Improving the Care of Older Patients by Decreasing Potentially Inappropriate Medications, Potential Medication Omissions, and Serious Drug Events Using Pharmacogenomic Data about Variability in Metabolizing Many Medications by Seniors
Why this work is in the frame
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Bibliographic record
Abstract
Polypharmacy, potentially inappropriate medications (PIMs) identified by the American Geriatrics Society and Screening Tool of Older People's Prescriptions (STOPP), potential prescribing omissions (PPOs) identified by Screening Tool to Alert to Right Treatment (START) and serious drug events (SDEs), are major problems for seniors. They correlate with increased risks of rehospitalization and death within six months of hospital discharge. About 75% of commonly prescribed medications are metabolized by P450 cytochrome enzymes. Electronic medical records (EMRs) providing integrated comprehensive pharmacogenomic advice are available only in very large health organizations. The study design of this article is a cross-sectional analysis of the American Geriatrics Society (AGS) and STOPP PIM and START PPO databases integrated with three P450 cytochrome enzyme databases (Flockhart Tables, DrugBank, and Rx Files) and the data are reported using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. To enable optimally prudent prescribing this article presents for primary care physicians and physicians in remote or rural areas without access to such services a comprehensive integration of the data on PIM and PPO medications with the data on the P450 cytochrome isoforms that metabolize these medications. Additionally presented are the medications metabolized by multiple isoforms and medications that inhibit or induce individual or multiple isoforms. The most extensive metabolic activities involve the central nervous system, anxiolytic, antidepressive, antipsychotic, musculoskeletal, and cardiovascular drugs. The P450 cytochrome isoforms that metabolize the most medications are 3A457, 2C9, 2D6, and 2C19 and nearly all central nervous systems medications compete to be metabolized by 3A457. Medications with the largest inducer or inhibitor activity are highlighted and also a list of commonly prescribed medications that are neither PIMs nor PPOs but compete for metabolism by the same isoforms.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it