The development and feasibility of a virtual heart failure clinic
Bibliographic record
Abstract
Heart failure (HF) self-management includes monitoring and reporting of changes in symptoms. We have explored the feasibility of an interactive, easy-to-use Web-based system that provides a link between the patient and the health professional. New HF clinic patients were enrolled into a six-month study. Patients were identified according to their ability to use the Internet daily and whether they would be able to complete baseline and follow-up visits. In the first 12 months, nine patients completed the study. There was an improvement in physical functioning as measured with the 6–min walk test, from 395 m (SD 105) to 457 m (SD 90). There was also an improvement in quality-of-life scores, from 47 (SD 29) to 40 (SD 26) (the lower the score, the better). Patients expressed high levels of satisfaction with the intervention. The system was shown to be safe and feasible when used with appropriate supports. The virtual HF clinic is simple, cheap and has potential for use in a range of chronic illnesses.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".