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Record W4412159602 · doi:10.1097/cce.0000000000001280

Effect of Inhaled Volatile and IV Anesthetics on Biological Markers of Inflammation in Adult ICU and Thoracic Surgical Patients: A Systematic Review and Meta-Analysis

2025· review· en· W4412159602 on OpenAlexaff
Soroush Rouhani, Sanchit Gupta, Hira Raheel, A. Gao, Ciara Hanley, Xingshan Cao, Alla Iansavitchene, Brian H. Cuthbertson, Marat Slessarev, Ewan C. Goligher, Aleksandra Leligdowicz, Douglas D. Fraser, Beverley A. Orser, Angela Jerath

Bibliographic record

VenueCritical Care Explorations · 2025
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsInstitute for Clinical Evaluative SciencesRobarts Clinical TrialsHealth Sciences CentreToronto General HospitalUniversity Health NetworkUniversity of TorontoLondon Health Sciences CentreSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsMeta-analysisMedicineInflammationVolatile anestheticAnesthesiaCardiothoracic surgeryIntensive care medicineInternal medicineSurgeryAnesthetic

Abstract

fetched live from OpenAlex

OBJECTIVES: Inhaled anesthetics may reduce alveolar and systemic inflammation in surgical and critically ill patients. This study aimed to perform a systematic review and meta-analysis comparing the effect of inhaled volatile and IV anesthetics on alveolar and plasma cytokines in patients with surgical or medical acute lung injury. DATA SOURCES: Medline, Embase, and Cochrane CENTRAL databases from 2000 to July 2021. STUDY SELECTION: Randomized control trials, prospective, and retrospective observational studies comparing inhaled volatile to IV anesthetics in ventilated adult patients with acute lung injury from lung resection or critical illness. DATA EXTRACTION: A systematic review and meta-analysis was performed. Primary outcome was alveolar inflammatory cytokines levels that were meta-analyzed using a random effects model. Secondary outcomes were plasma inflammatory cytokine levels, mortality, pulmonary complications, and duration of hospital and ICU stay. The quality of studies was assessed using the Cochrane Risk of Bias tool for randomized control trials and the Cochrane Risk Of Bias In Non-randomized Studies of Interventions tool for retrospective cohort studies. DATA SYNTHESIS: From 2522 screened studies, 28 (27 thoracic surgery and 1 ICU, n = 4175) were included. Meta-analysis of patients undergoing lung resection demonstrated lower levels of alveolar tumor necrosis factor-alpha (TNF-α) (standard mean difference 1.04; 95% CI, 0.32-1.77; p < 0.01; I2 82%) and interleukin (IL)-6 (0.64; 95% CI, 0.52-0.75; I2 0%; p < 0.01) at 1-2 hours in the inhaled anesthesia group, with no difference in other cytokines at various time points. The single ICU study demonstrated lower plasma TNF-α and IL-6 and alveolar TNF-α, IL-6, and IL-8 at 48 hours in patients sedated with sevoflurane compared with midazolam. Clinical outcomes were infrequently reported. CONCLUSIONS: Limited evidence suggests that inhaled anesthesia may reduce proinflammatory cytokines TNF-α and IL-6 during lung resection and critical illness. Further studies are needed to clarify its effects on biological markers and clinical outcomes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.034
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0250.051
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.396
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes1
Has abstractyes

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