DELAYED FOLLOW-UP IN PATIENTS WITH NEOVASCULAR AGE-RELATED MACULAR DEGENERATION TREATED UNDER UNIVERSAL HEALTH COVERAGE
Bibliographic record
Abstract
BACKGROUND/PURPOSE: To report the rate of delayed follow-up visits (DFU), to identify risk factors of DFU, and to assess the impact of DFU on outcomes in neovascular age-related macular degeneration. METHODS: This retrospective study included all patients with neovascular age-related macular degeneration (n = 1,291) treated with antivascular endothelial growth factor injections between January 2013 and December 2020 in 2 centers in Quebec, Canada. A DFU was defined as a delay of ≥4 weeks than scheduled. Visual outcomes, especially ≥15 letters loss, were reported. RESULTS: A total of 351 patients (27.2%) experienced ≥1 DFU. Odds were greater among older patients ( P = 0.005), patients treated at the hospital rather than the clinic ( P < 0.001), and patients with worse initial visual acuity ( P = 0.024). A DFU was associated with a mean visual acuity loss of 4.2 ± 13.4 letters ( P < 0.001) and an increased incidence of intraretinal fluid and subretinal fluid ( P = 0.001, P = 0.005) at 6 months despite resumption of injections. Central foveal thickness increased after DFU but returned to pre-DFU visit at 6 months. CONCLUSION: The DFU rate in patients with neovascular age-related macular degeneration treated under a universal health care system was around 27%. Delayed follow-up visits caused significant decreases in visual acuity and increases in intraretinal fluid and subretinal fluid on optical coherence tomography that did not recover after injections resumption despite normalization of central foveal thickness.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".