Understanding the Early Presentation of Mucopolysaccharidoses Disorders
Bibliographic record
Abstract
As therapies are developed for rare disorders, challenges of early diagnosis become particularly relevant. This article focuses on clinical recognition of mucopolysaccharidoses (MPS), a group of rare genetic diseases related to abnormalities in lysosomal function. As quality of outcomes with current therapies is impacted by timing of intervention, minimizing time to diagnosis is critical. The objective of this study was to characterize how, when, and to whom patients with MPS first present and develop tools to stimulate earlier recognition of MPS. A tripartite approach was used, including a systematic literature review yielding 194 studies, an online physician survey completed by 209 physicians who described 859 MPS cases, and a global panel of MPS experts who distilled the findings. Red flag signs/symptoms were identified for cardiology, pediatric neurology, otorhinolaryngology, rheumatology, orthopedics, pediatrics, and general medicine and converted into simple, specialty-specific tools intended to facilitate early diagnosis of MPS, enabling improved patient outcomes.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".