Antineutrophil cytoplasmic antibody positivity in systemic lupus erythematosus: Diagnostic dilemma and therapeutic implications
Bibliographic record
Abstract
Objectives: Antineutrophil cytoplasmic antibody (ANCA) positivity occurs in up to 25% of systemic lupus erythematosus (SLE) patients, but differentiating incidental ANCA from ANCA-associated vasculitis (AAV) in SLE nephritis remains a diagnostic and therapeutic challenge. Case: A 14-year-old female presented with a 3-month history of undiagnosed autoimmune manifestations and chronic kidney disease. Based on autoimmune workup and kidney biopsy, she was diagnosed with SLE nephritis with incidental ANCA positivity. Despite appropriate SLE nephritis-directed treatment as per guidelines, an inflammatory flare and superimposed acute kidney injury (AKI) prompted a diagnosis revision to SLE-AAV overlap syndrome. Broadening treatment to target concomitant AAV led to autoimmune remission and AKI resolution. Conclusions: This case underscores the importance of early suspicion of autoimmune disorders by primary care providers for a timely referral and the critical role of specialists in recognizing the limitations of conventional tools, including renal histology, when distinguishing incidental ANCA positivity from SLE-AAV overlap to guide appropriate treatment.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".