Recurrent Ileocolic Intussusception in Children: A Scoping Review
Bibliographic record
Abstract
Background: Intussusception is the most common cause of acute intestinal obstruction in children. It can be initial idiopathic intussusception or a recurrent intussusception (RI), and in this latter case, there is not a validated algorithm for optimal treatment. The aim of the study is to review the international literature to evaluate the incidence of RI, to determine the rates of surgical intervention and pathological leading point (PLP), and to define the most appropriate management for children with RI. We included English‐written papers with pediatric population, excluding case reports, papers with adult or mixed cases, studies focusing on ileo–ileal or colo–colic intussusception, meta‐analysis studies, or papers with unclear or replaced data. Results: A total number of 23 articles were included for a total of 26,731 patients affected by intussusception and 3164 recurrent patients (11.8%). The number of attempts of nonsurgical reduction ranged from 3 to 10 (median 5). On 2965 RI, 358 underwent surgery (12.1%). A pathologic leading point was found in 99 patients (3.95%). Conclusions: The presence of a PLP does not seem to be associated with the recurrence of intussusception. More than 85% of RI underwent successful nonsurgical management. RI should be safely approached in the same way as primary intussusception, and surgery should be reserved to cases where a PLP has been suspected. In cases of multiple episodes, surgery can be considered an effective way to avoid recurrences, and this possibility should be discussed with parents.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".