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Record W3097576650 · doi:10.1016/j.ophtha.2020.10.030

Evaluation of a New Model of Care for People with Complications of Diabetic Retinopathy

2020· article· en· W3097576650 on OpenAlexfundno aff
Noemi Lois, Jonathan Cook, Ariel Wang, S J Aldington, Hema Mistry, Mandy Maredza, Daniel F. McAuley, Tariq Aslam, Clare Bailey, Victor Chong, Faruque Ganchi, Peter H. Scanlon, Sobha Sivaprasad, David Steel, Caroline Styles, Augusto Azuara‐Blanco, Lindsay Prior, Norman Waugh, Ahmed Saad, Daniela Vaideanu-Collins, Christine McNally, Andrew Jackson, Rachael Rice, Clair Barbour, Leontia Bell, Faruque Ghanchi, Zeid Madanat, Geeta Menon, Manju Chandran, Sely Mathews, Omar Galal, Haralabos Eleftheriadis, Stefanos Efraimidis, William Sones, Nachiketa Acharya, Samia Fatum, Janette Savage, K. P. Ivanova, Zaria Ali

Bibliographic record

VenueOphthalmology · 2020
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
FundersHealth Technology Assessment ProgrammeDiabetes UKSheffield Teaching Hospitals NHS Foundation TrustUniversity of OxfordMoorfields Eye Hospital NHS Foundation TrustNational Institutes of HealthQueen's UniversityJames Cook UniversityNational Institute for Health and Care ResearchOxford University Hospitals NHS Foundation TrustUniversity Hospitals Bristol NHS Foundation TrustWellcome TrustCentral Manchester University Hospitals NHS Foundation Trust
KeywordsMedicineDiabetic retinopathyDiabetes mellitusFundus (uterus)Confidence intervalOphthalmologyRetinopathyProspective cohort studyOptometryPediatricsInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: The increasing diabetes prevalence and advent of new treatments for its major visual-threatening complications (diabetic macular edema [DME] and proliferative diabetic retinopathy [PDR]), which require frequent life-long follow-up, have increased hospital demands markedly. Subsequent delays in patient's evaluation and treatment are causing sight loss. Strategies to increase capacity are needed urgently. The retinopathy (EMERALD) study tested diagnostic accuracy, acceptability, and costs of a new health care pathway for people with previously treated DME or PDR. DESIGN: Prospective, multicenter, case-referent, cross-sectional, diagnostic accuracy study undertaken in 13 hospitals in the United Kingdom. PARTICIPANTS: Adults with type 1 or 2 diabetes previously successfully treated DME or PDR who, at the time of enrollment, had active or inactive disease. METHODS: A new health care pathway entailing multimodal imaging (spectral-domain OCT for DME, and 7-field Early Treatment Diabetic Retinopathy Study [ETDRS] and ultra-widefield [UWF] fundus images for PDR) interpreted by trained nonmedical staff (ophthalmic graders) to detect reactivation of disease was compared with the current standard care (face-to-face examination by ophthalmologists). MAIN OUTCOME MEASURES: Primary outcome: sensitivity of the new pathway. SECONDARY OUTCOMES: specificity; agreement between pathways; costs; acceptability; proportions requiring subsequent ophthalmologist assessment, unable to undergo imaging, and with inadequate images or indeterminate findings. RESULTS: The new pathway showed sensitivity of 97% (95% confidence interval [CI], 92%-99%) and specificity of 31% (95% CI, 23%-40%) to detect DME. For PDR, sensitivity and specificity using 7-field ETDRS images (85% [95% CI, 77%-91%] and 48% [95% CI, 41%-56%], respectively) or UWF images (83% [95% CI, 75%-89%] and 54% [95% CI, 46%-61%], respectively) were comparable. For detection of high-risk PDR, sensitivity and specificity were higher when using UWF images (87% [95% CI, 78%-93%] and 49% [95% CI, 42%-56%], respectively, for UWF versus 80% [95% CI, 69-88%] and 40% [95% CI, 34%-47%], respectively, for 7-field ETDRS images). Participants preferred ophthalmologists' assessments; in their absence, they preferred immediate feedback by graders, maintaining periodic ophthalmologist evaluations. When compared with the current standard of care, the new pathway could save £1390 per 100 DME visits and between £461 and £1189 per 100 PDR visits. CONCLUSIONS: The new pathway has acceptable sensitivity and would release resources. Users' suggestions should guide implementation.

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)0.017
metaresearch head score (Gemma)0.030
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.085
GPT teacher head0.356
Teacher spread0.271 · 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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Citations28
Published2020
Admission routes1
Has abstractno

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