Using technology to create a medication safety net for cardiac surgery patients: a nurse-led randomized control trial.
Bibliographic record
Abstract
PURPOSE: Interactive voice response (IVR) technology was used to increase medication compliance and reduce adverse events (hospitalization and emergency visits) in post-cardiac surgery patients. METHOD: Patients randomized to intervention received 11 automated IVR calls in the six months after discharge. A total of 331 patients (164 IVR, 167 usual care) participated. RESULTS: Findings showed significant differences in the IVR group for the primary composite outcome of compliance and adverse events (relative risk (RR] and 95% confidence interval [CI]: 0.60 [0.37, 0.96), p = 0.041) and the secondary outcome of medication compliance (RR: 0.34 (0.20, 0.56), p < 0.0001). There was no significant impact on emergency room visits (RR: 1.04 (0.63, 1.73J) and hospitalization (RR: 0.77 [0.41, 1.45]). Most patients (93%) preferred IVR follow-up to no follow-up.
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 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".