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ArticleTrials2025

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.

Nancy M Dale, Youssouf Djidita Hagre, Susan Shepherd, George Tomlinson, Stanley Zlotkin, Masra Ngaradoum, Mahmat Bechir, Marius Madjissem, Charles Tehoua, Christopher Parshuram

Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06123390 (Cluster-Randomized Trial of the Implementation of the Responses to Illness Severity Quantification System), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06123390 nacompletednot on this map

Cluster-Randomized Trial of the Implementation of the Responses to Illness Severity Quantification System (RISQ) in Children With Acute Malnutrition Six to Fifty-nine Months of Age in Ngouri, Chad

TypeinterventionalSponsorThe Hospital for Sick ChildrenRan2023 to 2024Enrolled14,671ConditionsSevere Acute MalnutritionArmsThe Responses to Illness Severity Quantification (RISQ) System
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Nancy M DaleThe Hospital for Sick Children, Toronto, Canada. nancy-m.dale@sickkids.ca.
Youssouf Djidita HagreMother-Child Teaching Hospital (MCTH)/Faculty of Sciences and Human Health at the University of Ndjamena, N'Djamena, Chad.
Susan ShepherdThe Alliance for International Medical Action (ALIMA), Paris, France.
George TomlinsonUniversity of Toronto, Toronto, Canada.
Stanley ZlotkinThe Hospital for Sick Children, Toronto, Canada.
Masra NgaradoumThe Alliance for International Medical Action (ALIMA), Paris, France.
Mahmat BechirDepartment of Food and Applied Nutrition, Ministry of Heath Chad, Faculty of Sciences and Human Health at the University of Ndjamena, N'Djamena, Chad.
Marius MadjissemMinistry of Health Chad, Lake District, Chad.
Charles TehouaThe Alliance for International Medical Action (ALIMA), Paris, France.
Christopher ParshuramThe Hospital for Sick Children, Toronto, Canada.

Funding

R2HC-ELRHA 78730
6 · The paper itself

Abstract

backgroundThe 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.

methodsA 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 registrationClinicalTrials.gov NCT06123390 . First posted date: 2023-11-08.

Indexed as

Child Nutrition DisordersDecision Support Systems, ClinicalDecision Support TechniquesSevere Acute MalnutritionChadChild, PreschoolClinical Decision-MakingFemaleHumansInfantNutritional StatusRandomized Controlled Trials as TopicSeverity of Illness IndexMalnutritionMortalityScoreSeverity of illness

Identifiers

PMID40462129
PMCPMC12135466

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.