Evidence map›Paper›PMID 34097753›Full record

ArticleActa anaesthesiologica Scandinavica2021

Long-term consequences in critically ill COVID-19 patients: A prospective cohort study.

Anna Schandl, Anders Hedman, Patrik Lyngå, Sozan Fathi Tachinabad, Jessica Svefors, Mari Roël, Anne Geborek, Mikael Andersson Franko, Mårten Söderberg, Eva Joelsson-Alm and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Acta anaesthesiologica Scandinavica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 6 pooled it
5.0field-weighted citation impact, top 4% 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

30 citing papers in PubMed, 6 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
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  4. ESCMID rapid guidelines for assessment and management of long COVID.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
    Guideline
  5. Prevalence of post-acute COVID-19 syndrome symptoms at different follow-up periods: a systematic review and meta-analysis.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2022
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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

11 authors at 2 institutions in 1 country.

Anna SchandlDepartment of Anesthesiology and Intensive Care, Södersjukhuset, Stockholm, Sweden.
Anders HedmanDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Patrik LyngåDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Sozan Fathi TachinabadDepartment of Internal Medicine, Södersjukhuset, Stockholm, Sweden.
Jessica SveforsDepartment of Internal Medicine, Södersjukhuset, Stockholm, Sweden.
Mari RoëlDepartment of Internal Medicine, Södersjukhuset, Stockholm, Sweden.
Anne GeborekDepartment of Internal Medicine, Södersjukhuset, Stockholm, Sweden.
Mikael Andersson FrankoDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Mårten SöderbergDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
Eva Joelsson-AlmDepartment of Anesthesiology and Intensive Care, Södersjukhuset, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-9041-2468
Pernilla DarlingtonDepartment of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-3411-8838
Karolinska Institutet · SEStockholm South General Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 can cause severe disease with need of treatment in the intensive care unit (ICU) for several weeks. Increased knowledge is needed about the long-term consequences.

methodsThis is a single-center prospective follow-up study of COVID-19 patients admitted to the ICU for respiratory organ support between March and July 2020. Patients with invasive ventilation were compared with those with high-flow nasal oxygen (HFNO) or non-invasive ventilation (NIV) regarding functional outcome and health-related qualify of life. The mean follow-up time was 5 months after ICU discharge and included clinical history, three well-validated questionnaires about health-related quality of life and psychological health, pulmonary function test, 6-minute walk test (6MWT) and work ability. Data were analyzed with multivariable general linear and logistic regression models with 95% confidence intervals.

resultsAmong 248 ICU patients, 200 patients survived. Of these, 113 patients came for follow-up. Seventy patients (62%) had received invasive ventilation. Most patients reported impaired health-related quality of life. Approximately one-third suffered from post-traumatic stress, anxiety and depression. Twenty-six percent had reduced total lung capacity, 34% had reduced 6MWT and 50% worked fulltime. The outcomes were similar regardless of ventilatory support, but invasive ventilation was associated with more bodily pain (MSD -19, 95% CI: -32 to -5) and <80% total lung capacity (OR 4.1, 95% CI: 1.3-16.5).

conclusionAmong survivors of COVID-19 who required respiratory organ support, outcomes 5 months after discharge from ICU were largely similar among those requiring invasive compared to non-invasive ventilation.

Indexed as

COVID-19Critical IllnessFollow-Up StudiesHumansIntensive Care UnitsProspective StudiesQuality of LifeSARS-CoV-2COVID-19intensive care unitlong-term effects

Identifiers

PMID34097753
PMCPMC8212104
OpenAlexW3170126859

What OpenQuestion holds

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LicenceCC BY-NC
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.