Evidence map›Paper›PMID 35292552›Full record

ArticleBMJ case reports2022

Systemic capillary leak syndrome (SCLS) after receiving BNT162b2 mRNA COVID-19 (Pfizer-BioNTech) vaccine.

Masatoshi Inoue, Yu Yasue, Yoichi Kobayashi, Yutaka Sugiyama

Open access · bronzeAbstract readCase Reports
In one paragraph

Article in BMJ case reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.3field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. The systemic capillary leak syndrome following COVID-19 vaccine.Human vaccines & immunotherapeutics · 2024
    Article
  3. Systemic capillary leak syndrome.Nature reviews. Disease primers · 2024
    Review
  4. Article
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  6. Article
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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

4 authors at 1 institution in 1 country.

Masatoshi InoueNephrology, Tajimi Hospital, Tajimi, Japan inoue.masatoshi333@gmail.com.
Yu YasueNephrology, Tajimi Hospital, Tajimi, Japan.
Yoichi KobayashiNephrology, Tajimi Hospital, Tajimi, Japan.
Yutaka SugiyamaNephrology, Tajimi Hospital, Tajimi, Japan.
Gifu Prefectural Tajimi Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic capillary leak syndrome (SCLS), also known as Clarkson's disease, is a rare disorder of unknown aetiology. Since SCLS was first described in 1960, fewer than 500 cases have been reported. SCLS is diagnosed by the classic triad of hypotension, haemoconcentration and hypoalbuminaemia resulting from fluid extravasation. Some reports show that SCLS may sometimes occur as a side effect of adenoviral vector COVID-19 vaccines, although there is only one report (two cases) of SCLS after receiving a messenger RNA vaccine. Survival rates for SCLS are very poor without treatment, so it is crucial for clinicians to recognise this disorder. A middle-aged woman who presented with generalised malaise and anasarca after receiving the BNT162b2 COVID-19 vaccine was diagnosed with SCLS. Treatment with methylprednisolone and intravenous immunoglobulin was commenced and her symptoms resolved. We expect that this case report will add to the existing literature on this rare disorder and the side effects of vaccinations.

Indexed as

Capillary Leak SyndromeCOVID-19VaccinesBNT162 VaccineCOVID-19 VaccinesFemaleHumansMiddle AgedmRNA VaccinesRNA, MessengerVaccines, SyntheticBNT162 VaccineCOVID-19 VaccinesmRNA VaccinesRNA, MessengerVaccinesVaccines, Syntheticadult intensive careimmunological products and vaccinesimmunologyrenal system

Identifiers

PMID35292552
PMCPMC8928276
OpenAlexW4221117506

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.