Covid-19 in Pregnancy: a French Population-based Cohort of Women and Newborns

NCT ID: NCT04463758

Last Updated: 2021-10-04

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 3060 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2020-05-11
• Study Completion Date: 2022-10-31

Brief Summary

The purpose of this study is to characterize the incidence and clinical features of the maternal COVID 19 infection, as well as the associated morbidity of the mother and the child, in the French context

Detailed Description

In the overall context of uncertainty about the morbidity associated with COVID-19 infection and its optimal management, knowledge is urgently required on infection during pregnancy.

First, pregnant women and newborns can have specific and severe reactions to infectious diseases, as seen in previous pandemics which justifies targeted surveillance. Second, optimal management must minimize the health risks of transmission to the newborn. While initial studies did not provide evidence for transmission in utero or during delivery, more recent data suggest that transmission is possible. The virus is present in vaginal secretions and stool, making vertical contamination possible during vaginal delivery. Similarly, transmission may occur during breastfeeding. These risks, which remain theoretical, must be weighed against known harmful consequences of mitigating strategies such as systematic caesarean (increase in maternal morbidity) and separating the child from the mother and contraindicating breastfeeding (negative impact on maternal-child bonding and optimal nutrition). In the absence of reliable data, some maternity hospitals have adopted a maximum precautionary principle, recommending caesarean for all COVID-19 positive women and imposing immediate mother-child separation after childbirth. These approaches are strongly debated in France. Third, optimal management of COVID-19 during pregnancy requires balancing maternal and newborn risks. Risks of maternal deterioration in the event of continuing pregnancy must be weighed against those to the child resulting from indicated preterm birth. This tradeoff is even more complex as evidence-based interventions to protect preterm infants, such as antenatal corticosteroid, may aggravate maternal infection. Finally, childbirth is not an elective procedure and requires managing large numbers of healthy women and newborns in a hospital setting where they are exposed to risks of infection.

Population-based research that captures the diversity of organizational structures and practices within maternity units is needed to guide management during the current epidemic and draw lessons for future infectious pandemics.

Principal innovative features are:

• A population-based approach: Current data systems will include a limited number of pregnant women, principally from university hospitals with specific patient populations and management strategies. Because all maternity hospitals care for COVID-19+ pregnant women, a population-based approach is needed to calculate reliable incidence rates, assess practice variability and measure the impact of differences in management on maternal and newborn infection rates and health.
• The inclusion of infected pregnant women who are not hospitalized and who recover before delivery will provide comprehensive data and measure early fetal in-utero exposure.
• Immediate feedback to clinicians on their practices will inform current controversies about optimal management.
• Joint follow-up of mother and child to 12 weeks after delivery, and longer if indicated, will document the medium-term impact of infection.
• Inclusion of regions with time-varying exposure to the epidemic will provide information to evaluate public health policies.

The results of this study will make it possible to:

1. guide care for COVID-19 + mothers and their newborns in real time, through a targeted analysis of key minimum data items, on a bimonthly basis during the epidemic. To achieve this objective, rapid deployment of the data collection system is necessary.

2. generate knowledge on the morbidity profile of maternal COVID-19 infection for mother and child, the subgroups at risk, and the impact of management options in real life settings;

3. document risks of intrapartum, peri-partum and postpartum transmission based on viral tests performed in the course of routine care; this approach is complementary to the biological collections set up in other projects, which aim to determine the infectious status of pregnant women from specialized centers that are not representative of the general population of pregnant women.

4. carry out comparative international research through collaboration with the international INOSS network which is coordinating similar data collection protocols and designs worldwide. The investigators are French INOSS partners.

5. evaluate the impact of the epidemic on the organization of care for all pregnant women and newborns. Major and rapid changes to prenatal and childbirth care have been made in response to the epidemic, including spacing out consultations, using teleconsultation instead of in-person visits, restricting the presence of relatives and early discharge. These changes may induce negative consequences, notably delays in the diagnosis of obstetrical complications. It is therefore crucial to document the impact of the epidemic and the resulting measures on the health of all women and newborns. For all pregnant women and newborns monitored in participating maternity hospitals, we will extract routinely collected data from the computerized records of the maternity hospitals and/or via the SNDS-PMSI databases. These data will also be collected for periods before the epidemic to enable comparisons with overall pregnancy outcomes between the two periods. These results can be placed in an international context through collaboration with the European Euro-Peristat network, coordinated by the investigators' research team.

The objective of this multi-regional population-based cohort is to assess the impact of COVID-19 infection during pregnancy on maternal and neonatal health, including rates of perinatal transmission and the influence of diverse management practices on morbidity. The study's focus on this specific population and its population-based coverage complement other facility-based surveillance systems on all cases in France.

Conditions

covid19 Infection; Pregnancy Complications; Neonatal Complications

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Interventions

An auto-questionnaire comprising three psychometric scales

three psychometric scales validated in French: _depression (Edinburgh Postpartum Depression Scale (EPDS)), anxiety (State-Trait Anxiety Inventory (STAI)

• and Impact of Event Scale (Revised) (IES-R)

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Any woman with :

either proven COVID-19 infection= positive PCR test, OR probable COVID-19 infection = typical clinical symptoms AND typical pulmonary radiology

• during pregnancy or within 42 days postpartum,
• whether or not this diagnosis is followed by hospitalization,

Exclusion Criteria

• Refusal to participate
• Major protected (curator, trusteeship)

• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

INSERM, Epopé team

UNKNOWN

Sponsor Role: collaborator

Assistance Publique - Hôpitaux de Paris

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Pierre Yv Ancel, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Assistance Publique - Hôpitaux de Paris

Locations

AP-HP Cochin

Paris, , France

Site Status: RECRUITING

Countries

France

Central Contacts

Catherine Deneux-Tharaux, MD, PhD

Role: CONTACT

catherine.deneux-tharaux@inserm.fr

+33 1 42 34 55 79

Laurence Lecomte, PhD

Role: CONTACT

laurence.lecomte@aphp.fr

+33 1 58 41 34 78

Facility Contacts

Jean-Marc Treluyer, M.D., PhD

Role: primary

jean-marc.treluyer@parisdescartes.fr

+ 00 1 58 41 28 85

Other Identifiers

APHP200513

Identifier Type: -

Identifier Source: org_study_id