Expanding the Use of Endoscopic Retrograde Cholangiopancreatography in Pediatrics: A National Database Analysis of Demographics and Complication Rates
Bibliographic record
Abstract
Background: This study aimed to aid in risk assessment of pediatric endoscopic retrograde cholangiopancreatography (ERCP) candidates by utilizing a national pediatric database with a large sample to assess how patient characteristics may affect ERCP complication rates. Methods: The Kids' Inpatient Database (KID) is a sample of pediatric discharges in states participating in the Healthcare Cost and Utilization Project (HCUP). This database provides demographic information, hospitalization duration, and outcome information for hospitalizations during which an ERCP occurred. International Classification of Diseases (ICD) codes were used to determine the hospitalization indication. ERCP complication rate was ascertained via ICD codes. All statistical analyses were performed using SAS 9.4. Results: Complications were seen in 5.4% of hospitalizations with mortality observed in less than 0.2%. This analysis captured a large Hispanic population, specifically in the South and West regions. Gallbladder calculus and cholecystitis were more likely to occur in females. A higher percentage of patients in the age 10 - 17 group were female (72.2% vs. 52.7%, P < 0.01) and Hispanic (33.4% vs. 22.7%, P < 0.01) compared to the age 0 - 9 group. Age 0 - 5 and male gender were associated with lower routine home discharge rates and longer lengths of stay. Complications occurred at a higher rate in ages 0 - 5, though the difference was not statistically significant. Conclusions: ERCP is a safe procedure for pediatric patients with low complication rates and rare mortality. We found statistically significant differences in the procedure indications between pediatric age groups, races, and genders. Age ≤ 5 years and male gender were associated with more complicated healthcare courses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".