Two-Step Biochemical Differential Diagnosis of Classic 21-Hydroxylase Deficiency and Cytochrome P450 Oxidoreductase Deficiency in Japanese Infants by GC-MS Measurement of Urinary Pregnanetriolone/ Tetrahydroxycortisone Ratio and 11β-Hydroxyandrosterone
Bibliographic record
Abstract
BACKGROUND: The clinical differential diagnosis of classic 21-hydroxylase deficiency (C21OHD) and cytochrome P450 oxidoreductase deficiency (PORD) is sometimes difficult, because both deficiencies can have similar phenotypes and high blood concentrations of 17α-hydroxyprogesterone (17OHP). The objective of this study was to identify biochemical markers for the differential diagnosis of C21OHD, PORD, and transient hyper 17α-hydroxyprogesteronemia (TH17OHP) in Japanese newborns. We established a 2-step biochemical differential diagnosis of C21OHD and PORD. METHODS: We recruited 29 infants with C21OHD, 9 with PORD, and 67 with TH17OHP, and 1341 control infants. All were Japanese and between 0 and 180 days old; none received glucocorticoid treatment before urine sampling. We measured urinary pregnanetriolone (Ptl), the cortisol metabolites 5α- and 5β-tetrahydrocortisone (sum of these metabolites termed THEs), and metabolites of 3 steroids, namely dehydroepiandrosterone, androstenedione (AD4), and 11β-hydroxyandrostenedione (11OHAD4) by GC-MS. RESULTS: At a cutoff of 0.020, the ratio of Ptl to THEs differentiated C21OHD and PORD from TH17OHP and controls with no overlap. Among metabolites of DHEA, AD4, and 11OHAD4, only 11β-hydroxyandrosterone (11HA), a metabolite of 11OHAD4, showed no overlap between C21OHD and PORD at a cutoff of 0.35 mg/g creatinine. CONCLUSIONS: A specific cutoff for the ratio of Ptl to THEs can differentiate C21OHD and PORD from TH17OHP and controls. Additionally, the use of a specific cutoff of 11HA can distinguish between C21OHD and PORD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".