Endometriosis and elite sports: a blind spot in research.
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A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.
INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.
Humans↗
Efficacy and Safety of Elagolix Versus Dienogest for Treatment of Moderate-to-Severe Endometriosis Pain: A Phase III, Multicentric, Double-Blind, Active-Controlled, Non-Inferiority Study.
OBJECTIVE: To compare the efficacy, safety and tolerability of elagolix with dienogest in women with moderate-to-severe endometriosis-associated pain. DESIGN: A multicentre, double-blind, double-dummy, randomised, parallel-group, active-controlled, non-inferiority phase III study. SETTING: Nineteen clinical centres across India. STUDY POPULATION: Women (18-49 years) diagnosed with endometriosis and experiencing moderate-to-severe pain. METHODS: Participants were randomised (1:1) to receive oral elagolix (150 mg once daily) or dienogest (2 mg once daily) for 24 weeks. OUTCOME MEASURES: The primary outcome was change in endometriosis-related pain (Numeric Rating Scale [NRS]) from baseline to Day 85. Secondary outcomes included changes in NRS (Day 169), dysmenorrhoea, non-menstrual pelvic pain (NMPP) scores (Days 85 and 169), rescue medication use, patient global impression of change (PGIC), adverse events and bone mineral density. RESULTS: Of 340 patients screened, 230 were randomised (115 per group). At Day 85, both arms showed similar reductions in NRS pain scores with a treatment difference of 0.04 (95% CI: -0.3, 0.37) [p = 0.9747] demonstrating non-inferiority as upper 95% CI was below pre-specified margin of 1.5. At Day 169, both arms showed comparable improvements in overall pain, dysmenorrhoea and NMPP from baseline (p = 0.9372, p = 0.8884, and p = 0.9616, respectively). Rescue medication use and PGIC were comparable between treatment arms. Adverse event incidence was similar (elagolix: 14.8%; dienogest: 19.1%), with no serious TEAEs or discontinuations. No significant bone mineral density changes were observed. CONCLUSIONS: Elagolix demonstrated non-inferiority to dienogest with an acceptable safety and tolerability profile, supporting its use in managing endometriosis-associated pain. TRIAL REGISTRATION: ClinicalTrials.gov identifier: CTRI/2023/01/049292.
Humans↗
Nociception-guided opioid administration within multimodal analgesia for laparoscopic endometriosis surgery: a randomized controlled trial.
Women with endometriosis are at increased risk of severe postoperative pain due to nociceptive sensitization. While multimodal analgesia reduces opioid use, the added value of objective nociception monitoring remains unclear. This study evaluated whether NOL®-guided opioid titration improves perioperative outcomes within a standardized multimodal regimen. In this prospective, randomized, single-blinded trial, premenopausal women undergoing laparoscopic surgery for suspected endometriosis or adenomyosis were assigned to NOL®-guided analgesia or standard care based on clinical assessment. All patients received a standardized multimodal protocol. The primary outcome was total perioperative opioid consumption. Secondary outcomes included postoperative pain scores (NRS) and PACU length of stay. Exploratory analyses assessed the association between preoperative pain (Mankoski Pain Scale, MPS) and postoperative outcomes. A total of 111 patients were analyzed (NOL®: n = 54; control: n = 57). Total perioperative opioid consumption did not differ significantly between groups (adjusted mean difference = 14 μg for Fentanyl and 52 μg for Remifentanil; p = 0.8). Surgery duration was an independent predictor of opioid use (p < 0.001) and PACU length of stay (p = 0.01), whereas treatment group had no significant effect. Postoperative pain scores were comparable between groups at all time points. NOL®-derived metrics were not associated with opioid consumption or pain. Higher preoperative MPS scores independently predicted higher pain scores in the late PACU phase. NOL®-guided opioid titration did not reduce perioperative opioid consumption or improve early postoperative outcomes compared with standard multimodal analgesia in women undergoing laparoscopic surgery for endometriosis.
Humans↗