Resource utilization associated with extracorporeal membrane oxygenation vs. microaxial flow pump for infarct-related cardiogenic shock
Bibliographic record
Abstract
AIMS: Microaxial flow pump and venoarterial extracorporeal membrane oxygenation (VA-ECMO) are increasingly used in infarct-related cardiogenic shock. This study provides a comparative overview of real-world resource utilization associated with these devices (PROSPERO: CRD42024505174). METHODS AND RESULTS: EMBASE, MEDLINE, and Cochrane Library were sought from inception to 13 November 2024 for studies reporting at least one primary outcome, including intensive care unit (ICU) length of stay (LOS), hospital LOS, in-hospital costs, and discharge destination. In-hospital mortality was included as secondary outcome. This study was guided by the PRISMA-2020 guideline. Study selection and data extraction were independently performed by two researchers. Risk-of-bias assessments were done using the Newcastle-Ottawa-Scale. Data were pooled using random-effect models. In total, 12 retrospective cohorts were identified encompassing 92 262 microaxial flow pump- and 16 474 VA-ECMO patients data. The meta-analysis of hospital LOS and in-hospital costs revealed favourable results for the microaxial flow pump, with mean differences (MD) of -5.3 days (95% CI: -6.6, -4.1) and -$113 983 (95% CI: -$143 153, -$84 812), respectively. Microaxial flow pump survivors were also 45% more likely to be discharged home (95% CI: 1.28-1.64). Intensive care unit-length of stay was reported by one study, reporting a 10 days MD in favour of the microaxial flow pump. The averaged in-hospital mortality rates were 44% and 57% for the microaxial flow pump and VA-ECMO, respectively. An inherent limitation of observational studies is confounding by indication. CONCLUSION: Microaxial flow pump was associated with lower resource utilization compared with VA-ECMO. Resource utilization should be incorporated in prospective RCTs and taken into account when considering these devices.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.016 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".