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Record W4402455055 · doi:10.1213/ane.0000000000007000

Comparison of Clinical Performance of I-gel and Fastrach Laryngeal Mask Airway as an Intubating Device in Adults: A Systematic Review and Meta-Analysis

2024· review· en· W4402455055 on OpenAlexaff
Maria Luisa Machado Assis, Fabricio B. Zasso, Matheus Pedrotti Chavez, Eduardo Cirne Toledo, Gabriel Motta, Leonardo Duarte Moraes, Eric Pasqualotto, Rafael Oliva Morgado Ferreira, Naveed Siddiqui, Kong Eric You-Ten

Bibliographic record

VenueAnesthesia & Analgesia · 2024
Typereview
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicineIntubationAirway managementSubgroup analysisConfidence intervalMeta-analysisAnesthesiaAirwayRandomized controlled trialTracheal intubationLaryngeal MasksSurgeryLaryngeal mask airwayInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The supraglottic airway device (SGD) was introduced as a breakthrough in airway management. The Fastrach emerged as the first commercially available intubating SGD, drawing extensive investigation. I-gel is a more recent device that has gained popularity, can be used as an intubating SGD, and replaced Fastrach in many institutions. However, there is uncertainty regarding the comparison between these devices in terms of efficacy for intubation and ventilation, and safety in an airway rescue situation. METHODS: PubMed, EMBASE, Scopus, and Cochrane databases were searched for randomized controlled trials (RCTs) comparing I-gel and Fastrach SGD in adult patients undergoing intubation. The primary outcome was the first-pass success rate for tracheal intubation. Secondary outcomes were tracheal intubation time, SGD insertion time and success, and complications. We computed risk ratios (RRs) to assess binary end points and weighted mean differences (WMDs) for continuous outcomes, with corresponding 95% confidence intervals (CIs) for the primary outcome and its subgroup analysis ( P < .05 was considered statistically significant) and 99% CI after Bonferroni correction for the secondary outcomes ( P < .01 was considered statistically significant). RESULTS: This study included a total of 14 RCTs encompassing 1340 patients. The results indicated a significant difference in the first-pass success rate favoring Fastrach (RR, 0.81; 95% CI, 0.67-0.98; P = .03; I² = 91%). In the subgroup analysis, when a flexible scope was utilized through I-gel, providers achieved a better tracheal intubation first-pass success rate (RR, 1.05; 95% CI, 1.01-1.11; P = .03; I² = 0%), compared with the Fastrach. Overall intubation success rates (RR, 0.92; 99% CI, 0.82-1.04; P = .08, I² = 92%) and time (WMD - 1.03 seconds; 99% CI, -4.75 to 2.69; P = .48; I² = 84%) showed no significant difference irrespective of the device used. There was no significant difference regarding device insertion time by the providers (WMD -6.48 seconds; 99% CI, -13.23 to 0.27; P = .01; I 2 = 98%). Success rates of the providers' initial SGD insertion and complications such as sore throat (RR, 1.01; 99% CI, 0.65-1.57; P = .95, I² = 33%) and blood presence post-SGD removal (RR, 0.89; 99% CI, 0.42-1.86; P = .68, I² = 0%) showed no significant difference. CONCLUSIONS: Based on our findings, a higher first-pass success rate was observed with the use of Fastrach when compared to I-gel. However, the use of I-gel might result in a better intubation success rate with the flexible scope-guided intubation. There are no significant differences in performance in terms of the success rate for intubation overall, time for device insertion, or time to intubation or complications regardless of the device used.

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)0.010
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0210.033
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
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 head0.121
GPT teacher head0.454
Teacher spread0.333 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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