Chest Compression Fraction Determines Survival in Patients With Out-of-Hospital Ventricular Fibrillation
Bibliographic record
Abstract
BACKGROUND: Quality cardiopulmonary resuscitation contributes to cardiac arrest survival. The proportion of time in which chest compressions are performed in each minute of cardiopulmonary resuscitation is an important modifiable aspect of quality cardiopulmonary resuscitation. We sought to estimate the effect of an increasing proportion of time spent performing chest compressions during cardiac arrest on survival to hospital discharge in patients with out-of-hospital ventricular fibrillation or pulseless ventricular tachycardia. METHODS AND RESULTS: This is a prospective observational cohort study of adult patients from the Resuscitation Outcomes Consortium Cardiac Arrest Epistry with confirmed ventricular fibrillation or ventricular tachycardia, no defibrillation before emergency medical services arrival, electronically recorded cardiopulmonary resuscitation before the first shock, and a confirmed outcome. Patients were followed up to discharge from the hospital or death. Of the 506 cases, the mean age was 64 years, 80% were male, 71% were witnessed by a bystander, 51% received bystander cardiopulmonary resuscitation, 34% occurred in a public location, and 23% survived. After adjustment for age, gender, location, bystander cardiopulmonary resuscitation, bystander witness status, and response time, the odds ratios of surviving to hospital discharge in the 2 highest categories of chest compression fraction compared with the reference category were 3.01 (95% confidence interval 1.37 to 6.58) and 2.33 (95% confidence interval 0.96 to 5.63). The estimated adjusted linear effect on odds ratio of survival for a 10% change in chest compression fraction was 1.11 (95% confidence interval 1.01 to 1.21). CONCLUSIONS: An increased chest compression fraction is independently predictive of better survival in patients who experience a prehospital ventricular fibrillation/tachycardia cardiac arrest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".