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Clinical Pertinence and Determinants of Potential Drug-Drug Interactions in Chronic Kidney Disease Patients: A Cross-sectional Study.
Khanna, Janvi; Kumar, Siddharth; Mehta, Sudhir; Chaudhary, Jasmine; Jain, Akash.
Afiliación
  • Khanna J; Department of Pharmacy Practice, M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, India.
  • Kumar S; Department of Pharmacy Practice, M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, India.
  • Mehta S; Department of Nephrology, M.M. Institute of Medical Sciences & Research, Maharishi Markandeshwar (Deemed to be University), Mullana, India.
  • Chaudhary J; Department of Pharmaceutical Chemistry, M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, India.
  • Jain A; Department of Pharmacology, M.M. College of Pharmacy, Maharishi Markandeshwar (Deemed to be University), Mullana, India.
J Pharm Technol ; 40(3): 142-151, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38784027
ABSTRACT

Background:

Chronic kidney disease (CKD) is one of the major health issues effecting around 15% of world population, and its further complications has raised the need of polypharmacy for management. But this polypharmacy also upsurges the risk of potential drug-drug interactions (pDDIs) in CKD patients, which may further be responsible for increased morbidity and mortality.

Objective:

The main objective is therefore to evaluate the distribution, severity, causes, associated drug interactions, and clinical relevance of determination of pDDIs in CKD patients.

Methods:

Medical files of CKD patients examined at nephrology department, Maharishi Markandeshwar Institute of Medical Sciences and Research (MMIMSR), Mullana, between December 2022 and May 2023 were cross-sectionally assessed for this study. Medscape drug interaction checker was used to study patient profiles for pDDIs, and suggestive measures to minimize those pDDIs were studied using DDInter to ensure better clinical decision-making and patient safety. IBM SPSS (version 24) was utilized for statistical analysis.

Results:

The data reveal that 74.5% of the 200 medical files being evaluated had 839 pDDIs in total, out of which nearly 78.3% of patients had moderate, 15.6% had minor, and 6.07% had serious interactions. The potential adverse outcomes of pDDIs included an irregular heartbeat, hypokalemia, central nervous system (CNS) adverse effects, hypoglycemia, and a decline in therapeutic efficacy. The prevalence of pDDIs was discovered to be substantially correlated with age ≥60 years, (odds ratio [OR] = 0.65; 95% CI = 0.4-0.9; P = 0.040), length of stay ≥10 days (OR = 4.0; 95% CI = 1.29-6.1; P = 0.016), and number of prescribed drugs ≥10 (OR = 5.5; 95% CI = 2.45-10.69; P = 0.004).

Conclusion:

Patients with CKD have a high incidence of pDDIs (mainly mild to moderate). Older age, duration of hospital stays, and polypharmacy all raise the risk of pDDIs. Healthcare professionals (physicians and clinical pharmacist) should use drug interaction checker software programs like Medscape and DDInter to acquire knowledge about different pDDIS and their alternative measures so that the associated adverse drug reactions (ADRs) can be controlled and rational drug combination can be prescribed for management of CKD ensuring better patient care.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Pharm Technol Año: 2024 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Pharm Technol Año: 2024 Tipo del documento: Article País de afiliación: India