Inter-observer reproducibility of the 2021 AAGL Endometriosis Classification.

BACKGROUND: Inter-observer agreement for the American Association of Gynecologic Laparoscopists (AAGL) 2021 Endometriosis Classification staging system has not been described. Its predecessor staging system, the revised American Society for Reproductive Medicine (rASRM), has historically demonstrated poor inter-observer agreement. AIMS: We aimed to determine the inter-observer agreement performance of the AAGL 2021 Endometriosis Classification staging system, and compare this with the rASRM staging system. MATERIALS AND METHODS: A database of 317 patients with coded surgical data was retrospectively analysed. Three independent observers allocated AAGL surgical stages (1-4), twice. Observers made their own interpretation of how to apply the tool in the first staging allocation. Consensus rules were then developed for a second staging allocation. RESULTS: First staging allocation: odds ratio (OR) (and 95% CI) for observer 1 to score higher than observer 2 was 8.08 (5.12-12.76). Observer 1 to score higher than observer 3 was 12.98 (7.99-21.11) and observer 2 to score higher than observer 3 was 1.61 (1.03-2.51). This represents poor agreement. Second staging allocation (after consensus): OR for observer 1 to score higher than observer 2 was 1.14 (0.64-2.03), observer 1 to score higher than observer 3 was 1.81 (0.99-3.28) and observer 2 to score higher than observer 3 was 1.59 (0.87-2.89). This represents good agreement. CONCLUSIONS: These findings suggest that in its current format the AAGL 2021 Endometriosis Classification staging system has poor inter-observer agreement, not superior to the rASRM staging system. However, performance improved when additional measures were taken to simplify and clarify areas of ambiguity in interpreting the staging system.

The bidirectional relationship between endometriosis and microbiome.

Endometriosis has been described by many different theories of pathogenesis over the years. It is now also appreciated to be a state of chronic inflammation, and the role of immune dysfunction in its development has been proven. There is increasing evidence to support the role of the microbiome in the formation and progression of endometriosis via inflammatory pathways. The dysbiosis seen in endometriosis is thought to be both causative and a consequence of the pathogenesis. Gut, peritoneal fluid and female reproductive tract microbiota has been studied to understand if there are any microbiome signatures specific to endometriosis. New research on how to manipulate the microbiome for better detection and treatment of endometriosis is emerging.

External Validation of the "2021 AAGL Endometriosis Classification": A Retrospective Cohort Study.

STUDY OBJECTIVE: Externally validate the American Association of Gynecologic Laparoscopists (AAGL) staging system against surgical complexity and compare diagnostic accuracy with revised American Society for Reproductive Medicine (rASRM) stage, as was done in original publication. DESIGN: Retrospective, diagnostic accuracy study. SETTING: Multicenter (Sydney, Australia). PATIENTS: A total of 317 patients (January 2016-October 2021) were used in the final analysis. INTERVENTIONS: A database of patients with coded surgical data was analyzed. MEASUREMENTS AND MAIN RESULTS: Three independent observers assigned an AAGL surgical stage (1-4) as the index test and surgical complexity level (A-D) as the reference standard. Results from the most accurate of the 3 observers were used in the final analysis. The weighted kappa score for the overall performance of AAGL stage and rASRM to predict AAGL level was 0.48 and 0.48, respectively (no difference). This represents weaker agreement with AAGL level than was observed in the reference paper, which reported a weighted kappa of 0.62. Diagnostic accuracy (sensitivity, specificity, positive predictive value, and negative predictive value) for stage 1 to predict level A was 98.5%, 64.3%, 66.3%, and 98.3%; stage 2 to predict level B 31.2%, 90.5%, 27.0%, and 92.1 %; stage 3 to predict level C 12.3%, 94.1%, 59.3%, and 60.7%; stage 4 to predict level D 95.65%, 88.10%, 38.60%, and 99.62%. Area under the receiver operating characteristic curve for A vs B/C/D (cut point 9) was 0.87, A/B vs C/D (cut point 16) was 0.78, and A/B/C vs D (cut point 22) was 0.94. CONCLUSION: There was weak to moderate agreement between AAGL stage and AAGL surgical complexity level. Across all key indicators, the AAGL system did not perform as well in this external validation, nor did it outperform rASRM as it did in the reference paper. Results suggest the system is not generalizable.

Effectiveness of ultrasound for endometriosis diagnosis.

PURPOSE OF REVIEW: Endometriosis is a chronic benign gynaecological condition characterized by pelvic pain, subfertility and delay in diagnosis. There is an emerging philosophical shift from gold standard histopathological diagnosis through laparoscopy to establishing diagnosis through noninvasive imaging. RECENT FINDINGS: The ENZIAN classification system was updated in 2021 to be suitable for both diagnostic imaging and laparoscopy. The accuracy of transvaginal ultrasound (TVUS) in diagnosing endometriosis varies depending on location of the lesion. A recent international pilot study found that when ultrasound is performed in accordance with the IDEA consensus, a higher detection of deep endometriosis is seen, with an overall sensitivity of 88% and specificity of 79% compared with direct surgical visualization. SUMMARY: Although ultrasound can detect adenomyosis, deep endometriosis and endometriomas, it is not possible to reliably detect superficial endometriosis. In the instance of a negative ultrasound with persistence of symptoms despite medical therapy, laparoscopy should be considered for diagnosis and treatment.

An Ultrasound-based Prediction Model to Predict Ureterolysis during Laparoscopic Endometriosis Surgery.

STUDY OBJECTIVE: To develop a model, including clinical features and ultrasound findings, to predict the need for ureterolysis (i.e., dissection of the ureter) during laparoscopy for endometriosis. DESIGN: A retrospective observational study of patients who had undergone transvaginal ultrasound (TVS) according to the International Deep Endometriosis Analysis consensus and subsequent laparoscopy ± excision of endometriosis between January 2017 and February 2021 was conducted. SETTING: Sydney Medical School Nepean, University of Sydney, Nepean Hospital, and Blue Mountains Hospital, New South Wales, Australia. PATIENTS/PARTICIPANT: 177 patients. INTERVENTION: The demographic, clinical, TVS, and intraoperative data were extracted through electronic clinical records. MEASUREMENTS AND MAIN RESULTS: Multicategorical decision-tree and baseline models were built to choose the variables most correlated to the outcome under study. Receiver operating characteristic analysis was performed on the binary classification. Based on our results, we selected the variables performing with significant statistical differences (p <.05). During the study period, 177 consecutive patients were recruited and divided into 2 subgroups, ureterolysis (51.4%) and nonureterolysis (48.6%). Ureterolysis was noted in 87.5% of patients in which the left ovary was immobile (p <.001) and in 82.5% in which the right ovary was fixed (p <.001). For patients with right uterosacral ligament (USL) deep endometriosis (DE), ureterolysis was performed in 96.2% patients (p <.001) and 64.6% (p = .043) for left USL DE. Among patients with bowel DE, the proportion of patients undergoing ureterolysis was 95.5% (p <.001). The prognostic variables used in the final model to predict ureterolysis included dyschezia, absence of ovarian mobility, presence of right or left USL DE, and presence of bowel DE on TVS. According to the developed model, the baseline risk for performing ureterolysis is 20% in our sample. The overall model performance demonstrated an area under the receiver operating characteristic curve 0.82. CONCLUSION: Our study demonstrates that it is possible to predict the need for ureterolysis with clinical and sonographic data. Furthermore, patients presenting with a combination of the variables of our model (dyschezia, ovarian immobility, USL, and bowel DE lesions) have a high risk of ureterolysis. In contrast, patients without these features have a low risk (approximately 20%) of needing ureterolysis.