Evidence map›Paper›PMID 32494928›Full record

ArticleIntensive care medicine2020

Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest.

Marion Moseby-Knappe, Erik Westhall, Sofia Backman, Niklas Mattsson-Carlgren, Irina Dragancea, Anna Lybeck, Hans Friberg, Pascal Stammet, Gisela Lilja, Janneke Horn and 6 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Intensive care medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07002294 (The Effect of SPecialty cAre on Recovery From Cardiac Arrest Trial), which is not on this map. Cited by 35 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 3 pooled it
13.5field-weighted citation impact, top 1% 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.

NCT07002294 narecruitingnot on this mapstarted 2026, after this paper: background citation

The Effect of SPecialty cAre on Recovery From Cardiac Arrest Trial (the SPARC Trial)

TypeinterventionalSponsorUniversity of PittsburghRan2026 to 2032Enrolled1,618ConditionsCardiac Arrest (CA), Heart Arrest, Heart Arrest, Out-Of-HospitalArmsTransfer to specialty care, Usual care
3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 102 citations in OpenAlex.

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  6. ECMO-Assisted In-Situ Normothermic Perfusion for Donation After Circulatory Determination of Death Kidney Transplantation: A Narrative Review.Medical science monitor : international medical journal of experimental and clinical research · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 3 countries.

Marion Moseby-KnappeDepartment of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Getingevägen 4, 222 41, Lund, Sweden. marion.moseby_knappe@med.lu.se.ORCID http://orcid.org/0000-0001-8160-5957
Erik WesthallDepartment of Clinical Sciences Lund, Clinical Neurophysiology, Skane University Hospital, Lund University, Lund, Sweden.
Sofia BackmanDepartment of Clinical Sciences Lund, Clinical Neurophysiology, Skane University Hospital, Lund University, Lund, Sweden.
Niklas Mattsson-CarlgrenDepartment of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Getingevägen 4, 222 41, Lund, Sweden.
Irina DraganceaDepartment of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Getingevägen 4, 222 41, Lund, Sweden.
Anna LybeckDepartment of Clinical Sciences Lund, Anaesthesia and Intensive Care, Skane University Hospital, Lund University, Lund, Sweden.
Hans FribergDepartment of Clinical Sciences Lund, Anaesthesia and Intensive Care, Skane University Hospital, Lund University, Malmö, Sweden.
Pascal StammetMedical and Health Department, National Fire and Rescue Corps, Luxembourg, Luxembourg.
Gisela LiljaDepartment of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Getingevägen 4, 222 41, Lund, Sweden.
Janneke HornDepartment of Intensive Care, Amsterdam UMC, Location Academic Medical Center, Amsterdam, The Netherlands.
Jesper KjaergaardDepartment of Cardiology, Rigshospitalet and Department of Clinical Medicine,, University of Copenhagen, Copenhagen, Denmark.
Christian RylanderDepartment of Anaesthesiology and Intensive Care Medicine, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Christian HassagerDepartment of Cardiology, Rigshospitalet and Department of Clinical Medicine,, University of Copenhagen, Copenhagen, Denmark.
Susann UllénClinical Studies Sweden - Forum South, Skane University Hospital, Lund, Sweden.
Niklas NielsenDepartment of Clinical Sciences Lund, Anaesthesia and Intensive Care, Helsingborg Hospital, Lund University, Lund, Sweden.
Tobias CronbergDepartment of Clinical Sciences Lund, Neurology, Skåne University Hospital, Lund University, Getingevägen 4, 222 41, Lund, Sweden.
Lund University · SEUniversity of Copenhagen · DKAmsterdam UMC Location University of Amsterdam · NLSkåne University Hospital · SEUniversity of Gothenburg · SE

Funding

AFA Försäkring 100001Hjärt-Lungfonden 20090275Hjärt-Lungfonden 20120491Swedish National Health System 353301Swedish National Health System M2010/1641Swedish National Health System M2010/1837Vetenskapsrådet 20133572
6 · The paper itself

Abstract

purposeTo assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM).

methodsRetrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72-96 h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3-5. Variations of the ERC/ESICM algorithm were explored within the same cohort.

resultsThe ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1-44.7) and 100% specificity (95% CI 98.8-100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7-48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8-100) remaining.

conclusionThe ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6-42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies.

Indexed as

Hypothermia, InducedOut-of-Hospital Cardiac ArrestAlgorithmsHumansPhosphopyruvate HydratasePrognosisRetrospective StudiesPhosphopyruvate HydrataseCardiac arrestComaGuideline algorithmPrognostic accuracyPrognostication

Identifiers

PMID32494928
PMCPMC7527324
OpenAlexW3028869006

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Registered trials

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.