Virtual Assessment of Patients with Dry Eye Disease During the COVID-19 Pandemic: One clinician’s experience
Bibliographic record
Abstract
ABSTRACT Objectives To report on 1) the impact of DED on social, mental, and financial well-being, and 2) the use of virtual consultations to assess DED during the COVID-19 pandemic. Design & Methods An exploratory retrospective review of 35 charts. Telephone consultations for patients with DED conducted during the first lock-down period in Ontario in 2020 were reviewed. Results The most commonly reported DED symptoms were ocular dryness, visual disturbances, and burning sensation. The most common dry eye management practices were artificial tears, warm compresses, and omega-3 supplements. 20.0% of charts documented worsening of DED symptoms since the onset of the pandemic and 17.1% reported the lockdown had negatively affected their ability to perform DED management practices. 42.8% of patients reported an inability to enjoy their daily activities due to DED symptoms. 52.0% reported feeling either depressed, anxious, or both with 26.9% of patients accepting a referral to a social worker for counselling support. More than a quarter of the charts recorded financial challenges associated with the cost of therapy, and more than a fifth of patients reported that financial challenges were a direct barrier to accessing therapy. Conclusions Patients living with DED reported that their symptoms negatively affected their daily activities including mental health and financial challenges, that in turn impacted treatment practices. These challenges may have been exacerbated during the COVID-19 pandemic. Telephone consultations may be an effective modality to assess DED symptom severity, the impact of symptoms on daily functioning, and the need for counselling and support. AUTHOR SUMMARY Dry Eye Disease occurs when your tears do not provide enough lubrication for your eyes, which can be caused by either decreased tear production, or by poor quality tears. This study reviewed 35 patient charts to examine 1) the impact of Dry Eye Disease on patients’ well-being, and 2) the use of telephone appointments to assess Dry Eye Disease during the COVID-19 pandemic. Patients reported an inability to enjoy their daily activities due to symptoms of dry eye including burning sensation and blurred vision. Over half of patients reported mental health challenges. Over a quarter of patients reported that financial challenges prevented them from treating their Dry Eye Disease, such as affording eye drops, dietary supplements, and appointments to see their optometrist. These findings highlight that healthcare providers should considering quality of life, mental health, and financial challenges when treating patients with Dry Eye Disease. Through the experience of an ophthalmologist who specializes in Dry Eye Disease, telephone appointments may be an effective way to assess Dry Eye Disease symptoms, the impact of symptoms on daily functioning, and the need for counselling and support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".