Predictors of unanticipated admission following ambulatory surgery in the pediatric population: a retrospective case–control study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Ambulatory surgery plays an important role in pediatric anesthesia. However, it is difficult to predict which patients will experience complications. Age >80, ASA class 3 or 4, duration of surgery >3 h, and BMI 30-35 are independent predictors of unanticipated admission in adults. In this study, we retrospectively evaluate risk factors for unanticipated admission, following ambulatory surgery in children. METHODS: All ambulatory patients requiring unanticipated admission between 2005 and 2013 were compared to a random sample of patients not requiring admission in this case-control study. Demographic data, surgical information, medications, intraoperative events, and patient comorbidities were collected from both groups. The reason for admission was classified according to five subtypes. Multiple conditional logistic regression was used to assess factors associated with unanticipated admissions. RESULTS: The incidence of unanticipated admission was 0.97% (213). Of these, 47% (98) was anesthesia related. Age <2 years (odds ratio [OR] 4.26 95% CI 1.19-15.25), ASA 3 class (OR 3.77 95% CI 1.46-9.71), duration of surgery >1 h (OR 6.54 95% CI 3.47-12.33), completion of surgery >3 pm (OR 2.17 95% CI 1.05-4.51), orthopedic (OR 2.52 95% CI 1.03-6.20), dental (OR 0.21 95% CI 0.06-0.81), ENT (OR 6.47 95% CI 2.99-14.03) surgery, intraoperative events (OR 4.45 95% CI 1.35-18.12), and OSA (OR 6.32 95% CI 1.54-25.94) were factors associated with unanticipated admission. CONCLUSION: The incidence of unanticipated admission in children following ambulatory surgery is low. Age, ASA class, duration, and time of completion of surgery are predictors common to pediatrics and adults. Interestingly, intraoperative complications, OSA, and type of surgery (ENT, orthopedic, dental) are specific to pediatrics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it