Antipsychotic Side Effects Identification Using the Naranjo Algorithm at Hospital X Yogyakarta

Odilia Danti Nugrahaningtyas; Bangunawati Rahajeng

doi:10.24198/ijpst.v12s1.57955

Antipsychotic Side Effects Identification Using the Naranjo Algorithm at Hospital X Yogyakarta

Odilia Danti Nugrahaningtyas, Bangunawati Rahajeng

Abstrak

The escalating utilization of antipsychotics undeniably contributes to the heightened risk of drug side effects. This study aims to identify antipsychotic side effects and their causality. This study belongs to observational research with a descriptive cross-sectional design. The participants were patients prescribed antipsychotic drugs at Hospital X Yogyakarta between April and July 2022 who met the specified inclusion criteria. This study utilized accidental sampling, generating 61 patients as the participants. Data collection was carried out prospectively through interviews and medical records. The Naranjo algorithm was used to analyze causality. The predominant drug type administered to patients was atypical antipsychotics, with a total of 72 prescriptions. Risperidone accounted for the highest number of prescriptions, totaling 37 (22.16%). Weight gain contributed to the highest percentage of reported side effects, with 16 (16.33%) instances. The side effects with the highest causality score of 7 (probable) were breast secretion, tremors, palpitations, weight gain, and decreased blood pressure. Weight gain was the most frequently observed side effect when taken together. The maximum score for the causality association of side effects was an average of 7, indicating a probable connection. This study provides insight into the numerous side effects associated with prescription antipsychotic drugs.

Kata Kunci

Antipsychotics; Causality; Naranjo Algorithm; Side effects

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Referensi

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DOI: https://doi.org/10.24198/ijpst.v12s1.57955