Evidence map›Paper›PMID 34496748›Full record

Observational studyBMC anesthesiology2021

Circulatory trajectories after out-of-hospital cardiac arrest: a prospective cohort study.

Halvor Langeland, Daniel Bergum, Trond Nordseth, Magnus Løberg, Thomas Skaug, Knut Bjørnstad, Ørjan Gundersen, Nils-Kristian Skjærvold, Pål Klepstad

Registry-linked trialOpen access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC anesthesiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02648061 (Transitions Between Clinical Circulatory States After Out-of-hospital Cardiac Arrest), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 14% 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.

NCT02648061 completednot on this map

Transitions Between Clinical Circulatory States After Out-of-hospital Cardiac Arrest

TypeobservationalSponsorNorwegian University of Science and TechnologyRan2016 to 2017Enrolled50ConditionsOut-of-Hospital Cardiac Arrest
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. CytoSorbBiomedicines · 2026
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Halvor LangelandDepartment of Anesthesiology and Intensive Care Medicine, St. Olav's University Hospital, Trondheim, Norway. halvor.langeland@ntnu.no.
Daniel BergumDepartment of Anesthesiology and Intensive Care Medicine, St. Olav's University Hospital, Trondheim, Norway.
Trond NordsethInstitute of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Magnus LøbergClinical Effectiveness Research Group, Institute of Health and Society, University of Oslo, Oslo, Norway.
Thomas SkaugDepartment of Cardiology, St. Olav's University Hospital, Trondheim, Norway.
Knut BjørnstadDepartment of Cardiology, St. Olav's University Hospital, Trondheim, Norway.
Ørjan GundersenDepartment of Anesthesiology and Intensive Care Medicine, St. Olav's University Hospital, Trondheim, Norway.
Nils-Kristian SkjærvoldDepartment of Anesthesiology and Intensive Care Medicine, St. Olav's University Hospital, Trondheim, Norway.
Pål KlepstadDepartment of Anesthesiology and Intensive Care Medicine, St. Olav's University Hospital, Trondheim, Norway.
St Olav's University Hospital · NONorwegian University of Science and Technology · NOOslo University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCirculatory failure frequently occurs after out-of-hospital cardiac arrest (OHCA) and is part of post-cardiac arrest syndrome (PCAS). The aim of this study was to investigate circulatory disturbances in PCAS by assessing the circulatory trajectory during treatment in the intensive care unit (ICU).

methodsThis was a prospective single-center observational cohort study of patients after OHCA. Circulation was continuously and invasively monitored from the time of admission through the following five days. Every hour, patients were classified into one of three predefined circulatory states, yielding a longitudinal sequence of states for each patient. We used sequence analysis to describe the overall circulatory development and to identify clusters of patients with similar circulatory trajectories. We used ordered logistic regression to identify predictors for cluster membership.

resultsAmong 71 patients admitted to the ICU after OHCA during the study period, 50 were included in the study. The overall circulatory development after OHCA was two-phased. Low cardiac output (CO) and high systemic vascular resistance (SVR) characterized the initial phase, whereas high CO and low SVR characterized the later phase. Most patients were stabilized with respect to circulatory state within 72 h after cardiac arrest. We identified four clusters of circulatory trajectories. Initial shockable cardiac rhythm was associated with a favorable circulatory trajectory, whereas low base excess at admission was associated with an unfavorable circulatory trajectory.

conclusionCirculatory failure after OHCA exhibits time-dependent characteristics. We identified four distinct circulatory trajectories and their characteristics. These findings may guide clinical support for circulatory failure after OHCA.

trial registrationClinicalTrials.gov: NCT02648061.

Indexed as

Cardiac Output, HighCardiac Output, LowCohort StudiesFemaleHumansIntensive Care UnitsMaleMiddle AgedOut-of-Hospital Cardiac ArrestTime FactorsVascular ResistanceCirculationClusterHemodynamicOut-of-hospital cardiac arrestPost-cardiac arrest syndromeSequence analysis

Identifiers

PMID34496748
PMCPMC8424149
OpenAlexW3198814006

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.