Mechanical chest compression versus manual chest compression for cardiopulmonary resuscitation for cardiac arrest patients: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Cardiac arrest (CA) is high‐risk for death and hard to rescue. There are two methods of chest compression: mechanical and manual. However, it remains unclear which provides better outcomes for patients. Therefore, we perform a systematic review and meta‐analysis for the efficacy of the two methods for CA patients. Method Randomized controlled trials (RCTs) and nonrandomized controlled trials (non‐RCTs) were searched from the Cochrane Library, PubMed, EMBASE, and Web of Science from the date of their establishment to 2 March 2024. RCTs were evaluated using Cochrane randomized trial bias risk tool and the Newcastle–Ottawa Scale for non‐RCTs. All statistical analyses were performed using Stata v18.0 and Review Manager v5.4. Results Twenty‐four studies included 10 RCTs and 14 non‐RCTs, and 224,245 CA patients. Manual extracorporeal cardiopulmonary resuscitation (CPR) may benefit CA patients in achieving return of spontaneous circulation (ROSC) (odds ratio [OR] = 0.90; 95% CI: 0.813–0.996; Z = −2.04; p = 0.04), admission survival rate (OR = 0.87; 95% CI: 0.80–0.94; Z = −3.64; p < 0.05), and discharge survival rate (OR = 0.80; 95% CI: 0.66–0.98; Z = −2.21; p = 0.03). However, there was no significant difference in 30‐day survival rate (OR = 0.80; 95% CI: 0.43–1.48; Z = −0.72; p = 0.47), good restoration of neurologic functions (OR = 0.79; 95% CI: 0.60–1.05; Z = −1.46; p = 0.15), and complication rate (OR = 0.91; 95% CI: 0.47–1.75; Z = −0.29; p = 0.78). Conclusion Manual CPR showed advantages in ROSC, admission survival rate, and discharge survival rate, whereas there was no significant difference in 30‐day survival rate, good recovery of neurological function, and complication compared with mechanical chest compression. Compared with previous systematic reviews and meta‐analyses, this study is the first to report the advantages of manual CPR in ROSC. Large sample size and high‐quality RCTs are needed, as the existing evidence primarily comes from non‐RCTs.
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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 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".