Monitoring for neovascular age-related macular degeneration (AMD) reactivation at home: the MONARCH study
Bibliographic record
Abstract
AIMS: This study aims to quantify the diagnostic test-accuracy of three visual function self-monitoring tests for detection of active disease in patients with neovascular age-related macular degeneration (nAMD) when compared with usual care. An integrated qualitative study will investigate the acceptability of these home-based testing strategies. METHODS: All consenting participants are provided with an equipment pack containing an iPod touch with two vision test applications installed and a paper journal of reading tests. Participants self-monitor their vision at home each week with all three tests for 12-18 months. Usual care continues over this period. Key eligibility criteria are: age ≥50 years; at least one eye with AMD with ≥6-≤42 months since first AMD treatment; and vision not worse than Snellen 6/60, LogMAR 1.04 or 33 letters. The primary outcome, and reference standard, is diagnosis of active disease during usual care monitoring in the Hospital Eye Service. Secondary outcomes include duration of study participation, ability of participants to do the tests, adherence to weekly testing and acceptability of the tests to participants. CONCLUSIONS: Recruitment is in progress at five NHS centres. Challenges in procuring equipment, setting up the devices and transporting devices containing lithium batteries to participating sites delayed the start of recruitment. The study will describe the performance of the tests self-administered at home in detecting active disease compared to usual care monitoring. It will also describe the feasibility of the NHS implementing patient-administered electronic tests or similar applications at home for monitoring health.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".