Evidence map›Paper›PMID 39027652›Full record

ArticleComputational and structural biotechnology journal2024

CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement.

Kristina Piontkovskaya, Yulian Luo, Pia Lindberg, Jing Gao, Michael Runold, Iryna Kolosenko, Chuan-Xing Li, Åsa M Wheelock

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2024. 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
–field-weighted citation impact
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.

  1. Article
  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

8 authors.

Kristina PiontkovskayaRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Yulian LuoRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Pia LindbergRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Jing GaoRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Michael RunoldRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Iryna KolosenkoRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Chuan-Xing LiRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
Åsa M WheelockRespiratory Medicine Unit, Department of Medicine Solna and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: During the COVID-19 pandemic a need to process large volumes of publications emerged. As the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID-19 (PASC) - that affects over 10 % of those who contract SARS-CoV-2 and presents a significant challenge in the medical field. The continuous influx of publications underscores a need for efficient tools for navigating the literature. Objectives: We aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to identify key publications and networks. Methods: We introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed to analyse COVID-19-related scientific articles and to identify research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and their associations. Results: CORACLE leverages PubMed data to categorize literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. Conclusion: CORACLE is an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of emerging trends in COVID-19 and PASC research.

Indexed as

Citation mapsCOVID-19Literature miningMeSH maps

Identifiers

PMID39027652
PMCPMC11254833

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.