A Novel Classification of Endometriosis Based on Clusters of Comorbidities

Real world perspectives on endometriosis disease phenotyping through surgery, omics, health data, and artificial intelligence

Endometriosis is an enigmatic disease whose diagnosis and management are being transformed through innovative surgical, molecular, and computational technologies. Integrating single-cell and other omic disease data with clinical and surgical metadata can identify multiple disease subtypes with translation to novel diagnostics and therapeutics. Herein, we present real-world perspectives on endometriosis and the importance of multidisciplinary collaboration in informing molecular, epidemiologic, and cell-specific data in the clinical and surgical contexts.

Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis

BACKGROUND

Symptoms frequently associated with endometriosis affect quality of life (QoL). Our aim investigated the hypothesis that cluster analysis can be used to identify homogeneous phenotyping subgroups of women according to the burden of the endometriosis for their QoL, and then to investigate the phenotype differences observed between these subgroups.

METHODS

We developed an anonymous online survey, which received responses from 1,586 French women with endometriosis. K-means, a major clustering algorithm, was performed to show structure in data and divide women into groups based on the burden of endometriosis. This was defined using 9 dimensions. Multivariable logistic regression was performed to highlight the association between QoL and several factors. Covariables were age, BMI, smoking, education, children, marital status and surgery.

RESULTS

K-means clustering was implemented with 8 clusters (optimal CCC value of 17.2162). In one cluster, women presented a high level of QoL and represented 234 women for 60% of women with a high level of QoL, and another with 410 women for 34% of women with worse QoL. Independent factors determining high QoL were age (over 45 years compared to below 25 years, OR = 0.17 [0.07-0.46], p<0.001), BMI (high vs low, OR = 0.47 [0.28-0.80], p = 0.005), having children (OR = 0.30 [0.18-0.48], p<0.001), having surgery for endometriosis (OR = 0.55 [0.32-0.94], p = 0.029), and education (high vs low, OR = 2.75 [1.75-4.31], p<0.001).

CONCLUSION

Cluster analysis identifies homogeneous women phenotypes for QoL with endometriosis. Implementing new methodological approaches improves QoL of endometriosis women and allows appropriate preventive strategies.

Characterization of COVID-19 infected pregnant women with ICU admission and the risk of preterm: A cluster analysis

BACKGROUND

The unique physiological changes during pregnancy present challenges in understanding the full scope and effects of COVID-19 on pregnant women, adding complexity to their medical management. Given the significant changes in the immune, circulatory, respiratory, and hormonal systems during the progression of the pregnancy, and the specific factors with higher risk of COVID-19, like metabolic, vascular, and endothelial factors, typically also associated with maternal and neonatal unfavorable outcomes, the full understanding of how COVID-19 affects pregnant women is not clarified yet.

METHODS

In this study, anonymous data from medical records of pregnant women with lab-confirmed COVID-19 in Astana, Kazakhstan from May 1, 2021, to July 14, 2021, were collected retrospectively. A multivariate regression model was built to identify factors associated with the risk of ICU admission. Cluster analysis was performed to identify distinct groups among women admitted to the ICU based on their blood parameters, coagulation profiles, and oxygenation saturation levels.

RESULTS

10.7 % of pregnant women were admitted to ICU. Among them, 4.36 % were in the 2nd trimester and 13.58 % in the 3rd trimester. No women in the 1st trimester were admitted to ICU. A multivariate regression model demonstrates that gestational diabetes, leukocytes, CRP, and saturation were the factors significantly associated with a higher risk of ICU admission. Three clusters of pregnant women were segmented, and preterm birth was frequent in clusters 1 (serious systemic conditions affecting multiple organs) and 3 (women with hypertension and preeclampsia), whereas cluster 2 represents women who can also be characterized as suffering from infections with a possible autoimmune component. Neutrophil to lymphocyte ratio was frequent in clusters 1 and 3.

CONCLUSION

In this study, multivariable analysis identified factors with a risk of ICU admission, and clustering analysis helped to identify groups of COVID-19-infected pregnant women admitted to ICU with similar risk profiles. Differences in clusters can help to explain discrepancies in COVID-19 outcomes and suggest biochemical and molecular mechanisms involved in COVID-19 and outline a more personalized approach to understanding, diagnosing, and treating women.

Pain from Internal Organs and Headache: The Challenge of Comorbidity

Headache and visceral pain are common clinical painful conditions, which often co-exist in the same patients. Numbers relative to their co-occurrence suggest possible common pathophysiological mechanisms. The aim of the present narrative review is to describe the most frequent headache and visceral pain associations and to discuss the possible underlying mechanisms of the associations and their diagnostic and therapeutic implications based on the most recent evidence from the international literature. The conditions addressed are as follows: visceral pain from the cardiovascular, gastrointestinal, and urogenital areas and primary headache conditions such as migraine and tension-type headache. The most frequent comorbidities involve the following: cardiac ischemic pain and migraine (possible shared mechanism of endothelial dysfunction, oxidative stress, and genetic and hormonal factors), functional gastrointestinal disorders, particularly IBS and both migraine and tension-type headache, primary or secondary dysmenorrhea and migraine, and painful bladder syndrome and headache (possible shared mechanisms of peripheral and central sensitization processes). The data also show that the various visceral pain-headache associations are characterized by more than a simple sum of symptoms from each condition but often involve complex interactions with the frequent enhancement of symptoms from both, which is crucial for diagnostic and treatment purposes.

Endometriosis and mental health disorders: identification and treatment as part of a multimodal approach

Endometriosis is a disease marked by more than just pain and infertility, as it transcends the well-characterized physical symptoms to be frequently associated with mental health issues. This review focuses on the associations between endometriosis and anxiety, depression, sexual dysfunction, and eating disorders, all of which show a higher prevalence in women with the disease. Studies show that pain, especially the chronic pelvic pain of endometriosis, likely serves as a mediating factor. Recent studies evaluating genetic predispositions for endometriosis and mental health disorders suggest a shared genetic predisposition. Healthcare providers who treat women with endometriosis should be aware of these associations to best treat their patients. A holistic approach to care by gynecologists as well as mental health professionals should emphasize prompt diagnosis, targeted medical interventions, and psychological support, while also recognizing the role of supportive relationships in improving the patient's quality of life.