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Record W4415489346 · doi:10.3390/life15111662

Impact of General Anesthetics on Postoperative Infections—A Narrative Review

2025· article· en· W4415489346 on OpenAlexaff
Lynn Jazzar, Palak Watts, Christine Lehmann

Bibliographic record

VenueLife · 2025
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNarrative reviewAnestheticVolatile anestheticReview articleImmune systemComplicationInflammatory responseMEDLINE

Abstract

fetched live from OpenAlex

Postoperative infections represent the most frequent complication after surgery. Anesthetic agents, while essential during surgical procedures to ensure unconsciousness, are becoming increasingly recognized as modulators of immune function. Volatile anesthetics have been identified as being able to attenuate the inflammatory response in diverse experimental models. Propofol, a widely used intravenous anesthetic, has also been described to exhibit strong anti-inflammatory mechanisms. This review synthesizes current cellular, experimental, and clinical evidence on the immunomodulatory effects of anesthetic agents, highlighting their impact on host defense mechanisms and postoperative infections. By exploring mechanistic properties and clinical outcomes, it underscores the importance of anesthetic choice in enhancing immune function and postoperative recovery.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.339
Teacher spread0.323 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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