ArticleIntensive care medicine2020
Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest.
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.
What it found
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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.
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.
The Effect of SPecialty cAre on Recovery From Cardiac Arrest Trial (the SPARC Trial)
Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 102 citations in OpenAlex.
- European Resuscitation Council and European Society of Intensive Care Medicine guidelines 2025: post-resuscitation care.Intensive care medicine · 2025Guideline
- Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest.Neurocritical care · 2023Guideline
- Prediction of good neurological outcome in comatose survivors of cardiac arrest: a systematic review.Intensive care medicine · 2022Pooled it
- Review
- Neuroprognostication after cardiac arrest in patients without withdrawal of life-sustaining therapy: a prospective observational multicenter study.Critical care (London, England) · 2026Observational
- 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 · 2026Review
- How much information is needed to predict outcomes after cardiac arrest?Resuscitation · 2025Article
- Estimating bias from withdrawal of life sustaining treatment in clinical trials.Critical care (London, England) · 2025Review
- Post-Coma Neurorehabilitation: Neurophysiological Assessment as an Additional Strategic and Essential Competence for the Physiatrist.Journal of personalized medicine · 2025Review
- System for Predicting Neurological Outcomes Following Cardiac Arrest Based on Clinical Predictors Using a Machine Learning Method: The Neurological Outcomes After Cardiac Arrest Method.Neurocritical care · 2025Article
- Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest.Resuscitation plus · 2024Review
- Alteration in early resting‑state functional MRI activity in comatose survivors of cardiac arrest: a prospective cohort study.Critical care (London, England) · 2024Observational
- Performance of the MRI lesion pattern score in predicting neurological outcome after out of hospital cardiac arrest: a retrospective cohort analysis.Critical care (London, England) · 2024Article
- Neuroimmune activation is associated with neurological outcome in anoxic and traumatic coma.Brain : a journal of neurology · 2024Article
- The capacity of neurological pupil index to predict the absence of somatosensory evoked potentials after cardiac arrest - An observational study.Resuscitation plus · 2024Article
- Normal value of neuron-specific enolase for predicting good neurological outcomes in comatose out-of-hospital cardiac arrest survivors.PloS one · 2024Observational
- Review
- Combination strategy for prognostication in patients undergoing post-resuscitation care after cardiac arrest.Scientific reports · 2023Article
- Additional predictive value of optic nerve sheath diameter for neurological prognosis after cardiac arrest: a prospective cohort study.The ultrasound journal · 2023Article
- Novel serum biomarkers for predicting neurological outcomes in postcardiac arrest patients treated with targeted temperature management.Critical care (London, England) · 2023Observational
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Authors and funding
16 authors at 5 institutions in 3 countries.
Funding
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.
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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.