Measurement Issues in Trials of Pediatric Acute Diarrheal Diseases: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Worldwide, diarrheal diseases rank second among conditions that afflict children. Despite the disease burden, there is limited consensus on how to define and measure pediatric acute diarrhea in trials. OBJECTIVES: In RCTs of children involving acute diarrhea as the primary outcome, we documented (1) how acute diarrhea and its resolution were defined, (2) all primary outcomes, (3) the psychometric properties of instruments used to measure acute diarrhea and (4) the methodologic quality of included trials, as reported. METHODS: We searched CENTRAL, Embase, Global Health, and Medline from inception to February 2009. English-language RCTs of children younger than 19 years that measured acute diarrhea as a primary outcome were chosen. RESULTS: We identified 138 RCTs reporting on 1 or more primary outcomes related to pediatric acute diarrhea/diseases. Included trials used 64 unique definitions of diarrhea, 69 unique definitions of diarrhea resolution, and 46 unique primary outcomes. The majority of included trials evaluated short-term clinical disease activity (incidence and duration of diarrhea), laboratory outcomes, or a composite of these end points. Thirty-two trials used instruments (eg, single and multidomain scoring systems) to support assessment of disease activity. Of these, 3 trials stated that their instrument was valid; however, none of the trials (or their citations) reported evidence of this validity. The overall methodologic quality of included trials was good. CONCLUSIONS: Even in what would be considered methodologically sound clinical trials, definitions of diarrhea, primary outcomes, and instruments employed in RCTs of pediatric acute diarrhea are heterogeneous, lack evidence of validity, and focus on indices that may not be important to participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".