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Agreement between WHO-UMC causality scale and the Naranjo algorithm for causality assessment of adverse drug reactions
BACKGROUND: The Pharmacovigilance Program of India recommends the use of the World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, while many clinicians prefer the Naranjo algorithm for its simplicity. In the present study, we assessed agreement between the two widely used causality a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8565125/ https://www.ncbi.nlm.nih.gov/pubmed/34760748 http://dx.doi.org/10.4103/jfmpc.jfmpc_831_21 |
Sumario: | BACKGROUND: The Pharmacovigilance Program of India recommends the use of the World Health Organization-Uppsala Monitoring Centre (WHO-UMC) scale, while many clinicians prefer the Naranjo algorithm for its simplicity. In the present study, we assessed agreement between the two widely used causality assessment scales, that is, the WHO-UMC criteria and the Naranjo algorithm. MATERIALS AND METHODS: In this study, 842 individual case safety reports were randomly selected from 1000 spontaneously reported forms submitted to the ADR Monitoring Center at a tertiary healthcare Institute in Central India between 2016 and 2018. Two well-trained independent groups performed the causality assessment. One group performed a causality assessment of the 842 ADRs using the WHO-UMC criteria and the other group performed the same using the Naranjo algorithm. The agreement between two ADR causality scales was assessed using the weighted kappa (κ) test. RESULTS: Cohen's kappa coefficient (κ) statistical test was applied between the two scales (WHO-UMC scale and Naranjo algorithm) to find out the agreement between these two scales. “No” agreement was found between the two scales {Kappa statistic with 95% confidence interval = 0.048 (P < 0.001)}. CONCLUSION: There was no agreement found between the WHO-UMC criteria and the Naranjo algorithm in our study. |
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