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Nuffield Department of Women's & Reproductive Health sits within the Medical Sciences Division of the University of Oxford. The department encompasses multi-disciplinary research across four overarching themes; Cancer, Global Health, Maternal & Fetal Health and Reproductive Medicine & Genetics
Development and validation of prediction models for fetal growth restriction and birthweight: an individual participant data meta-analysis.
BACKGROUND: Fetal growth restriction is associated with perinatal morbidity and mortality. Early identification of women having at-risk fetuses can reduce perinatal adverse outcomes. OBJECTIVES: To assess the predictive performance of existing models predicting fetal growth restriction and birthweight, and if needed, to develop and validate new multivariable models using individual participant data. DESIGN: Individual participant data meta-analyses of cohorts in International Prediction of Pregnancy Complications network, decision curve analysis and health economics analysis. PARTICIPANTS: Pregnant women at booking. External validation of existing models (9 cohorts, 441,415 pregnancies); International Prediction of Pregnancy Complications model development and validation (4 cohorts, 237,228 pregnancies). PREDICTORS: Maternal clinical characteristics, biochemical and ultrasound markers. PRIMARY OUTCOMES: fetal growth restriction defined as birthweight <10th centile adjusted for gestational age and with stillbirth, neonatal death or delivery before 32 weeks' gestation birthweight. ANALYSIS: First, we externally validated existing models using individual participant data meta-analysis. If needed, we developed and validated new International Prediction of Pregnancy Complications models using random-intercept regression models with backward elimination for variable selection and undertook internal-external cross-validation. We estimated the study-specific performance (c-statistic, calibration slope, calibration-in-the-large) for each model and pooled using random-effects meta-analysis. Heterogeneity was quantified using τ2 and 95% prediction intervals. We assessed the clinical utility of the fetal growth restriction model using decision curve analysis, and health economics analysis based on National Institute for Health and Care Excellence 2008 model. RESULTS: Of the 119 published models, one birthweight model (Poon) could be validated. None reported fetal growth restriction using our definition. Across all cohorts, the Poon model had good summary calibration slope of 0.93 (95% confidence interval 0.90 to 0.96) with slight overfitting, and underpredicted birthweight by 90.4 g on average (95% confidence interval 37.9 g to 142.9 g). The newly developed International Prediction of Pregnancy Complications-fetal growth restriction model included maternal age, height, parity, smoking status, ethnicity, and any history of hypertension, pre-eclampsia, previous stillbirth or small for gestational age baby and gestational age at delivery. This allowed predictions conditional on a range of assumed gestational ages at delivery. The pooled apparent c-statistic and calibration were 0.96 (95% confidence interval 0.51 to 1.0), and 0.95 (95% confidence interval 0.67 to 1.23), respectively. The model showed positive net benefit for predicted probability thresholds between 1% and 90%. In addition to the predictors in the International Prediction of Pregnancy Complications-fetal growth restriction model, the International Prediction of Pregnancy Complications-birthweight model included maternal weight, history of diabetes and mode of conception. Average calibration slope across cohorts in the internal-external cross-validation was 1.00 (95% confidence interval 0.78 to 1.23) with no evidence of overfitting. Birthweight was underestimated by 9.7 g on average (95% confidence interval -154.3 g to 173.8 g). LIMITATIONS: We could not externally validate most of the published models due to variations in the definitions of outcomes. Internal-external cross-validation of our International Prediction of Pregnancy Complications-fetal growth restriction model was limited by the paucity of events in the included cohorts. The economic evaluation using the published National Institute for Health and Care Excellence 2008 model may not reflect current practice, and full economic evaluation was not possible due to paucity of data. FUTURE WORK: International Prediction of Pregnancy Complications models' performance needs to be assessed in routine practice, and their impact on decision-making and clinical outcomes needs evaluation. CONCLUSION: The International Prediction of Pregnancy Complications-fetal growth restriction and International Prediction of Pregnancy Complications-birthweight models accurately predict fetal growth restriction and birthweight for various assumed gestational ages at delivery. These can be used to stratify the risk status at booking, plan monitoring and management. STUDY REGISTRATION: This study is registered as PROSPERO CRD42019135045. FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/148/07) and is published in full in Health Technology Assessment; Vol. 28, No. 14. See the NIHR Funding and Awards website for further award information.
Initial experience of ureteric visualization using methylene blue during laparoscopy for gynecological surgery.
OBJECTIVES: Iatrogenic ureteral injury is a severe surgical complication, with a highest incidence of 1.5% in gynecological surgeries. The purpose of this report is to document our initial experience with using methylene blue (MB) to label the ureter in gynecological laparoscopic surgeries and to explore its effectiveness and safety. This is also a novel description of simultaneously visualizing ureteral MB fluorescence and sentinel lymph nodes (SLN's) Indocyanine Green (ICG) fluorescence using the same camera. METHODS: This study included patients undergoing gynecological laparoscopic surgeries, with the same surgeon performing all cases. During the early stages of each surgery, rapid intravenous infusion of MB was administered. For cases requiring SLN imaging, we also injected ICG solution into the cervix. Assessment of the included cases was conducted both intraoperatively and postoperatively. The group that had MB fluorescence (Group A) was compared to a control group that did not have it (Group B). RESULTS: A total of 25 patients (Group A) received MB during surgery, demonstrating 45 ureters clearly, with an imaging success rate of 90%. Continuous and clearer fluorescence imaging was achieved in cases with ureteral hydronephrosis. In most patients, ureteral fluorescence was visible 15-20 min after intravenous infusion of MB, and 64% still exhibited fluorescence at the end of the surgery. In patients who had both ICG and MB, dual fluorescence imaging was achieved clearly. Among the included cases, there were no iatrogenic ureteral injuries (0%), which we observed to be lower than in patients who did not receive MB (1.3%). The rate of adverse events was similar in both groups. CONCLUSION: Using MB fluorescence is an effective and safe method of visualizing the ureters during gynecological surgeries, and can diminish iatrogenic ureteral injury without increased associated adverse events. It therefore may offer promising prospects for clinical application.
Effect of AMH on primordial follicle populations in mouse ovaries and human pre-pubertal ovarian xenografts during doxorubicin treatment
Introduction: Survival rates of the childhood cancer patients are improving, however cancer treatments such as chemotherapy may lead to infertility due to loss of the primordial follicle (PMF) reserve. Doxorubicin (DXR) is a gonadotoxic chemotherapy agent commonly used in childhood cancers. Anti-Müllerian Hormone (AMH) has been reported to have a protective effect on the mouse ovarian reserve against DXR in vivo. However, whether AMH can prevent PMF loss in conjunction with DXR in human ovarian tissue in vivo has not been determined. Methods: In order to investigate this, we first established an optimum dose of DXR that induced PMF loss in cultured mouse ovaries and investigated the efficacy of AMH on reducing DXR-induced PMF loss in mice in vitro. Second, we investigated the effects of DXR on pre-pubertal human ovarian tissue and the ability of AMH to prevent DXR-induced damage comparing using a mouse xenograft model with different transplantation sites. Results: Mouse ovaries treated with DXR in vitro and in vivo had reduced PMF populations and damaged follicle health. We did not observe effect of DXR-induced PMF loss or damage to follicle/stromal health in human ovarian cortex, this might have been due to an insufficient dose or duration of DXR. Although AMH does not prevent DXR-induced PMF loss in pre-pubertal and adult mouse ovaries, in mouse ovaries treated with higher concentration of AMH in vitro, DXR did not cause a significant loss in PMFs. This is the first study to illustrate an effect of AMH on DXR-induced PMF loss on pre-pubertal mouse ovaries. However, more experiments with higher doses of AMH and larger sample size are needed to confirm this finding. Discussion: We did not observe that AMH could prevent DXR-induced PMF loss in mouse ovaries in vivo. Further studies are warranted to investigate whether AMH has a protective effect against DXR in xenotransplanted human ovarian tissue. Thus, to obtain robust evidence about the potential of AMH in fertility preservation during chemotherapy treatment, alternative AMH administration strategies need to be explored alongside DXR administration to fully interrogate the effect of DXR and AMH on human xenografted tissues.
Cardiophrenic lymph node metastasis as the sole presentation of high grade serous ovarian carcinoma.
KEY CLINICAL MESSAGE: Cardiophrenic metastasis is typically a late stage manifestation of ovarian high grade serous carcinoma. Here we present a case where this was the sole presentation of this disease. This case challenges our current understanding of the natural course of ovarian high grade serous carcinoma. ABSTRACT: Ovarian cancer is typically described to spread from its primary site within the fallopian tubes or ovaries into the peritoneal cavity and beyond with cardiophrenic lymph node involvement being considered a late stage disease process. Here we present the case of a lady in her 60s where increased metabolic activity of the cardiophrenic lymph node was picked up in the investigation of an adenocarcinoma of the lung. Post-thoracoscopic resection histopathological analysis of this lymph node showing an epithelial structure with positive immunohistochemical markers PAX8, WT1, ER, and p16 with a p53 wild type-pattern were the sole presenting features of a high grade serous ovarian carcinoma, that was otherwise undetectable by radiological or hematological screening. Only histopathological analysis after modified radical hysterectomy in gynae-oncological fashion were able to identify a 4 mm lesion within the left fallopian tube. This case questions our current understanding of the natural history of ovarian carcinomas.
Deep Facial Phenotyping with Mixup Augmentation
The classification of genetic disorders from face images has the potential to assist with early diagnosis and effective treatment. A key objective in this field is to enhance the accuracy and robustness of deep learning models in classifying genetic disorders from face images for disorders that are not represented in the training data. In this paper, we propose the use of input mixup augmentation to improve few-shot classification performance on this task. Furthermore, we present a specialised version of mixup that warps together face images using face keypoints, and show that this improves performance further. The motivation for using keypoint guided mixup is to align face structure and produce an intermediate image between two disorders. We compare the performance of our proposed method with the baseline model and demonstrate significant improvements in accuracy, with a classification accuracy of 31.3% on the GMDB-Rare benchmark dataset. Our results show that incorporating input mixup augmentation and face keypoint-based mixup can enhance the ability of deep learning models to identify genetic disorders from face images, providing a promising approach for future research in this area.
The impact of COVID-19 on people with epilepsy: Global results from the coronavirus and epilepsy study.
OBJECTIVE: To characterize the experience of people with epilepsy and aligned healthcare workers (HCWs) during the first 18 months of the COVID-19 pandemic and compare experiences in high-income countries (HICs) with non-HICs. METHODS: Separate surveys for people with epilepsy and HCWs were distributed online in April 2020. Responses were collected to September 2021. Data were collected for COVID-19 infections, the effect of COVID-related restrictions, access to specialist help for epilepsy (people with epilepsy), and the impact of the pandemic on work productivity (HCWs). The frequency of responses for non-HICs and HICs were compared using non-parametric Chi-square tests. RESULTS: Two thousand one hundred and five individuals with epilepsy from 53 countries and 392 HCWs from 26 countries provided data. The same proportion of people with epilepsy in non-HICs and HICs reported COVID-19 infection (7%). Those in HICs were more likely to report that COVID-19 measures had affected their health (32% vs. 23%; p
[Analysis of the factors contributing to endometriosis in China and UK].
OBJECTIVE: To explore the differences in the factors associated with endometriosis between Chinese and British patients. METHODS: This case-control study was conducted in 387 patients with endometriosis and 199 non-endometriosis patients admitted to John Radcliffe Hospital (Oxford, UK) and in 101 patients with endometriosis and 50 non-endometriosis patients admitted in the First Affiliated Hospital of Guangzhou University of Chinese Medicine. The clinical data including height, weight, body mass index, marital status, employment, menstruation, fertility, and operation reasons were collected via a standardized WERF EPHect questionnaire. RESULTS: Multivariate logistic regression analysis indicated that body mass index, surgery for dysmenorrhea, history of pregnancy, counts of previous surgeries for endometriosis and status of employment were all significantly associated with endometriosis in the UK (P < 0.05), while a history of dysmenorrhea was significantly correlated with endometriosis in Chinese patients (P < 0.05). CONCLUSION: Dysmenorrhea may be the most important common factor associated with endometriosis in China and the UK, but the other factors contributing to endometriosis may differ between these two countries.
Calibrated Bayesian Neural Networks to Estimate Gestational Age and Its Uncertainty on Fetal Brain Ultrasound Images
© 2020, Springer Nature Switzerland AG. We present an original automated framework for estimating gestational age (GA) from fetal ultrasound head biometry plane images. A novelty of our approach is the use of a Bayesian Neural Network (BNN), which quantifies uncertainty of the estimated GA. Knowledge of estimated uncertainty is useful in clinical decision-making, and is especially important in ultrasound image analysis where image appearance and quality can naturally vary a lot. A further novelty of our approach is that the neural network is not provided with images pixel size, thus making it rely on anatomical appearance characteristics and not size. We train the network using 9,299 scans from the INTERGROWTH-21st[22] dataset ranging from weeks to weeks GA. We achieve average RMSE and MAE of 9.6 and 12.5 days respectively over the GA range. We explore the robustness of the BNN architecture to invalid input images by testing with (i) a different dataset derived from routine anomaly scanning and (ii) scans of a different fetal anatomy.
An integrated single-cell reference atlas of the human endometrium
AbstractThe complex and dynamic cellular composition of the human endometrium remains poorly understood. Previous endometrial single-cell atlases profiled few donors and lacked consensus in defining cell types. We introduce the Human Endometrial Cell Atlas (HECA), a high-resolution single-cell reference atlas (313,527 cells) combining published and new endometrial single-cell transcriptomics datasets of 63 women with and without endometriosis. HECA assigns consensus and identifies previously unreported cell types, mapped in situ using spatial transcriptomics and validated using a new independent single-nuclei dataset (312,246 nuclei, 63 donors). In the functionalis, we identify intricate stromal–epithelial cell coordination via transforming growth factor beta (TGFβ) signaling. In the basalis, we define signaling between fibroblasts and an epithelial population expressing progenitor markers. Integration of HECA with large-scale endometriosis genome-wide association study data pinpoints decidualized stromal cells and macrophages as most likely dysregulated in endometriosis. The HECA is a valuable resource for studying endometrial physiology and disorders, and for guiding microphysiological in vitro systems development.
Real-world assessment of the patient-centredness of endometriosis care: European countries benchmarked by patients.
European patients cross the borders of their countries to receive more patient-centred healthcare. Benchmarking across European countries for the patient-centredness of endometriosis care had yet to be performed. This study proved the factorial structure and reliability of translation of the ENDOCARE questionnaire in nine different languages. Moreover, the benchmark potential of the ENDOCARE questionnaire was shown by the significant between-country variance for case-mix-adjusted overall and dimensional patient-centredness scores, explaining 3-9% of the total variance in patient-centredness assessed across 10 European countries. Compared with the least patient-centred country, endometriosis care was more patient-centred in Denmark, Italy and Belgium. 'Reaching a diagnosis quickly' and 'physicians demarcating the endometriosis complexity level which they can treat' were consistently rated of more-than-average importance and were experienced negatively by more than half of the European sample. National and European policymakers and specialized clinics are prompted to monitor their patient-centredness and set up improvement projects.
Crimson clues: advancing endometriosis detection and management with novel blood biomarkers.
Endometriosis is an inflammatory condition affecting approximately 10% of the female-born population. Despite its prevalence, the lack of noninvasive biomarkers has contributed to an established global diagnostic delay. The intricate pathophysiology of this enigmatic disease may leave signatures in the blood, which, when detected, can be used as noninvasive biomarkers. This review provides an update on how investigators are utilizing the established disease pathways and innovative methodologies, including genome-wide association studies, next-generation sequencing, and machine learning, to unravel the clues left in the blood to develop blood biomarkers. Many blood biomarkers show promise in the discovery phase, but because of a lack of standardized and robust methodologies, they rarely progress to the development stages. However, we are now seeing biomarkers being validated with high diagnostic accuracy and improvements in standardization protocols, providing promise for the future of endometriosis blood biomarkers.