Rheumatologists' recommended patient information when prescribing methotrexate for rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVES: Accurate communication of information concerning the risks and benefits of medications is essential for adherence and patient safety. A diverse array of information and sources makes it difficult to know exactly what to tell a patient with rheumatoid arthritis about methotrexate. OBJECTIVE: Our objective is to determine what key information patients must know about methotrexate and the key reasons they should call their doctor while they are taking methotrexate. METHODS: Three hundred and forty-four Canadian rheumatologists were sent a survey containing open-ended questions to gain uncued narrative perspectives from each individual's experience. The survey was designed to determine what must all patients taking methotrexate know and when must patients taking methotrexate call a physician? Emergent coding was used to establish a set of categories to form a checklist for coding. A second member checking survey was sent to gain confirmation and validation of themes developed from the initial survey. RESULTS: One hundred and seventy out of 344 (49.5%) surveys were completed. Regular blood testing, once weekly dosing, risk of infection, pregnancy and lactation information, alcohol limitation, potential lung toxicity, and drug interactions were thought to be important. Patients should call if they became pregnant, developed symptoms suggestive of lung toxicity, developed an infection, severe mouth sores, or were concerned about any side effects warranting the discontinuation of the medication. CONCLUSIONS: This study is the first to describe, from a rheumatologist's perspective, the key important information that all patients should know and when patients should call their doctor when taking methotrexate.
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 | 0.004 | 0.035 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".