Incidence of Postoperative Pain at 7 Days After Day Surgery Reported Using a Text Messaging Platform: Retrospective Observational Study
Bibliographic record
Abstract
BACKGROUND: The most frequent complication observed after ambulatory surgery is acute postoperative pain. OBJECTIVE: The purpose of this study was to evaluate the late incidence of postoperative pain at 7 days after day surgery. METHODS: We retrospectively included patients who underwent day surgery under general or regional anesthesia and those who underwent local anesthesia in Rouen University Hospital from January 2018 to February 2020. Data collected were moderate-to-severe pain reports defined as numeric rating scale (NRS)>3/10 at 1 day (secondary end point) and 7 days (primary end point) after surgery. These data were collected using a semi-intelligent SMS text messaging platform to follow up with the patient at home after ambulatory surgery. Univariate and multivariate analyses were performed to analyze the risk factors for pain. RESULTS: We analyzed 6099 patients. On the day after the surgery, 5.2% (318/6099) of the patients presented with moderate-to-severe pain: 5.9% (248/4187) in the general or regional anesthesia group and 3.7% (70/1912) in the local anesthesia group. At 7 days after the surgery, 18.6% (1135/6099) of the patients presented with moderate-to-severe pain, including 21.3% (892/4187) of the patients in the general or regional anesthesia group and 12.7% (243/1912) of the patients in the local anesthesia group. General surgery (odds ratio [OR] 1.54, 95% CI 1.23-1.92; P<.01) and orthopedic surgery (OR 1.66, 95% CI 1.42-1.94; P<.01) were associated with more late postoperative pain risk. Male gender (OR 0.66, 95% CI 0.57-0.76; P<.01), ophthalmology surgery (OR 0.51, 95% CI 0.42-0.62; P<.01), and gynecologic surgery (OR 0.67, 95% CI 0.50-0.88; P=.01) were associated with less late postoperative pain risk. The rate of emergency consultation or rehospitalization at 7 days after the surgery was 11.1% (679/6099). Late postoperative pain (OR 2.54, 95% CI 1.98-3.32; P<.001), general surgery (OR 2.15, 95% CI 1.65-2.81; P<.001), and urology surgery (OR 1.62, 95% CI 1.06-2.43; P=.02) increased the risk of emergency consultation or rehospitalization. Orthopedic surgery (OR 0.79, 95% CI 0.63-0.99; P=.04) and electroconvulsive therapy (OR 0.43, 95% CI 0.27-0.65; P<.001) were associated with less rates of emergency consultation or rehospitalization. CONCLUSIONS: Our study shows that postoperative pain at 7 days after ambulatory surgery was reported in more than 18% of the cases, which was also associated with an increase in the emergency consultation or rehospitalization rates.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".