Evidence map›Paper›PMID 39093430›Full record

ArticleMedizinische Klinik, Intensivmedizin und Notfallmedizin2025

Evaluation of score-based tertiary triage policies during the COVID-19 pandemic: simulation study with real-world intensive care data.

Christina C Bartenschlager, Jens O Brunner, Michael Kubiciel, Axel R Heller

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Article in Medizinische Klinik, Intensivmedizin und Notfallmedizin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Christina C BartenschlagerApplied Data Science in Healthcare, Nürnberg School of Health, Ohm University of Applied Sciences Nuremberg, 90489, Nürnberg, Germany. christina.bartenschlager@th-nuernberg.de.
Jens O BrunnerDecision Science in Healthcare, Department of Technology, Management, and Economics, Technical University of Denmark, Akademivej, Kongens Lyngby, 2800, Denmark.
Michael KubicielChair of German, European and International Criminal, Medical and Economic Law, University of Augsburg, Universitätsstraße 24, 86159, Augsburg, Germany.
Axel R HellerAnaesthesiology and Operative Intensive Care Medicine, Faculty of Medicine, University of Augsburg, University Hospital of Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe explicit prohibition of discontinuing intensive care unit (ICU) treatment that has already begun by the newly established German Triage Act in favor of new patients with better prognoses (tertiary triage) under crisis conditions may prevent saving as many patients as possible and therefore may violate the international well-accepted premise of undertaking the "best for the most" patients. During the COVID-19 pandemic, authorities set up lockdown measures and infection-prevention strategies to avoid an overburdened health-care system. In cases of situational overload of ICU resources, when transporting options are exhausted, the question of a tertiary triage of patients arises.

methodsWe provide data-driven analyses of score- and non-score-based tertiary triage policies using simulation and real-world electronic health record data in a COVID-19 setting. Ten different triage policies, for example, based on the Simplified Acute Physiology Score (SAPS II), are compared based on the resulting mortality in the ICU and inferential statistics.

resultsOur study shows that score-based tertiary triage policies outperform non-score-based tertiary triage policies including compliance with the German Triage Act. Based on our simulation model, a SAPS II score-based tertiary triage policy reduces mortality in the ICU by up to 18 percentage points. The longer the queue of critical care patients waiting for ICU treatment and the larger the maximum number of patients subject to tertiary triage, the greater the effect on the reduction of mortality in the ICU.

conclusionA SAPS II score-based tertiary triage policy was superior in our simulation model. Random allocation or "first come, first served" policies yield the lowest survival rates, as will adherence to the new German Triage Act. An interdisciplinary discussion including an ethical and legal perspective is important for the social interpretation of our data-driven results.

Indexed as

COVID-19Critical CareIntensive Care UnitsPandemicsTriageComputer SimulationGermanyHospital MortalityHumansSARS-CoV-2Intensive care unitPandemicsReal-world dataSimulationTriage

Identifiers

PMID39093430
PMCPMC12041167

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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.