Rate and appropriateness of polypharmacy in older patients with hemophilia compared with age‐matched controls
Bibliographic record
Abstract
BACKGROUND: In older people, multiple chronic ailments lead to the intake of multiple medications (polypharmacy) that carry a number of negative consequences (adverse events, prescription and intake errors, poor adherence, higher mortality). Because ageing patients with haemophilia (PWHs) may be particularly at risk due to their pre-existing multiple comorbidities (arthropathy, liver disease), we chose to analyse the pattern of chronic drug intake in a cohort of PWHs aged 60 years or more. PATIENTS AND METHODS: S + PHERA is a multicentre observational study, with the broad goal to evaluate prospectively the health status and medication intake in 102 older patients with severe haemophilia A or B compared with 204 age- and residence-matched controls chosen randomly from the same general practices of PWHs. The rate of potential drug-drug interactions (PDDI) was evaluated as a proxy of prescription appropriateness. RESULTS: After excluding replacement therapies and antiviral drugs, PWHs took in average less daily drugs than controls (2.4 ± 2.5 vs 3.0 ± 2.4) and had a lower rate of polypharmacy. Moreover, their prevalence of PDDI was lower (16.7% vs 27%). CONCLUSIONS: The rate of polypharmacy and the appropriateness of medications other than those for haemophilia and related comorbidities are acceptable in Italian PWHs, and better than those in their age peers without haemophilia, perhaps owing to drug tailoring and deprescribing by the specialized haemophilia centres at the time of regular visits. However, the PWHs investigated herewith were relatively young and the rate of polypharmacy and related PDDIs may become more prominent and crucial when older ages are reached, suggesting the need of continuous surveillance on prescribed drugs and the risk of drug-drug interactions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".