Caregiver Experience Survey of Anti-Vascular Endothelial Growth Factor Treatment for Diabetic Macular Edema and Neovascular Age-Related Macular Degeneration
Bibliographic record
Abstract
INTRODUCTION: Diabetic macular edema (DME) and neovascular age-related macular degeneration (nAMD) require frequent anti-vascular endothelial growth factor (VEGF) treatment and monitoring visits. We aimed to understand the burden of treatment on caregivers. METHODS: This multinational, noninterventional study used a cross-sectional survey of adult patients with DME or nAMD treated with anti-VEGF injections in the USA, Canada, France, Italy, Spain, and the UK. The survey assessed caregivers' sociodemographic characteristics, patient relationships, patients' clinical history and treatment experiences, caregivers' experiences, and the Caregiver Reaction Assessment of caregiving burden. RESULTS: Caregivers for patients with DME (n = 30) and nAMD (n = 95) completed surveys. Mean ± standard deviation (SD) age was 64.0 ± 13.4 years, and most were female (71.2%), white (70.4%), married (66.4%), and from Europe (67.2%). Most were caring for their mother/father or partner/spouse (85.6%). Mean ± SD length of time as a caregiver was 9.1 ± 10.0 years. Caregivers estimated they provided support for 4.2 ± 2.9 days/week and 6.0 ± 7.1 h/day on average. Nearly half of caregivers (45.6%) reported some impairment in daily activities, and more than two-thirds (70.5%) of working caregivers (n = 44) reported work absenteeism due to anti-VEGF treatment/monitoring appointments. At least one treatment barrier was reported by 66.7% and 50.5% of caregivers of patients with DME and nAMD, respectively, which were related to coronavirus disease 2019- (38.4%), clinic- (18.4%), social-/health- (13.6%), treatment- (10.4%), or financial-related factors (4.8%). Caregiver Reaction Assessment scores indicated mild-to-moderate burden, with higher caregiver schedule disruption scores associated with an increasing number of anti-VEGF treatment/monitoring visits among DME caregivers (r = 0.61). CONCLUSION: Caregivers devote substantial time to caregiving, leading to schedule disruptions and absenteeism for some working caregivers. Positive and negative impacts on caregiver mental health were reported.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".