The Efficacy of the BioFire FilmArray Gastrointestinal Panel to Reduce Hospital Costs Associated With Contact Isolation: A Pragmatic Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Molecular syndromic panels can rapidly detect common pathogens responsible for acute gastroenteritis in hospitalized patients. Their impact on both patient and healthcare system outcomes is uncertain compared to conventional stool testing. This randomized trial evaluates the impact of molecular testing on in-hospital resource utilization compared to conventional stool testing. METHODS: Hospitalized patients with acute diarrheal illness were randomized 1:1 to either conventional or molecular stool testing with the BioFire FilmArray gastrointestinal panel (FGP). The primary outcome was the duration of contact isolation, and secondary outcomes included other in-hospital resource utilization such as diagnostic imaging and antimicrobial use. RESULTS: A total of 156 patients were randomized. Randomization resulted in a balanced allocation of patients across all three age strata (<18, 18-69, ≥70 years old). The proportion of positive stools was 20.5% vs 29.5% in the control and FGP groups, respectively (p=0.196). The median duration of contact isolation was 51 hours (interquartile range [iqr] 66) and 69 hours (iqr 81) in the conventional and FGP groups, respectively (p=0.0513). There were no significant differences in other in-hospital resource utilization between groups. CONCLUSIONS: There were no differences in in-hospital resource utilization observed between the FGP and conventional stool testing groups.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".