Inconclusive Diagnosis of Cystic Fibrosis After Newborn Screening
Bibliographic record
Abstract
OBJECTIVES: To prospectively study infants with an inconclusive diagnosis of cystic fibrosis (CF) identified by newborn screening (NBS; "CF screen positive, inconclusive diagnosis" [CFSPID]) for disease manifestations. METHODS: Infants with CFSPID and CF based on NBS from 8 CF centers were prospectively evaluated and monitored. Genotype, phenotype, repeat sweat test, serum trypsinogen, and microbiology data were compared between subjects with CF and CFSPID and between subjects with CFSPID who did (CFSPID→CF) and did not (CFSPID→CFSPID) fulfill the criteria for CF during the first 3 years of life. RESULTS: Eighty-two subjects with CFSPID and 80 subjects with CF were enrolled. The ratio of CFSPID to CF ranged from 1:1.4 to 1:2.9 in different centers. CFTR mutation rates did not differ between groups; 96% of subjects with CFSPID and 93% of subjects with CF had 2 mutations. Subjects with CFSPID had significantly lower NBS immunoreactive trypsinogen (median [interquartile range]:77 [61-106] vs 144 [105-199] μg/L; P < .0001) than did subjects with CF. Pseudomonas aeruginosa and Stenotrophomonas maltophilia were isolated in 12% and 5%, respectively, of subjects with CFSPID. CF was diagnosed in 9 of 82 (11%) subjects with CFSPID (genotype and abnormal sweat chloride = 3; genotype alone = 4; abnormal sweat chloride only = 2). Sweat chloride was abnormal in CFSPID→CF patients at a mean (SD) age of 21.3 (13.8) months. CFSPID→CF patients had significantly higher serial sweat chloride (P < .0001) and serum trypsinogen (P = .009) levels than did CFSPID→CFSPID patients. CONCLUSIONS: A proportion of infants with CFSPID will be diagnosed with CF within the first 3 years. These findings underscore the need for clinical monitoring, repeat sweat testing at age 2 to 3 years, and extensive genotyping.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".