Do P-Glycoprotein medications alter the risk of Ventriculoperitoneal Shunt in Adults with Hydrocephalus?
Jason Rafael GrullonGeorge W KoutsourasNneka F OnwumereDavid F LehmannSatish KrishnamurthyPublished in: Journal of clinical pharmacology (2023)
Hydrocephalus is a disorder caused by excess fluid accumulation in the brain and results in brain damage with consequent cognitive and physical problems. This condition has no cure; the only treatment is brain surgery. Experimental data indicate that P-glycoprotein (P-gp) plays a crucial role in the pathogenesis of hydrocephalus due to its function in clearing macromolecules from the brain. Numerous medications frequently used are classified as P-gp inducers or inhibitors, and comprehending their effects may aid in attaining improved patient outcomes. Therefore, in this single-center retrospective study, we examined the risk of the need for ventriculoperitoneal shunt placement over ten years among 4,588 adult patients with hydrocephalus not exposed to any P-gp inhibitors/inducer or exclusively exposed to either P-gp inhibitors or inducers. Our analysis shows that patients exposed to P-gp inhibitors had a 3.2 times higher risk of requiring ventriculoperitoneal shunt surgery (p < 0.0001). In contrast, the relative risk was not significantly affected (p = 0.07) among those exposed to P-gp inducers. Our findings indicate the need for caution when prescribing P-gp inhibitors to patients with hydrocephalus. Additional studies using larger cohorts are required to confirm whether P-gp inducers in patients with hydrocephalus can mitigate the risk of ventriculoperitoneal shunt. This article is protected by copyright. All rights reserved.
Keyphrases
- subarachnoid hemorrhage
- cerebrospinal fluid
- resting state
- white matter
- cerebral ischemia
- pulmonary artery
- minimally invasive
- end stage renal disease
- mental health
- chronic kidney disease
- brain injury
- newly diagnosed
- ejection fraction
- functional connectivity
- coronary artery bypass
- magnetic resonance
- coronary artery disease
- big data
- prognostic factors
- percutaneous coronary intervention
- acute coronary syndrome
- machine learning
- deep learning
- drug induced
- adverse drug