Lactulose/Mannitol Test Has High Efficacy for Excluding Organic Causes of Chronic Diarrhea
Bibliographic record
Abstract
OBJECTIVES: Diagnosis in chronic diarrhea in the absence of a distinctive clinical pattern is often challenging, as biochemical tests prescribed at the first evaluation do not show enough sensitivity and specificity to tailor further investigation. Intestinal permeability to sugars is an accurate test for detecting intestinal damage. The aim of this study was to evaluate the diagnostic value of the lactulose/mannitol (L/M) test in patients with chronic diarrhea. METHODS: We conducted a prospective cohort study to evaluate the diagnostic value of the L/M test in chronic diarrhea. The test was administered to 261 consecutive patients presenting with three or more bowel movements daily for at least 3 wk. Biochemical tests including complete blood cell count, acute phase reactive proteins, serum albumin and iron, and stool cultures for bacteria, ova, and parasites were assessed at the same time. Additional diagnostic investigations were directed by clinical features as well as first-line test results. RESULTS: Over 3 yr, 120 (46%) of our patients were found to have an organic cause for chronic diarrhea, whereas in 141 (54%) a functional condition was diagnosed. Multivariate logistic regression analysis revealed that the L/M test and C-reactive protein were independent predictors for the final diagnosis of organic cause of chronic diarrhea, with odds ratios of 1.5 (95% CI = 1.29-1.78) and 5.2 (95% CI = 1.90-14.12), respectively. The area under the receiver operating characteristic (ROC) curve of the adjusted model was 0.82, with positive predictive value of 80.4% and negative predictive value of 77.7%. CONCLUSIONS: The L/M test is a powerful tool for workup in patients with chronic diarrhea. Introducing the L/M test as first-level test effectively improves the selection of patients who need further evaluation.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".