Diagnosis Of Polycystic Ovary Syndrome Research Articles

Diagnostic value of ultrasound elastography in polycystic ovary syndrome: a systematic review and meta-analysis

Objective The main purpose of this systematic review and meta-analysis was to investigate the diagnostic value of ultrasound elastography in the evaluation of polycystic ovary syndrome (PCOS). Methods A comprehensive and methodical investigation was carried out in the databases of PubMed, EMBASE, Cochrane, Scopus, Web of Science, and China National Knowledge Infrastructure, covering the entire duration of these databases until October 18, 2023. The primary purpose of this research was to evaluate and contrast ovarian tissue elasticity in people with and without PCOS. The elasticity of ovarian tissue was quantified using standardized mean difference (SMD). Results A total of eight studies were ultimately selected for systematic evaluation and meta-analysis. Five studies used shear wave elastography (SWE) as a diagnostic tool, and it was discovered that women with PCOS had higher levels of ovarian shear wave elasticity than their healthy counterparts. The SMD was determined to be 1.86 kilopascal (95% CI: 1.27 to 2.44). Three studies were conducted using strain elastography (SE) to compare the ovarian strain ratio of patients with PCOS to that of a healthy control group. The SMD for the PCOS group was 2.07 (95% CI: 1.79 to 2.34), which indicated that the ovarian strain ratio was significantly higher in that group. Conclusion This systematic review and meta-analysis found that women with PCOS had stiffer ovarian tissue than women without the disorder. Ultrasound elastography may provide clinicians with value beyond 2D ultrasound in the diagnosis of PCOS.

Predictive Analysis and Discerning of Polycystic Ovary Syndrome in Women using Machine Learning Computations

This paper focuses on the data-driven diagnosis of polycystic ovary syndrome (PCOS) in women. For this, machine learning algorithms are applied to a dataset freely available in Kaggle repository. This dataset has 43 attributes of 541 women, among which 177 are patients of PCOS disease. Firstly, univariate feature selection algorithm is applied to find the best features that can predict PCOS. The ranking of the attributes is computed and it is found that the most important attribute is the ratio of Follicle stimulating hormone (FSH) and Luteinizing hormone (LH), Next, holdout and cross validation methods are applied to the dataset to separate the training and testing data. A number of classifiers such as gradient boosting, random forest, logistic regression, and hybrid random forest and logistic regression (RFLR) are applied to the attributed are good enough to predict the PCOS disease

Irregular Cycles, Ovulatory Disorders, and Cardiometabolic Conditions in a US-Based Digital Cohort

Polycystic ovary syndrome (PCOS), characterized by irregular menstrual cycles and hyperandrogenism, is a common ovulatory disorder. Having an irregular cycle is a potential marker for cardiometabolic conditions, but data are limited on whether the associations differ by PCOS status or potential interventions. To evaluate the association of PCOS, time to regularity since menarche (adolescence), and irregular cycles (adulthood) with cardiometabolic conditions. This cross-sectional study used a large, US-based digital cohort of users of the Apple Research application on their iPhone. Eligibility criteria were having ever menstruated, living in the US, being at age of consent of at least 18 years (or 19 years in Alabama and Nebraska or 21 years in Puerto Rico), and being able to communicate in English. Participants were enrolled between November 14, 2019, and December 13, 2022, and completed relevant surveys. Self-reported PCOS diagnosis, prolonged time to regularity (not spontaneously establishing regularity within 5 years of menarche), and irregular cycles. The primary outcome was self-reported cardiometabolic conditions, including obesity, prediabetes, type 1 and 2 diabetes, high cholesterol, hypertension, metabolic syndrome, arrhythmia, congestive heart failure, coronary artery disease, heart attack, heart valve disease, stroke, transient ischemic attack (TIA), deep vein thrombosis, and pulmonary embolism measured using descriptive statistics and logistic regression to estimate prevalence odds ratios (PORs) and 95% CIs. Effect modification by lifestyle factors was also estimated. The study sample (N = 60 789) had a mean (SD) age of 34.5 (11.1) years, with 12.3% having PCOS and 26.3% having prolonged time to regularity. Among a subset of 25 399 participants who completed the hormonal symptoms survey, 25.6% reported irregular cycles. In covariate-adjusted logistic regression models, PCOS was associated with a higher prevalence of all metabolic and several cardiovascular conditions, eg, arrhythmia (POR, 1.37; 95% CI, 1.20-1.55), coronary artery disease (POR, 2.92; 95% CI, 1.95-4.29), heart attack (POR, 1.79; 95% CI, 1.23-2.54), and stroke (POR, 1.66; 95% CI, 1.21-2.24). Among participants without PCOS, prolonged time to regularity was associated with type 2 diabetes (POR, 1.24; 95% CI, 1.05-1.46), hypertension (POR, 1.09; 95% CI, 1.01-1.19), arrhythmia (POR, 1.20; 95% CI, 1.06-1.35), and TIA (POR, 1.33; 95% CI, 1.01-1.73), and having irregular cycles was associated with type 2 diabetes (POR, 1.36; 95% CI, 1.08-1.69), high cholesterol (POR, 1.17; 95% CI, 1.05-1.30), arrhythmia (POR, 1.21; 95% CI, 1.02-1.43), and TIA (POR, 1.56; 95% CI, 1.06-2.26). Some of these associations were modified by high vs low body mass index or low vs high physical activity. These findings suggest that PCOS and irregular cycles may be independent markers for cardiometabolic conditions. Early screening and intervention among individuals with irregular menstrual cycles may be beneficial.

Unraveling the Complexities of Polycystic Ovarian Syndrome: A Comprehensive Review

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder affecting reproductive-age women, characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. This comprehensive review delves into the multifaceted nature of PCOS, exploring its etiology, pathophysiology, clinical manifestations, diagnostic criteria, and management strategies. Key topics include the role of insulin resistance and hyperinsulinemia in PCOS pathogenesis, the impact of hormonal imbalances on menstrual irregularities and fertility, and the association of PCOS with metabolic syndrome and cardiovascular risk factors. Furthermore, the review discusses current diagnostic criteria and controversies surrounding PCOS diagnosis, as well as evidence-based approaches to treatment, encompassing lifestyle modifications, pharmacological interventions, and assisted reproductive technologies. By synthesizing current knowledge and emerging research findings, this review aims to provide a comprehensive overview of PCOS for clinicians, researchers, and individuals affected by this prevalent endocrine disorder.

The effect of bariatric surgery on polycystic ovary syndrome patients' obstetric and neonatal outcomes: a population-based study.

To examine the effect of bariatric surgery (BS) on obstetric and neonatal outcomes in patients with polycystic ovary syndrome (PCOS). A retrospective population-based cohort study utilizing the Healthcare Cost and Utilization Project Nationwide Inpatient Sample database, including women who delivered in the third trimester or had a maternal death in the USA (2004-2014). We compared obstetric and neonatal outcomes between groups in three analyses: (1) Primary analysis-women with an ICD-9 PCOS diagnosis who underwent BS compared to pregnant PCOS patients without BS. (2) Sub-group analysis-PCOS women with BS compared to obese PCOS women (body mass index (BMI) ≥ 30 kg/m2) without BS. (3) Women with and without PCOS who underwent BS. In the primary analysis, pregnant PCOS women who underwent BS (N = 141), compared to pregnant PCOS women without BS (N = 14,741), were less likely to develop pregnancy-induced hypertension (PIH) (9.2% vs. 16.2%, respectively, aOR 0.39, 95% CI 0.21-0.72) and gestational diabetes mellitus (GDM) (9.9% vs. 18.8, aOR 0.40, 95% CI 0.23-0.70). In the sub-group analysis, PCOS women with BS, compared to obese PCOS women without BS (N = 3231), were less likely to develop gestational hypertension, preeclampsia, and preeclampsia or eclampsia superimposed on hypertension (P < 0.05). Lastly, PCOS patients with BS had a higher cesarean section rate when compared to non-PCOS patients with BS (N = 9197) (61.7% vs. 49.2%, aOR 1.48, 95% CI 1.05-2.09), with otherwise comparable obstetric and neonatal outcomes. BS in PCOS patients was associated with reduced risks for GDM and PIH when compared to PCOS controls without BS and reduced risk for gestational hypertension, preeclampsia, and preeclampsia or eclampsia superimposed on hypertension when compared to obese PCOS controls without BS. Moreover, BS was associated with reduced inherent pregnancy risks of PCOS, almost equating them to those of non-PCOS counterparts.

Associations between Polycystic Ovary Syndrome (PCOS) and Antibiotic Use: Results from the UAEHFS

Women with polycystic ovary syndrome (PCOS) have a higher susceptibility to infections compared to those without PCOS. Studies evaluating antibiotic use based on PCOS status are scarce. Therefore, we aimed to (i) assess the associations between self-reported PCOS and antibiotic use, and (ii) whether PCOS treatment and the age at PCOS diagnosis modified the associations above. This cross-sectional analysis used the United Arab Emirates Healthy Future Study (UAEHFS) conducted from February 2016 to March 2023 involving 2063 Emirati women aged 18–62 years. We performed ordinal logistic regressions under unadjusted and demographic-health-characteristic-adjusted models to obtain the odds ratios (ORs) and 95% confidence intervals (CIs) to analyze PCOS and antibiotic use. Subgroup analyses were performed by treatment status and age at diagnosis. We found that women with PCOS were 55% more likely to frequently take a course of antibiotics in the past year (aOR 1.55; 95% CI 1.26–1.90). Similar likelihoods were also found among those being treated for PCOS and those without treatment but with a PCOS diagnosis at ≤25 years. Our study suggests that PCOS was associated with an increased use of antibiotics among Emirati women. Understanding the frequent antibiotic use susceptibility among those with PCOS may improve antibiotic use surveillance and promote antibiotic stewardship in these at-risk individuals.

Prolidase activity in women with polycystic ovarian syndrome undergoing assisted conception

Background: Prolidase is a manganese (Mn)-dependent cytosolic exopeptidase that degrades imidodipeptides with C-terminal proline or hydroxyproline. Prolidase recycling from imidodipeptides plays a critical role in collagen resynthesis and extracellular matrix (ECM) remodelling. Following an increase in gonadotropins, ovarian and follicular collagen undergo substantial degradation. Abnormal ovarian ECM composition is associated with polycystic ovary syndrome (PCOS). This study aimed to examine prolidase activity in the serum and follicular fluid (FF) of women undergoing in vitro fertilisation/intracytoplasmic sperm injection (IVF/ICSI) treatment, comparing those with PCOS to those with normal ovarian function.Methods: This prospective study enrolled 50 participants, of whom 44 were included. PCOS diagnosis followed the Rotterdam consensus criteria, with 20 patients constituting the study group. The control group comprised 24 individuals with mild-to-moderate male infertility. Prolidase enzyme activity in serum and FF was measured using the Chinard reagent via spectrophotometric analysis and compared between the groups.Results: Serum and FF prolidase levels were significantly lower in patients with PCOS (p < 0.05). A direct correlation was observed between serum and FF prolidase levels (p < 0.05). Although blastocyst quality scoring (BQS) significantly decreased in PCOS patients, no statistical difference was observed in the clinical pregnancy rate between the groups (p < 0.05) (p > 0.05). A negative correlation existed between serum prolidase levels and total antral follicle (AF) count (p < 0.05). Conversely, both serum and FF prolidase levels positively correlated with BQS (r = 0.574)(p < 0.05) (r = 0.650)(p < 0.05).Conclusions: Patients with PCOS showed lower serum and FF prolidase levels, indicating abnormal degradation of ovarian and follicular collagen, potentially causing anovulation.

Hybrid Machine Learning Approach for Early Diagnosis of Polycystic Ovary Syndrome with Stable Features

Polycystic Ovary Syndrome (PCOS) is a hormonal condition that typically affects female during the time of their reproduction. It is identified by the disruptions in hormonal balance, particularly an increase in levels of androgen (male hormone) in the female body. PCOS can lead to various symptoms and health complications including irregular menstrual cycles, ovarian cysts, fertility issues, insulin resistance, weight gain, acne, and excess hair growth. The real-world PCOS detection is a challenging task whilst PCOS specific cause is unknown and its symptoms are unclear. Thus, accurate and timely diagnosis of PCOS is crucial for effective management and prevention of long-term complications. In such cases, Machine learning based PCOS prediction model support diagnostic process, address potential errors and time constraints. Machine learning algorithms can analyze large set of patient data, including medical history, hormonal profiles, and imaging results, to assist in the diagnosis of PCOS. In particular, the performance of data analysis chore and prediction model is improved by ensemble feature selection strategies. These methods concentrate on selecting a subset of pertinent features from a broader range of features. The unstable nature of the outcome of feature selection algorithm is a frequent issue in practical applications, when it is applied multiple times on similar dataset or with slight modifications in the data. Thus, evaluating the robustness of feature selection algorithm is most important. To address these issues and quantify the robustness, this study uses Jenson-Shannon divergence, an information theoretic approach with ensemble feature selection method to handle the various findings, such as complete ranking, half ranking and top-k lists (without ranking). Furthermore, this article proposes a hybrid machine learning classifier with SMOTE – SVM for the prompt detection of PCOS and the performance of the model is compared with a number of other individual classifiers including KNN (K-Nearest Neighbour), Support Vector Machine (SVM), AdaBoost, LR –Logistic Regression, NB –Nave Bayes, RF –Random Forest, Decision Tree. The proposed SWISS-AdaBoost classifier surpassed other models with 97.81% of accuracy and AUC of 99.08%.

Self-esteem and body image satisfaction in women with PCOS in the Middle East: Cross-sectional social media study.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of childbearing age, associated with increased incidence of emotional disorders, anxiety and depression. The aim was of this study was to investigate whether those women reporting PCOS differed to women without PCOS in measures of psychological well-being including body-image satisfaction and self-esteem across a Middle Eastern population. An online survey link of 21 questions was shared and distributed across social media platforms (Instagram and WhatsApp). The main outcome measured was levels of self-esteem and body image satisfaction in association with symptoms experienced by the participants. 12,199 female subjects completed the survey of whom 3,329 respondents (27.3%) self-reported a diagnosis of PCOS. PCOS respondents felt less attractive compared to non-PCOS respondents (73.9% vs 80.5%, p<0.0001). More respondents with PCOS reported avoidance of their reflection in the mirror (61.7% vs 49.8%, p<0.001) and avoidance of social interactions (22.3% vs 32.3%, p<0.0001). More PCOS respondents wanted to lose weight (75.2% vs 68.5%, p<0.001) with increasing weight being associated with being less attractive (p<0.001). Fewer PCOS respondents felt satisfied/confident compared non-PCOS respondents (38.6% vs 50.7%, p<0.001). PCOS respondents reported significantly lower measures of self-esteem and body image satisfaction compared to non-PCOS respondents in this population.

Unraveling PCOS: Exploring its causes and diagnostic challenges

Abstract Women in the reproductive age range are usually affected with Polycystic Ovary Syndrome (PCOS), a complex and multifaceted condition. Anovulation, hyperandrogenism, and metabolic difficulties like hyperglycemia, hypertension, and obesity in women are all manifestations of this condition, which also affects the reproductive system. The National Institutes of Health in the 1990s, Rotterdam in 2003, and Androgen Excess Polycystic Ovary Syndrome in 2009 all contributed to the evolution of the diagnostic criteria for PCOS. The 2003 Rotterdam criteria are currently the most generally used criteria. They call for at least two of the three criteria – irregular menstrual periods, polycystic ovary morphology on imaging, and hyperandrogenism – either clinically or biochemically – to be present in order to diagnose PCOS. It is currently being suggested that the anti-Müllerian hormone in serum be used instead of follicular count as an official indicator of polycystic ovarian morphology/PCOS. Hyperandrogenism and irregular periods are essential components in determining PCOS in adolescent patients. More recently, it has been shown that artificial intelligence, especially machine learning, holds great promise for detecting and predicting PCOS with high accuracy, potentially assisting in early management and treatment decisions. Examining the underlying mechanisms, clinical symptoms, and challenges involved in making a diagnosis of PCOS in females is the premise of this review article.

Management of Polycystic Ovarian Syndrome: A Qualitative Inquiry among Complementary and Alternative Medicine Practitioners in South Africa.

Polycystic ovarian syndrome (PCOS) is a complex reproductive endocrinopathy affecting 4-20% of females of reproductive age. PCOS and its consequent complications such as infertility, diabetes mellitus and cardiovascular disease significantly impact clinical management. Complementary and alternative medicine (CAM), including homeopathy, is gaining recognition in PCOS management. There remains a paucity of formal protocols for managing PCOS within homeopathy and other CAM systems. This study aimed to explore and document existing therapeutic practices in the management of PCOS from diagnosis to treatment used by practitioners within various disciplines of CAM: viz., homeopathy, ayurveda, unani tibb, traditional Chinese medicine (TCM) and naturopathy, in the context of their unique philosophical background. In this explorative, descriptive study, data were collected from CAM practitioners in eThekwini Municipality, KwaZulu Natal, South Africa, using semi-structured interviews and analysed using Tesch's and Creswell's methods for qualitative analysis. Four themes emerged from the data, namely: CAM philosophical perspectives on PCOS, contributing factors, diagnosis of PCOS, and management of PCOS. Five sub-themes emerged: clinical diagnosis of PCOS, CAM-specific characterisation of PCOS, CAM-specific treatment of PCOS, adjunctive therapies, and lifestyle interventions. Homeopathic management comprised several prescribing methods, the most common ones being miasmatic/constitutional, keynote and clinical, alongside adjunctive therapies and lifestyle interventions. Other CAM modalities adopted similar holistic approaches. This paper offers a comprehensive exploration of the perceptions, clinical investigations and management practices in PCOS by homeopaths and four other CAM modalities - ayurveda, unani tibb, TCM and naturopathy - as documented in the study. Homeopaths and other CAM practitioners employed CAM-specific therapies, along with adjunctive therapies and lifestyle interventions, adopting holistic approaches. Enhancing the quality of life through emotional counselling, stress reduction and lifestyle improvements emerged as shared objectives across modalities. Our findings underscore the need to further explore inter-disciplinary collaboration in PCOS management among registered CAM practitioners, with the potential to expand the scope of comprehensive care for PCOS patients.

Assessing the clinical diagnostic value of anti-Müllerian hormone in polycystic ovarian syndrome and its correlation with clinical and metabolism indicators

BackgroundThis study investigated the association between Anti-Müllerian Hormone (AMH) and relevant metabolic parameters and assessed its predictive value in the clinical diagnosis of polycystic ovarian syndrome (PCOS).MethodsA total of 421 women aged 20–37 years were allocated to the PCOS (n = 168) and control (n = 253) groups, and their metabolic and hormonal parameters were compared. Spearman correlation analysis was conducted to investigate associations, binary logistic regression was used to determine PCOS risk factors, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of AMH in diagnosing PCOS.ResultsThe PCOS group demonstrated significantly higher blood lipid, luteinizing hormone (LH), and AMH levels than the control group. Glucose and lipid metabolism and hormonal disorders in the PCOS group were more significant than in the control group among individuals with and without obesity. LH, TSTO, and AMH were identified as independent risk factors for PCOS. AMH along with LH, and antral follicle count demonstrated a high predictive value for diagnosing PCOS.ConclusionAMH exhibited robust diagnostic use for identifying PCOS and could be considered a marker for screening PCOS to improve PCOS diagnostic accuracy. Attention should be paid to the effect of glucose and lipid metabolism on the hormonal and related parameters of PCOS populations.

The use of an Internet resource in young people to identify female students at risk for polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a polygenic endocrine disorder caused by both genetic and epigenetic factors. Depending on the period of a woman’s life, the clinical picture, diagnosis, and treatment tactics of the disease are different. The syndrome has a set of reproductive, metabolic, and psychological features. Objective. To study the prevalence of PCOS among female students and to evaluate the effectiveness of using Internet platforms in identifying the manifestations that characterize reproductive health disorders. Subjects and methods. A total of 330 respondents studying in the higher educational establishments of Khabarovsk were interviewed using the Google Forms platform in October to December 2021 in order to identify whether they had irregular menstruation, hyperandrogenism, which was followed by an examination and verification of the diagnosis of PCOS in an outpatient setting. Results. According to the survey results, 87.58% of the respondents did not plan pregnancy in the next 2 years, so infertility as one of the PCOS symptoms did not cause anxiety in them. According to the survey among the female students with an irregular menstrual cycle, the incidence rate of PCOS was 24.7%. Conclusion. In our opinion, the active detection of PCOS in patients with an irregular menstrual cycle among young people using Internet resources allows them to focus their attention on reproductive health disorders and on the need to consult a gynecologist.

Validation of mitochondrial biomarkers and immune dynamics in polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS), a prevalent endocrine-metabolic disorder, presents considerable therapeutic challenges due to its complex and elusive pathophysiology. We employed three machine learning algorithms to identify potential biomarkers within a training dataset, comprising GSE138518, GSE155489, and GSE193123. The diagnostic accuracy of these biomarkers was rigorously evaluated using a validation dataset using area under the curve (AUC) metrics. Further validation in clinical samples was conducted using PCR and immunofluorescence techniques. Additionally, we investigate the complex interplay among immune cells in PCOS using CIBERSORT to uncover the relationships between the identified biomarkers and various immune cell types. Our analysis identified ACSS2, LPIN1, and NR4A1 as key mitochondria-related biomarkers associated with PCOS. A notable difference was observed in the immune microenvironment between PCOS patients and healthy controls. In particular, LPIN1 exhibited a positive correlation with resting mast cells, whereas NR4A1 demonstrated a negative correlation with monocytes in PCOS patients. ACSS2, LPIN1, and NR4A1 emerge as PCOS-related diagnostic biomarkers and potential intervention targets, opening new avenues for the diagnosis and management of PCOS.

Use of nutraceuticals and micronutrient supplementation for the management of Polycystic Ovary Syndrome: a scoping review

Polycystic Ovary Syndrome (PCOS) is a common hormonal condition affecting women of reproductive age(1). Women with PCOS experience a broad range of clinical symptoms, collectively grouped into reproductive, metabolic, psychological and anthropometric features(2). Complementary therapies, such as nutrient supplementation, have been identified as potential adjunct therapeutic approaches to support currently recommended lifestyle and pharmacological interventions(3). However, evidence for their overall efficacy and safety is inconsistent and unclear. This review aimed to systematically map the available literature on the use of nutrient supplementation for the management of PCOS features, including metabolic, reproductive, psychological and anthropometric. This review followed a systematic approach with literature searches using CINHAL, Cochrane reviews, Medline, PsycINFO, Scopus and LILACS conducted up to April 2022. All types of study designs were included if they reported on the efficacy or association between micronutrient supplementation and/or nutraceuticals on features of PCOS in women (≥ 18 years) with a confirmed diagnosis of PCOS. A total of 317 articles were included involving n = 23,926 women. Forty-three different supplements examined various clinical features of PCOS grouped into metabolic, reproductive, psychological and anthropometric. The most studied supplements included Inositols (n = 83), Vitamin D (n = 51), N-acetylcysteine (n = 25), Omega-3 fatty acids (n = 18) and Biotics (n = 14). Most studies (n = 262; 83%) reported on reproductive features followed by metabolic (n = 212; 66%), anthropometric (n = 181; 57%) and psychological (n = 5; 2%). Less than half (n = 148; 47%) of the included studies reported on the potential for adverse events. Our results highlight that the potential therapeutic benefit of micronutrient and nutraceutical supplementation on psychological features of PCOS warrants future exploration. Additional primary studies that are adequately powered are needed to investigate therapeutic doses needed for clinical benefits. Lastly, a more rigorous approach to monitoring and recording adverse event data is recommended.

AI-algorithm training and validation for identification of endometrial CD138+ cells in infertility-associated conditions; polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF)

BackgroundEndometrial CD138+ plasma cells serve as a diagnostic biomarker for endometrial inflammation, and their elevated occurrence correlates positively with adverse pregnancy outcomes. Infertility-related conditions like polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) are closely associated with systemic and local chronic inflammatory status, wherein endometrial CD138+ plasma cell accumulation could also contribute to endometrial pathology. Current methods for quantifying CD138+ cells typically involve laborious and time-consuming microscopic assessments of only a few random areas from a slide. These methods have limitations in accurately representing the entire slide and are susceptible to significant biases arising from intra- and interobserver variations. Implementing artificial intelligence (AI) for CD138+ cell identification could enhance the accuracy, reproducibility, and reliability of analysis. MethodsHere, an AI algorithm was developed to identify CD138+ plasma cells within endometrial tissue. The AI model comprised two layers of convolutional neural networks (CNNs). CNN1 was trained to segment epithelium and stroma across 28,363 mm2 (2.56 mm2 of epithelium and 24.87 mm2 of stroma), while CNN2 was trained to distinguish stromal cells based on CD138 staining, encompassing 7345 object layers (6942 CD138- cells and 403 CD138+ cells). The training and performance of the AI model were validated by three experienced pathologists. We collected 193 endometrial tissues from healthy controls (n = 73), women with PCOS (n = 91), and RIF patients (n = 29) and compared the CD138+ cell percentages based on cycle phases, ovulation status, and endometrial receptivity utilizing the AI model. ResultsThe AI algorithm consistently and reliably distinguished between CD138- and CD138+ cells, with total error rates of 6.32% and 3.23%, respectively. During the training validation, there was a complete agreement between the decisions made by the pathologists and the AI algorithm, while the performance validation demonstrated excellent accuracy between the AI and human evaluation methods (intraclass correlation; 0.76, 95% confidence intervals; 0.36–0.93, p = 0.002) and a positive correlation (Spearman's rank correlation coefficient: 0.79, p < 0.01). In the AI analysis, the AI model revealed higher CD138+ cell percentages in the proliferative phase (PE) endometrium compared to the secretory phase or anovulatory PCOS endometrium, irrespective of PCOS diagnosis. Interestingly, CD138+ percentages differed according to PCOS phenotype in the PE (p = 0.03). On the other hand, the receptivity status had no impact on the cell percentages in RIF samples. ConclusionOur findings emphasize the potential and accuracy of the AI algorithm in detecting endometrial CD138+ plasma cells, offering distinct advantages over manual inspection, such as rapid analysis of whole slide images, reduction of intra- and interobserver variations, sparing the valuable time of trained specialists, and consistent productivity. This supports the application of AI technology to help clinical decision-making, for example, in understanding endometrial cycle phase-related dynamics, as well as different reproductive disorders.

Risk Factors for Incident Polycystic Ovary Syndrome Diagnosis.

Objective: While highly prevalent, risk factors for incident polycystic ovary syndrome (PCOS) are poorly delineated. Using a population-based cohort, we sought to identify predictors of incident PCOS diagnosis. Materials and Methods: A matched case-control analysis was completed utilizing patients enrolled in Kaiser Permanente Washington from 2006 to 2019. Inclusion criteria included female sex, age 16-40 years, and ≥3 years of prior enrollment with ≥1 health care encounter. PCOS cases were identified using International Classification of Diseases codes. For each incident case (n = 2,491), 5 patients without PCOS (n = 12,455) were matched based on birth year and enrollment status. Potential risk factors preceding diagnosis included family history of PCOS, premature menarche, parity, race, weight gain, obesity, valproate use, metabolic syndrome, epilepsy, prediabetes, and types 1 and 2 diabetes. Potential risk factors for incident PCOS diagnosis were assessed with univariate and multivariable conditional logistic regressions. Results: Mean age of PCOS cases was 26.9 years (SD 6.8). PCOS cases, compared with non-PCOS, were more frequently nulliparous (70.9% versus 62.4%) and in the 3 years prior to index date were more likely to have obesity (53.8% versus 20.7%), metabolic syndrome (14.5% versus 4.3%), prediabetes (7.4% versus 1.6%), and type 2 diabetes (4.1% versus 1.7%) (p < 0.001 for all comparisons). In multivariable models, factors associated with higher risk for incident PCOS included the following: obesity (compared with nonobese) Class I-II (body-mass index [BMI], 30-40 kg/m2; odds ratio [OR], 3.8; 95% confidence interval [CI], 3.4-4.2), Class III (BMI > 40 kg/m2; OR, 7.5, 95% CI, 6.5-8.7), weight gain (compared with weight loss or maintenance) of 1-10% (OR, 1.7, 95% CI, 1.3-2.1), 10-20% (OR, 1.9; 95% CI, 1.5-2.4), and >20% (OR, 2.6; 95% CI, 1.9-3.6), prediabetes (OR, 2.7; 95% CI, 2.1-3.4), and metabolic syndrome (OR, 1.8: 95% CI, 1.5-2.1). Conclusion: Excess weight gain, obesity, and metabolic dysfunction may play a key role in the ensuing phenotypic expression of PCOS. Treatment and prevention strategies targeted at preventing weight gain in early reproductive years may help reduce the risk of this syndrome.

Comparative analysis of clinical symptoms and biochemical alterations in women with polycystic ovary syndrome: assessing the impact of type 1 diabetes versus non-diabetic controls

BackgroundWomen with type 1 diabetes depend on insulin injections throughout their life. However, the recommendation for strict metabolic control of diabetes requires the administration of supra-physiological doses of insulin, which might result in insulin-mediated stimulation of androgen synthesis. Hyperandrogenism in women with type 1 diabetes may be associated with polycystic ovary syndrome (PCOS). This study was performed to investigate PCOS and its associated clinical symptoms and biochemical alterations in women with type 1 diabetes in the Palestinian Territories. This retrospective cohort study consists of 50 women with type 1 diabetes and 50 apparently healthy non-diabetic controls. Questionnaire interviews were conducted. The diagnosis of PCOS was based on chronic anovulation and biochemical evidence of hyperandrogenism. Serum total testosterone, follicle-stimulating hormone (FSH), luteinizing hormone (LH), and insulin were measured by ELISA.ResultsThe mean waist-to-hip ratio and age at menarche were significantly higher in diabetic women than in non-diabetic controls (81.9 ± 7.9 and 13.9 ± 1.6 years vs. 78.8 ± 5.7 and 13.2 ± 1.2 years, and P = 0.045, P = 0.020, respectively). Oligomenorrhea, acanthosis nigricans, seborrhea, and hirsutism were more frequent in diabetics. The levels of total testosterone and insulin were significantly higher in diabetics (0.58 ± 0.11 ng/ml and 15.8 ± 12.4 mlU/ml vs. 0.44 ± 0.11 ng/ml and 10.8 ± 4.5 mlU/ml, P < 0.001 and P = 0.010, respectively). PCOS was present in 11 (22.0%) of diabetic women compared to 3 (6.0%) in non-diabetics (P = 0.044). Diabetic women with PCOS received higher doses of insulin than non-PCOS women (72.7 ± 23.9 vs. 55.0 ± 19.8 UI.cc/ml/day, P = 0.023). PCOS women showed more frequent oligomenorrhea (100% vs. 15.4%, P < 0.001) and higher levels of total testosterone and insulin (0.64 ± 0.09 and 23.1 ± 13.0 vs. 0.53 ± 0.11 and 14.1 ± 11.8, P = 0.023 and P = 0.041, respectively). PCOS cases were significantly more frequent in diabetic women receiving intensive insulin therapy than their counterparts with non-intensive insulin therapy (40.9% vs. 7.1%, P = 0.012).ConclusionIntensive insulin treatment in type 1 diabetes potentiates the development of PCOS and its related clinical and biochemical features particularly oligomenorrhea, hyperinsulinemia, and hyperandrogenemia.

Adolescents diagnosed with polycystic ovary syndrome under the Rotterdam criteria but not meeting the diagnosis under the updated guideline.

What are the characteristics of adolescents diagnosed with polycystic ovary syndrome (PCOS) based on the 2003 Rotterdam criteria, but who do not meet the diagnosis according to the international evidence-based guideline? Adolescents who had features of PCOS but did not meet the evidence-based guideline adolescent criteria exhibited unfavorable metabolic profiles compared to controls and shared considerable metabolic and hormonal features with adolescents who did meet the adolescent criteria. The international evidence-based PCOS guideline recommended that ultrasound should not be used for the diagnosis of PCOS in girls with a gynecological age of <8 years. Thus far, few studies have evaluated the clinical characteristics of the girls diagnosed with PCOS based on the Rotterdam criteria but who do not meet the diagnosis according to the updated guideline. This is a retrospective study, and subjects attended for care from 2004 to 2022. Adolescent girls with PCOS diagnosed according to the 2003 Rotterdam criteria and healthy controls. All participants were between 2 and 8 years since menarche. Of the 315 girls diagnosed with PCOS according to the Rotterdam criteria, those with irregular menstruation (IM)/hyperandrogenism (HA)/polycystic ovary (PCO), IM/HA, HA/PCO, and IM/PCO phenotypes accounted for 206 (65.4%), 30 (9.5%), 12 (3.8%), and 67 (21.3%) participants, respectively. According to the evidence-based guideline, 79 girls (25.1%) with the HA/PCO or IM/PCO phenotypes were not diagnosed with PCOS, and aligned to the international guideline; they were designated as the 'at-risk' group. As expected, the girls meeting the evidence-based guideline adolescent criteria showed the worst metabolic profiles (degree of generalized or central obesity, frequency of insulin resistance, prediabetes or diabetes, and metabolic syndrome) and higher hirsutism scores than the at-risk group or controls. Approximately 90% of the at-risk group were not overweight or obese, which was similar to the controls. However, they showed worse metabolic profiles, with higher blood pressure, triglyceride, and insulin resistance parameters than controls; furthermore, these profiles were similar to those of the girls meeting the adolescent criteria. The at-risk group showed similarly elevated serum LH levels and LH/FSH ratio with the girls meeting adolescent criteria. We could not evaluate hormonal or ultrasound parameters in controls. Compared to the conventional Rotterdam criteria, the recent international evidence-based guideline-avoiding ultrasound in PCOS diagnosis in adolescents-still gives the opportunity to identify young girls at risk, aligned to the findings in this study. A practical approach to this adolescent population would involve establishing IM or HA (with ultrasound not indicated) and designating 'at-risk' PCOS status with regular check-ups for newly developed or worsening PCOS-related symptoms or metabolic abnormalities, with subsequent reassessment including ultrasound or anti-Müllerian hormone, once 8 years post-menarche. No funding was received in support of this study. The authors have no conflicts of interest to disclose. N/A.

PCOS phenotype focus: phenotype D under the magnifying glass.

Polycystic ovary syndrome (PCOS) is defined as the combination of polycystic morphology, hyperandrogenism, and ovulatory disruption; this heterogeneity presents a conundrum for the medical community. The Rotterdam criteria have governed the diagnosis of PCOS, separating the patient cohort into four distinct phenotypes. It has been suggested that the lone normoandrogenic phenotype, so-called phenotype D, should not be classified as a PCOS subtype, with phenotypes A, B, and C displaying a hyperandrogenic biochemical and clinical profile thought to be characteristic of PCOS. To understand how to treat phenotype D patients, this review shines a spotlight on the phenotype, gathering various reports of how phenotype D is differentiated from the other PCOS phenotypes.