Biomarkers in Pediatric Neuropsychiatric Systemic Lupus Erythematosus: A Systematic Review
Bibliographic record
Abstract
This is the protocol for a systematic review aiming To evaluate and synthesize current evidence on the diagnostic, predictive, or disease-monitoring value of biomarkers in pediatric patients with neuropsychiatric systemic lupus erythematosus (pNPSLE). Inclusion criteria Population: Children and adolescents (≤18 years old) diagnosed with SLE and presenting neuropsychiatric symptoms. Study Types: Original peer-reviewed studies (cohort, case-control, cross-sectional). Intervention/Exposure: Measurement of biomarkers related to neuropsychiatric involvement in SLE. Outcomes: Diagnostic accuracy, association with NP symptoms, or prognostic relevance of biomarkers. Exclusion criteria Case reports, case series, review articles. Studies without separate pediatric data. Animal studies or non-human participants. Studies without data on relevant biomarkers. Databases and Search Strategy Databases searched: We followed the PRISMA guidelines to perform a systematic literature search of articles relevant to pediatric NPSLE and biomarkers in four databases PubMed (n=24) EMBASE (n=24) Scopus (n=7) Google Scholar (n=48) A total of 29 studies were selected for data extraction and narrative synthesis.Data were extracted manually from full texts and supplementary materials. Extracted information included: author, year, country, study design, population size, NP symptomatology, biomarker type and measurement method, sensitivity/specificity, and association with NP outcomes.The Newcastle-Ottawa Scale (NOS) adapted for cohort, case-control, and cross-sectional studies was used. Quality grading followed the AHRQ thresholds. Most studies were of poor quality due to small samples and lack of control for confounding.A qualitative synthesis was performed. No meta-analysis was conducted due to high heterogeneity in study designs, biomarkers, and outcome measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.377 |
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; both teacher heads agree on what is shown here.
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".