MétaCan
Menu
Back to cohort
Record W4313472318 · doi:10.3390/pharmaceutics15010147

Management of Sjogren’s Dry Eye Disease—Advances in Ocular Drug Delivery Offering a New Hope

2022· review· en· W4313472318 on OpenAlexaff
Kevin Y. Wu, Wei T. Chen, Y-Kim Chu-Bédard, Gauri Patel, Simon D. Tran

Bibliographic record

VenuePharmaceutics · 2022
Typereview
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsMcGill UniversityUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineModalitiesDiseaseDrug deliveryDry eyesIntensive care medicineTreatment modalityDrugDermatologySurgeryPathologyOphthalmologyPharmacology

Abstract

fetched live from OpenAlex

Sjögren's syndrome is a chronic and insidious autoimmune disease characterized by lymphocyte infiltration of exocrine glands. Patients typically present with dry eye, dry mouth, and other systemic manifestations. Currently, the available molecules and drug-delivery systems for the treatment of Sjögren's syndrome dry eye (SSDE) have limited efficacy since they are not specific to SSDE but to dry eye disease (DED) in general. The current treatment modalities are based on a trial-and-error approach using primarily topical agents. However, this approach gives time for the vicious cycle of DED to develop which eventually causes permanent damage to the lacrimal functional unit. Thus, there is a need for more individualized, specific, and effective treatment modalities for SSDE. The purpose of this article is to describe the current conventional SSDE treatment modalities and to expose new advances in ocular drug delivery for treating SSDE. A literature review of the pre-clinical and clinical studies published between 2016 and 2022 was conducted. Our current understanding of SSDE pathophysiology combined with advances in ocular drug delivery and novel therapeutics will allow the translation of innovative molecular therapeutics from the bench to the bedside.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.065
GPT teacher head0.387
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations22
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePharmaceuticsSame topicOcular Surface and Contact LensFrench-language works237,207