Bedside Focused Echocardiography as Predictor of Survival in Cardiac Arrest Patients: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: The objective was to determine if focused transthoracic echocardiography (echo) can be used during resuscitation to predict the outcome of cardiac arrest. METHODS: A literature search of diagnostic accuracy studies was conducted using MEDLINE via PubMed, EMBASE, CINAHL, and Cochrane Library databases. A hand search of references was performed and experts in the field were contacted. Studies were included for further appraisal and analysis only if the selection criteria and reference standards were met. The eligible studies were appraised and scored by two independent reviewers using a modified quality assessment tool for diagnostic accuracy studies (QUADAS) to select the papers included in the meta-analysis. RESULTS: The initial search returned 2,538 unique papers, 11 of which were determined to be relevant after screening criteria were applied by two independent researchers. One additional study was identified after the initial search, totaling 12 studies to be included in our final analysis. The total number of patients in these studies was 568, all of whom had echo during resuscitation efforts to determine the presence or absence of kinetic cardiac activity and were followed up to determine return of spontaneous circulation (ROSC). Meta-analysis of the data showed that as a predictor of ROSC during cardiac arrest, echo had a pooled sensitivity of 91.6% (95% confidence interval [CI] = 84.6% to 96.1%), and specificity was 80.0% (95% CI = 76.1% to 83.6%). The positive likelihood ratio for ROSC was 4.26 (95% CI = 2.63 to 6.92), and negative likelihood ratio was 0.18 (95% CI = 0.10 to 0.31). Heterogeneity of the results (sensitivity) was nonsignificant (Cochran's Q: χ(2) = 10.63, p = 0.16, and I(2) = 34.1%). CONCLUSIONS: Echocardiography performed during cardiac arrest that demonstrates an absence of cardiac activity harbors a significantly lower (but not zero) likelihood that a patient will experience ROSC. In selected patients with a higher likelihood of survival from cardiac arrest at presentation, based on established predictors of survival, echo should not be the sole basis for the decision to cease resuscitative efforts. Echo should continue to be used only as an adjunct to clinical assessment in predicting the outcome of resuscitation for cardiac arrest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".