ReviewF1000Research2019
Recent advances in personalizing cardiac arrest resuscitation.
Review in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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
8 citing papers in PubMed.
- Current and emerging innovations in technology, strategy, and artificial intelligence: a new era in cardiac arrest and cardiopulmonary resuscitation.World journal of emergency medicine · 2025Article
- Local DEA app: Saving lives with accessible and well-located automated external defibrillators.PloS one · 2025Article
- Efficacy of mechanical against manual method in cardiopulmonary resuscitation for out‑of‑hospital cardiac arrest: A meta‑analysis.Experimental and therapeutic medicine · 2024Article
- Differential Effects of Targeted Temperature Management on Sex-Dependent Outcomes After Experimental Asphyxial Cardiac Arrest.Therapeutic hypothermia and temperature management · 2024Article
- What factors are effective on the CPR duration of patients under extracorporeal cardiopulmonary resuscitation: a single-center retrospective study.International journal of emergency medicine · 2024Article
- Convolution Neural Network Algorithm for Shockable Arrhythmia Classification Within a Digitally Connected Automated External Defibrillator.Journal of the American Heart Association · 2023Article
- Utilizing community level factors to improve prediction of out of hospital cardiac arrest outcome using machine learning.Resuscitation · 2022Article
- Cerebral protection of epigallocatechin gallate (EGCG) via preservation of mitochondrial function and ERK inhibition in a rat resuscitation model.Drug design, development and therapy · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiac arrest remains a significant cause of death and disability throughout the world. However, as our understanding of cardiac arrest and resuscitation physiology has developed, new technologies are fundamentally altering our potential to improve survival and neurologic sequela. Some advances are relatively simple, requiring only alterations in current basic life support measures or integration with pre-hospital organization, whereas others, such as extra-corporeal membrane oxygenation, require significant time and resource investments. When combined with consistent rescuer and patient-physiologic monitoring, these innovations allow an unprecedented capacity to personalize cardiac arrest resuscitation to patient-specific pathophysiology. However, as more extensive options are established, it can be difficult for providers to incorporate novel resuscitation techniques into a cardiac arrest protocol which can fit a wide variety of cases with varying complexity. This article will explore recent advances in our understanding of cardiac arrest physiology and resuscitation sciences, with particular focus on the metabolic phase after significant ischemia has been induced. To this end, we establish a practical consideration for providers seeking to integrate novel advances in cardiac arrest resuscitation into daily practice.
Indexed as
Identifiers
What OpenQuestion holds
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.