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

January 12, 2026 updated by: Ken Bisabu, Kelu, University of Kinshasa

Pediatric In-Hospital Mortality Risk in Congolese Children With Severe Malaria: Derivation of Clinical Prediction Models Using Machine Learning Based-Algorithms

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).

Study Overview

Status

Completed

Conditions

Intervention / Treatment

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.

Study Type

Observational

Enrollment (Actual)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child

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.

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
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
  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

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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]
Time Frame: Day 7
Death was defined as a categorical variable, defining patients who died and those who survived.
Day 7

Secondary Outcome Measures

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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University of Kinshasa

Investigators

  • Study Director: Celestin Ndosimao Nsibu, Full professor, Kinshasa University
  • Study Chair: Joseph Mabiala Bodi, Full professor, Kinshasa University
  • Study Chair: Leon Tshilolo, Full professor, Kinshasa University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 30, 2017

Primary Completion (Actual)

February 1, 2017

Study Completion (Actual)

August 30, 2025

Study Registration Dates

First Submitted

September 11, 2025

First Submitted That Met QC Criteria

January 12, 2026

First Posted (Actual)

January 21, 2026

Study Record Updates

Last Update Posted (Actual)

January 21, 2026

Last Update Submitted That Met QC Criteria

January 12, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SM_PEDCUK

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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