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Record W3123181185 · doi:10.18240/ijo.2021.02.20

Safety, effectiveness, and cost-effectiveness of Argus II in patients with retinitis pigmentosa: a systematic review

2021· review· en· W3123181185 on OpenAlexaboutno aff
Zakieh Ostad-Ahmadi, Mohammad-Reza Modabberi, Ali Mostafaie

Bibliographic record

VenueInternational Journal of Ophthalmology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicOcular Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVisual prosthesisArgusVisual acuityRetinitis pigmentosaProsthesisAdverse effectCost effectivenessMeta-analysisMEDLINEOptometrySurgeryOphthalmologyInternal medicineRetinal

Abstract

fetched live from OpenAlex

AIM: To assess the effectiveness, safety, and cost-effectiveness of the Argus II in treatment of the retinitis pigmentosa (RP) patients. METHODS: PubMed) were searched using combinations of the keywords of Argus, safety, effectiveness, bionic eye, retinal prosthesis, and RP through March 2018. The retrieved records were screened and then assessed for eligibility. RESULTS: Totally 926 records were retrieved from the searched databases and finally 12 studies included. The RP patients showed improvements in visual function after receiving the prosthesis, compared to the time before the prosthesis or the time it was off. This was measured by square localization, direction of motion, and grating visual acuity tests. No major adverse effect was reported for the Argus II prosthesis itself and/or the surgery to implement it, but the most frequently reported items were hypotony, and conjunctival dehiscence. The incremental cost-effectiveness ratio (ICER) was calculated to be €14603 per quality-adjusted life year (QALY) in UK and $207 616 per QALY in Canada. CONCLUSION: The available evidence shows that the Argus II prosthesis in RP patients is effective in improvement of their visual function. Some minor adverse effects are reported for the prosthesis. The cost-effectiveness studies show that the technology is cost-effective only at high levels of willingness-to-pay.

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)0.001
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.041
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.015
GPT teacher head0.330
Teacher spread0.315 · 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 designSystematic review
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

Citations12
Published2021
Admission routes1
Has abstractyes

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