The Role of Sex, Age and Genetic Polymorphisms of CYP Enzymes on the Pharmacokinetics of Anticholinergic Drugs
Bibliographic record
Abstract
Drugs exhibiting anticholinergic properties are commonly used by older adults even with the associated risk of adverse drug events. Aging, sex and genetic polymorphisms of cytochrome P450 (CYP) enzymes are associated with alterations in pharmacokinetic processes which may increase drug exposure and further increase the risk of adverse drug events. Age-related changes include; pseudocapillarization of liver sinusoidal endothelial cells which limit passage of drugs through the liver, an approximate 3.5% decline in CYP450 content for each decade of life, and a reduction in kidney function reducing drug excretion. Sex-related differences include; women having delayed gastric and colonic emptying, higher gastric pH, reduced catechol-O-methyl transferase activity, reduced glucuronidation, and reduced renal clearance and men having larger stomachs which may allow them to dissolve and absorb medication more completely. The overlay of poor metabolism phenotypes for CYP2D6 and CYP2C19 may further modify anticholinergic drug exposure in a significant proportion of the population. These factors help explain clinical trials that show older adults and specifically women achieve higher plasma concentrations of anticholinergic drugs. Despite this knowledge, age and sex are rarely considered when making decisions about the dosing of anticholinergic medications. As this is relevant to the future use of personalized medicine, the objective of this review is to provide a clinical perspective on age, sex, and CYP genetic polymorphisms and their role in the metabolism and exposure to anticholinergic drugs. Future work needs to account for age, sex and CYP polymorphism so that we may better approach personalized medicine for optimal outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".