Evidence map›Paper›PMID 34950368›Full record

ArticleJournal of atrial fibrillation2021

Incidence and Prognostic Impact of New-Onset Atrial Fibrillation in Patients with Severe Covid-19: A Retrospective Cohort Study.

Vijayabharathy Kanthasamy, Richard J Schilling

Open access · hybridAbstract read
In one paragraph

Article in Journal of atrial fibrillation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
0.3field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Observational
  4. Review
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

2 authors at 1 institution in 1 country.

Vijayabharathy KanthasamySt Bartholomew's Hospital,Barts Health NHS Trust, London.
Richard J SchillingSt Bartholomew's Hospital,Barts Health NHS Trust, London.
St Bartholomew's Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCorona virus disease 2019 (COVID-19) contributes to cardiovascular complications including arrhythmias due to high inflammatory surge. Nevertheless, the common types of arrhythmia amongst severe COVID-19 is not well described. New onset atrial fibrillation(NOAF) is frequentlyseen in critically ill patients and therefore we aim to assess the incidence of NOAF in severe COVID -19and its association with prognosis.

methodsThis is a retrospective multicentre study including 109 consecutive patients admitted to intensive care units (ICU) with confirmed COVID-19 pneumonia and definitive outcome (death or discharge). The study period was between 11th March and 5th May 2020.

resultsMedian age of our population was 59 years (IQR 53-65) and 83% were men. Nearly three-fourth of the population had two or more comorbidities. 14.6% developed NOAF during ICU stay with increased risk amongst older age and with underlying chronic heart failure and chronic kidney disease. NOAF developed earlier during the course of severe COVID-19 infection amongst non-survivors than those survived the illness andstrongly associated with increased in-hospital death (OR 5.4; 95% CI 1.7-17; p=0.004).

conclusionsIn our cohort with severe COVID-19, the incidence of new onset atrial fibrillation is comparatively lower than patients treated in ICU with severe sepsis in general. Presence of NOAF has shown to be a poor prognostic marker in this disease entity.

Indexed as

COVID-19 pneumoniaIn-hospital mortalityNew onset Atrial Fibrillation

Identifiers

PMID34950368
PMCPMC8691275
OpenAlexW4206325959

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.