Home to Stay: A randomized controlled trial protocol to assess use of a mobile app to reduce readmissions following colorectal surgery
Why this work is in the frame
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Bibliographic record
Abstract
AIM: Patients undergoing colorectal surgery face high rates of emergency room visits and readmission to hospital. These unplanned hospital visits lead to both increased patient anxiety and health care costs. The aim of this study is to evaluate the use of mobile application to support patients undergoing colorectal surgery following discharge from hospital. METHOD: This study is a randomized controlled trial in which the control group will receive standard follow-up care following discharge after surgery and the intervention group will receive standard follow-up care in addition to the mobile application. The primary outcome is the proportion of patients with unplanned hospital visits within 30 days of discharge. The secondary outcomes are patient-reported outcomes on validated scales evaluating their quality of recovery following discharge. A sample size of 670 subjects is planned. For the primary outcome, the control and intervention groups will be compared using a generalized linear model to account for clustering of patients within centres. For the secondary outcomes, the overall scores on the Quality of Recovery 15 and Patient Activation Measure will be analysed using a linear regression model. RESULTS: It is expected that the results of this study will show that the mobile app will lead to significant improvements in unplanned hospital visits as well as improved quality of recovery for patients. CONCLUSION: If the trial is successful, the mobile app can be easily adopted more widely into clinical practice to support patients at home following surgery.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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