Review for the generalist: The antinuclear antibody test in children - When to use it and what to do with a positive titer
Bibliographic record
Abstract
The antinuclear antibody test (ANA) is a much overused test in pediatrics. The ANA does have a role in serologic testing but it should be a very limited one. It is often ordered as a screening test for rheumatic illnesses in a primary care setting. However, since it has low specificity and sensitivity for most rheumatic and musculoskeletal illnesses in children, it should not be ordered as a screening test for non-specific complaints such as musculoskeletal pain. It should only be used as a diagnostic test for children with probable Systemic Lupus Erythematosus (SLE) or Mixed Connective Tissue Disease, (MCTD) and other possible overlap-like illnesses. Such children should have developed definite signs and symptoms of a disease before the ANA is ordered. This review presents data supporting these conclusions and a review of the ANA literature in adults and children.By limiting ANA testing, primary care providers can avoid needless venipuncture pain, unnecessary referrals, extra medical expenses, and most importantly, significant parental anxieties. It is best not to do the ANA test in most children but if it ordered and is positive in a low titer (<1:640), the results can be ignored if the child is otherwise well and does not have other features of a systemic illness.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.011 |
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".