Implementation of an Activity-Monitoring System in Hospital-Based COPD Patients: A Retrospective Cohort Study
Bibliographic record
Abstract
Introduction: Patients with chronic obstructive pulmonary disorder are at risk of complications after hospitalization, including readmissions. The purpose of this study was to assess the effects of an activity-monitoring device on the outcomes of patient with chronic obstructive pulmonary disorder during and after a hospital admission. Methods: During a hospitalization, 52 patients (experimental group) diagnosed with chronic obstructive pulmonary disorder were provided with an activity monitor (Tractivity; (Kineteks Corporation, Vancouver, British Colombia, http://tractivity-online.squarespace.com/)) and 99 usual care patients were chosen as controls. Following hospital discharge, retrospective chart analysis examined patient demographics including falls, length of stay, discharge disposition, and hospital readmissions. Results: No difference in number of falls, length of stay, discharge disposition, and hospital readmissions could be found between groups ( P > .05). Within the experimental group, those who were discharged home (n = 45) displayed a greater daily activity, number of steps, and ambulation distance as compared with patients who were discharged to another facility (n = 7, P < .05). Discussion: Readmissions are multifactorial and activity during a hospitalization may not be the primary cause of readmissions. Activity monitoring can help quantify ambulation and may be useful as a means to predict discharge disposition. Conclusion: No clear effect of using an activity monitor could be found on length of stay, readmission rates, and discharge disposition between the 2 groups. However, less activity and shorter ambulation distance were associated with discharge to another facility instead of home.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".