Evidence map›Paper›PMID 26322336›Full record

ArticleJournal of neurology & translational neuroscience

Predicting Survival with Good Neurological Outcome Within 24 Hours Following Out of Hospital Cardiac Arrest:The Application and Validation of a Novel Clinical Score.

Aiham Albaeni, Shaker M Eid, Dhananjay Vaidya, Nisha Chandra-Strobos

Abstract read
In one paragraph

Article in Journal of neurology & translational neuroscience. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

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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

4 authors.

Aiham AlbaeniDivision of Hospital Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Shaker M EidDivision of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Dhananjay VaidyaDivision of Cardiology, Johns Hopkins Bayview Medical Center, USA.
Nisha Chandra-Strobos

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
NCATS NIH HHS UL1 TR001079
6 · The paper itself

Abstract

backgroundDespite 50 years of research, prognostication post cardiac arrest traditionally occurs at 72 hours. We tested the accuracy of a novel bedside score within 24 hours of hospital admission, in predicting neurologically intact survival.

methodsWe studied 192 adults following non-traumatic out-of-hospital cardiac arrest. In a 50% random modeling sample, a model for survival to discharge with good neurological outcome was developed using univariate analysis and stepwise multivariate logistic regression for predictor selection. The diagnostic efficiency of this modeled score was assessed in the remaining 50% sample using receiver operating characteristic (ROC) analysis.

resultsIn this study, 20% of patients survived to discharge with good neurological outcome. The final logistic regression model in the modeling sample retained three predictors: initial rhythm Ventricular Fibrillation, Return of Spontaneous Circulation ≤ 20 minutes from collapse, and Brainstem Reflex Score ≥ 3 within 24 hours. These variables were used to develop a three-point Out of Hospital Cardiac Arrest score. The area under the (ROC) curve was 0.84 [95% CI, 0.75-0.93] in the modeling sample and 0.92 [95% CI, 0.87-0.98] in the validation sample. A score ≥ 2 predicted good neurological outcome with a sensitivity of 79%, a specificity of 92%, and a negative predictive value of 93%. A score ≥1 had a sensitivity of 100% and a negative predictive value of 100%; however, the specificity was only 55%.

conclusionThis study demonstrates that a score based on clinical and easily accessible variables within 24 hours can predict neurologically intact survival following cardiac arrest.

Indexed as

Cardiopulmonary resuscitationHeart arrestPrognosisSudden deathSurvival

Identifiers

PMID26322336
PMCPMC4550201

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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.