Degree of Histologic Inflammation in Lupus Erythematosus and Direct Immunofluorescence Results: Red and Inflamed Lesions Do Not Increase the Chances of Getting a Bright Band
Bibliographic record
Abstract
BACKGROUND: In the diagnostic work-up of lupus erythematosus (LE), direct immunofluorescence (DIF) examination could be helpful. Classically, clinically red lesions are targeted by clinicians in the hope of yielding an informative DIF result. However, the investigative correlation between the degree of inflammation and DIF positivity has never been published in the literature. OBJECTIVE: In this study, we sought to discover if histologically inflamed lesions correlated with DIF positivity results. METHOD: We studied 112 lesions histologically consistent with LE and correlated the degree of histologic inflammation on the DIF hematoxylin and eosin-stained biopsy with DIF positivity. The degree and location of the inflammation, as well as the involvement of the dermoepidermal interface, were documented. RESULTS: A positive lupus band test was defined as the presence of either (1) granular IgG alone ± other immunoglobulins and/or C3 or (2) granular IgM or Ig A plus other immunoglobulins ± C3. Fifty-four of 112 (48%) cases had positive DIF (DIF+) results, 26 of 112 (23%) had negative DIF (DIF-) results, and 32 of 112 (29%) had nonspecific DIF patterns. Of the DIF+ cases, 41 of 54 (76%) showed some degree of inflammation, whereas 25 of 26 (96%) DIF- cases had inflammation (p = .60). Most of the biopsies in the study (85%) were inflamed, but the degree and location of the inflammation had no influence on DIF+ results. The intensity of the DIF+ band further failed to show any relationship with the degree of inflammation. CONCLUSION: The level of inflammatory activity in a clinical lesion fails to correlate with DIF positivity. Furthermore, other common histopathologic findings of LE are not predictive of DIF results.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".