Evaluasi Penggunaan Antibiotik Pada Pasien Pneumonia Rawat Inap Di Rsu Mitra Sejati
Abstract
Pneumonia is a lower respiratory tract infection that remains a leading cause of death globally. Irrational use of antibiotics in its treatment worsens antibiotic resistance. This study aims to evaluate antibiotic use in hospitalized pneumonia patients at RSU Mitra Sejati using ATC/DDD and DU90% methods. This descriptive observational study used secondary data from adult inpatient medical records between January and December 2023. Results showed 37 patients, majority male (51.35%), mostly aged 26–35 and 56–65 years. A total of 273 antibiotic uses were recorded, dominated by third-generation cephalosporins, especially Cefixime 200 mg (31.14%). ATC/DDD analysis showed highest DDD/100 days for Cefixime 200 mg (21.04), Levofloxacin 500 mg (18.32), and Ceftriaxone 1 g (12.87). DU90% analysis identified six antibiotics comprising 91.04% of total use, indicating rational use according to national guidelines.
Read the paper
Related studies
- Severe clinical outcomes of COVID-19 associated with proton pump inhibitors: a nationwide cohort study with propensity score matching
- Thiophenes—Naturally Occurring Plant Metabolites: Biological Activities and In Silico Evaluation of Their Potential as Cathepsin D Inhibitors
- Inhalable Mannosylated Rifampicin–Curcumin Co-Loaded Nanomicelles with Enhanced In Vitro Antimicrobial Efficacy for an Optimized Pulmonary Tuberculosis Therapy
- Association between cord blood 25-hydroxyvitamin D concentrations and respiratory tract infections in the first 6 months of age in a Korean population: a birth cohort study (COCOA)
- GC-MS Analysis and Biomedical Therapy of Oil from n-Hexane Fraction of Scutellaria edelbergii Rech. f.: In Vitro, In Vivo, and In Silico Approach
- Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure–Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.