Cluster-randomized trial of the implementation of the Responses to Illness Severity Quantification (RISQ) system in children with acute malnutrition 6 to 59 months of age in Ngouri, Chad: the CRIMSON trial protocol
Bibliographic record
Abstract
BACKGROUND: The Responses to Illness Severity Quantification (RISQ) System is a scientifically developed clinical decision support tool comprised of four parts: (1) a validated 7-item severity of illness score, (2) age-specific documentation forms, (3) context-relevant score-matched recommendations, and (4) implementation programming. Care recommendations, expertly derived from a panel of clinicians extensively experienced in humanitarian contexts, include frequency of observation, consideration of secondary review, inpatient admission, and transfer into/out of advanced inpatient care areas. The RISQ System is to be used as an adjunct to current care practice to aid clinicians in clinical decision-making. The objective of the CRIMSON study is to estimate the effect of implementation of the RISQ System on mortality and processes of care in a nutritional program. METHODS: A cluster randomized trial will compare the RISQ System to usual care. Eligible clusters are community health centers that enroll patients into the Ministry of Health/ALIMA OptiMA acute malnutrition program in the Ngouri district of Chad. Eligible patients are aged 6-59 months with mid-upper arm circumference (MUAC) < 125 mm and/or edema. Participating centers will be allocated in a 1:1 ratio to usual care or the RISQ System. The primary outcome is mortality to the earlier of 60 days after program entry or program discharge. A 14-month baseline period will precede a 14-month intervention period. With a sample of 20,000 patients in 34 centers (assuming an intraclass correlation coefficient of 0.0005, equal-sized clusters, and 1.5% baseline mortality) provides 80% power to detect a 0.5% absolute decrease in mortality using a one-sided alpha of 0.05. Bayesian logistic regression will be used in analyses of the primary outcome. DISCUSSION: This cluster randomized evaluation of the RISQ System will estimate effect on program mortality as well as provide detailed information on the implementation of a clinical decision support tool in a low-resource humanitarian setting. Improving the precision of clinical determinations about hospitalization could potentially reduce mortality by 30% within nutrition treatment programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT06123390 . First posted date: 2023-11-08.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".