Thirsty Eyes: A Look at Dry Eyes in Autoimmune/inflammatory Syndrome Induced by Adjuvants (ASIA; Shoenfeld’s Syndrome)
Bibliographic record
Abstract
Objectives Many patients with autoimmune syndrome induced by adjuvants (ASIA) due to silicone breast implants complain of dry eyes, which may be due to impaired tear production or increased tear evaporation. The clinical differences between ASIA patients with dry eyes, compared to other rheumatic diseases (eg, Sjögren’s syndrome) are largely unknown. Methods We utilized a cross-sectional design to enroll 78 consecutive patients with ASIA due to breast implants, Sjögren syndrome (SS) (n=16), and healthy controls (HC) (n=17) from a single center in our study. We assessed each participant using a Schirmer test and the 5-item, SS Screening Questionnaire (SSSQ) - a validated questionnaire that has been suggested to distinguish SS patients from non-SSc patients in the SICCA study.[1] Results 80% of our ASIA patients complained of dry eyes. 57 of 78 (73.1%) had impairments of tear production (Schirmer test < 15 mm), with severe impairment of tear production (Schirmer’s test < 5 mm) in 37/78 (47.4%) in ASIA patients. Severely impaired tear production was more prevalent in ASIA patients than HC (p = 0.017), with rates similar SS patients (p = 0.681). ASIA and SS patients had similar SSSQ scores (p = 0.6355), and rates of abnormal SSSQ (p = 0.339). Differences were however evident between ASIA and SS patients with regards to ANA, anti-SSA, anti-SSB and IgM levels (p < 0.05). Further analysis of ASIA patients with severe impairments in tear production (Schirmer’s test < 5 mm) had reduced circulating Helper T cells (p = 0.038) and Naïve Helper T cells (p = 0.004) compared to ASIA patients with non-severe tear production - suggesting that tear production may be associated with a more profound immune dysregulatory state. Conclusion ASIA patients with silicone breast implants likely suffer from dry eyes due to impaired tear production, though they do not fulfill the classification criteria for Sjögren syndrome. The SSSQ was unable to differentiate sicca symptoms from SS or ASIA, however other biomarkers such as antinuclear antibodies may be helpful. Further investigation and mechanistic characterization are required to determine the relevance of more decreased circulating Helper T cells in breast implant-induced ASIA patients with dry eyes. [1.] Yu K. J Clin Rheumatol 2022;28(2):e456-61.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".