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Record W4415653611 · doi:10.62713/aic.3943

Surgical Techniques for the Treatment of Hirschsprung's Disease—A Historical Systematic Review and Current Status Quo

2025· review· en· W4415653611 on OpenAlexaff
Josef Häger, Consolato Sergi

Bibliographic record

VenueAnnali Italiani di Chirurgia · 2025
Typereview
Languageen
FieldMedicine
TopicCongenital gastrointestinal and neural anomalies
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of AlbertaUniversity of Ottawa
Fundersnot available
KeywordsStatus quoCurrent (fluid)MEDLINESurgical proceduresPrecision medicine

Abstract

fetched live from OpenAlex

AIM: Hirschsprung's disease, or aganglionosis of the colon, is a congenital disease characterized by a lack of neurons in the enteric plexus of the large bowel due to either migration failure or defective differentiation of neural crest cells. We aimed to conduct a historical systematic review of available literature and personal experience to exhibit the surgical techniques performed in the past and the current status quo of surgery for Hirschsprung's disease. METHODS: We searched PubMed, EMBASE, Google Scholar databases for studies examining surgery in aganglionosis or Hirschsprung's disease. The search included all studies published from inception until 9 November 2024. Eligible criteria included all peer-reviewed articles, not necessarily written in English, but also German, French, Italian, and Spanish items dealing with surgery and the prognosis of patients with Hirschsprung's disease after surgical intervention. RESULTS: A total of 2527 studies were reviewed, and the studies relevant to the surgery were extracted for this historical review. This article delivers a unique historical path and an analysis of some of the most critical surgical techniques for the approach to Hirschsprung's disease, with two outstanding sections on innovative robotic-assisted surgery and life quality after surgery. Currently, surgeons often tailor their approach to Hirschsprung's disease by combining their knowledge and expertise on several surgical procedures and incorporating subtle adjustments based on each patient's imaging, inspection, and pathological findings. The conventional wisdom held that surgeons should perform whichever surgery they felt most comfortable with, regardless of whether a particular technique produced better results. Although the core elements of surgical care have been identified and surgery has been shown to improve outcomes in patients affected with Hirschsprung's disease, the precise etiology and correct treatment for reconstitution of ganglion cells in the aganglionic portions of the bowel are lacking. The surgical treatment options for Hirschsprung's disease have been conceived and implemented after the etiology of Hirschsprung's disease was successfully clarified in the 1940s. CONCLUSIONS: There is still no internationally valid agreement on which techniques should be used for the various forms of intestinal aganglionosis, especially for total colonic and ultra-short intestinal forms. On the other hand, minimally invasive surgery, artificial intelligence, and machine learning are quickly entering medicine and surgery. These approaches will probably modify the surgical approaches to Hirschsprung's disease. In the future, surgeons may integrate new knowledge derived from proteomics and genomics into current surgical procedures. This integration pinpoints a therapeutic approach that may eventually entail aspects of personalized medicine.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0130.014
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.054
GPT teacher head0.359
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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