Abstract 16264: Ace-inhibitors and Vasoplegia in the Post Cabg Population/valvular Surgery Population: An Updated Systematic Review and Meta-analysis
Bibliographic record
Abstract
Introduction: Chronic use of ACE-i has been presented as a risk factor of post operative vasoplegia after cardiac surgery. However, a recent meta analysis of studies in the general cardiac surgery population identified renal failure as the only pre-operative risk factor for vasoplegia. We sought to systematically review the relationship of chronic ACE-i and vasoplegia in patients undergoing CABG /valve surgery. Hypothesis: Studies on vasoplegia after CABG / valve surgery were extracted by a research librarian (registered review CRD42017072923) before bias and quality of studies were assessed. We adjudicated vasoplegia as MAP < 60 mmHg and use of at least one non dopaminergic vasoactive drug up to 4 hours post operatively. Otherwise, studies reported vasoplegia as MAP < 60 mmHg, CI > 2.5 l/min/m2 and SVR < 600 dynes/sec/cm2 in the CSICU. We pooled the incidence of vasoplegia then completed a meta-analysis with random effect model using RevMan and Stata. Methods: Of the 2337 articles obtained (1940 non relevant, 22 reviews, 5 duplicates and 5 editorials), we pre-selected 365 abstracts and summarized data from 8,818 patients out of 7 articles selected after full text review. Results: All but one study looked at patients with LVEF > 40%. The pooled incidence of vasoplegia was 11.2% (95% CI 4.7-28.2). The OR of vasoplegia in patients on chronic ACE-i was 1.74 (95% CI: 1.47-2.06). We could not investigate the importance of pre-existing renal failure on the risk of post operative vasoplegia in patients on ACE-i. Accounting for substantial heterogeneity, the Egger test was in favour of small-study effects due to the number of cases of vasoplegia and the size of the cohorts studied (p=0.073). Conclusions: The risk of vasoplegia seems to be higher in patients on ACE-i undergoing CABG/valve surgery in this population. Two RCT's (161 patients) did not prove the benefit of temporary discontinuation of RAS blockade on the incidence of distributive shock during the first days after surgery. Because ACE-i are frequently prescribed in patients awaiting CABG, our work calls for larger and more elaborated studies to reduce the risk of vasoplegia.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.026 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".