Risk factors for adverse drug reactions in pediatric inpatients: A cohort study

Andrade, Paulo Henrique Santos; Lobo, Iza Maria Fraga; Silva, Wellington Barros da

doi:10.1371/journal.pone.0182327

Cited by 17 publications

(12 citation statements)

References 23 publications

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“…Regression methods were primarily used to analyze EMR data. Using survival analysis, the risk of ADR was calculated using single-center EMR [44,68–76] . Using EMR, these studies examined the detection of ADR at multiple centers [77–79] .…”

Section: Resultsmentioning

confidence: 99%

Analyzing adverse drug reaction using statistical and machine learning methods

et al. 2022

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Background: Adverse drug reactions (ADRs) are unintended negative drug-induced responses. Determining the association between drugs and ADRs is crucial, and several methods have been proposed to demonstrate this association. This systematic review aimed to examine the analytical tools by considering original articles that utilized statistical and machine learning methods for detecting ADRs. Methods: A systematic literature review was conducted based on articles published between 2015 and 2020. The keywords used were statistical, machine learning, and deep learning methods for detecting ADR signals. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) guidelines. Results: We reviewed 72 articles, of which 51 and 21 addressed statistical and machine learning methods, respectively. Electronic medical record (EMR) data were exclusively analyzed using the regression method. For FDA Adverse Event Reporting System (FAERS) data, components of the disproportionality method were preferable. DrugBank was the most used database for machine learning. Other methods accounted for the highest and supervised methods accounted for the second highest. Conclusions: Using the 72 main articles, this review provides guidelines on which databases are frequently utilized and which analysis methods can be connected. For statistical analysis, >90% of the cases were analyzed by disproportionate or regression analysis with each spontaneous reporting system (SRS) data or electronic medical record (EMR) data; for machine learning research, however, there was a strong tendency to analyze various data combinations. Only half of the DrugBank database was occupied, and the k-nearest neighbor method accounted for the greatest proportion.

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Section: Resultsmentioning

confidence: 99%

Analyzing adverse drug reaction using statistical and machine learning methods

et al. 2022

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“…The ADRs represent a public health problem, particularly in pediatric patients (Andrade et al, 2017a) and often are the cause of emergency department (ED) admission. In the last years, an increased number of ED visits of pediatric population has been observed, thus causing an overcrowding in the hospital.…”

Section: Introductionmentioning

confidence: 99%

A 7-Years Active Pharmacovigilance Study of Adverse Drug Reactions Causing Children Admission to a Pediatric Emergency Department in Sicily

et al. 2020

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Children represent one of the most susceptible groups to adverse drug reactions (ADRs), as a consequence of physiological growth and maturation of different organ systems. The aim of this study was to characterize the frequency, preventability and seriousness of ADRs recorded in the Pediatric Emergency Department (ED) of the University hospital of Messina, in Sicily. All the suspected adverse reactions to drugs and vaccines collected from 2012 to 2018 were selected and then analyzed. Only adverse drug reactions (ADRs) with a probable or possible causality assessment were included, according to the Naranjo Algorithm and the World Health Organization criteria; the preventability assessment using Schumock and Thornton criteria was also carried out. The Medical Dictionary for Regulatory Activities (MedDRA) was used to group ADRs. Of 75,935 admissions to the Pediatric ED, 120 were due to suspected ADRs. The rate of hospital admission due to ADRs (75.8%) was significantly greater than that of patients without ADRs (11.9%). Among pediatric patients with ADRs the median (Q1-Q3) age was 29.5 (12-73.25) months. Most of ADRs were observed in infants and children (43.3% and 41.7%, respectively vs adolescents, 15%). In addition, in children with ADRs, females [41 (14-105)] were older than males [23 (11-45)] (p=0.044). Most adverse reactions were serious (75.8%) and 20.8% were preventable or probably preventable; however, the majority of serious ADRs (93.4%) resulted without sequelae. The reactions were found to be as probable (54.2%) or possible (45.8%). Vaccines (n=63), antibacterials (n=31) and antiinflammatory medicines (n=14) were the most frequently drugs involved. Organ toxicity mapping due to vaccines was general disorders and administration site conditions (65.1%), nervous disorders (50.2%), cutaneous disorders (35%), followed by gastrointestinal disorders (20.6%). Cutaneous disorders (76%) gastrointestinal (20.7%),

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“…In the present study, dipyrone was the drug with the highest frequency of administration and responsible for 03 of the 10 drug interactions of moderate severity, all related to difficult blood pressure control. In other studies dipyrone was also the most frequent medication in prescriptions on potential interactions in hospitalized patients (DE OLIVEIRA;SCHUELTER-TREVISOL;TREVISOL, 2014;ANDRADE;LOBO;DA SILVA, 2017;BURKE;SMYTH;FITZGERALD, 2006).…”

Section: Potential and Clinical Evaluation Ddismentioning

confidence: 88%

Incidência de Interações Medicamentosas e Avaliação Clínica nos Pacientes de um Hospital Público Brasileiro

et al. 2020

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Interações droga-droga (IDDs) são responsáveis por problemas terapêuticos e as principais causas de reações adversas a medicamentos que levam a hospitalização. O objetivo do trabalho foi analisar a incidência de IDDs em pacientes admitidos em hospital público no Brasil, em 2015. Em um estudo transversal, 351pacientes foram selecionados com IDDs utilizando-se o banco de dados da Micromedex®, e as interações foram classificadas de acordo com a severidade e documentação. Os potenciais IDDs foram avaliados durante o acompanhamento farmacoterapêutico diário por anamnese farmacêutica e a análise dos exames laboratoriais foi realizada. Um total de 2.937 potenciais IDDs foram identificados e 28,42% deles tinham sinais e sintomas clínicos confirmados em 87 pacientes (29%). Entre os pacientes que apresentaram interações, 62,07% tinham mais que 60 anos. Neste grupo de idade, 61,27% de todos os sinais e sintomas clínicos observados foram também identificados, demonstrando uma associação positiva entre interações clínicas e idade. Além disso, uma correlação positiva entre o número de drogas prescritas e a ocorrência de sinais clínicos também foram observados. Muitos IDDs observados foram de severidade moderada e estavam relacionados a alterações das pressões arteriais e níveis glicêmicos. Este estudo demonstrou que IDDs estão diretamente relacionados a idade e número de drogas prescritas. E a grande frequência de IDDs com documentação fraca alertam para a necessidade de se analisar esse tipo de interação. Sendo assim, este estudo mostrou que potenciais IDDs e sinais e sintomas clínicos significantes em pacientes só reforçam a necessidade de se apoiar a farmácia clínica. Palavras-chave: Interação Droga-Droga (IDD). Pacientes Internados. Farmacoterapia, Poli Farmácia. Sinais e Sintomas. Abstract Drug-drug interactions (DDIs) are responsible for therapeutic problems and the main causes of adverse drug reactions that require hospitalization. The aim of this study was to analyze the incidence of DDIs in patients admitted in a Public Hospital in Brazil, in 2015. In a cross-sectional study, DDIs were screened in 351 patients, using Micromedex® database, that classify interactions according to severity and documentary evidence. Potential DDIs were assessed at the daily pharmacotherapeutic follow-up through pharmaceutical anamnesis and analysis of laboratory tests were performed. A total of 2,937 potential DDIs were identified and 28.42% of these had confirmed signs and symptoms clinical in 87 patients (29%). Among the patients that presented interactions, 62.07% were older than 60 years. In this age group, 61.27% of all signs and symptoms clinical observed in the study were also identified, demonstrating a positive association between the occurrence of clinical interactions and age. In addition, a positive correlation between the number of drugs prescribed and the occurrence of signs clinicals was also observed. Most DDIs observed were of moderate severity and were related to imbalance of blood pressure and glycemic levels. This study demonstrated that DDIs are directly related to the age and number of drugs prescribed. And the greater frequency of DDIs with fair documentary evidence alerts to the need to consider all the possible interactions. Thereafter, this study showed that potential DDIs and sign and clinical symptoms are significant in patients and reinforce the need to support Clinical Pharmacy. Keywords: Drug-Drug Interaction (DDI). Inpatients. Pharmacotherapy. Poly Pharmacy. Sign and Symptom.

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Risk factors for adverse drug reactions in pediatric inpatients: A cohort study

Cited by 17 publications

References 23 publications

Analyzing adverse drug reaction using statistical and machine learning methods

Analyzing adverse drug reaction using statistical and machine learning methods

A 7-Years Active Pharmacovigilance Study of Adverse Drug Reactions Causing Children Admission to a Pediatric Emergency Department in Sicily

Incidência de Interações Medicamentosas e Avaliação Clínica nos Pacientes de um Hospital Público Brasileiro

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