22: Mechanical circulatory support for cardiogenic shock: a network meta-analysis of randomised controlled trials and propensity score matched studies.
Bibliographic record
Abstract
Background: Cardiogenic shock is associated with high mortality. In refractory shock, it is unclear if mechanical circulatory support (MCS) devices improve survival. We conducted a systematic review and network meta-analysis to determine the impact of using various MCS devices in this population. Methods: We searched four databases through 1 March 2023 for eligible randomised controlled trials (RCTs) and propensity-score matched studies (PSMs). We conducted frequentist network meta-analysis, investigating mortality as the primary outcome. We assessed risk of bias using the Cochrane risk of bias 2.0 tool or Newcastle Ottawa Scale, and evaluated certainty in pooled estimates using the GRADE approach. As a sensitivity analysis, we reconstructed survival data from published survival curves, and conducted one-stage unadjusted IPD meta-analysis using a stratified Cox model. Results: We included 36 studies (48,297 patients), most reporting on patients with Society for Cardiovascular Angiography and Intervention shock stage (SCAI) C-E cardiogenic shock. Compared with no MCS, extracorporeal membrane oxygenation (ECMO) with intra-aortic balloon pump (ECMO-IABP; odds ratio [OR]: 0.60, 95%- confidence interval (CI): 0.37-0.98, moderate certainty) may be associated with lower mortality. There were no important differences in mortality using ECMO alone, microaxial ventricular assist device (mVAD) alone, IABP alone, centrifugal VAD alone, ECMO-mVAD, or mVAD-IABP (all very low certainty). One-stage IPD meta-analysis found only ECMO-IABP was associated with lower mortality (HR: 0.54, 95%-CI: 0.44-0.66). Conclusions: In patients with cardiogenic shock, ECMO-IABP may reduce mortality. Nonetheless, results for other MCS devices are based on very low to low certainty and require further confirmation from 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 | 0.034 | 0.081 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.050 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".