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Prospective Evaluation of Teleophthalmology in Screening and Recurrence Monitoring of Neovascular Age-Related Macular Degeneration

2014· article· en· W2014335954 on OpenAlexaff
Bo Li, Anne-Marie Powell, Philip L. Hooper, Tom Sheidow

Bibliographic record

VenueJAMA Ophthalmology · 2014
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineMacular degenerationProspective cohort studyReferralRandomized controlled trialNeuro-ophthalmologyOphthalmologyClinical trialSurgeryInternal medicineGlaucoma

Abstract

fetched live from OpenAlex

IMPORTANCE: Teleophthalmology has the potential to reduce costs and inconveniences associated with frequent patient visits. Evaluating teleophthalmology in the management of age-related macular degeneration (AMD) will allow for future implementation of this technology. OBJECTIVE: To evaluate teleophthalmology as a tool for the screening and monitoring of neovascular AMD. DESIGN, SETTING, AND PARTICIPANTS: Prospective, randomized clinical trial that included 106 referral eyes for suspected neovascular AMD and 63 eyes with stable neovascular AMD. New referrals for patients with suspected neovascular AMD and patients with stable neovascular AMD were randomized into either routine or teleophthalmologic groups. In the routine group, patients received clinical assessment and diagnostic imaging at a tertiary hospital-based retina clinic. In the teleophthalmologic group, patients received basic examination and diagnostic imaging at a stand-alone teleophthalmologic site, where patient information and imaging studies were acquired and electronically sent over to tertiary hospital-based retina specialists. Patients in the teleophthalmologic group were called back to the tertiary treatment center if the teleophthalmologic data set suggested pathology or was inconclusive for diagnosis. MAIN OUTCOMES AND MEASURES: Patient wait times for diagnosis and/or treatment, referral accuracy, and visual outcome. RESULTS: For neovascular AMD screening, the average referral-to-diagnostic imaging time was 22.5 days for the teleophthalmologic group and 18.0 days for the routine group, for a difference of 4.5 days (95% CI, 11.8 to -2.8 days; P = .23). The average diagnostic imaging to treatment time was 16.4 days for the teleophthalmologic group and 11.6 days for the routine group, for a difference of 4.8 days (95% CI, 10.7 to -1.1 days; P = .11). For neovascular AMD monitoring, the average recurrence to treatment time was shorter for the routine group (0.04 days) compared with 13.6 days for the teleophthalmologic group, for a difference of -13.5 days (95% CI, -18.2 to -9.0 days; P < .01). There was no difference identified between end-of-study visual acuities in the 2 groups (P = .99). CONCLUSIONS AND RELEVANCE: A delay of referral to treatment time could not be identified when comparing teleophthalmologic screening for suspected neovascular AMD with retinal specialist-based screening. Teleophthalmologic monitoring for neovascular AMD recurrence resulted in longer wait times for treatment reinitiation, but no adverse visual outcomes were identified. TRIAL REGISTRATION: clinicaltrials.gov Identifier:NCT01581606.

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)0.014
metaresearch head score (Gemma)0.019
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 score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.341
Teacher spread0.301 · 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

Citations71
Published2014
Admission routes1
Has abstractyes

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