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Effect of Lens Base Curve on Subjective Comfort and Assessment of Fit with Silicone Hydrogel Continuous Wear Contact Lenses

2002· article· en· W2057201559 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptometry and Vision Science · 2002
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsKeratometerSilicone hydrogelLens (geology)Contact lensBase (topology)OphthalmologyMedicineSiliconeOptometryMaterials scienceOpticsMathematicsVisual acuityPhysicsComposite material

Abstract

fetched live from OpenAlex

PURPOSE: To study the effect of base curve on subjective comfort of silicone hydrogel extended wear lenses. METHODS: Ninety-five subjects were first trial fitted with 8.6-mm base curve lotrafilcon A (Focus Night & Day) lenses and then with 8.4-mm lenses only if poor subjective comfort or poor fit was present. Comfort and fit were assessed after 15 min. Subjects with discomfort or signs of poor fit were then trial fitted with 8.4-mm lenses. RESULTS: Of 190 eyes, 74.2% were fitted with 8.6-mm lenses, and 23.7% required 8.4-mm lenses. Two (2.1 %) subjects could not be fitted with either base curve. Mean steep keratometry (K) reading for eyes dispensed with 8.6-mm lenses was 43.88 D and 45.56 D for eyes dispensed in the 8.4-mm lenses (p < 0.001). CONCLUSIONS: A clinically useful criterion showing the need for 8.4-mm lenses was steep K of > or = 45.50 D; 77% of these eyes required the steeper lens for good comfort and fit. Subjective discomfort with 8.6-mm lenses was also a useful signal for the need of a steeper lens; mean comfort scores for those subjects rose from 6.33 with 8.6-mm lenses to 9.44 with the 8.4-mm lenses for eyes requiring the steeper lens (p < 0.001).

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.

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 score0.097
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.443
Teacher spread0.415 · 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