Evidence map›Paper›PMID 34497055›Full record

ArticleBMJ case reports2021

Critical COVID-19 in a 24-week pregnant woman with 32 days of invasive mechanical ventilation before delivery of fetus: a case of successful collaborative multidisciplinary care.

Kaladerhan Osemwengie Agbontaen, Khevan Somasundram, Matthew Baker

Open access · bronzeAbstract readCase Reports
In one paragraph

Article in BMJ case reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Kaladerhan Osemwengie AgbontaenIntensive Care Medicine, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK kaladerhan.agbontaen@nhs.net.ORCID http://orcid.org/0000-0002-5571-230X
Khevan SomasundramIntensive Care Medicine, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK.
Matthew BakerIntensive Care Medicine, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK.
Chelsea and Westminster Hospital NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe the successful treatment of a 24-week pregnant, 44-year-old woman with COVID-19. Management of this complex case required multidisciplinary collaboration and included prolonged invasive mechanical ventilation and prone positioning. Caesarean section delivery was delayed for 32 days, with no monitored fetal compromise, while stabilising the mother. To our knowledge, this is the longest reported duration of invasive ventilation while pregnant in a patient with COVID-19. COVID-19 has been shown to cause increased disease severity in pregnant women, and certain pregnancy-related physiological adaptations that occur could help explain this association. While COVID-19 has been shown to cause no increased adverse neonatal outcomes, clinicians should be aware that data show increased preterm birth in symptomatic pregnant women, thereby increasing the chance of prematurity-related complications. Further research on COVID-19 in pregnancy is crucial to facilitate better management, and full inclusion of pregnant women in therapeutic clinical trials will help achieve this.

Indexed as

COVID-19Premature BirthAdultCesarean SectionFemaleFetusHumansInfant, NewbornPregnancyPregnant PeopleRespiration, ArtificialSARS-CoV-2adult intensive careCOVID-19infectious diseasesmechanical ventilationpregnancy

Identifiers

PMID34497055
PMCPMC8438726
OpenAlexW3197823311

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.