ArticleResuscitation2020
Data-driven classification of arrest location for emergency department cardiac arrests.
Article in Resuscitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Diagnostic Yield of CT Imaging and Point-of-Care Ultrasound After In-Hospital Cardiac Arrest.Chest · 2026Observational
- Brain computed tomography after resuscitation from in-hospital cardiac arrest.Resuscitation · 2024Article
- Article
- Development and Validation of a Novel Triage Tool for Predicting Cardiac Arrest in the Emergency Department.The western journal of emergency medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundResuscitation research is inconsistent in how emergency department (ED) arrests are classified. We tested whether clinical features of ED arrests more closely resembled out-of-hospital cardiac arrest (OHCA) or in-hospital cardiac arrest (IHCA).
methodsWe performed a retrospective study including all patients resuscitated from cardiac arrest at a single academic medical center from January 2010 to December 2019. We abstracted clinical information from our prospective registry. We used unsupervised learning (k-prototypes) to identify clusters within the OHCA and IHCA cohorts. We determined the number of subgroups using scree plots. We assigned individual ED arrest patients the nearest OHCA or IHCA cluster based on the shortest Gower distance from that patient to the nearest cluster center. In our secondary analysis, we determined the optimal number of clusters in each of the 3 arrest cohorts, and then calculated the mean Gower distances with the standard deviation (SD) between cluster centers (ED-IHCA, ED-OHCA, IHCA-OHCA).
resultsWe included 2723 patients: 372 (14%) ED arrests, 1709 (63%) OHCA, and 642 (23%) IHCA. We identified 3 clusters of OHCA patients, and 4 clusters of IHCA patients. Of ED arrest cases, 292 (78%) most closely resembled an IHCA cluster and 80 (22%) most closely resembled an OHCA cluster. Mean (SD) Gower distance between ED arrest and IHCA centers was 0.33 (0.2). Mean Gower distances between ED arrest-OHCA centers and between IHCA-OHCA centers were 0.41 (0.11).
conclusionAcross multiple aggregated measures, ED arrests resemble IHCA more than OHCA.
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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.