Evidence map›Paper›PMID 41684532›Full record

ArticleGeburtshilfe und Frauenheilkunde2026

Current Endometriosis Classifications (rASRM, #Enzian, AAGL2021) and their Correlation with Operative Time.

Teresa Eichinger, Peter Oppelt, Julia Lastinger, Natalia Anna Palasz, Hanna Elisabeth Fickert, Simon-Hermann Enzelsberger

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In one paragraph

Article in Geburtshilfe und Frauenheilkunde, 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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2 · The registry

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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

6 authors.

Teresa EichingerDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
Peter OppeltDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
Julia LastingerDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
Natalia Anna PalaszDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
Hanna Elisabeth FickertDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.
Simon-Hermann EnzelsbergerDepartment of Gynecology, Obstetrics and Gynecological Endocrinology, Kepler University Hospital, Johannes Kepler University Linz, Linz, Austria.ORCID 0000-0002-3487-4561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In the ongoing effort to identify or develop the optimal classification system for endometriosis, there is a paucity of data regarding the association between currently used classification systems and operative times. This study aims to evaluate the correlation between the rASRM, #Enzian, and AAGL2021 classifications and the duration of endometriosis surgery to determine the most accurate system for planning operating room resources. Materials and Methods: This retrospective study included patients who underwent laparoscopic endometriosis surgery at Kepler University Hospital in 2021 and 2022. Surgeries were performed by experienced gynecologic surgeons, with endometriosis extent assessed using rASRM, #Enzian, and AAGL2021 classifications. Corrected operative time (total time minus fixed durations for common concomitant procedures) was used for analysis. Statistical analyses included descriptive statistics, Kendall's tau correlation, Spearman's correlation, Mann-Whitney U test, and generalized linear models. Results: Out of 248 patients with laparoscopic surgery for endometriosis, 139 met the in-/exclusion criteria. The median corrected operative time was 68.50 minutes. Significant positive correlations were found between surgery duration and stages in both rASRM and AAGL2021 classifications. The #Enzian classification also showed positive correlations with more complex analyses attributable to the classification structure. Operative times were longest in surgeries affecting compartments C3, A3, FI, and FU. Regression analysis identified several significant variables impacting surgery duration. Conclusions: All three classification systems significantly impact operative time, with higher stages or specific coding correlating with longer durations. The AAGL2021 and #Enzian classifications can be used as preoperative diagnostic tools, with #Enzian offering more detailed coding. Future research should focus on prospective, multi-center studies to develop algorithms incorporating #Enzian codings for enhanced preoperative planning.

Indexed as

AAGL2021endometriosis#EnzianrASRMsurgery time

Identifiers

PMID41684532
PMCPMC12893800

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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.