Evidence map›Paper›PMID 42552486›Full record

ArticleSurgical endoscopy2026

Beyond acronyms: a domain-based structural analysis of abdominal wall hernia repair techniques in the contemporary literature.

Francesco Brucchi, Rita Stanco, Giampaolo Formisano, Paolo Pietro Bianchi, Maaike Vierstraete, Gianlorenzo Dionigi, Filip Muysoms

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Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Francesco BrucchiDepartment of Pathophysiology and Transplantation, University of Milan, 20122, Milan, Italy. Francesco.brucchi@unimi.it.ORCID http://orcid.org/0000-0003-3191-4369
Rita StancoUniversity of Pavia, Pavia, Italy.
Giampaolo FormisanoDipartimento Scienze Della Salute, Univesity of Milano, Milan, Italy.
Paolo Pietro BianchiDipartimento Scienze Della Salute, Univesity of Milano, Milan, Italy.
Maaike VierstraeteDepartment of Plastic, Reconstructive and Aesthetic Surgery, ZAS Antwerp, Antwerp, Belgium.
Gianlorenzo DionigiDepartment of Pathophysiology and Transplantation, University of Milan, 20122, Milan, Italy.
Filip MuysomsDepartment of General Surgery, AZ Maria Middelares, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgical techniques in abdominal wall surgery are commonly described using labels, including acronyms, eponyms, and narrative descriptors, that only partially capture their technical characteristics. Whether these labels correspond to genuinely distinct procedures or instead represent variations within a smaller number of underlying technical configurations remains empirically untested.

methodsBuilding on our methodological study of reporting completeness, we performed a structured domain-based analysis of abdominal wall hernia repair techniques. Each surgical arm was decomposed into five predefined operative domains: surgical approach (A), hernia type (H), mesh position (M), mesh type (T), and fixation method (F). Unique technical configurations were defined as distinct domain combinations. Terminological redundancy was evaluated by mapping labels to their corresponding configurations. Technical diversity was quantified using Shannon entropy.

resultsTwo hundred studies met inclusion criteria, yielding 290 surgical arms. Domain decomposition identified 184 unique technical configurations. Among 170 unique labels, 21 (12.4%) mapped to more than one five-domain configuration. Conversely, among 93 fully specified configurations linked to at least one label, 21 (22.6%) were described by more than one label. The most polysemous label (TEP) corresponded to 24 distinct configurations. Groin hernia repairs accounted for the largest number of arms (n = 130) but showed moderate structural diversity relative to sample size, whereas ventral and incisional repairs demonstrated higher variability per arm. In the sensitivity analysis restricted to the 149 fully specified arms, 94 unique configurations were identified; polysemy and redundancy remained substantial (TEP mapped to 11 configurations).

conclusionAbdominal wall hernia repair techniques are more completely represented when the labels in common use-acronyms, eponyms, and narrative descriptors-are supplemented by structured operative domains rather than relied upon in isolation. Domain-based descriptors provide a reproducible, machine-readable complement to existing nomenclature that may improve reporting clarity, support comparative research, and facilitate structured classification of surgical techniques.

Indexed as

Abdominal wall herniaDomain-based classificationLabel redundancyMesh repairMuysoms nomenclatureNomenclatureOperative domainsShannon entropySurgical technique

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.