Pelvic examination may be meaningfully taught to novices and be used to predict operating times for laparoscopic excision of endometriosis in one surgical procedure

Guideline No. 449: Diagnosis and Impact of Endometriosis - A Canadian Guideline

OBJECTIVE

To provide a contemporary approach to the understanding of the impact and methods for the diagnosis of endometriosis in Canada.

TARGET POPULATION

Individuals, families, communities, health care providers, and health care administrators who are affected by, care for patients with, or manage delivery of services for endometriosis.

OPTIONS

The diagnosis of endometriosis is facilitated by a detailed history, examination, and imaging tests with providers who are experienced in endometriosis care. Surgical evaluation with pathology confirms a diagnosis of endometriosis; however, it is not required for those whose diagnosis was confirmed with imaging.

OUTCOMES

There is a need to address earlier recognition of endometriosis to facilitate timely access to care and support. Education directed at the public, affected individuals and families, health care providers, and health care administrators are essential to reduce delays in diagnosis and treatment.

BENEFITS, HARMS, AND COSTS

Increased awareness and education about the impact and approach to diagnosis may support timely access to care for patients and families affected by endometriosis. Earlier and appropriate care may support a reduced health care system burden; however, improved clinical evaluation may require initial investments.

EVIDENCE

Each section was reviewed with a unique search strategy representative of the evidence available in the literature related to the area of focus. The literature searches for each section of this guideline are listed in Appendix A and include information from published systematic reviews described in the text.

VALIDATION METHODS

The recommendations were developed following two rounds of review by a national expert panel through an iterative 2-year consensus process. Further details on the process are shared in Appendix B. The authors rated the quality of evidence and strength of recommendations using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. See Appendix C (Table C1 for definitions and Table C2 for interpretations of strong and conditional recommendations).

INTENDED AUDIENCE

This guideline is intended to support health care providers and policymakers involved in the care of those impacted by endometriosis and the systems required to support them.

TWEETABLE ABSTRACT

Endometriosis impact and diagnosis updated guidelines for Canadian health care providers and policymakers.

SUMMARY STATEMENTS

RECOMMENDATIONS.

A preoperative predictive model for stage IV endometriosis

This was a retrospective study that evaluated a total of 280 patients who underwent surgery for complete removal of endometriosis to develop and validate the predictive model for stage IV endometriosis. The differences between stage I-III and stage IV endometriosis were performed by logistic regression. A model for the prediction of stage IV endometriosis was constructed, which was subsequently validated. The independent variables were visual analogue scale (VAS)≥4 [3.855, 95% confidence interval (CI): 1.675-8.871, p = 0.002], painful nodularity on uterosacral ligaments (13.954, 95% CI: 1.658-117.423, p = 0.015), and bilateral endometriosis (5.933, 95% CI: 1.931-18.225, p = 0.002). The AUC of the model was 0.777, with a sensitivity of 71.9% and specificity of 76.3% for stage IV endometriosis. Therefore, a complete collection of patient information prior to surgery, asking about pain and VAS scores, careful completion of pelvic examinations, and application of imaging techniques are conducive to better diagnosis and prediction of advanced endometriosis.IMPACT STATEMENTWhat is already known on this subject? Endometriosis, a chronic disease causing pain and infertility, is characterised by endometrial-like tissue outside the uterine cavity, which is often treated via surgery at present. Considering the risks of surgery, it is necessary to identify patients with stage IV endometriosis through non-invasive predictive models for adequate preparation for surgery. However, there is no reliable non-invasive predictive model now, despite utilisation of patient medical history, symptoms especially pain-related ones, pelvic examinations, laboratory examinations, and images in the preoperative diagnosis of endometriosis in the clinic.What do the results of this study add? A model developed based on three simple, accessible and non-invasive indicators displays good performance in predicting stage IV endometriosis.What are the implications of these findings for clinical practice and/or further research? It is conducive to diagnosing and predicting advanced endometriosis before surgery, so as to reduce the difficulty and improve the safety of surgery.