MétaCan
Menu
Back to cohort
Record W4223970281 · doi:10.4330/wjc.v14.i4.250

Effect of preoperative renin-angiotensin system blockade on vasoplegia after cardiac surgery: A systematic review with meta-analysis

2022· review· en· W4223970281 on OpenAlexaff
Jean Jacques Noubiap, Brice Nouthé, Ying Tung Sia, Marco Spaziano

Bibliographic record

VenueWorld Journal of Cardiology · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsMcGill University Health CentreCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecUniversity of British Columbia
Fundersnot available
KeywordsMedicineOdds ratioInternal medicineMeta-analysisInotropeCardiologyRandomized controlled trial

Abstract

fetched live from OpenAlex

BACKGROUND: Vasoplegia is a common complication of cardiac surgery but its causal relationship with preoperative use of renin angiotensin system (RAS) blockers [angiotensin converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARB)] is still debated. AIM: To update and summarize data on the effect of preoperative use of RAS blockers on incident vasoplegia. METHODS: All published studies from MEDLINE, EMBASE, and Web of Science providing relevant data through January 13, 2021 were identified. A random-effects meta-analysis method was used to pool estimates, and post-cardiac surgery shock was differentiated from vasoplegia. RESULTS: 77%). Two randomized control trials (RCTs), not eligible for the meta-analysis, did not show an association between continuation of RAS blockers and vasoplegia. CONCLUSION: Preoperative continuation of ACEIs is associated with an increased need for inotropic support postoperatively and with an increased risk of vasoplegia in observational studies but not in RCTs. The absence of a consensus definition of vasoplegia should lead to the use of perioperative cardiovascular monitoring when designing RCTs to better understand this discrepancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.337
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0480.036
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.313
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of CardiologySame topicCardiac and Coronary Surgery TechniquesFrench-language works237,207