Corresponding author:
Dr Jill C S Lee
Associate Consultant
KK Women’s and Children’s Hospital
100 Bukit Timah Road
+65 6394 3096
jill.lee.c.s@singhealth.com.sg
It has been six months since the outbreak of the Coronavirus Disease
2019 (COVID-19) and despite ongoing research efforts, much of it still
remains uncertain. Since December 2019 when the infection was first
identified, more than 16000 MEDLINE-indexed papers have been published
surrounding this subject matter. It is of utmost importance to learn
about COVID-19 infection and its potential effects on pregnancy and
perinatal outcomes, in order to guide obstetrical management during this
current disease outbreak. As such, many obstetric units have been
expeditiously publishing data from their studies in an attempt to
rapidly disseminate information on COVID-19 in pregnancy. To date, most
of these publications have been in the form of case reports and case
series. While these reports provide valuable information which have
helped to guide early management in this rapidly evolving global
pandemic, they are not ranked highly in the traditional hierarchy of
evidence. [1]
Case reports are known to be at risk of publication bias and may not be
suitable for statistical inferences. Case series typically lack
controls, and are prone to bias. Furthermore, inconsistency across
reporting and small sample size, make it difficult for conclusive
inferences to be drawn. This may not be representative of the larger
global situation. Thus, findings from these studies may not be widely
applicable to larger populations of patients.[2] As we await better
quality evidence from large laboratories and population databases,
current systematic reviews and management guidelines have developed
their recommendations based on findings from studies done during
previous disease outbreak (e.g. Severe Acute Respiratory Syndrome (SARS)
Coronavirus) and personal experiences with COVID-19, in addition to the
current available literature on COVID-19. This has led to discrepancies
in recommendations especially in areas with scarce data. This commentary
aims to highlight some of the potential problems and limitations one may
encounter when reviewing the existing literature.
In addition to the limitations in the study design of case reports and
series, the problem of duplicate reporting needs to be addressed. Not
only does duplicate reporting of the same patient overload available
medical information, it also overemphasizes findings. This will in turn
affect the accuracy of all subsequent data analyses and preclude valid
systematic reviews. Therefore, it is of paramount importance to screen
for overlapping cases before performing analysis.
This process has been challenging as some studies may not have clearly
indicated if their patient series includes patients who may have been
included in other published papers. This is especially of concern in
areas where care or isolation facilities for COVID-19 are limited and
patients may transfer between hospitals resulting in such cases being
reported by both the admitting and receiving hospitals. Case studies may
report on different aspects of the same case, rendering efforts to
screen for duplicates by direct comparison of clinical characteristics
and outcomes impossible. Some investigators have unfortunately reported
failed attempts of contacting the corresponding author to identify the
actual source of cases.[3]
A strict and rigorous system to screen for duplicates needs to be in
place when performing a systematic review. Special attention should be
paid to studies originating from countries with high COVID-19 related
research output as risk of case duplication could be higher. Identifying
the roles of the various healthcare institutions within the same country
might be useful in identifying the admitting and receiving hospitals and
thus, the possibility of overlapping cases. For studies derived from the
same institution, direct comparison of data should be undertaken where
applicable.
Apart from studies done during the peak of the COVID-19 outbreak in
Hubei province, where patients were diagnosed with COVID-19 based on
clinical signs and symptoms, epidemiological history and typical chest
computed tomography (CT) findings, all other studies included only
patients with laboratory confirmed positive quantitative reverse
transcriptase polymerase chain reaction (qRT-PCR) assay. However, the
viral nucleic acid test has a false-negative rate of up to 30%. [4]
Furthermore, studies have reported asymptomatic carriers who were only
incidentally picked up during universal screening.[5] This suggests
that many asymptomatic cases of COVID-19 have likely been undiagnosed.
Thus, current literature may have underreported the actual prevalence of
COVID-19 amongst pregnant women as well as the associated COVID-19
pregnancy outcomes and complications.
Conversely, as the follow-up period for these studies have been short
and most patients are in their third trimester of pregnancy, there might
be an overestimation of risks such as preterm birth whilst
underestimating longitudinal risks such as fetal growth restriction.
[6] The increased risk of preterm birth may also be confounded by
the fact that some of these deliveries were expedited to optimize the
maternal condition. As the indication for delivery may not always be
clearly specified in case reports, it is near-impossible to extrapolate
data about the rate of spontaneous versus iatrogenic preterm birth. It
is important to recognise that other factors such as stress and anxiety,
especially prevalent during a time of pandemic, can also have
detrimental impact on perinatal outcomes. Hence, the lack of comparable
controls negates attributing these complications and outcomes solely to
COVID-19 infection.
Existing case reports and case series mainly focus on the
characteristics of COVID-19 infection in pregnant women and the
potential effects on pregnancy outcomes. Information revolving other
peripartum issues such as breastfeeding, possibility of vertical
transmission and the need for postpartum isolation, remains relatively
limited.
Systematic reviews need to follow a strict study protocol with clearly
stated inclusion and exclusion criteria. As a result, a large proportion
of other resources such as commentaries, opinions, expert reviews, and
letters to editors are typically excluded. Important clinical
observations and findings based on experiences or experts’ own research
regarding COVID-19 might not be captured in these reviews.
Additionally, it should be highlighted that the findings of a systematic
review are only accurate and updated up to the point of submission for
publication. However, in the face of an evolving disease, new
information and literature are emerging rapidly. Accounting for the time
required for processing, findings may not always be the most updated by
the time of publication. If more than 16000 papers can be published
within a 6-month period, it is a massive challenge for both researchers
and readers to make conclusive decisions based on a single systematic
review. To date, there are at least 8 published systematic reviews on
COVID-19 and pregnancy with varying conclusions. [3, 6-12]
While timely reporting of findings regarding COVID-19 is necessary and
crucial to supplement our understanding of the infection and thus, guide
clinical management, reviewers and guideline developers should bear in
mind the limitations and interpret findings with caution. At present,
the conclusions drawn from the current body of evidence may be at risk
of bias. Establishment of rigorously governed national and international
registries can help to address some of these issues. Although it is
important to recognize the limitations of these studies and reviews, we
are immensely grateful for the tremendous ongoing research efforts
during this challenging time of a global pandemic. The quick
dissemination of information inevitably helps clinicians to keep abreast
of the latest developments, thereby guiding and updating clinical
management as deemed appropriate. As we continue the fight against
COVID-19, we look forward to more extensive research outcomes,
contributing to a higher level of evidence.