Bibliographic record
Abstract
Objective To assess whether family physicians are using the CHADS2 (congestive heart failure, hypertension, age ≥ 75, diabetes mellitus, and stroke or transient ischemic attack) score in the decision to initiate warfarin therapy to prevent stroke in patients with atrial fibrillation. Design Retrospective analysis of the medical records of patients with atrial fibrillation. Setting Data were gathered from records at 3 clinics in a primary care network in Edmonton, Alta. Participants The medical records of patients with atrial fibrillation who were currently taking warfarin therapy. Main outcome measures Percentage of patients whose CHADS2 scores indicated warfarin therapy for stroke prophylaxis compared with the actual percentage of patients taking warfarin therapy. Data on patients’ age, number of medications, and number of comorbid conditions were also recorded. Results Among these patients, 7% had a CHADS2 score of 0, for which no warfarin therapy was indicated; 21% had a score of 1, for which either acetylsalicylic acid or warfarin was indicated; and 72% had a score of 2 or greater, for which warfarin therapy was indicated. About 80% of patients were taking medication to control their heart rate. Conclusion The CHADS2 score is not being used in all cases to assess the need for warfarin therapy for preventing stroke in patients with atrial fibrillation. The CHADS2 score might be of limited use because it is not sensitive enough to stratify patients clearly into high-, intermediate-, and low-risk groups. Although guidelines for stroke prevention should be followed, the CHADS2 portion of the guidelines might not be the most effective way to assess patients’ risk of stroke.
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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".