Factors influencing leaving the bed in post-gynecological surgery patients: An exploratory study using a “walking diary”
Bibliographic record
Abstract
Objective: Early walking post-surgery is vital to prevent surgical complications and enhance recovery. This study aimed to investigate the factors that affect the number of steps taken after leaving the bed by patients following gynecological surgery using a “walking diary” and clinical outcomes.Methods: Data collected from the walking diary included the target number of steps and general condition of 95 gynecological patients who underwent laparoscopy or laparotomy following clinical pathways. We analyzed the data using logistic regression.Results: The average number of steps on the first postoperative day of laparoscopy and laparotomy was 878 and 250 steps respectively, and increased to 2,525 and 1,023 steps, respectively, on the second postoperative day. The target number of steps and motivation at the time of waking up increased significantly with the postoperative course, and pain decreased significantly. The amount of bleeding and laparotomy were factors that inhibited the number of steps taken. Additionally, the larger the target number of steps on the two days after surgery, the greater the steps taken may be promoted. The surgical invasiveness of the procedure was a factor that influenced the number of steps taken.Conclusions: Patients who set a higher target number of steps for themselves took a higher number of steps in practice. They were presented with a guideline for the target number of steps for patients post-surgery: around 900 on post-operative day 1 (POD 1) and 2500 in POD 2. Improving postoperative symptoms might aid patients’ feeling of recovery, and reviewing the walking diary may enhance their motivation for walking as well as self-efficacy.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".