General Gynecology · Pelvic Pain
Tucker DR, Dungate B, Chiu DS, Noga HL, Lee C, Bedaiwy MA, Williams C, Allaire C, Talhouk A, Yong PJ
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Predictive tools are lacking for pain-related outcomes after endometriosis surgery. The objective of this study was to develop and validate a machine learning-based clinical model to predict poor pain-related quality of life after endometriosis surgery. Registry data from a prospective longitudinal cohort at a tertiary referral center (2013-2020) was used for model development and validation. Participants underwent an index endometriosis surgery, and completed the pain subscale of the Endometriosis Health Profile-30 (EHP-30) at baseline and 1-2-year follow-up. The outcome was poor pain-related quality of life defined as EHP-30 pain subscale above the 75th percentile for North America, at 1 to 2 years postsurgery. Thirty-two preoperative factors were evaluated, with final models retaining the top 10 most important predictors. Elastic net logistic regression, random forest (RF) and multilayer perceptron neural network models were developed. Internal validation was performed using 500 bootstrap samples, and a held-out test cohort. The study included 650 participants: 488 in the training cohort and 162 in a held-out test cohort. The RF model exhibited the most consistent discrimination, measured by the area under the receiver operating characteristic curve, between the training cohort (0.768; 95% CI: 0.690-0.837) and test cohort (0.766; 95% CI: 0.676-0.863, Δ = -0.002). The RF model also demonstrated the best integrated calibration index (0.029) and highest net benefit. Final preoperative predictors for the RF model included baseline EHP-30 score, surgery type (conservative fertility-sparing vs hysterectomy), anxiety scores, depression scores, pain catastrophizing scale scores, abdominal wall pain, pelvic floor myalgia, smoking status, back pain, and race/ethnicity. We present the RF model as the Endometriosis Pain Index to aid preoperative counselling for endometriosis surgery.
Rojas HE et al., 2026 · Journal of women's health (2002)
To characterize differences between individuals with and without mid-cycle pain in a registry cohort with endometriosis. Prospective analysis of data from the Endometriosis Pelvic Pain Interdisciplinary Cohort Data Registry (Clinicaltrials.gov #NCT02911090) at a tertiary referral center in Western Canada. Three hundred forty-five individuals aged 18-49 years who: (1) had at least one episode of menstrual bleeding in the last 3 months, (2) attended a baseline initial visit, and (3) subsequently had surgery with histological confirmation of endometriosis between January 2018 and December 2023. Exclusion criteria included (1) previous hysterectomy; (2) hormonal suppressive therapy use in the last 3 months; and (3) missing data on mid-cycle pain, history of hormonal therapy use, or menstrual cycle regularity. N/A. Mid-cycle pain in the last month versus No mid-cycle pain in the last month. Of the 345 participants, 67% (n = 232) reported mid-cycle pain in the last month. Mid-cycle pain in the last month was significantly associated with higher mean Central Sensitization Inventory score (48 ± 17 versus 36 ± 16, p < 0.001) and more months of prior hormonal suppressive therapy use (58 [14-120] versus 26 [0-109], p = 0.012). Abnormal anatomy at the time of surgery (e.g., endometrioma, ovarian adhesions) was not associated with mid-cycle pain in the last month. In this endometriosis cohort at a tertiary referral center, most participants reported mid-cycle pain in the last month, which was associated with central sensitization but was not clearly related to endometriosis anatomical distortion.
Bouchard TP et al., 2026 · Reproductive biomedicine online · Free to read
Do quantitative urinary hormone measurements on the Mira monitor predict and confirm ovulation accurately compared with ultrasound in women with regular menstrual cycles? Do Mira urine hormones correlate with serum hormones? This was a prospective, single-centre, blinded diagnostic accuracy study with 52 women aged 19-44 years with regular cycles (24-38 days) who tracked 153 cycles over 18 months. Daily first-morning urine was tested with the Mira monitor for follicle stimulating hormone (FSH), oestrone-3-glucuronide (E13G), luteinizing hormone (LH) and pregnanediol glucuronide (PDG). Serial transvaginal ultrasounds (890 scans) confirmed the day of ovulation. Serum hormones were measured twice per cycle. The 121 ovulatory cycles from 49 participants with sufficient index test and reference standard data were included in the final analysis. The Mira LH peak day strongly predicted ultrasound-confirmed ovulation (R² = 0.96, P < 0.001; intraclass correlation coefficient = 0.971), with 96% of ovulations occurring within ±1 day. The Mira PDG increase was also strongly associated with ultrasound-confirmed day of ovulation (R² = 0.87, P < 0.001). First-morning urine hormones were significantly associated with serum hormones when collected within 90 min (LH: R² = 0.92; E13G: R² = 0.73; R² = 0.61; R² = 0.75). Anovulatory cycles were identified in 11% of regularly cycling participants. Quantitative urinary hormone monitoring with the Mira monitor provides accurate prediction and confirmation of ovulation, with strong urine-serum associations supporting reduced reliance on serial serum draws in select patients. These findings support clinical adoption of quantitative urinary fertility monitoring.
Balachandran S et al., 2026 · Journal of obstetrics and gynaecology Canada : JOGC = Journal d'obstetrique et gynecologie du Canada : JOGC
To assess the impact of the COVID-19 pandemic on reproductive outcomes in patients with recurrent pregnancy loss (RPL) and the influence of material and social deprivation on these outcomes. This retrospective cohort study included RPL patients seen at a specialized clinic between March 1, 2018, and February 28, 2022. Patients were categorized into two groups based on care period: pre-pandemic (March 1, 2018-February 29, 2020) and pandemic (March 1, 2020-February 28, 2022). Cumulative probabilities of birth were estimated using the cumulative incidence function within a competing risk framework, treating pregnancy loss as a competing event. Fine and Gray regression models calculated sub-distribution hazard ratio (sHR) of birth. 544 patients were included in the study, with 255 in the pre-pandemic group and 289 in the pandemic group. Individuals in the pandemic group were less likely to achieve pregnancy than those in the pre-pandemic group (relative risk = 0.50, 95% confidence interval [CI] 0.39 - 0.66). Among those who conceived, the cumulative probability of live birth was 0.77 in both groups. Relative to individuals residing in high-social deprivation neighborhoods, those living in moderately deprived areas had higher sub-distribution hazards of live birth (adjusted sHR = 1.97, 95% CI 1.25 - 3.10; P = 0.003). Within specialized RPL care and a universal maternity care system, pregnancy rates were lower during the first two years of the COVID-19 pandemic. However, among those who conceived, the probability of achieving a live birth remained similar between the pre-pandemic and pandemic periods.
Bouchard TP et al., 2026 · Reproductive biomedicine online · Free to read
Does formation of the corpus luteum help to identify the day of ovulation on ultrasound when follicular collapse is missed, and how reliable are sonographers versus a review panel in identifying the day of ovulation on ultrasound? Sonographers in a clinic in Canada performed serial endovaginal ultrasound scans (six to eight per cycle) to identify the day of ovulation in regularly cycling women (n = 40) who were followed for one to five cycles (n = 85). The day of ovulation was identified by: (i) identification of the dominant follicle; (ii) disappearance of the dominant follicle; and (iii) identification and dating of the corpus luteum. The main outcome measures were inter-rater reliability between two sonographers, and Bland-Altman agreement between the supervising sonographer and a panel that reviewed each scan to identify the day of ovulation. Of the 85 menstrual cycles reviewed, two cycles did not have sufficient data to date ovulation, one cycle showed an incidental dermoid cyst, and 11 cycles showed anovulatory patterns. This left a total of 71 cycles (84%) for which intra-rater reliability between two sonographers for identifying the day of ovulation was high (intraclass correlation coefficient = 0.99, P < 0.0001), and Bland-Altman agreement showed no significant difference in the estimated day of ovulation between the supervising sonographer and the panel (t = -0.28, P = 0.78). Corpus luteum criteria were necessary to help identify the day of ovulation in 14 of 71 cycles (20%). The estimated day of ovulation can be determined reliably on ultrasound by trained sonographers using collapse of the dominant follicle and formation of the corpus luteum based on six to eight scans per cycle.
Elgendi M et al., 2020 · Frontiers in digital health · Free full text on PubMed Central
Chronic pelvic pain affects one in seven women worldwide, and there is an urgent need to reduce its associated significant costs and to improve women's health. There are many correlated factors associated with chronic pelvic pain (CPP), and analyzing them simultaneously can be complex and involves many challenges. A newly developed interaction ensemble, referred to as INTENSE, was implemented to investigate this research gap. When applied, INTENSE aggregates three machine learning (ML) methods, which are unsupervised, as follows: interaction principal component analysis (IPCA), hierarchical cluster analysis (HCA), and centroid-based clustering (CBC). For our proposed research, we used INTENSE to uncover novel knowledge, which revealed new interactions in a sample of 656 patients among 25 factors: age, parity, ethnicity, body mass index, endometriosis, irritable bowel syndrome, painful bladder syndrome, pelvic floor tenderness, abdominal wall pain, depression score, anxiety score, Pain Catastrophizing Scale, family history of chronic pain, new or re-referral, age when first experienced pain, pain duration, surgery helpful for pain, infertility, smoking, alcohol use, trauma, dysmenorrhea, deep dyspareunia, CPP, and the Endometriosis Health Profile for functional quality of life. INTENSE indicates that CPP and the Endometriosis Health Profile are correlated with depression score, anxiety score, and the Pain Catastrophizing Scale. Other insights derived from these ML methods include the finding that higher body mass index was clustered with smoking and a history of life trauma. As well, sexual pain (deep dyspareunia) was found to be associated with musculoskeletal pain contributors (abdominal wall pain and pelvic floor tenderness). Therefore, INTENSE provided expert-like reasoning without training any model or prior knowledge of CPP. ML has the potential to identify novel relationships in the etiology of CPP, and thus can drive innovative future research.
Gentles AJ et al., 2025 · The journal of pain · Free to read
There is increasing recognition that nociplastic pain and central sensitization may play a role in endometriosis-associated pain. The Pain Sensitivity Questionnaire Minor (PSQ-M) evaluates subjective widespread pain sensitivity, and is linked to pain outcomes in chronic pain populations. However, evidence connecting the PSQ-M to central sensitization in endometriosis is limited. Using the Central Sensitization Inventory (CSI) as a comparison, this study compared the PSQ-M as a clinical proxy for central sensitization in endometriosis individuals. Data collected from 983 endometriosis participants (mean age of 34 years), between January 2020 and December 2022, were analyzed from a prospective registry. A significant but weak positive correlation was observed between PSQ-M and CSI scores (r=0.099, p<0.001). A significant but weak correlation was found between the number of central sensitivity syndromes and pelvic pain-related comorbidities with the PSQ-M (r=0.093, p<0.001), compared to a stronger correlation with the CSI (r=0.687, p<0.05). PSQ-M scores were not significantly associated with baseline (r=0.013, p=0.797) or post-operative (r=-0.046, p=0.801) quality-of-life. There was no change in the PSQ-M and a small change in CSI after endometriosis surgery, suggesting that surgical treatment of endometriosis does not directly address central sensitization. In conclusion, the PSQ-M may not be the optimal clinical proxy for central sensitization in endometriosis. This study evaluates the Pain Sensitivity Questionnaire - Minor (PSQ-M) as a proxy for central sensitization in endometriosis. The PSQ-M showed weak correlations with central sensitivity syndromes and pain scores and was not associated with post-surgical quality-of-life, suggesting it may not be the optimal tool for assessing central sensitization in endometriosis.
Tucker DR et al., 2023 · American journal of obstetrics and gynecology
After endometriosis surgery, pain can persist or recur in a subset of patients. A possible reason for persistent pain after surgery is central nervous system sensitization and associated pelvic pain comorbidities. Surgery addresses the peripheral component of endometriosis pain pathophysiology (by lesion removal) but may not treat this centralized pain. Therefore, endometriosis patients with pelvic pain comorbidities related to central sensitization may experience worse pain-related outcomes after surgery, such as lower pain-related quality of life. This study aimed to determine whether baseline (preoperative) pelvic pain comorbidities are associated with pain-related quality of life at follow-up after endometriosis surgery. This study used longitudinal prospective registry data from the Endometriosis Pelvic Pain Interdisciplinary Cohort at the BC Women's Centre for Pelvic Pain and Endometriosis. Participants were aged ≤50 years with confirmed or clinically suspected endometriosis, and underwent surgery (fertility-sparing or hysterectomy) for endometriosis pain. Participants completed the pain subscale of the Endometriosis Health Profile-30 quality of life questionnaire preoperatively and at follow-up (1-2 years). Linear regression was performed to measure the individual relationships between 7 pelvic pain comorbidities at baseline and follow-up Endometriosis Health Profile-30 score, controlling for baseline Endometriosis Health Profile-30 and type of surgery received. These baseline (preoperative) pelvic pain comorbidities included abdominal wall pain, pelvic floor myalgia, painful bladder syndrome, irritable bowel syndrome, Patient Health Questionnaire 9 depression score, Generalized Anxiety Disorder 7 score, and Pain Catastrophizing Scale score. Least absolute shrinkage and selection operator regression was then performed to select the most important variables associated with follow-up Endometriosis Health Profile-30 from 17 covariates (including the 7 pelvic pain comorbidities, baseline Endometriosis Health Profile-30 score, type of surgery, and other endometriosis-related factors such as stage and histologic confirmation of endometriosis). Using 1000 bootstrap samples, we estimated the coefficients and confidence intervals of the selected variables and generated a covariate importance rank. The study included 444 participants. The median follow-up time was 18 months. Pain-related quality of life (Endometriosis Health Profile-30) of the study population significantly improved at follow-up after surgery (P<.001). The following pelvic pain comorbidities were associated with lower quality of life (higher Endometriosis Health Profile-30 score) after surgery, controlling for baseline Endometriosis Health Profile-30 score and type of surgery (fertility-sparing vs hysterectomy): abdominal wall pain (P=.013), pelvic floor myalgia (P=.036), painful bladder syndrome (P=.022), Patient Health Questionnaire 9 score (P<.001), Generalized Anxiety Disorder 7 score (P<.001), and Pain Catastrophizing Scale score (P=.007). Irritable bowel syndrome was not significant (P=.70). Of the 17 covariates included for least absolute shrinkage and selection operator regression, 6 remained in the final model (lambda=3.136). These included 3 pelvic pain comorbidities that were associated with higher follow-up Endometriosis Health Profile-30 scores or worse quality of life: abdominal wall pain (β=3.19), pelvic floor myalgia (β=2.44), and Patient Health Questionnaire 9 depression score (β=0.49). The other 3 variables in the final model were baseline Endometriosis Health Profile-30 score, type of surgery, and histologic confirmation of endometriosis. Pelvic pain comorbidities present at baseline before surgery, which may reflect underlying central nervous system sensitization, are associated with lower pain-related quality of life after endometriosis surgery. Particularly important were depression and musculoskeletal/myofascial pain (abdominal wall pain and pelvic floor myalgia). Therefore, these pelvic pain comorbidities should be candidates for a formal prediction model of pain outcomes after endometriosis surgery.
Kiser AC et al., 2024 · PLoS One · Free full text on PubMed Central
Endometriosis is a debilitating, chronic disease that is estimated to affect 11% of reproductive-age women. Diagnosis of endometriosis is difficult with diagnostic delays of up to 12 years reported. These delays can negatively impact health and quality of life. Vague, nonspecific symptoms, like pain, with multiple differential diagnoses contribute to the difficulty of diagnosis. By investigating previously imprecise symptoms of pain, we sought to clarify distinct pain symptoms indicative of endometriosis, using an artificial intelligence-based approach. We used data from 473 women undergoing laparoscopy or laparotomy for a variety of surgical indications. Multiple anatomical pain locations were clustered based on the associations across samples to increase the power in the probability calculations. A Bayesian network was developed using pain-related features, subfertility, and diagnoses. Univariable and multivariable analyses were performed by querying the network for the relative risk of a postoperative diagnosis, given the presence of different symptoms. Performance and sensitivity analyses demonstrated the advantages of Bayesian network analysis over traditional statistical techniques. Clustering grouped the 155 anatomical sites of pain into 15 pain locations. After pruning, the final Bayesian network included 18 nodes. The presence of any pain-related feature increased the relative risk of endometriosis (p-value < 0.001). The constellation of chronic pelvic pain, subfertility, and dyspareunia resulted in the greatest increase in the relative risk of endometriosis. The performance and sensitivity analyses demonstrated that the Bayesian network could identify and analyze more significant associations with endometriosis than traditional statistical techniques. Pelvic pain, frequently associated with endometriosis, is a common and vague symptom. Our Bayesian network for the study of pain-related features of endometriosis revealed specific pain locations and pain types that potentially forecast the diagnosis of endometriosis.
