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Record W4205544583 · doi:10.3928/23258160-20211213-01

Sutured Scleral-Fixated Versus Anterior Chamber Intraocular Lens Implantation: A Meta-Analysis

2022· review· en· W4205544583 on OpenAlexaff
Anubhav Garg, Tsz Hin Alexander Lau, Marko M. Popovic, Peter J. Kertes, Rajeev H. Muni

Bibliographic record

VenueOphthalmic surgery, lasers & imaging retina · 2022
Typereview
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineOphthalmologyVisual acuitySubluxationIntraocular pressureMeta-analysisIncidence (geometry)Prospective cohort studyIntraocular lensSurgeryMathematicsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: No consensus exists on the comparative efficacy and safety of sutured scleral-fixated (SSF) and anterior chamber (AC) intraocular lens (IOL) implantation. We aim to compare outcomes of these two techniques. PATIENTS AND METHODS: A systematic literature search of MEDLINE, Embase, and Cochrane CENTRAL was conducted (2005 to 2020). Studies comparing SSFIOLs with ACIOLs were included. Outcomes included corrected distance visual acuity and complications. A meta-analysis was conducted with a random effects model. Weighted mean differences and risk ratios with 95% CIs were computed. RESULTS: Seven hundred eighty-three eyes from nine studies were included. SSFIOLs had a significantly higher absolute postoperative spherical equivalent (weighted mean difference, 0.32; 95% CI, 0.03 to 0.60; P = .03; low certainty) and incidence of IOL decentration/subluxation (risk ratio, 2.69; 95% CI, 1.03 to 7.01; P = .04; moderate certainty) than ACIOLs. There was no difference in final corrected distance visual acuity ( P = .26). CONCLUSIONS: SSFIOLs have a higher absolute postoperative spherical equivalent and incidence of IOL decentration/subluxation than ACIOLs. Future prospective studies are needed to confirm these findings. [ Ophthalmic Surg Lasers Imaging Retin a. 2022;53:12–21.]

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.643
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.014
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0200.000

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 head0.173
GPT teacher head0.365
Teacher spread0.192 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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