Nimodipine Pharmacokinetic Variability in Various Patient Populations.
Sherif Hanafy MahmoudXinqi JiFadumo Ahmed IssePublished in: Drugs in R&D (2021)
Nimodipine has been shown to improve outcomes following aneurysmal subarachnoid hemorrhage. Guidelines recommend that all patients receive a fixed dose of oral nimodipine for 21 days. However, pharmacokinetic studies have suggested variability of nimodipine pharmacokinetics in subarachnoid hemorrhage and in other patient populations. The clinical relevance of such variability is unknown. Therefore, the objective of the present review is, first, to conduct a literature review and summarize nimodipine pharmacokinetic data and sources of variability in various patient groups. Second, to determine if there is any evidence reporting an association between nimodipine exposure and clinical outcomes in patients with subarachnoid hemorrhage. A systematic literature search was performed in MEDLINE and EMBASE. The following keywords were used: ("nimodipine" OR "nymalize" OR "nimotop") AND ("pharmacokinetic*", OR "PK"). The search results were limited to English language and human studies. A large interpatient variability in nimodipine pharmacokinetics has been reported. Patient-specific factors that had an influence on pharmacokinetic parameters are age, comorbidities, variabilities in metabolism due to genetic polymorphism and co-administered medications, as well as nimodipine administration technique. The association between nimodipine exposure and clinical outcomes remains unclear and data available are too scarce to reach a firm conclusion. Here, we present a narrative review with a systematic literature search discussing nimodipine pharmacokinetic variability in various patient populations. It is not clear if minimal or lack of systemic exposure to nimodipine denies its benefit and contributes to worsening outcomes in patients with subarachnoid hemorrhage. Further studies are needed to determine if such an association exists.
Keyphrases
- subarachnoid hemorrhage
- brain injury
- cerebral ischemia
- case report
- systematic review
- ejection fraction
- adipose tissue
- electronic health record
- autism spectrum disorder
- newly diagnosed
- type diabetes
- end stage renal disease
- weight loss
- machine learning
- deep learning
- emergency department
- skeletal muscle
- artificial intelligence
- dna methylation
- prognostic factors