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.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".