Patient and Process Outcomes among Pediatric Patients Undergoing Appendectomy during the COVID-19 Pandemic: An International Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: COVID-19 forced healthcare systems to make unprecedented changes in clinical care processes. The authors hypothesized that the COVID-19 pandemic adversely impacted timely access to care, perioperative processes, and clinical outcomes for pediatric patients undergoing primary appendectomy. METHODS: A retrospective, international, multicenter study was conducted using matched cohorts within participating centers of the international PEdiatric Anesthesia COVID-19 Collaborative (PEACOC). Patients younger than 18 yr old were matched using age, American Society of Anesthesiologists Physical Status, and sex. The primary outcome was the difference in hospital length of stay of patients undergoing primary appendectomy during a 2-month period early in the COVID-19 pandemic (April to May 2020) compared with prepandemic (April to May 2019). Secondary outcomes included time to appendectomy and the incidence of complicated appendicitis. RESULTS: A total of 3,351 cases from 28 institutions were available with 1,684 cases in the prepandemic cohort matched to 1,618 in the pandemic cohort. Hospital length of stay was statistically significantly different between the two groups: 29 h (interquartile range: 18 to 79) in the pandemic cohort versus 28 h (interquartile range: 18 to 67) in the prepandemic cohort (adjusted coefficient, 1 [95% CI, 0.39 to 1.61]; P < 0.001), but this difference was small. Eight centers demonstrated a statistically significantly longer hospital length of stay in the pandemic period than in the prepandemic period, while 13 were shorter and 7 did not observe a statistically significant difference. During the pandemic period, there was a greater occurrence of complicated appendicitis, prepandemic 313 (18.6%) versus pandemic 389 (24.1%), an absolute difference of 5.5% (adjusted odds ratio, 1.32 [95% CI, 1.1 to 1.59]; P = 0.003). Preoperative SARS-CoV-2 testing was associated with significantly longer time-to-appendectomy, 720 min (interquartile range: 430 to 1,112) with testing versus 414 min (interquartile range: 231 to 770) without testing, adjusted coefficient, 306 min (95% CI, 241 to 371; P < 0.001), and longer hospital length of stay, 31 h (interquartile range: 20 to 83) with testing versus 24 h (interquartile range: 14 to 68) without testing, adjusted coefficient, 7.0 (95% CI, 2.7 to 11.3; P = 0.002). CONCLUSIONS: For children undergoing appendectomy, the COVID-19 pandemic did not significantly impact hospital length of stay.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".