Fear associated with COVID-19 in neovascular age-related macular degeneration patients
Bibliographic record
Abstract
Purpose : Since the beginning of the COVID-19 pandemic, news related to the pandemic have created a feeling of fear, particularly among high-risk groups including elderly patients. We performed a prospective, cross-sectional study to assess the fear associated with COVID-19 and the fear of vision decrease related to the delay of treatment inneovascular age related macular degeneration patients (nAMD) during the pandemic. Methods : 160 actively treated nAMD patients were enrolled between September to November 2020 in a tertiary university hospital in Quebec, Canada. Exclusion criteria included: patients with memory disorders and patients with incomplete questionnaire. For each participant, demographic and clinical data were collected. The fear was rated in a questionnaire composed of two sections: the Fear of COVID-19 Scale (FCV-19S) and eight additional questions to assess ophthalmology-related COVID-19 statements. A multivariate linear regression model was built for FCV-19S score and a multivariable ordinal regression model for ophthalmology-related statements. Results : The mean level of FCV-19S was 17.05±4.38. In the multivariate analysis, it was significantly higher in women (p<0.001) and patients with elementary school level (compared to high school education level) (p=0.009). In the ophthalmology-related statements, 16% of patients feared vision loss because of difficulties in maintaining regular follow-ups during the pandemic. The female gender was significantly associated with a higher tendency to postpone their appointment (p=0.03) and to prefer “sacrificing” their vision to avoid contracting COVID-19 (p=0.05). No association was found between the patients' underlying nAMD characteristics (visual acuity, bilaterality, duration) and higher fear of vision loss. Conclusions : Despite the massive impact the pandemic has had on our functioning in most aspects of life, the anxiety related to COVID-19 and delaying ophthalmology treatments remained relatively low in nAMD patients. Greater explanations to address this fear may reduce anxiety level, especially among female patients and those with an elementary school education level.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".