADPSG
𝑁 = 236 𝑝value
Maternal outcomes
Maternal age (years)
Mean (sd) . (.) . (.) .
Parity
Median (IQR) (–.) (–.) .
Caesarean section
𝑁(%) (%) (%) .
Blood loss (mL)
Median (IQR) (–) (–) .
Birth trauma (rd/th degree tear) 𝑁(%) (%) (%) .
Newborn outcomes
Gestational age (days)
Mean (sd) () () .
Birthweight (grams)
Mean (sd) () () .
Birthweight >th centile for gestational age
𝑁(%) (%) (%) .
Apgar
Mean (sd) (.–) (-) .
Apgar
Mean (sd) (.–) (-) .
Arterial cord blood
Mean (sd) . (.) . (.) .
Venous cord blood
Mean (sd) . (.) . (.) .
Admission to neonatal nursery 𝑁(%) (%) (%) .
Acknowledgments
e authors acknowledge Research Assistant Ms. Ronni
Highet and Research Student Ms. Danielle Lam who con-
tributed towards extraction of audit data. ey also acknowl-
edge Joondalup Health Campus for providing the GDM
follow-up clinical service during the audit period and for
funding the gestational diabetes postnatal audit clinics.
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