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Record W2899988560 · doi:10.17140/droj-4-138

Ocular Health Screening in a Type 1 Diabetes Mellitus Population

2018· article· en· W2899988560 on OpenAlexaboutno aff
Subhashini Chandrasekaran, Bernard C. Szirth, Kim Duong, Jim Stroud, Peter Khouri, Christopher Khouri, Kelly Soules

Bibliographic record

VenueDiabetes Research - Open Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusPopulationType 2 diabetesType 1 diabetesInternal medicineEndocrinologyEnvironmental health

Abstract

fetched live from OpenAlex

Background: Type 1 Diabetes Mellitus is among the most common conditions worldwide, affecting nearly 95 million children worldwide.One of the detrimental effects of this condition can be vision loss.Comprehensive annual ocular screenings can have an important role in early detection and management of vision-threatening complications.Over 2,200 family members and children with diabetes type 1 (www.childrenwithdiabetes.com)from Australia, Asia, Canada, Europe, Latin America and the United States of America attended an annual meeting where participants wishing to undergo a full ocular wellness screening had to pre-register for this weeklong activity.Methods: Sixteen (16) volunteer screeners made up of second year medical students, allied health care specialist, physician optometrist and ophthalmologist participated in this yearly event since 2007.Ocular wellness screening involved several stations where participants went through 8 stations, which included personal/family health history, visual acuity (Snellen visual chart), non-contact auto-tonometry for measurement of intra-ocular pressure, automated-refractor, and optical coherence tomography angiography (OCT and OCTA).The last station was a Canon non-mydriatic retinal camera used to acquire an anterior segment, as well as 45-degree fundus color and mono-chromatic auto fluorescence images (FAF).Results: Two hundred and sixteen (216) participants or 10% of the attendees (average age 21-years-old) underwent this screening event at the Disney Property in Orlando, Florida.Forty-one (41) participants had some retinal hemorrhages findings including microaneurysms, dot hemorrhages, flame hemorrhages and Intraretinal Microvascular Abnormalities (IrMa).Fifty-six (56) cases had varying levels of nuclear sclerosis.Three on-site readers evaluated all collected data and counseled families on findings.Participants with proliferative diabetic retinopathy findings or macular edema seen on OCT were referred to a remote off-site board-certified ophthalmologist through a secure line following Digital Imaging and Communications in Medicine (DICOM) and Health Insurance Portability and Accountability Act (HIPPA) protocols and recommended for further workup or treatment by the participant's eye-care professional.Conclusions: Creating a safe and comprehensive yearly ocular screening for children with type 1 diabetes mellitus along with a positive learning experience for can improve the lives of those living with type 1 diabetes and their families.Early detection, prevention and management of vision threatening diseases (VTDs) insures the affected individual can safeguard their vision.

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)0.003
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.117
GPT teacher head0.466
Teacher spread0.349 · 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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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