Development and Validation of a Diabetic Retinopathy Screening Modality Using a Hand-Held Nonmydriatic Digital Retinal Camera by Physician Graders at a Tertiary-Level Medical Clinic: Protocol for a Validation Study
Bibliographic record
Abstract
BACKGROUND: Visual impairment and blindness from diabetic retinopathy (DR), which can be reduced by early screening and treatment, is an emerging public health concern in low-income and middle-income countries (LMICs) owing to the increasing prevalence of diabetes mellitus (DM). However, no systematic screening exists in most LMIC settings. The Western province of Sri Lanka has the highest prevalence of DM (18.6%) in the country. A situational analysis identified a marked gap in DR screening (DRS) and treatment services uptake in this region; only opportunistic screening is practiced currently. OBJECTIVE: The aim of this protocol is to describe the methods of development and validation of a DRS intervention using a hand-held nonmydriatic digital camera by physician graders in a non-ophthalmological setting at a tertiary-level medical clinic to propose a valid and feasible modality to improve uptake. METHODS: DRS modality was developed after assessing barriers and identifying the most appropriate personnel, methods, and location for screening services, following formative research work. The validation will be conducted in a public sector tertiary care center in the Western province of Sri Lanka. The selected physicians will be trained on capturing and grading images according to a valid locally adopted protocol. Two physicians rated high on training will screen a sample of 506 people with DM at a medical clinic. They will use nonmydriatic and mydriatic 2-field imaging strategy. The validity of the proposed screening procedure will be assessed and compared with the mydriatic indirect biomicroscopic examination by a senior retinologist. RESULTS: The validity of screening by physician graders will be analyzed and the sensitivity, specificity, and predictive values (with 95% CIs) calculated by the dilation status and for each grader. The diagnostic accuracy at each level of severity of DR will be assessed to define the most appropriate referable criteria. Data is currently being collected. CONCLUSIONS: The outcome of this study will be useful for the detection of a defined level of DR at non-ophthalmological setting to filter the people with DM before referral to an eye clinic. This will be helpful to improve the uptake and identify risk groups in advance to prevent sight-threatening DR. Furthermore, evidence from this study will be useful for the implementation of a DRS program in this region and in similar communities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/10900.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".