β‐adrenergic sweat test in children with inconclusive cystic fibrosis diagnosis: Do we need new reference ranges?
Bibliographic record
Abstract
BACKGROUND: Investigating inconclusive cystic fibrosis (CF) diagnosis in children is difficult without advanced cystic fibrosis transmembrane conductance regulator (CFTR) function tests. This study investigated the utility of beta (β)-adrenergic sweat test to exclude CF in participants with inconclusive diagnosis (CF suspects) in South Africa. METHODS: /h) following intradermal injections. Next-generation sequencing of CFTR was performed in CF suspects. CF diagnosis was defined by genotype. RESULTS: Thirty-seven controls (10 healthy, 14 CF, 13 CFTR heterozygotes) and 32 CF suspects (26 children; 6 adults) were enrolled. Six were excluded from formal analyses due to β-adrenergic sweat test failure. In adults, evaporimetry was superior to SCT for diagnosis of CF with β-adrenergic:cholinergic ratio TEWL ≤ 0.05 achieving 100% sensitivity and specificity. Twenty-two CF suspect children (age range: 3.4-15.6 years) completed β-adrenergic sweat testing of which none had CF confirmed by genotyping: β-adrenergic:cholinergic ratio > 0.05 successfully excluded CF in all but one child who was CFTR heterozygous. Median peak β-adrenergic TEWL and β-adrenergic:cholinergic ratio in CFTR negative and CFTR heterozygous children was significantly lower than adult controls. CONCLUSION: β-adrenergic sweat test is more accurate than SCT for excluding CF in children with inconclusive diagnosis. Established reference ranges for β-adrenergic sweat test may not be suitable for children due to lower β-adrenergic sweat secretion compared to adults.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".