#4594 INPATIENT POLYPHARMACY AND THE AGING KIDNEY
Bibliographic record
Abstract
Abstract Background and Aims Individuals aged ≥80 years have been found to have some of the highest rates of polypharmacy. Nearly 50% of these people are likely to have significant renal impairment, either from chronic kidney disease or age-related decline. Since many drugs are renally excreted, reduced renal function will cause pharmacokinetic and pharmacodynamic changes. As a result, some medications are inappropriate and there is an increased risk of adverse effects which are dose-related or related to drug interactions. We aim to examine the prevalence of highly renally excreted and nephrotoxic medications taken by our oldest old medical inpatients. Method Data was obtained as part of an ongoing prospective cross-sectional observational study examining polypharmacy in elderly inpatients at Ballina Hospital, Australia. Data as of 03/01/2019 for participants aged ≥80 years were retrieved as part of this nested study involving acute medical inpatients with sufficient capacity to provide informed consent. Exclusion criteria comprised of people with insufficient working knowledge of English, cognitive impairment (including delirium) and those under the age of 80 years. Information with regards to inpatient medication use, co-morbidities and renal function (creatinine clearance, CrCl) were retrieved from inpatient medical records as part of routine clinical care. Renally excreted medications and potential nephrotoxic medications were identified via the Australian Medicines Handbook and Renal Drug Database. Cognition was assessed by the Montreal Cognitive Assessment, multimorbidity via the Charlson Co-morbidity Index and frailty using the Clinical Frailty Score. A polypharmacy questionnaire was used to further probe participant insight and aptitude towards medication use. Results One hundred and five inpatients, with mean age of 86.7 years (range 80.2 to 102.7) met the inclusion criteria and participated in the study. The patients were prescribed an average of 12 medications (range 3–26). They had multiple co-morbidities (mean CCI 6), 64% were assessed to have mild cognitive impairment and 62% were classified as frail. Also, 28% did not know the indication for their medication and 30% reported missing medications. The calculated CrCl ranged from 19–99ml/min, with the majority of patients falling between the range of 30–60ml/min (mean 49ml/min). On average, each patient was taking 1 medication that is ≥50% renally excreted unchanged (or their active metabolites), 1 medication that requires dose reduction when CrCl is 30–60ml/min, 2 medications that require dose reduction when CrCl is 10–30ml/min and 1 medication infrequently or commonly classed as nephrotoxic. The average total number of medications did not change significantly with decrease in CrCl, however, there was a non-significant increase in potentially nephrotoxic medication use. Patients experienced a similar anticholinergic or sedative load (as measured by the drug burden index) regardless of CrCl. Conclusion A substantal burden of medications was found in individuals of advanced age (>80years) with renal impairment. The risk of medication-related harm may be further compounded by age-related barriers and challenges to managing multi-drug regimens. Regular medication reviews are essential for this vulnerable patient group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".