Related Experiment Videos

A clinical decision support system for predicting drug-related adverse effects in pediatric patients with congenital

Esmaeel Toni1, Haleh Ayatollahi2, Reza Abbaszadeh3

  • 1Student Research Committee, Iran University of Medical Sciences, Tehran, Iran.

The Journal of International Medical Research
|August 1, 2026
PubMed

Insights

A new hybrid system combining machine learning and clinical rules accurately predicts drug side effects in children with heart defects. This approach enhances pharmacotherapy safety and personalization for vulnerable pediatric patients.

Area of Science:

  • Pharmacogenomics
  • Clinical Informatics
  • Pediatric Cardiology

Background:

  • Children with congenital heart disease (CHD) face high risks of drug-related adverse effects due to complex medication regimens.
  • Predicting these adverse effects is crucial for improving patient safety and treatment outcomes.

Purpose of the Study:

  • To develop and evaluate a hybrid clinical decision support system (CDSS) for predicting drug-related adverse effects in pediatric patients with CHD.
  • To enhance the safety and personalization of pharmacotherapy in this vulnerable population.

Main Methods:

  • A two-phase approach combining machine learning (ML) and expert clinical rules.
  • Phase 1: Retrospective analysis of 4651 pediatric CHD reports from FDA Adverse Event Reporting System to train and select the best ML model (Random Forest).
  • Phase 2: Development and retrospective evaluation of a hybrid CDSS integrating Random Forest with a rule-based engine using 330 inpatient CHD records.

Main Results:

  • The Random Forest model achieved a high performance with a mean area under the receiver operating characteristic curve of 0.902.
  • The hybrid CDSS demonstrated a mean accuracy of 0.85 across 11 common drug-adverse effect pairs.
  • The hybrid system outperformed standalone ML and rule-based approaches in clinical validation.

Conclusions:

  • The study confirms the feasibility and clinical fidelity of the hybrid CDSS for predicting drug-related adverse effects in pediatric CHD patients.
  • This hybrid approach supports safer and more personalized pharmacotherapy for children with congenital heart disease.
  • The developed system offers a promising tool for mitigating adverse drug events in a high-risk pediatric population.

Keywords:
Congenital heart diseaseclinical decision support systemdrug-related adverse effects and adverse reactionsmachine learningpediatrics

Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
Pharmacokinetics in Pediatric Patients: Drug Excretion01:26

Pharmacokinetics in Pediatric Patients: Drug Excretion

In pediatric medicine, understanding the renal function and drug elimination nuances is crucial for administering safe and effective treatments. Newborns, in particular, display markedly slower renal functions than adults, profoundly affecting how drugs are cleared from their bodies. This slower drug clearance requires clinicians to extend the dosing intervals for many medications to prevent drug accumulation and toxicity while ensuring therapeutic efficacy.One key area where these adjustments...
Pharmacokinetics in Pediatric Patients: Drug Distribution01:17

Pharmacokinetics in Pediatric Patients: Drug Distribution

Drug distribution in the pediatric population exhibits unique challenges and considerations due to the physiological differences between children, particularly neonates and infants, and adults. A crucial aspect of pediatric pharmacology is understanding how these differences impact the pharmacokinetics of various drugs, necessitating age-specific dosing strategies to ensure efficacy and safety.Neonates and infants have a higher total body water content, ~75%–90% of their body weight, compared...
Pharmacokinetics in Pediatric Patients: Overview and Drug Absorption01:23

Pharmacokinetics in Pediatric Patients: Overview and Drug Absorption

Understanding the physiological differences in the pediatric population is crucial for effective pharmacotherapy. Neonates, infants, and children exhibit significant variations in gastric pH, gastric emptying time, intestinal transit time, and biliary function. These variations profoundly affect oral drug absorption, necessitating a nuanced approach to pediatric dosing.Neonates present with a unique physiological profile, having a gastric pH greater than 4 and faster and more irregular gastric...
Drug Toxicity: Risk factors01:24

Drug Toxicity: Risk factors

Adverse Drug Reactions (ADRs) are potential complications that arise during pharmacotherapy, influenced by multiple risk factors. Age plays a significant role; both neonates and the elderly are at heightened risk due to their respective immature and diminished metabolic and elimination processes. Gender also impacts ADRs, with females experiencing a 1.5 to 1.7-fold greater risk than males, which may be linked to pharmacokinetic, pharmacodynamic, and hormonal differences. Notably, neonates, the...