Is Chymotrypsin Output a Better Diagnostic Index than theMeasurement of Chymotrypsin in Random Stool?
Bibliographic record
Abstract
This study compares the diagnostic utility of fecal chymotrypsin (CT) output in timed stool collections and random stools using a new photometric enzyme assay. The CT output (mean +/- SD, U/24 h) was 1,487 +/- 1,980 in 127 children with normal fat absorption and negative sweat-chloride test (mean age 45 months), and 1,804 +/- 1,452 in 27 cases with fat malabsorption due to nonpancreatic disease (mean age 41 months). 66 cases of cystic fibrosis (CF) were examined (mean age 119 months). Stool output in 19 newly diagnosed patients before therapy was 85 +/- 94, in 42 patients receiving enzyme replacement therapy was 3,462 +/- 2,841, and in 5 patients with pancreatic sufficiency 1,754 +/- 1,482. Using nonparametric statistics, 120 U/24 h was defined as the lower limit of the 95-percentile for stool CT output. Only 5 of the 127 patients with normal fat absorption had output below that limit. None of the patients with nonpancreatic malabsorption and only 1 treated CF patient had lower values. Sixteen of the newly diagnosed CF patients had stool CT less than 120 U/24 h. The sensitivity of the test is therefore 84% and its specificity 97% at this decision threshold. However, no diagnostic advantage is gained from measuring CT output in timed stool collections as compared to random stools.
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".