Consensus on Diagnostic Criteria of Idiopathic Orbital Inflammation Using a Modified Delphi Approach
Bibliographic record
Abstract
Importance: Current practice to diagnose idiopathic orbital inflammation (IOI) is inconsistent, leading to frequent misdiagnosis of other orbital entities, including cancer. By specifying criteria, diagnosis of orbital inflammation will be improved. Objective: To define a set of criteria specific for the diagnosis of IOI. Design, Setting, and Participants: A 3-round modified Delphi process with an expert panel was conducted from June 8, 2015, to January 25, 2016. Fifty-three orbital scientist experts, identified through membership in the Orbital Society, were invited to participate in on online survey and they scored, using 5-point Likert scales, items that are eligible as diagnostic criteria from the literature and from personal experience. The items were clustered around the anatomic subtypes of IOI: idiopathic dacryoadenitis and idiopathic orbital fat inflammation (2 nonmyositic IOIs), and idiopathic orbital myositis (myositic IOI). Items with dissensus were rescored in the second round, and all items with consensus (median, ≥4; interquartile range, ≤1) were ranked by importance in the third round. Main Outcomes and Measures: Consensus on items to be included in the criteria. Results: Of the 53 experts invited to participate, a multinational panel of 35 (66%) individuals with a mean (SD) years of experience of 31 (11) years were included. Consensus was achieved on 7 of 14 clinical and radiologic items and 5 of 7 pathologic items related to diagnosis of nonmyositic IOI, and 11 of 14 clinical and radiologic items and 1 of 5 pathologic items for myositic IOI. There was agreement among panelists to focus on surgical tissue biopsy results in the diagnosis of nonmyositic IOI and on a trial with systemic corticosteroids in myositic IOI. Panelists agreed that a maximum number of 30 IgG4-positive plasma cells per high-power field in the orbital tissue is compatible with the diagnosis of IOI. Conclusions and Relevance: An international panel of experts endorsed consensus diagnostic criteria of IOI. These criteria define a level of exclusion suggested for diagnosis and include tissue biopsy for lesions not confined to the extraocular muscles. This consensus is a step toward developing guidelines for the management of IOI, which needs to be followed by validation studies of the criteria.
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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 | 0.209 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".