Virtual Assessment of Patients with Dry Eye Disease During the COVID-19 Pandemic: One clinician’s experience
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».