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Record W1964144698 · doi:10.1167/3.12.18

Astigmatism and emmetropization in a native american population

2010· article· en· W1964144698 on OpenAlexaboutno aff
J. M. Mïller, J. Daniel Twelker, D. Sherrill, E. M. Harvey

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAutorefractorAstigmatismRefractive errorOdds ratioOddsOptometryDemographyPopulationMedicineOphthalmologyEye diseaseLogistic regressionPhysicsOpticsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Previous research has shown a high prevalence of astigmatism among preschool-age, school-age, and adult members of some Native American tribes (1,2). Data from cross-sectional studies indicate that prevalence of astigmatism decreases or remains stable during the school years in some tribal groups (3–5). However, longitudinal data are needed to determine whether emmetropization of astigmatism occurs. Subjects in the present study were 208 three- to five-year-old children who were participants in the Tohono O'Odham Nation's Head Start program. Each child had cycloplegic refractive error measured with the Nikon Retinomax K-Plus autorefractor on at least three occasions during two academic years. For each child's dataset, an estimate of slope was calculated and compared statistically to a slope of zero (6,7). Results showed that the 69 subjects with high baseline astigmatism (>1.50 D) were more likely than the 139 subjects with low astigmatism (<1.50 D) to have decreasing (odds ratio=1.68, p=0.003) or increasing (odds ratio=1.39, p=0.002) slopes over time. However, most subjects (63.8% of the high astigmats and 87.8% of the low astigmats) showed no change in amount of astigmatism over time. Average change was 0.04 D/year (SD 0.36) in the high astigmatism group, compared to 0.02 D/year (SD 0.18) in the low astigmatism group, which was not a significant difference. Thus, we found little evidence for emmetropization of astigmatism during the preschool years. Follow-up of refractive error development in this population of children during elementary school is in progress, and data will be presented concerning whether the failure of emmetropization seen in the preschool years continues as children get older. 1. MillerJ.M.DobsonV.HarveyE.M.SherrillD.L.(2000). Astigmatism and amblyopia among Native American children (AANAC): Design and methods. Ophthalmic Epidemiology, 7, 187–207. 2. GossD.A.(1990). Astigmatism in American Indians: prevalence, descriptive analysis, and management issues. In: GossD.A.EdmondsonL.L., editors. Eye and Vision Conditions in the American Indian. Yukon, OKPueblo Publishing Press, pp. 61–76. 3. AbrahamJ.E.VolovickJ.B.(1072). Preliminary Navajo optometric study. Journal of the American Optometric Association, 43, 1257–1260. 4. HamiltonJ.E.(1976). Vision anomalies of Indian school children: the Lame Deer study. Journal of the American Optometric Association, 47, 479–487. 5. DobsonV.MillerJ.M.HarveyE.M.SherrillD.L.(1999). Prevalence of astigmatism, astigmatic anisometropia, and glasses wearing among preschool- and school-age Native American children. In Vision Science and Its Applications, Vol. 1, OSA Tec 6. MillerJ.M.SherrillD.L.DobsonV.HarveyE.M.(2003). Stability of spherical equivalent refraction in Native American preschool children. Presentation at Association for Research in Vision and Ophthalmology, Annual Meeting, Fort Lauderdale, 7. DobsonV.MillerJ.M.SherrillD.L.HarveyE.M.(2003). Stability of astigmatism in Native American preschool children. Presentation at Association for Research in Vision and Ophthalmology. Presentation at Association for Research in Vision and Ophthalmology, Annual Meeting, Fort Lauderdale, Florida, May 4–9,

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.385
Teacher spread0.370 · 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 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".

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Citations2
Published2010
Admission routes1
Has abstractyes

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