The Application of Disease Management to Clinical Trial Designs
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 utilization of disease management (DM) as a minimum standard of care is believed to facilitate pronounced benefits in overall patient outcome and cost management. Randomized clinical trials remain the gold standard evaluative tool in clinical medicine. However, the extent to which contemporary cardiovascular clinical trials incorporate DM components into their treatment or control arms is unknown. Our study is the first to evaluate the extent to which clinical trials incorporate DM as a minimum standard of care for both the intervention and control groups. In total, 386 clinical trials published in 3 leading medical journals between 2003 and 2006 were evaluated. For each study, elements related to DM care, as defined using the American Heart Association Taxonomy, were abstracted and characterized. Our results demonstrate that while the application of DM has increased over time, only 3.4% of the clinical trials examined incorporated all 8 DM elements (and only 11% of such trials incorporated 4 DM elements). A significant association was found between study year and the inclusion of more than 3 elements of DM (chi(2) = 10.10 (3); p = 0.018). In addition, associations were found between study objective and DM criteria, as well as between cohort type and domains described. Our study serves as a baseline reference for the tracking of DM within, and its application to, randomized clinical trials. Moreover, our results underscore the need for broader implementation and evaluation of DM as a minimum care standard within clinical trial research.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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