Rationale and design of OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people (OPERAM): a cluster randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Multimorbidity and polypharmacy are important risk factors for drug-related hospital admissions (DRAs). DRAs are often linked to prescribing problems (overprescribing and underprescribing), as well as non-adherence with drug regimens for different reasons. In this trial, we aim to assess whether a structured medication review compared with standard care can reduce DRAs in multimorbid older patients with polypharmacy. METHODS AND ANALYSIS: OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people is a European multicentre, cluster randomised, controlled trial. Hospitalised patients ≥70 years with ≥3 chronic medical conditions and concurrent use of ≥5 chronic medications are included in the four participating study centres of Bern (Switzerland), Utrecht (The Netherlands), Brussels (Belgium) and Cork (Ireland). Patients treated by the same prescribing physician constitute a cluster, and clusters are randomised 1:1 to either standard care or Systematic Tool to Reduce Inappropriate Prescribing (STRIP) intervention with the help of a clinical decision support system, the STRIP Assistant. STRIP is a structured method performing customised medication reviews, based on Screening Tool of Older People's Prescriptions/Screening Tool to Alert to Right Treatment criteria to detect potentially inappropriate prescribing. The primary endpoint is any DRA where the main reason or a contributory reason for the patient's admission is caused by overtreatment or undertreatment, and/or inappropriate treatment. Secondary endpoints include number of any hospitalisations, all-cause mortality, number of falls, quality of life, degree of polypharmacy, activities of daily living, patient's drug compliance, the number of significant drug-drug interactions, drug overuse and underuse and potentially inappropriate medication. ETHICS AND DISSEMINATION: The local Ethics Committees in Switzerland, Ireland, The Netherlands and Belgium approved this trial protocol. We will publish the results of this trial in a peer-reviewed journal. MAIN FUNDING: European Union's Horizon 2020 programme. TRIAL REGISTRATION NUMBER: NCT02986425 , SNCTP000002183 , NTR6012, U1111-1181-9400.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.035 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".