How to Distinguish Attenuated Forms of Mucopolysaccharidosis and Articular Forms of Juvenile Arthritis: Development of Diagnostic Algorithm Based on the Data from Multicenter Retrospective Study
Bibliographic record
Abstract
Background. Differential diagnosis of attenuated forms of mucopolysaccharidosis (MPS) and juvenile idiopathic arthritis (JIA) can be challenging due to their similarities. Objective. The aim of the study is to create simple diagnostic criteria (DScore) that would allow to differentiate MPS from JIA for earlier MPS diagnosis. Methods. The retrospective multicenter study included analysis of clinical (joint, heart, eye involvement, hearing loss, hernias, psychomotor delay, noisy breathing, posture disorders, macrocephaly, hepatomegaly, splenomegaly, and growth delay) and laboratory data (ESR, CRP, hemoglobin, WBC, and platelets) from MPS patients (n = 41) and from rheumatoid factor-negative polyarticular category of JIA patients (n = 255). These variables allowed to differentiate both conditions and were used to create DScore. Results. Patients with MPS had younger onset age, male predominance, height and weight delay, lower inflammation markers (WBC, platelets, and ESR), and usually involved joints, especially cervical spine, upper limbs joints, hip, and small foot joints. The prevalence of eye involvement was similar for both diseases, however, the type of involvement was different. JIA patients had uveitis and its’ complications and MPS patients — corneal opacity and cataract. No differences in CRP levels were revealed in most cases. The major diagnostic criterion of MPS was the presence of more than one extra-articular manifestation associated with polyarticular involvement. DScore has included 5 following criteria: ESR ≤ 11 mm/h (38 points), height ≤ -2.0 SD (20 points), onset age of articular manifestations ≤ 1.1 year (24 points), male gender (15 points), and symmetrical limitation of movements in elbow joints (29 points). The sum > 38 points allowed us to differentiate MPS and JIA with sensitivity of 92.7% and specificity of 91.0%. Conclusion. This DScore can be used for differential diagnosis of mild MPS and JIA alongside with routine diagnostic procedures. DScore allows us to identify a group of patients with joint involvement who require MPS exclusion.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".