THE RELATIONSHIP OF THE LEVEL OF ANTINUCLEAR ANTIBODIES WITH CLINICAL AND IMMUNOLOGICAL SUBTYPES OF SYSTEMIC LUPUS ERYTHEMATOSUS
Bibliographic record
Abstract
PV232 / #222 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose Antinuclear antibodies (ANA) are a specific marker related to the classification criteria of systemic lupus erythematosus (SLE). The purpose of our study was evaluating ANA levels in relation to clinical and immunological subtypes of SLE. Methods Sera from 94 patients (pts) diagnosed with SLE (SLICC criteria, 2012), including 80 women and 14 men, age (Median, [25th;75th percentile] 31 [27;47] years, disease duration 84.0 [24.0;168.0] months were studied. The following clinical manifestations were investigated: skin/mucous membrane lesions, kidney, central nervous system, constitutional manifestations, serositis, and hematological abnormalities. ANA were determined by multiplex immunoassay (MIA) based on magnetic microspheres using BioPlex ® 2200 ANA Screen test system (Laboratories Inc. Hercules, CA, USA). Positive ANA measurements corresponded to the following values: for antibodies to double-stranded (anti-ds) DNA≥10.0 IU/ml; for other ANAs (aSm, aSS-A/Ro, aSS-B/La, antibodies to nucleosomes, RibP, RNP-70) ≥1.0 AI (Antibody Index). Results Elevated levels of antibodies to dsDNA, nucleosomes, and RibP were detected in SLE pts with kidney damage, serositis, hematological disorders, and skin and/or mucous membrane lesions: anti-dsDNA in the group of pts with kidney damage (14.5 [7.0;68.0]), serositis (45.0 [9.0;70.0]) and hematological disorders (22.0 [9.0;70.0]); antibodies to nucleosomes in the group of pts with kidney damage (3.7 [0.5;8.0]), serositis (5.7 [0.7;8.0]) and hematological disorders (8.0 [0.7;8.0]); anti-RibP in the group of pts with skin and/or mucous membrane damage (0.3 [0.2;0.8]) and hematological disorders (0.3 [0.2;0.6]). Pts without these clinical manifestations had lower antibody levels (Table 1). For all groups, p<0.05. Table 1. Correlation of ANA levels with disease activity and presence or absence of clinical manifestations Conclusions The development of the pathological process in SLE is accompanied by the formation of a wide range of autoantibodies. The presence of certain ANA is associated with different clinical and immunological subtypes of SLE and may be useful for personalization of therapy.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".