ArticleChildren (Basel, Switzerland)2022
An Artificial Intelligence Approach to Support Detection of Neonatal Adverse Drug Reactions Based on Severity and Probability Scores: A New Risk Score as Web-Tool.
Article in Children (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 23 citations in OpenAlex.
- Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.Future healthcare journal · 2026Review
- Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- Risk prediction models for adverse drug reactions in pediatrics: a scoping review.International journal of clinical pharmacy · 2026Article
- Adverse Drug Reactions in Neonates: How to Detect and Address Signals in the Noise.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2025Article
- Real-World Safety Profile of Proton Pump Inhibitors in Infants as Reported in the FDA Adverse Event Reporting System (FAERS): Tiny Tummies, Key Decisions.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Serious Adverse Events: A Replicability and Validation Study of Naranjo Causality Assessment Tool in a Canadian Clinical Setting.Journal of evaluation in clinical practice · 2025Article
- Electronic Prescribing in the Neonatal Intensive Care Unit: Analysis of Prescribing Errors and Risk Factors.Journal of medical systems · 2025Article
- Adverse events in the neonatal intensive care unit identified by triggers.Frontiers in pharmacology · 2025Article
- Neural network analysis of the contribution of psychotropic prescription sequences to the risk of non-psychiatric adverse events in bipolar and schizophrenia spectrum disorders.Frontiers in digital health · 2025Article
- Development and validation of a clinical score to identify hospitalised patients at high risk of drug-related problems.Journal of pharmaceutical policy and practice · 2025Article
- Digital monitoring of medication safety in children: an investigation of ADR signalling techniques in Malaysia.BMC medical informatics and decision making · 2024Article
- Drug Safety During Breastfeeding: A Comparative Analysis of FDA Adverse Event Reports and LactMedPharmaceuticals (Basel, Switzerland) · 2024Article
- Artificial intelligence in community pharmacy practice: Pharmacists' perceptions, willingness to utilize, and barriers to implementation.Exploratory research in clinical and social pharmacy · 2024Article
- Artificial intelligence in the field of pharmacy practice: A literature review.Exploratory research in clinical and social pharmacy · 2023Review
- The neonatal adverse event severity scale: current status, a stakeholders' assessment, and future perspectives.Frontiers in pediatrics · 2023Article
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Authors and funding
7 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCritically ill neonates are at greater risk for adverse drug reactions (ADRs). The differentiation of ADRs from reactions associated with organ dysfunction/immaturity or genetic variability is difficult.
methodsIn this prospective cohort study, each ADR was assessed using newborn-specific severity and probability scales by the clinical pharmacist. Subsequently, a machine learning-based risk score was designed to predict ADR presence in neonates.
resultsIn 98/412 (23.8%) of (56.3%; male) neonates included, 187 ADRs (0.42 ADR/patient) were determined related to 49 different drugs (37.12%). Drugs identified as high risk were enoxaparin, dexmedetomidine, vinblastine, dornase alfa, etoposide/carboplatin and prednisolone. The independent variables included in the risk score to predict ADR presence, according to the random forest importance criterion, were: systemic hormones (2 points), cardiovascular drugs (3 points), diseases of the circulatory system (1 point), nervous system drugs (1 point), and parenteral nutrition treatment (1 point), (cut-off value: 3 points). This risk score correctly classified 91.1% of the observations in the test set (c-index: 0.914).
conclusionsUsing the high-performing risk score specific to neonates, it is expected that high-risk neonatal ADRs can be determined and prevented before they occur. Moreover, the awareness of clinicians of these drugs can be improved with this web-tool, and mitigation strategies (change of drug, dose, treatment duration, etc.) can be considered, based on a benefit-harm relationship for suspected drugs with a newborn-centered approach.
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