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Record W1981580798 · doi:10.1097/ijg.0000000000000099

Priming the Ahmed Glaucoma Valve

2014· article· en· W1981580798 on OpenAlexaff
Jason Cheng, Milad Abolhasani, Laura Beltran-Agulló, Edward B. Moss, Yvonne M. Buys, Graham E. Trope

Bibliographic record

VenueJournal of Glaucoma · 2014
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPriming (agriculture)Intraocular pressureGlaucomaMedicineBiomedical engineeringAnesthesiaSurgeryOphthalmology

Abstract

fetched live from OpenAlex

PURPOSE: To determine the pressure required to prime an Ahmed Glaucoma Valve (AGV) and determine whether the valve can be damaged by "over-priming pressure." METHODS: Three AGVs, a syringe pump, and a manometer were used to assess priming pressure. Balanced salt solution was pumped through the AGV tube at increasing pressures until a jet of fluid was seen to eject from the AGV, as per manufacturer instructions. This was repeated 3 times for 3 different virgin AGVs giving the "priming pressure." A second experiment used the same experimental set up to determine the "over-priming pressure" on 3 other AGVs. Fluid was pumped through the AGV at increasing pressures until evidence of damage was seen. The valve function was assessed before and after the "over-priming" stress test. Valve function was determined by the closing pressure, which is the pressure at which the valve closes and fluid was no longer seen passing through the valve. RESULTS: The priming pressure in the 3 AGVs was 2844, 3154, and 3051 mm Hg (mean, 3017±158 mm Hg). The maximum pressure generated using the syringe pump was 10,860, 10,343, and 10,860 mm Hg (mean, 10,688±299 mm Hg). No damage was observed in the valve mechanism. AGV closing pressure before the "over-priming" stress test was 8, 6, and 13 mm Hg and after the stress test was 6, 7, and 13 mm Hg. CONCLUSION: This study demonstrates that the priming pressure is consistent at around 3000 mm Hg. In addition, over-priming is not likely to damage or disturb the closing pressure.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2014
Admission routes1
Has abstractyes

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