BACKGROUND: Placental site nodules (PSNs) are benign tumor-like growths that develop from chorionic-type intermediate trophoblastic cells. Their clinical significance is unknown. This study aims to determine the risk factors associated with PSNs, with focus on possible reproductive impact.
METHODS: We performed a retrospective case series of all patients with a pathology diagnosis of PSN in a large urban hospital system from 2018 to 2022. We collected clinical variables such as pathology diagnosis/description, presenting symptoms, method of prior delivery, and prior history of infertility, pregnancy loss, and uterine instrumentation.
RESULTS: A total of 32 patients were included in this case series. The most common presenting symptom was abnormal uterine bleeding (40.6%, 13/32). Recurrent pregnancy loss (RPL) (15.6%, 5/32) and infertility (15.6%, 5/32) were common presenting symptoms as well. 62.5% (20/32) patients had a history of prior uterine instrumentation. Coexisting chronic endometritis was identified in 9.4% (3/32) of cases. Of the 5 RPL/infertility patients who underwent hysteroscopic resection of a PSN, 1 achieved a live birth.
CONCLUSIONS: PSNs may be associated with abnormal uterine bleeding, recurrent pregnancy loss, infertility, history of prior uterine instrumentation, and chronic endometritis. Although a rare diagnosis, the presence of a PSN should be considered in patients presenting for infertility or recurrent pregnancy loss workup.

UNASSIGNED: Recurrent pregnancy loss (RPL) frequently links to a prolonged endometrial receptivity (ER) window, leading to the implantation of non-viable embryos. Existing ER assessment methods face challenges in reliability and invasiveness. Radiomics in medical imaging offers a non-invasive solution for ER analysis, but complex, non-linear radiomic-ER relationships in RPL require advanced analysis. Machine learning (ML) provides precision for interpreting these datasets, although research in integrating radiomics with ML for ER evaluation in RPL is limited.
UNASSIGNED: To develop and validate an ML model that employs radiomic features derived from multimodal transvaginal ultrasound images, focusing on improving ER evaluation in RPL.
UNASSIGNED: This retrospective, controlled study analyzed data from 346 unexplained RPL patients and 369 controls. The participants were divided into training and testing cohorts for model development and accuracy validation, respectively. Radiomic features derived from grayscale (GS) and shear wave elastography (SWE) images, obtained during the window of implantation, underwent a comprehensive five-step selection process. Five ML classifiers, each trained on either radiomic, clinical, or combined datasets, were trained for RPL risk stratification. The model demonstrating the highest performance in identifying RPL patients was selected for further validation using the testing cohort. The interpretability of this optimal model was augmented by applying Shapley additive explanations (SHAP) analysis.
UNASSIGNED: Analysis of the training cohort (242 RPL, 258 controls) identified nine key radiomic features associated with RPL risk. The extreme gradient boosting (XGBoost) model, combining radiomic and clinical data, demonstrated superior discriminatory ability. This was evidenced by its area under the curve (AUC) score of 0.871, outperforming other ML classifiers. Validation in the testing cohort of 215 subjects (104 RPL, 111 controls) confirmed its accuracy (AUC: 0.844) and consistency. SHAP analysis identified four endometrial SWE features and two GS features, along with clinical variables like age, SAPI, and VI, as key determinants in RPL risk stratification.
UNASSIGNED: Integrating ML with radiomics from multimodal endometrial ultrasound during the WOI effectively identifies RPL patients. The XGBoost model, merging radiomic and clinical data, offers a non-invasive, accurate method for RPL management, significantly enhancing diagnosis and treatment.

It has been recognized that oxidative stress (OS) is implicated in the etiology of recurrent pregnancy loss (RPL), yet the biomarkers reflecting oxidative stress in association with RPL remain scarce. The dataset GSE165004 was retrieved from the Gene Expression Omnibus (GEO) database. From the GeneCards database, a compendium of 789 genes related to oxidative stress-related genes (OSRGs) was compiled. By intersecting differentially expressed genes (DEGs) in normal and RPL samples with OSRGs, differentially expressed OSRGs (DE-OSRGs) were identified. In addition, four machine learning algorithms were employed for the selection of diagnostic markers for RPL. The Receiver Operating Characteristic (ROC) curves for these genes were generated and a predictive nomogram for the diagnostic markers was established. The functions and pathways associated with the diagnostic markers were elucidated, and the correlations between immune cells and diagnostic markers were examined. Potential therapeutics targeting the diagnostic markers were proposed based on data from the Comparative Toxicogenomics Database and ClinicalTrials.gov. The candidate biomarker genes from the four models were further validated in RPL tissue samples using RT-PCR and immunohistochemistry. A set of 20 DE-OSRGs was identified, with 4 genes (KRAS, C2orf69, CYP17A1, and UCP3) being recognized by machine learning algorithms as diagnostic markers exhibiting robust diagnostic capabilities. The nomogram constructed demonstrated favorable predictive accuracy. Pathways including ribosome, peroxisome, Parkinson\'s disease, oxidative phosphorylation, Huntington\'s disease, and Alzheimer\'s disease were co-enriched by KRAS, C2orf69, and CYP17A1. Cell chemotaxis terms were commonly enriched by all four diagnostic markers. Significant differences in the abundance of five cell types, namely eosinophils, monocytes, natural killer cells, regulatory T cells, and T follicular helper cells, were observed between normal and RPL samples. A total of 180 drugs were predicted to target the diagnostic markers, including C544151, D014635, and CYP17A1. In the validation cohort of RPL patients, the LASSO model demonstrated superiority over other models. The expression levels of KRAS, C2orf69, and CYP17A1 were significantly reduced in RPL, while UCP3 levels were elevated, indicating their suitability as molecular markers for RPL. Four oxidative stress-related diagnostic markers (KRAS, C2orf69, CYP17A1, and UCP3) have been proposed to diagnose and potentially treat RPL.

OBJECTIVE: Recurrent pregnancy loss (RPL) represents a common disorder with consequences on family and society. As more than half of the RPL cases do not have a clearly identified cause, uncovering the mechanisms behind the idiopathic RPL is urgently needed.
METHODS: Using label-free data-independent LC-MS/MS acquisition coupled with ion mobility, we compared the proteome of chorionic villi from 13 RPL cases with 10 age and gestational week-matched elective pregnancies. Transcriptional levels of selected candidate biomarkers were determined in chorionic villi of 35 RPL cases and 25 controls using quantitative polymerase chain reaction (qPCR).
RESULTS: Statistically significant difference in abundance (Benjamini-Hochberg [B-H] p ≤ 0.05) and fold change ≥1.5 showed 128 proteins. Bioinformatics analysis identified complement and coagulation cascades, platelet activation, tricarboxylic acid cycle (TCA) cycle, and ferroptosis as pathways with the highest significance. Correlation with transcriptome datasets revealed a weak statistically significant positive correlation with 45% of the co-differentially expressed proteins/genes displaying the same regulation trend. The transcription levels of neurofilament light polypeptide (NEFL), dihydrolipoyllysine-residue succinyltransferase component of 2-oxoglutarate dehydrogenase complex_mitochondrial (DLST), nitric oxide synthase 3 (NOS3), and ceruloplasmin (CP) were significantly increased in the RPL, consistent with the proteomics findings.
CONCLUSIONS: Our data suggests alteration of several pathways as potential causes of idiopathic RPL from the fetal side and opens the way for investigations concerning clinical management.

OBJECTIVE: Could the risk of subsequent pregnancy loss be predicted based on the risk factors of recurrent pregnancy loss (RPL) patients?
CONCLUSIONS: A nomogram, constructed from independent risk factors identified through multivariate logistic regression, serves as a reliable tool for predicting the likelihood of subsequent pregnancy loss in RPL patients.
BACKGROUND: Approximately 1-3% of fertile couples experience RPL, with over half lacking a clear etiological factor. Assessing the subsequent pregnancy loss rate in RPL patients and identifying high-risk groups for early intervention is essential for pregnancy counseling. Previous prediction models have mainly focused on unexplained RPL, incorporating baseline characteristics such as age and the number of previous pregnancy losses, with limited inclusion of laboratory and ultrasound indicators.
METHODS: The retrospective study involved 3387 RPL patients who initially sought treatment at the Reproductive Immunology Clinic of Renji Hospital, Shanghai Jiao Tong University School of Medicine, between 1 January 2020 and 31 December 2022. Of these, 1153 RPL patients met the inclusion criteria and were included in the analysis.
METHODS: RPL was defined as two or more pregnancy losses (including biochemical pregnancy loss) with the same partner before 28 weeks of gestation. Data encompassing basic demographics, laboratory indicators (autoantibodies, peripheral immunity coagulation, and endocrine factors), uterine and endometrial ultrasound results, and subsequent pregnancy outcomes were collected from enrolled patients through initial questionnaires, post-pregnancy visits fortnightly, medical data retrieval, and telephone follow-up for lost patients. R software was utilized for data cleaning, dividing the data into a training cohort (n = 808) and a validation cohort (n = 345) in a 7:3 ratio according to pregnancy success and pregnancy loss. Independent predictors were identified through multivariate logistic regression. A nomogram was developed, evaluated by 10-fold cross-validation, and compared with the model incorporating solely age and the number of previous pregnancy losses. The constructed nomogram was evaluated using the AUC, calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CICA). Patients were then categorized into low- and high-risk subgroups.
RESULTS: We included age, number of previous pregnancy losses, lupus anticoagulant, anticardiolipin IgM, anti-phosphatidylserine/prothrombin complex IgM, anti-double-stranded DNA antibody, arachidonic acid-induced platelet aggregation, thrombin time and the sum of bilateral uterine artery systolic/diastolic ratios in the nomogram. The AUCs of the nomogram were 0.808 (95% CI: 0.770-0.846) in the training cohort and 0.731 (95% CI: 0.660-0.802) in the validation cohort, respectively. The 10-fold cross-validated AUC ranged from 0.714 to 0.925, with a mean AUC of 0.795 (95% CI: 0.750-0.839). The AUC of the nomogram was superior compared to the model incorporating solely age and the number of previous pregnancy losses. Calibration curves, DCAs, and CICAs showed good concordance and clinical applicability. Significant differences in pregnancy loss rates were observed between the low- and high-risk groups (P < 0.001).
CONCLUSIONS: This study was retrospective and focused on patients from a single reproductive immunology clinic, lacking external validation data. The potential impact of embryonic chromosomal abnormalities on pregnancy loss could not be excluded, and the administration of medication to all cases impacted the investigation of risk factors for pregnancy loss and the model\'s predictive efficacy.
CONCLUSIONS: This study signifies a pioneering effort in developing and validating a risk prediction nomogram for subsequent pregnancy loss in RPL patients to effectively stratify their risk. We have integrated the nomogram into an online web tool for clinical applications.
BACKGROUND: This study was supported by the National Natural Science Foundation of China (82071725). All authors have no competing interests to declare.
BACKGROUND: N/A.

UNASSIGNED: Unexplained recurrent pregnancy loss (URPL) is a clinical dilemma in reproductive fields. Its diagnosis is mainly exclusionary after extensive clinical examination, and some of the patients may still face the risk of miscarriage.
UNASSIGNED: We analyzed follicular fluid (FF) from in vitro fertilization (IVF) in eight patients with URPL without endocrine abnormalities or verifiable causes of abortion and eight secondary infertility controls with no history of pregnancy loss who had experienced at least one normal pregnancy and delivery by direct data-independent acquisition (dDIA) quantitative proteomics to identify differentially expressed proteins (DEPs). In this study, bioinformatics analysis was performed using online software including g:profiler, String, and ToppGene. Cytoscape was used to construct the protein-protein interaction (PPI) network, and ELISA was used for validation.
UNASSIGNED: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEPs are involved in the biological processes (BP) of complement and coagulation cascades. Apolipoproteins (APOs) are key proteins in the PPI network. ELISA confirmed that APOB was low-expressed in both the FF and peripheral blood of URPL patients.
UNASSIGNED: Dysregulation of the immune network intersecting coagulation and inflammatory response is an essential feature of URPL, and this disequilibrium exists as early as the oogenesis stage. Therefore, earlier intervention is necessary to prevent the development of URPL. Moreover, aberrant lipoprotein regulation appears to be a key factor contributing to URPL. The mechanism by which these factors are involved in the complement and coagulation cascade pathways remains to be further investigated, which also provides new candidate targets for URPL treatment.

Recurrent pregnancy loss is a reproductive disorder affecting about 1 to 5 % of pregnant women worldwide that requires our attention, especially considering that about 50 % of cases are idiopathic. The present study is focused on testing a possible association between extreme skewed X-chromosome inactivation patterns and/or shortened telomeres with idiopathic cases since both are considered non-consensual potential causes underlying recurrent pregnancy loss in the scientific community. For this purpose, two groups of women were analyzed and compared: a group of women with idiopathic recurrent pregnancy loss and a second group of age-matched women with proven fertility, and both X-chromosome inactivation patterns and telomere length were measured and compared from maternal DNA extracted from peripheral blood. Our data showed no statistically significant differences between groups, suggesting no association between extreme skewed X-chromosome inactivation or shortened telomeres with recurrent pregnancy losses. Additionally, the effect of maternal age on both X-chromosome inactivation pattern and telomere length was tested, but no significant correlation was observed between advanced maternal age and extreme skewed X-chromosome inactivation or telomere shortening. This study represents one more valid contribution to the investigation of causes underlying recurrent pregnancy loss suggesting that, new variables may be considered since the pattern of X-chromosome inactivation and telomere length do not seem to be related to this reproductive disorder. Briefly, considering its clinical relevance, it is mandatory a continuous effort in the scientific community to cover new potential recurrent pregnancy loss-related causes.

OBJECTIVE: PGT-A to deselect aneuploid embryos in ART cycles may hold promise by augmenting pregnancy rates per transfer and reducing pregnancy loss rates for patients with unexplained recurrent pregnancy loss.
OBJECTIVE: To explore effectiveness of PGT-A in managing unexplained recurrent pregnancy loss by evaluating several key aspects: (i) the likelihood of a live birth in a subsequent spontaneous pregnancy, (ii) whether women with unexplained recurrent pregnancy loss have higher rate of aneuploidy, (iii) whether euploid blastocysts offer comparable live birth rate in patients with unexplained recurrent pregnancy loss, (iv) whether the endometrium is less selective in unexplained recurrent pregnancy loss, and (v) whether PGT-A increases live birth rate or reduces pregnancy losses until delivery.
METHODS: PubMed and Cochrane Library databases were searched from inception until June 2024.
UNASSIGNED: Studies involving patients with ≥2 unexplained recurrent pregnancy loss, who underwent ART with or without PGT-A, or expectant management were included.
METHODS: The primary outcome measure was the live birth rate. Secondary outcome measures were aneuploidy rate, clinical pregnancy rate, and clinical pregnancy loss rate.
RESULTS: Whether couples with unexplained recurrent pregnancy loss have higher embryo aneuploidy rates remains equivocal. Euploid blastocyst transfers yielded comparable clinical pregnancy loss rate (OR:1.10, 95%CI:0.57-2.13), and live birth rate (OR:1.04, 95%CI: 0.74-1.44) in patients with and without unexplained recurrent pregnancy loss. Comprehensive chromosome analysis of products of conception shows similar aneuploidy rates between patients with and without recurrent pregnancy loss and does not support less selective endometrium hypothesis. PGT-A decreased clinical pregnancy loss rate (OR: 0.42, 95% CI: 0.27-0.67) and enhanced live birth rate per transfer (OR: 2.17, 95% CI: 1.77-2.65) and live birth rate per patient (OR: 1.85, 95% CI: 1.18-2.91) in unexplained recurrent pregnancy loss patients.
CONCLUSIONS: Current low-quality evidence suggests that PGT-A enhances live birth rate per transfer and per patient in unexplained recurrent pregnancy loss. Well-designed randomized controlled trials comparing ART with-PGT-A versus expectant management for unexplained recurrent pregnancy loss are warranted.

Endometriosis, infertility, or recurrent pregnancy loss (RPL) are entities characterised by a decrease in Lactobacillus spp. and an increase in bacterial vaginosis-associated bacteria, (BVAV) according with 16S rRNA sequencing studies. However, the use of nucleic acid amplification tests (NAAT) as a tool for diagnosis algorithms is unknown. Seventy-four patients were included, with a median age of 36.5 years old (IQR: 34-39) including infertility (n=31), endometriosis (n=25), or RPL (n=18), for culturing and NAAT using the Allplex™ Bacterial Vaginosis Plus (ABVP) assay (SeegeneⓇ) with endometrial samples. The objective was determining the utility of ABVP assay for diagnosing the entities. Forty-six microorganisms were isolated from 31 out of 74 patients (41.9 %). Twenty-five endometrial samples (33.8 %) were positive for some targets included in the ABVP-assay, with median Ct value ∼37 (IQR: 31.3-37.1) and Qt value 1.43 Log10copies/reaction (IQR:1.1-2.6). For Lactobacillus species, sensitivity and specificity were 80 % and 84 %, respectively. Gardnerella vaginalis, 63.6 % and 95.7 %. No significant increase in BVAV was detected in any of the gynaecological entities. The ABVP and culture based algorithm did not show utility as a tool for endometriosis, infertility, or RPL diagnosis.

BACKGROUND: Patients with previous recurrent pregnancy loss are subject to increased maternal anxiety and reduced antenatal attachment during the subsequent pregnancy. Maternal anxiety is associated with worse pregnancy and neonatal outcomes. Home ultrasound is a feasible tool with the potential to alleviate maternal anxiety by ensuring fetal well-being.
OBJECTIVE: This study aimed to investigate the impact of complementing standard prenatal care with twice-weekly telemedicine visits incorporating home ultrasound on maternal anxiety and antenatal attachment in individuals with a history of recurrent pregnancy loss.
METHODS: In this randomized controlled trial, patients with a history of 2 or more prior abortions were randomized early in their subsequent pregnancy in a 1:1 ratio into either the control group, which received standard high-risk prenatal care, or the study group, which received additional twice-weekly home-ultrasound sessions. The home-ultrasound scans assessed fetal pulse, movements, and amniotic fluid volume, aiming to provide maternal reassurance. Patients performed the scans themselves using the Pulsenmore device, with real-time guidance from a physician. Maternal anxiety was assessed using the validated State-Trait Anxiety Inventory Scale (STAI-S) and the Revised Prenatal Distress Questionnaire (NuPDQ), while maternal attachment was measured with the validated Maternal Antenatal Attachment Scale (MAAS-2) at 3 time points during pregnancy. The primary outcome was the STAI-S score at the final prenatal visit. A sample size of 50 patients was calculated to detect a 20% difference in the primary outcome.
RESULTS: Of the 57 patients recruited, 50 completed the follow-up, 25 in each group. There were no significant differences in demographics between the groups. The primary outcome (STAI score at the last visit) was significantly lower in the device group compared to the control group (P=.037). In addition, the study group exhibited a greater reduction in STAI scores between the first and last visits (P=.045), and a significantly higher MAAS score at the end of the follow-up period (P=.046).
CONCLUSIONS: Integrating routine home-ultrasound telemedicine visits into prenatal care can significantly reduce maternal anxiety during pregnancy and contribute to greater maternal attachment in individuals with a history of recurrent pregnancy loss. These results emphasize the potential benefits of home ultrasound as a tool to alleviate anxiety, provide a sense of control, and foster a deeper maternal connection among pregnant individuals who have experienced previous pregnancy loss.