The Frequencies of Different Inborn Errors of Metabolism in Adult Metabolic Centres: 10 Years Later, Another Report From the SSIEM Adult Metabolic Physicians Group
Bibliographic record
Abstract
There are still few centres, which specialise in the care of adults with inborn errors of metabolism (IEM). All physicians who participated in the SSIEM adult metabolic physicians group paper in 2014 were contacted to provide updated data on their IEM patients. Fifteen adult centres responded to our survey with information on their patients. Nine thousand, six hundred fifty-one patients were included in the final cohort, compared with 6 182 in the previous analysis. There were 394 separate diagnoses. The most common diseases were phenylketonuria (19.6%), mitochondrial disorders (12.3%) and lysosomal storage disorders such as Fabry disease (20.1% of LSD's), Pompe disease (3.1%), and Gaucher disease (2.8%). Among the disorders that can present with acute metabolic decompensation, the urea cycle disorders (4.0%), were most common (ornithine transcarbamylase deficiency 2.6%), followed by maple syrup urine disease (1.1%) and glycogen storage disease type I (0.7%). Patients were frequently diagnosed as adults, particularly those with mitochondrial disease and lysosomal storage disorders. Many patients are only diagnosed in adulthood (> 40%) and the cohort is increasing substantially with 9 651 patients included in the final analysis (34% increase compared to our original paper). Thus reinforcing the need for adult specialists to be trained in this area.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".