Evidence map›Paper›PMID 42831011›Full record

ArticleResuscitation plus2026

Validation and comparison of two prearrest prediction scores for in-hospital cardiac arrest survival.

Hritul Karim, Eva Piscator, Gabriel Riva, Karl Oskar Ekvall, Kasper G Lauridsen, Therese Djärv

Abstract read
In one paragraph

Article in Resuscitation plus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hritul KarimDepartment of Anesthesiology and Intensive Care, Capio S:t Görans Hospital, S:t Göransplan 1, 112 19 Stockholm, Sweden.
Eva PiscatorDepartment of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Gabriel RivaCentre for Resuscitation Science, Department of Clinical Science and Education KI/SÖS, Stockholm, Sweden.
Karl Oskar EkvallResearch Centre for Emergency Medicine, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark.
Kasper G LauridsenResearch Centre for Emergency Medicine, Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark.
Therese DjärvDepartment of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The optimal pre-arrest prediction model for survival with favorable neurological outcomes following in-hospital cardiac arrest (IHCA) to aid Do-Not-Attempt-Cardiopulmonary-Resuscitation-decisions remains uncertain. This study aimed to externally validate the Prediction of Outcome for In-Hospital Cardiac Arrest (PIHCA) score and the Good Outcome Following Attempted Resuscitation (GO-FAR) 2 score and compare their performance for IHCA survival prediction. Method: We collected data from IHCAs across three Swedish hospitals covering all care levels. We identified IHCAs through the Swedish Registry of Cardiopulmonary Resuscitation during 2015-2021 and extracted prediction model data through electronic medical records. Outcome measure was survival with favorable neurological survival defined as Cerebral Performance Category 1-2 at discharge, obtained from the registry. Prediction model performance was assessed with AUROC-curves (c-statistic), calibration coefficients and nonparametric calibration plots. Results: We identified 647 IHCAs of which 501 were eligible for inclusion. Overall, 28% had survival with favorable neurological outcome. AUROC for the PIHCA score was 0.73 (95% CI: 0.67-0.78), compared to 0.70 (95% CI: 0.65-0.75) for the GO-FAR 2 score. The 95% CI for difference of AUROC-score when PIHCA score was compared to GO-FAR 2 score was -0.01 to 0.06, i.e. not significant. The PIHCA score calibration coefficient was 0.69 (95% CI 0.51-0.88) compared to the GO FAR 2 score calibration coefficient of 1.02 (95% CI 0.73-1.34). The calibration plots were adequate for both scores, although with some degree of miscalibration at certain ranges for each model. Conclusion: PIHCA score and the GO-FAR 2 score performed well and comparatively for prediction of survival with favorable neurological outcome following IHCA in a Swedish setting. Both scores could be considered for clinical use, in addition to sound clinical judgment, where the PIHCA score seems more adapted for clinical use.

Indexed as

Decision-aidDecision toolDNARDNRPrediction modelRisk scoreWithhold Life-Sustaining Treatment (WLST)

Identifiers

PMID42831011
PMCPMC13634461

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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.