IMPORTANCE OF SEQUENTIAL FOLLOW-UP OF AUTOANTIBODIES IN ANA-POSITIVE PATIENTS WITH DIFFUSE HAIR LOSS
Bibliographic record
Abstract
PV287 / #776 Case Report Poster Topic: AS07 - Cutaneous Lupus Late-Breaking Abstract Introduction Diffuse hair loss can be an early manifestation of systemic lupus erythematosus (SLE), particularly when other common causes such as alopecia areata, drug-induced alopecia, iron deficiency, and androgenic alopecia are excluded. The presence of high-titer antinuclear antibodies (ANA) without immediate clinical signs of SLE necessitates close monitoring, as the disease may evolve over time. Sequential follow-up of autoantibodies in ANA-positive patients with unexplained hair loss is crucial for early detection and intervention. Case Presentation With Investigation A 20-year-old female initially presented to the dermatology department at CHA Bundang Medical Center on June 9, 2021, with diffuse hair loss and folliculitis. She had no prior treatment history and was prescribed topical minoxidil 5% and alfatradiol solution 0.025% for daily application. Laboratory tests, including CBC, U/A, routine chemistry, ESR, CRP, ANA, anti-dsDNA IgG, SS-A/Ro Ab, SS-B/La Ab, syphilis reagin test, serum ferritin, T3, f T4, TSH, free testosterone, DHEA-S, zinc, iron, and SHBG, revealed ANA positivity at 1:1250 (speckled pattern), f T4 of 0.85 ng/dL, and a zinc level of 61.09 µg/dL, with all other results within normal limits. No clinical evidence of polycystic ovary syndrome (PCOS), arthritis, or thyroid disease was noted. The patient was treated with topical minoxidil 5% and alfatradiol solution 0.025% for 5 months, along with oral polaprezinc twice daily. Due to gastrointestinal side effects, polaprezinc was discontinued, and dietary zinc intake was encouraged. Despite 8 months of topical treatment, hair regrowth was inadequate, leading to the addition of low-dose oral minoxidil (5 mg/day) for 8 months. Over time, serial autoantibody testing revealed progression to positive anti-dsDNA IgG (>150), ANA 1:2560 (speckled pattern), and anti-Sm Ab positivity. The patient also developed proteinuria (urine protein 323 mg/24 hours), multiple arthralgia, fatigue, and fever. A kidney biopsy confirmed focal lupus nephritis (Class III), leading to a definitive diagnosis of SLE. She was initiated on mycophenolate mofetil (2 g/day), hydroxychloroquine, and low-dose prednisolone (5 mg/day). Following treatment, arthralgia resolved, proteinuria decreased (323 mg to 30 mg/24 hours), and anti-dsDNA IgG levels significantly declined (from 379 to 6). Literature Review Nonscarring alopecia is a common and reversible manifestation in SLE, primarily driven by immune-mediated inflammation, hair cycle disruption, vascular dysfunction, oxidative stress, hormonal dysregulation, and drug-induced effects. 1) Immune-Mediated Inflammation: Autoantibodies and immune complexes in SLE contribute to follicular damage through increased IFN-α signaling, CD4+ T cell and B cell infiltration, and microvascular injury. 2) Alterations in the Hair Cycle: Inflammatory stress promotes telogen effluvium by shifting follicles to the resting phase, while anagen arrest leads to premature shedding and impaired regrowth. 3) Vascular Damage & Oxidative Stress: Vasculitis-induced endothelial damage compromises scalp microvasculature, reducing blood flow. Oxidative stress further exacerbates follicular cell apoptosis. 4) Hormonal & Metabolic Dysregulation: Chronic inflammation activates the HPA axis, increasing cortisol levels that inhibit hair cycling. Autoimmune thyroid disorders, such as Hashimoto’s thyroiditis, contribute to hair thinning. 5) Drug-Induced Hair Loss: Medications like hydroxychloroquine, methotrexate, mycophenolate mofetil, and corticosteroids can trigger telogen effluvium, disrupting normal follicular cycling. Discussion Regular follow-up of autoantibodies in ANA-positive patients with diffuse hair loss is essential for early SLE detection. Monitoring ANA, anti-dsDNA, and lupus-specific antibodies aids in timely intervention, improving patient outcomes. Early recognition and surveillance facilitate prompt diagnosis and management, reducing disease progression risks.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".