Validation of the Modified Vesikari Score in Children With Gastroenteritis in 5 US Emergency Departments
Bibliographic record
Abstract
OBJECTIVES: The burden of acute gastroenteritis (AGE) in US children is substantial. Research into outpatient treatment strategies has been hampered by the lack of easily used and validated gastroenteritis severity scales relevant to the populations studied. We sought to evaluate, in a US cohort, the reliability, construct validity, and generalizability of a gastroenteritis severity scale previously derived in a Canadian population, the modified Vesikari score (MVS). METHODS: We conducted a prospective, cohort, clinical observational study of children 3 to 48 months of age with acute gastroenteritis presenting to 5 US emergency departments. A baseline MVS score was determined in the emergency department, and telephone follow-up 14 days after presentation was used to assign the follow-up MVS. We determined reliability using inter-item correlations; construct validity via principal component factor analysis; cross-sectional construct validity via correlations with the presence of dehydration, hospitalization, and day care and parental work absenteeism; and generalizability via score distribution among sites. RESULTS: Two hundred eighteen of 274 patients (80%) were successfully contacted for follow-up. Cronbach α was 0.63, indicating expectedly low internal reliability because of the multidimensional properties of the MVS. Factor analysis supported the appropriateness of retaining all variables in the score. Disease severity correlated with dehydration (P < 0.001), hospitalization (P < 0.001), and subsequent day care (P = 0.01) and work (P < 0.001) absenteeism. The MVS was normally distributed, and scores did not differ among sites. CONCLUSIONS: The MVS effectively measures global severity of disease and performs similarly in varying populations within the US health care system. Its characteristics support its use in multisite outpatient clinical trials.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".