Study of Medicine Dosage Adjustments in Inpatients with Chronic Kidney Disease
Katharina Kening Weking(1*), Liniati Geografi(2), Clara Ritawany Sinaga(3)
(1) Program Studi S1 Farmasi, Sekolah Tinggi Ilmu Kesehatan Dirgahayu Samarinda
(2) Program Studi S1 Farmasi, Sekolah Tinggi Ilmu Kesehatan Dirgahayu Samarinda
(3) Program Studi S1 Farmasi, Sekolah Tinggi Ilmu Kesehatan Dirgahayu Samarinda
(*) Corresponding Author
Abstract
Background: Decreased kidney function in patients with Chronic Kidney Disease (CKD) necessitates dose adjustment, especially for medicines that have a narrow therapeutic index to avoid unwanted medicine effects.
Objectives: The purpose of this study was to determine the medicine dosage adjustments in CKD patients and their therapy outcomes.
Methods: This type of research is descriptive with a retrospective approach. The sample in this study is the medical records of inpatient CKD patients at Abdoel Wahab Sjahranie Samarinda Hospital for the period May to November 2022. Calculation of GFR (Glomerular Filtration Rate) uses the MDRD (Modification of Diet in Renal Disease) formula.
Results: The results showed that the sex of most patients was male as many as 56.25%. The age of most patients in the range of 53-59 years old as many as 33.75%. Most CKD severity level is stage 5 as many as 91.25%. The most common comorbidities were hypertension (61 patients), diabetes mellitus (15 patients), and edema or pulmonary edema (11 patients). There were 77 patients requiring dose adjustment out of a total of 80 patients. There were 149 (34.89%) medicines requiring dose adjustment out of a total of 427 medicines, with the 5 most medicines being calcium carbonate (24.16%), furosemide (24.16%), metoclopramide (10.74%), paracetamol (10.74%), and ranitidine (7.39%). There were 128 (85.91%) medicines with doses appropriate to the Lexicomp 2023 or Renal Pharmacotherapy 2013. The therapy outcome improved in patients who required dose adjustments by 90.91%.
Conclusion: It is recommended to calculate GFR using a new formula such as eGFR using CKD-EPI, and collecting data with a larger number of samples.
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DOI: https://doi.org/10.22146/jmpf.88181
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