| アブストラクト | ObjectiveChildren with congenital heart disease are highly vulnerable to drug-related adverse effects due to the use of complex polypharmacy. This study aimed to develop and retrospectively evaluate a hybrid clinical decision support system for predicting drug-related adverse effects in this population.MethodsThis two-phase study combined machine-learning techniques and expert clinical rules. Phase 1 included a retrospective analysis of 4651 pediatric congenital heart disease reports from the Food and Drug Administration Adverse Event Reporting System to train and compare five machine-learning models. The best-performing model, Random Forest, was selected. In Phase 2, a hybrid clinical decision support system integrating the Random Forest model with an expert-validated rule-based engine was developed and retrospectively evaluated using 330 inpatient records of pediatric patients with congenital heart disease.ResultsThe Random Forest model achieved a mean area under the receiver operating characteristic curve of 0.902. During clinical validation, the hybrid clinical decision support system demonstrated a mean accuracy of 0.85 across 11 common drug-adverse effect pairs, outperforming standalone machine-learning- and rule-based approaches. This study demonstrated the feasibility and clinical fidelity of using a hybrid clinical decision support system for predicting drug-related adverse effects in pediatric patients with congenital heart disease, supporting safer and more personalized pharmacotherapy.ConclusionsThis study demonstrated the feasibility and clinical fidelity of using a hybrid clinical decision support system for predicting drug-related adverse effects in pediatric patients with congenital heart disease, supporting safer and more personalized pharmacotherapy. |
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| ジャーナル名 | The Journal of international medical research |
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| Pubmed追加日 | 2026/8/2 |
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| 投稿者 | Toni, Esmaeel; Ayatollahi, Haleh; Abbaszadeh, Reza; Fotuhi Siahpirani, Alireza |
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| 組織名 | Student Research Committee, Iran University of Medical Sciences, Tehran, Iran.;RINGGOLD: 440827;Health Management and Economics Research Center, Health Management Research;Institute, Iran University of Medical Sciences, Tehran, Iran. RINGGOLD: 440827;Heart Research Center, Rajaie Cardiovascular Medical and Research Center, Iran;University of Medical Sciences, Tehran, Iran.;Institute of Biochemistry and Biophysics (IBB), Department of Bioinformatics,;University of Tehran, Tehran, Iran. RINGGOLD: 48425 |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/42541705/ |
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