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CompletedNCT07355426Updated Jan 21, 2026

Clinical Prediction Models for Pediatric In-Hospital Death Risk in Congolese Severe Malaria Children Using Machine Learning Based-Algorithms

An observational study in Severe Malaria, sponsored by University of Kinshasa. Completed at 1 site in Democratic Republic of the Congo. Open to participants aged 2 Years to 9 Years. Per ClinicalTrials.gov, last updated 2026-01-21.

Sponsored by University of Kinshasa · Observational

Study type
Observational
Model
Cohort
Time perspective
Other
Enrollment
100
Ages
2 Years to 9 Years
Sex
All
01

Study summary

The goal of this observational study is to optimize the management of severe childhood malaria, based on understanding and controlling the severity factors of the disease in Congolese children aged 2 to 9 years (the age group at risk of developing various severe forms of malaria), admitted to the paediatric intensive care units (PICU).

The main question it aims to answer is whether the scores or models used to predict the severity of severe malaria and the associated risk of mortality accurate enough to warrant early interventions, including treatments, on their own?

Thus, investigators aim to fill three knowledge gaps associated with the following hypotheses:

Hypothesis-1: Children with severe malaria show signs of disease severity based on their severity scores on admission. Higher severity scores on admission are associated with a higher risk of mortality.

Hypothesis-2: Validation of the predictive power and transferability of severe malaria severity scores to additional independent populations is needed to support their clinical utility.

Hypothesis-3: The severity of the clinical and biological changes induced by plasmodium depends not only on the ability of the parasite to invade and grow in the host organism, but also and above all on the number of parasites present in the host (parasitemia).

For any child admitted to the PICU and meeting the inclusion criteria, as part of clinical care, investigators proceeded before any treatment:

  1. An arterial blood sample of 3 ml by puncture of the radial artery for instant arterial blood gaz as well as for venous biochemistry, including albumin, phosphate, chlorine, magnesium, urea, creatinine and total bilirubin dosages, and,
  2. A one-drop finger pulp blood test for parasitemia measurement and the rapid diagnosis test for plasmodium falciparum.

Then, the diagnostic parameters of acid-base disorders will be calculated, including AG (anion gap), AGCAP (AG corrected for albumin and phosphate plasmatic concentrations), SIG (Strong ion gap), SBE (Standard base excess) and SBDCAP (Standard base deficit corrected for albumin and phosphate plasmatic concentrations).

Read the detailed description

Background:

Severe malaria has associated with a high risk of paediatric hospital mortality in resource-constrained countries, which remains deplorable. Improved methods of risk-stratification can assist in referral decision making and resource allocation. Investigators aim to i) create prediction model for in-hospital mortality risk among children presenting with severe malaria and compare its predictive performance to the current models, ii) validate the latter, and iii) assess the plasmodium-induced changes in clinical and biological parameters.

Methods:

This is a retrospective study of data collected prospectively during a period from January 30, 2017 to August 01, 2025, from children with severe malaria, admitted to the PICU of the Monkole Hospital Center (MHC) and the Kimbondo Pediatric Center (KPC), all in Kinshasa, DR. Congo. Baseline clinical and laboratory variables were collected on enrolled children. The primary outcome is death up to 1 week post-admission, and the second outcome, the length of stay in pediatric intensive care following admission for severe malaria. Machine learning algorithms will be employed to accomplish the three specific research objectives.

Expected Results:

In line with research objectives, the following results are expected:

  1. The prevalence of Multiple Organ Dysfunction Syndrome (MODS) and metabolic acidosis in children presenting with severe malaria will be determined.
  2. A novel model for predicting associated mortality risk of severe malaria will be developed:

    1. This novel model will be based on predictors of disease severity and will measure:

      • The degree of severity of MODS and metabolic acidosis.
      • The length of stay for severe malaria in the PICU
      • The risk of death following hospitalization for severe malaria
      • The influence of parasitemia on disease severity
    2. The performance of the proposed novel model will be measured
    3. The predictive nomogram and scoring system will be associated with it.
  3. Investigators validate and compare the performance of existing models for predicting severe malaria severity against the proposed novel model.

Together, research data will provide proof of principle supporting early interventions and treatment choices in children presenting with severe malaria.

02

Conditions studied

  • Severe Malaria

Keywords

  • Severe malaria
  • Paediatric in-hospital mortality risk
  • Machine learning-based algorithms
  • Predictive model
  • Plasmodium falciparum
  • Multiple Organ Dysfunction Syndrome (MODS)
  • Metabolic acidosis
03

In context

Malaria

1,299 studies on the registry are indexed under Malaria; 86 are open to participants now.

This study's enrollment of 100 is below the median of 600 across 218 observational studies indexed under Malaria.

Browse Malaria studies →

Lead sponsor

University of Kinshasa is the lead sponsor of 4 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
2 Years to 9 Years
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Probability sample

Study population

Children with severe malaria, admitted to the pediatric intensive care units of the Monkole Hospital Center (MHC) and the Kimbondo Pediatric Center (KPC), all in Kinshasa, DR. Congo.

Eligibility criteria

I) Inclusion Criteria:

-Admission to the pediatric intensive care unit (PICU) for severe malaria, as defined by the World Health Organization (WHO) criteria.

Definitions:

  1. Severe malaria was defined by the presence of at least one major clinical manifestation, including:

    • Coma
    • Repeated seizures (≥ 2 episodes within 24 hours)
    • Neurological disorders
    • Respiratory distress
    • Liver failure
    • Dark ("Coca-Cola") urine
    • Jaundice
    • Renal failure (anuria)
    • Severe anaemia (Hb ≤ 5 g/dL)
    • Bleeding abnormalities
    • Circulatory collapse or systolic blood pressure \< 50 mmHg
  2. Data collection periods varied by health zone and clinical unit. However, within each zone, all consecutively admitted patients during the study period were included.

II) Exclusion Criteria:

  • Another medical condition (non-parasitic infection or other) capable of causing anemia or similar abnormalities.
  • Comorbidities that could interfere with the clinical presentation or outcomes of severe malaria.
05

Study design

Observational model
Cohort
Time perspective
Other
Enrollment
100 participants (actual)
Target follow-up
1 Week
Patient registry
Yes
Biospecimen retention
Samples without dna

Groups and cohorts

  • PEDCUK_0000

    Children aged 2 to 9 years, admitted to the paediatric intensive care units for severe malaria

    Diagnostic Test: Puncture of the radial artery for instant arterial blood gaz as well as for venous biochemistry

Interventions

  • Diagnostic testPuncture of the radial artery for instant arterial blood gaz as well as for venous biochemistry

    1. The puncture of the radial artery was made for the instant arterial blood gaz as well as for venous biochemistry 2. The one-drop finger pulp blood test was made for parasitemia measurement and the rapid diagnosis test for plasmodium falciparum

06

What researchers measure

Primary outcomes

  1. The primary outcome is death during hospitalization for severe malaria [From day 1 of admission to the pediatric intensive care unit (PICU) up to day 7 post-admission]

    Death was defined as a categorical variable, defining patients who died and those who survived.

    Time frame: Day 7

Secondary outcomes

  1. The secondary outcome is survival time, defined as the interval between hospital admission and death occurring during the hospitalization period [From day1 of admission until death/recovery (discharge from hospital), assessed up to day7 post-admission]

    Survival Time was defined as the interval between hospital admission for severe malaria and death occurring during the hospitalization period. The hospitalization period extended from day 1 of admission to death (for non-survivors) or discharge (for survivors). Patients who were still alive at the end of the hospitalization period of up to day 7 (follow-up period for each patient = 7 days) or those lost to follow-up were considered censored.

    Time frame: From day 1 of admission to the PICU until death or recovery (discharge from hospital), assessed up to day 7 post-admission.

07

Study locations

1 site
  • Kinshasa
    Kinshasa, Kinshasa City, Democratic Republic of the Congo
08

References and documents

Publications

  • Berkley JA, Ross A, Mwangi I, Osier FH, Mohammed M, Shebbe M, Lowe BS, Marsh K, Newton CR. Prognostic indicators of early and late death in children admitted to district hospital in Kenya: cohort study. BMJ. 2003 Feb 15;326(7385):361. doi: 10.1136/bmj.326.7385.361. PubMed 12586667 ↗
  • Kumar N, Thomas N, Singhal D, Puliyel JM, Sreenivas V. Triage score for severity of illness. Indian Pediatr. 2003 Mar;40(3):204-10. PubMed 12657751 ↗
  • Helbok R, Kendjo E, Issifou S, Lackner P, Newton CR, Kombila M, Agbenyega T, Bojang K, Dietz K, Schmutzhard E, Kremsner PG. The Lambarene Organ Dysfunction Score (LODS) is a simple clinical predictor of fatal malaria in African children. J Infect Dis. 2009 Dec 15;200(12):1834-41. doi: 10.1086/648409. PubMed 19911989 ↗
  • Njim T, Tanyitiku BS. Prognostic models for the clinical management of malaria and its complications: a systematic review. BMJ Open. 2019 Nov 26;9(11):e030793. doi: 10.1136/bmjopen-2019-030793. PubMed 31772089 ↗
  • World malaria report 2024. Geneva: World Health Organization. 2024

Study documents

  • Protocol and statistical analysis plan · Jan 25, 2017

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: Undecided

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 21, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07355426
Lead sponsor
University of Kinshasa
Responsible party
Ken Bisabu, Kelu (Principal Investigator, University of Kinshasa) — Principal investigator
First posted
Jan 21, 2026
Start date
Jan 30, 2017
Primary completion
Feb 1, 2017
Completion
Aug 30, 2025
Last update
Jan 21, 2026

Study contacts

Celestin Ndosimao Nsibu, Full professor
study director · Kinshasa University
Joseph Mabiala Bodi, Full professor
study chair · Kinshasa University
Leon Tshilolo, Full professor
study chair · Kinshasa University

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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