Sex Similarities in Postoperative Recovery and Health Care Contacts Within 14 Days With mHealth Follow-Up: Secondary Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Previous studies have shown that women tend to have a poorer postanesthesia recovery than men. Our research group has developed a mobile phone app called Recovery Assessment by Phone Points (RAPP) that includes the Swedish Web version of the Quality of Recovery (SwQoR) questionnaire to monitor and assess postoperative recovery. OBJECTIVE: The aim of this study was to investigate sex differences in postoperative recovery and the number of health care contacts within 14 postoperative days in a cohort of day-surgery patients using RAPP. METHODS: This study was a secondary analysis from a single-blind randomized controlled trial. Therefore, we did not calculate an a priori sample size regarding sex differences. We conducted the study at 4 day-surgery settings in Sweden from October 2015 to July 2016. Included were 494 patients (220 male and 274 female participants) undergoing day surgery. The patients self-assessed their postoperative recovery for 14 postoperative days using the RAPP. RESULTS: There were no significant sex differences in postoperative recovery or the number of health care contacts. Subgroup analysis showed that women younger than 45 years reported significantly higher global scores in the SwQoR questionnaire (hence a poorer recovery) on postoperative days 1 to 10 than did women who were 45 years of age or older (P=.001 to P=.008). Men younger than 45 years reported significantly higher global scores on postoperative days 2 to 6 than did men 45 years of age or older (P=.001 to P=.006). Sex differences in postoperative recovery were not significant between the age groups. CONCLUSIONS: This study found sex similarities in postoperative recovery and the number of health care contacts. However, subgroup analysis showed that age might be an independent factor for poorer recovery in both women and men. This knowledge can be used when informing patients what to expect after discharge. TRIAL REGISTRATION: ClinicalTrials.gov NCT02492191; https://clinicaltrials.gov/ct2/show/NCT02492191 (Archived by WebCite at http://www.webcitation.org/6y2UtMbvz).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".