The effect of low- and high-mean arterial pressure levels on short-term mortality in cardiac arrest and cardiogenic shock due to acute myocardial infarction: a meta-analysis
Bibliographic record
Abstract
Abstract Background/Introduction Optimal mean arterial pressure (MAP) in patients with acute myocardial infarction related out-of-hospital cardiac arrest (AMI-OHCA) and cardiogenic shock (AMI-CS) remains unclear. Randomized controlled trials (RCTs) comparing MAP targets have been performed in OHCA patients with presumed cardiac cause, but did not provide answers to the important question what MAP target would be optimal for the AMI-OHCA population. To our knowledge, no RCTs comparing MAP targets in AMI-CS patients have been performed. Purpose This comprehensive systematic review and meta-analysis aimed to evaluate the effect of low- and high-MAP levels on short-term mortality in AMI-OHCA and AMI-CS patients. Methods We conducted a systematic search of MEDLINE (OVID), EMBASE (OVID), CINAHL (Ebsco) and Cochrane CENTRAL databases. Eligible studies reported outcomes for AMI-OHCA or AMI-CS patients for at least two groups of different average MAP levels. Both RCTs and observational studies were eligible to ensure comprehensive data collection. Authors were proactively contacted for supplementary AMI data. Random-effects models were used to pool data. Results Of 7,728 screened studies, 57 were assessed for eligibility, and 11 were included in the final analysis (4 RCTs and 7 observational studies), encompassing 3,846 patients. The primary analysis included 1,251 AMI-OHCA patients. In the AMI-OHCA patients, no significant difference in short-term mortality was observed between low- and high-MAP groups in RCT (34.9% vs. 39.4%, RR 0.88, 95%-CI 0.70-1.10), observational-, and combined data. As only one of the 11 included studies reported on separate AMI-CS data, no meta-analyses of solely AMI-CS patients could be performed. Conclusions Our meta-analysis showed no significant difference in short-term mortality between low- and high-MAP levels in AMI-OHCA patients. Only one study in selected AMI-CS patients without OHCA patients was available. This highlights the importance of identifying tailored MAP strategies in both AMI-OHCA and AMI-CS patients.Flow chart of the selection of studies Short term mortality – AMI-OHCA patients
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.050 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".