Your browser doesn't support javascript.
SARS-CoV-2 (COVID-19) infection in pregnant women: characterization of symptoms and syndromes predictive of disease and severity through real-time, remote participatory epidemiology.
Molteni, Erika; Astley, Christina M; Ma, Wenjie; Sudre, Carole H; Magee, Laura A; Murray, Benjamin; Fall, Tove; Gomez, Maria F; Tsereteli, Neli; Franks, Paul W; Brownstein, John S; Davies, Richard; Wolf, Jonathan; Spector, Tim D; Ourselin, Sebastien; Steves, Claire J; Chan, Andrew T; Modat, Marc.
  • Molteni E; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Astley CM; Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
  • Ma W; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Sudre CH; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Magee LA; Department of Women and Children's Health, School of Life Course Sciences and the Institute of Women and Children's Health, King's College London, London, United Kingdom.
  • Murray B; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Fall T; Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Sweden.
  • Gomez MF; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenströms gata 35, SE-21428, Malmo, Sweden.
  • Tsereteli N; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenströms gata 35, SE-21428, Malmo, Sweden.
  • Franks PW; Department of Clinical Sciences, Lund University Diabetes Centre, Jan Waldenströms gata 35, SE-21428, Malmo, Sweden.
  • Brownstein JS; Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
  • Davies R; Zoe Global Limited, London, United Kingdom.
  • Wolf J; Zoe Global Limited, London, United Kingdom.
  • Spector TD; Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.
  • Ourselin S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
  • Steves CJ; Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.
  • Chan AT; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Modat M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
medRxiv ; 2020 Oct 14.
Article in English | MEDLINE | ID: covidwho-900748
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT

OBJECTIVE:

To test whether pregnant and non-pregnant women differ in COVID-19 symptom profile and severity. To extend previous investigations on hospitalized pregnant women to those who did not require hospitalization.

DESIGN:

Observational study prospectively collecting longitudinal (smartphone application interface) and cross-sectional (web-based survey) data.

SETTING:

Community-based self-participatory citizen surveillance in the United Kingdom, Sweden and the United States of America. POPULATION Two female community-based cohorts aged 18-44 years. The discovery cohort was drawn from 1,170,315 UK, Sweden and USA women (79 pregnant tested positive) who self-reported status and symptoms longitudinally via smartphone. The replication cohort included 1,344,966 USA women (134 pregnant tested positive) who provided cross-sectional self-reports.

METHODS:

Pregnant and non-pregnant were compared for frequencies of symptoms and events, including SARS-CoV-2 testing and hospitalization rates. Multivariable regression was used to investigate symptoms severity and comorbidity effects.

RESULTS:

Pregnant and non-pregnant women positive for SARS-CoV-2 infection were not different in syndromic severity. Pregnant were more likely to have received testing than non-pregnant, despite reporting fewer symptoms. Pre-existing lung disease was most closely associated with the syndromic severity in pregnant hospitalized women. Heart and kidney diseases and diabetes increased risk. The most frequent symptoms among all non-hospitalized women were anosmia [63% pregnant, 92% non-pregnant] and headache [72%, 62%]. Cardiopulmonary symptoms, including persistent cough [80%] and chest pain [73%], were more frequent among pregnant women who were hospitalized.

CONCLUSIONS:

Symptom characteristics and severity were comparable among pregnant and non-pregnant women, except for gastrointestinal symptoms. Consistent with observations in non-pregnant populations, lung disease and diabetes were associated with increased risk of more severe SARS-CoV-2 infection during pregnancy.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Language: English Year: 2020 Document Type: Article Affiliation country: 2020.08.17.20161760

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Language: English Year: 2020 Document Type: Article Affiliation country: 2020.08.17.20161760