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Record W4417495661 · doi:10.2196/84240

Central Nervous System Mechanisms and Treatment Response in Chronic Ocular Surface Pain: Protocol for a Cross-Sectional Observational Phenotyping Study

2025· article· en· W4417495661 on OpenAlexvenueno aff
Lindsey B. De Lott, Steven E. Harte, Chelsea Kaplan, Roni M. Shtein, Maria A. Woodward, Alexander Tsodikov, Tatiana Deveney, Anat Galor, Clare McKolay, Kathy Scott, Daniel J. Clauw

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsnot available
Fundersnot available
KeywordsCentral nervous systemObservational studyProtocol (science)Component (thermodynamics)Clinical trial

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic ocular surface pain (COSP), occurring either in isolation or as part of numerous ocular conditions, such as dry eye syndrome, is a leading cause of eye care visits in the United States. Conventional treatments directed at the ocular surface-the perceived pain source-are often inadequate for pain relief. We hypothesize that some individuals with COSP are experiencing symptoms driven by central nervous system (CNS) dysfunction, similar to chronic overlapping pain conditions, rather than solely pathological problems in the eye. Some individuals with chronic overlapping pain conditions (eg, fibromyalgia) show evidence of nociplastic pain mechanisms, where the pain results from amplified or dysregulated CNS signaling and sensory processing. Although data exist suggesting the presence of nociplastic pain features in COSP, there is a need for comprehensive studies. OBJECTIVE: Our aim is to rigorously define the role of nociplastic pain in COSP with a large, representative cohort of 200 participants with COSP using established clinical, neurobiological, and treatment response features. We propose that as sign and symptom discordance increases, features indicative of nociplastic pain will also increase. METHODS: In aim 1, we will clinically phenotype participants with COSP, using validated patient-reported outcome measures and standard ocular exams. In aim 2, we will compare the neurobiological features of nociplastic pain across the discordance spectrum among a subset of aim 1 participants using multimodal evoked sensory testing (pressure, thermal, and visual testing) at sites both local to and remote from the eye. Participants will also complete structural and functional brain magnetic resonance imaging to assess regions important for pain perception and modulation. In aim 3, we will examine and validate predictors of COSP pain responses before and after application of a topical anesthetic to the ocular surface, which should block peripherally induced discomfort to allow for clarification of pain origination. RESULTS: We received funding for this project in August 2024. Recruitment and enrollment began in January 2025 after protocol development and piloting were completed. This study is ongoing with 59 participants enrolled and 51 participants completing the study visits as of January 2026. CONCLUSIONS: Findings from the study have the potential to fundamentally change the way ocular pain syndromes are conceptualized, diagnosed, and treated. This work will not only help identify new CNS-directed pain treatments for a subset of patients with COSP but also help us better understand why many peripherally directed therapies are destined to be ineffective in a subset of individuals experiencing COSP. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/84240.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.027
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.012
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0270.006

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 head0.267
GPT teacher head0.535
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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