Do Out‐of‐Hospital Cardiac Arrest Patients Have Increased Chances of Survival When Transported to a Cardiac Resuscitation Center?
Bibliographic record
Abstract
Background Patients suffering from an out-of-hospital cardiac arrest are often transported to the closest hospital. Although it has been suggested that these patients be transported to cardiac resuscitation centers, few jurisdictions have acted on this recommendation. To better evaluate the evidence on this subject, a systematic review and meta-analysis of the currently available literature evaluating the association between the destination hospital's capability (cardiac resuscitation center or not) and resuscitation outcomes for adult patients suffering from an out-of-hospital cardiac arrest was performed. Methods and Results PubMed, EMBASE , and the Cochrane Library databases were first searched using a specifically designed search strategy. Both original randomized controlled trials and observational studies were considered for inclusion. Cardiac resuscitation centers were defined as having on-site percutaneous coronary intervention and targeted temperature management capability at all times. The primary outcome measure was survival. Twelve nonrandomized observational studies were retained in this review. A total of 61 240 patients were included in the 10 studies that could be included in the meta-analysis regarding the survival outcome. Being transported to a cardiac resuscitation center was associated with an increase in survival (odds ratio=1.95 [95% confidence interval 1.47-2.59], P<0.001). Conclusions Adult patients suffering from an out-of-hospital cardiac arrest transported to cardiac resuscitation centers have better outcomes than their counterparts. When possible, it is reasonable to transport these patients directly to cardiac resuscitation centers (class II a, level of evidence B, nonrandomized). Clinical Trial Registration URL : www.crd.york.ac.uk/PROSPERO/ . Unique identifier: CRD 42018086608.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".