Adopting STOPP/START Criteria Version 3 in Clinical Practice: A Q&A Guide for Healthcare Professionals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growing complexity of geriatric pharmacotherapy necessitates effective tools for mitigating the risks associated with polypharmacy. The Screening Tool of Older Persons' Potentially Inappropriate Prescriptions (STOPP)/Screening Tool to Alert doctors to Right Treatment (START) criteria have been instrumental in optimizing medication management among older adults. Despite their large adoption for improving the reduction of potentially inappropriate medications (PIM) and patient outcomes, the implementation of STOPP/START criteria faces notable challenges. The extensive number of criteria in the latest version and time constraints in primary care pose practical difficulties, particularly in settings with a high number of older patients. This paper critically evaluates the challenges and evolving implications of applying the third version of the STOPP/START criteria across various clinical settings, focusing on the European healthcare context. Utilizing a "Questions & Answers" format, it examines the criteria's implementation and discusses relevant suitability and potential adaptations to address the diverse needs of different clinical environments. By emphasizing these aspects, this paper aims to contribute to the ongoing discourse on enhancing medication safety and efficacy in the geriatric population, and to promote more person-centred care in an aging society.
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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 | 0.004 | 0.004 |
| 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 | 0.001 |
| 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