Evidence map›Paper›PMID 38774371›Full record

ArticleEuropean heart journal. Digital health2024

Prediction of survival in out-of-hospital cardiac arrest: the updated Swedish cardiac arrest risk score (SCARS) model.

Pedram Sultanian, Peter Lundgren, Antros Louca, Erik Andersson, Therese Djärv, Fredrik Hessulf, Anna Henningsson, Andreas Martinsson, Per Nordberg, Adam Piasecki and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European heart journal. Digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

16 authors.

Pedram SultanianDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.ORCID https://orcid.org/0000-0002-6941-6659
Peter LundgrenDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.ORCID https://orcid.org/0000-0003-0500-4070
Antros LoucaDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Erik AnderssonDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Therese DjärvDepartment of Clinical Medicine, Medicine Solna, Karolinska Institutet, Framstegsgatan, 171 64 Solna, Sweden.
Fredrik HessulfDepartment of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
Anna HenningssonDepartment of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
Andreas MartinssonDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Per NordbergCenter for Resuscitation Science, Department of Clinical Science and Education, Karolinska Institutets, Södersjukhuset, Jägargatan 20, staircase 1, 171 77 Stockholm, Sweden.
Adam PiaseckiDepartment of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
Vibha GuptaDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Zacharias MandalenakisDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.ORCID https://orcid.org/0000-0001-5093-9743
Amar TahaDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Bengt RedforsDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
Johan HerlitzDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.ORCID https://orcid.org/0000-0003-4139-6235
Araz RawshaniDepartment of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, staircase H, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Out-of-hospital cardiac arrest (OHCA) is a major health concern worldwide. Although one-third of all patients achieve a return of spontaneous circulation and may undergo a difficult period in the intensive care unit, only 1 in 10 survive. This study aims to improve our previously developed machine learning model for early prognostication of survival in OHCA. Methods and results: We studied all cases registered in the Swedish Cardiopulmonary Resuscitation Registry during 2010 and 2020 ( Conclusion: We improved our previous prediction model by creating a parsimonious model with an AUC ROC at 0.96, with excellent calibration and no apparent risk of underestimating survival in the critical probability range (0-10%). The model is available at www.gocares.se.

Indexed as

Extreme gradient boostingLightGBMMachine learningOut-of-hospital cardiac arrest

Identifiers

PMID38774371
PMCPMC11104459

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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.