Preoperative Intra-Aortic Balloon Pump in Patients Undergoing Coronary Bypass Surgery: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: To assess the effectiveness of preoperative intra-aortic balloon pump (IABP) placement in high-risk patients undergoing coronary bypass surgery (CABG). The primary outcome was hospital mortality and secondary outcomes were IABP-related complications (bleeding, leg ischemia, aortic dissection). METHODS: MEDLINE, EMBASE, Cochrane registry of Controlled Trials, and reference lists of relevant articles were searched. We included randomized controlled trials (RCTs), and cohort studies that fulfilled our a priori inclusion criteria. Eligibility decisions, relevance, study validity, and data extraction were performed in duplicate using pre-specified criteria. Meta-analysis was conducted using a random effects model. RESULTS: Ten publications fulfilled our eligibility criteria, of which four were RCTs and six were cohort studies with controls. There were statistical as well as clinical heterogeneity among included studies. A total of 1034 patients received preoperative IABP and 1329 did not receive preoperative IABP. The pooled odds ratio (OR) for hospital mortality in patients treated with preoperative IABP was 0.41 (95% CI, 0.21-0.82, p = 0.01). The number needed to treat was 17. The pooled OR for hospital mortality from randomized trials was 0.18 (95% CI, 0.06-0.57, p = 0.003) and from cohort studies was 0.54 (95% CI, 0.24-1.2, p = 0.13). Overall, 3.7% (13 of 349) of patients who received preoperative IABP developed either limb ischemia or haematoma at the IABP insertion site, and most of these complications improved after discontinuation of IABP. CONCLUSION: Evidence from this meta-analysis support the use of preoperative IABP in high-risk patients to reduce hospital mortality.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.003 | 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".