Methylene blue for vasoplegic syndrome in cardiopulmonary bypass surgery: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: To evaluate the benefit of methylene blue as an adjunct treatment by assessing hemodynamic, morbidity rate, intensive care unit length of stay, and mortality rate outcomes in adult patients with vasoplegic syndrome. METHODS: A systematic search through electronic databases including Pubmed, Embase, Scopus, and Medline for studies assessing the use of methylene blue in patients with vasoplegic syndrome compared to control treatments. The Newcastle-Ottawa Scale tool was used for observational studies, and Jadad Scale was used for controlled trials to assess the risk of bias. RESULTS: This systematic review included six studies for qualitative synthesis and five studies for quantitative synthesis. Pooled analysis revealed that mean arterial pressure, systemic vascular resistance, heart rate, and hospital stay were not statistically significant in methylene blue administration compared to control. However, administration of methylene blue in vasoplegic syndrome patients significantly reduces renal failure (OR = 0.25; 95% CI = 0.08-0.75), development of multiple organ failure (OR = 0.09; 95% CI = 0.02-0.51), and mortality rate (OR = 0.12; 95% CI = 0.03-0.46). CONCLUSION: Adjunct administration of methylene blue for vasoplegic syndrome patients significantly reduces renal failure, multiple organ failure, and 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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.022 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".