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Record W2767841454

A Systematic Review and Meta-Analysis of Intravenous Sedation in Modern Cataract Surgery

2017· review· en· W2767841454 on OpenAlexaff
Efstathia Kiatos

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typereview
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsWestern University
Fundersnot available
KeywordsIntravenous sedationMedicineCataract surgeryMeta-analysisSedationAnesthesiaSurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Phacoemulsification is a surgical technique in which a cataract is extracted and replaced with an intraocular lens implant. This can be done under intravenous sedation, oral sedation, or no sedation, in addition to local anesthetic techniques. The purpose of this systematic review and meta-analysis is to assess the effectiveness of intravenous sedation versus non-intravenous sedation methods. Results found that intravenous sedation was significantly associated with a decrease in pain when compared to non- intravenous methods (SMD = -0.86, 95% CI 1.49 to -0.23, p=0.0008) (WMD = -1.01, 95% CI -1.66 to -0.36, p=0.002). The subgroup analysis found patients did not have a statistically significant reduction in pain when using intravenous sedation over oral sedation. The meta-analysis of perioperative complications found that intravenous sedation did not have a statistically significant increase in adverse events when compared to non-intravenous anesthesia techniques. These findings could inform policy and help develop definitive guidelines for sedation and anesthesia strategies during phacoemulsification.

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)0.007
metaresearch head score (Gemma)0.023
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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.024
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.345
GPT teacher head0.408
Teacher spread0.063 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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