Should we be examining the ovaries in pregnancy? Prevalence and natural history of adnexal pathology detected at first-trimester sonography

ABSTRACT Objective To assess the prevalence and natural history of ovarian pathology in pregnancy. Method

Intra- and interobserver agreement with regard to describing adnexal masses using International Ovarian Tumor Analysis terminology: reproducibility study involving seven observers

To estimate intraobserver repeatability and interobserver agreement in assessing the presence of papillary projections in adnexal masses and in classifying adnexal masses using the International Ovarian Tumor Analysis terminology for ultrasound examiners with different levels of experience. We also aimed to identify ultrasound findings that cause confusion and might be interpreted differently by different observers, and to determine if repeatability and agreement change after consensus has been reached on how to interpret 'problematic' ultrasound images

Managing pregnancy of unknown location based on initial serum progesterone and serial serum hCG: development and validation of a two-step triage protocol.

A uniform rationalized management protocol for pregnancies of unknown location (PUL) is lacking. We developed a two-step triage protocol based on presenting serum progesterone (step 1) and hCG ratio two days later (step 2) to select PUL at high-risk of ectopic pregnancy (EP).Cohort study of 2753 PUL (301 EP), involving a secondary analysis of prospectively and consecutively collected PUL at two London-based university teaching hospitals. Using a chronological split we used 1449 PUL for development and 1304 for validation. We aimed to select PUL as low-risk with high confidence (high negative predictive value, NPV) while classifying most EP as high-risk (high sensitivity). The first triage step selects low-risk PUL at presentation using a serum progesterone threshold. The remaining PUL are triaged using a novel logistic regression risk model based on hCG ratio and initial serum progesterone (second step), defining low-risk as an estimated EP risk <5%.On validation, initial serum progesterone ≤2nmol/l (step 1) selected 16.1% PUL as low-risk. Second step classification with the risk model M6P selected an additional 46.0% of all PUL as low-risk. Overall, the two-step protocol classified 62.1% of PUL as low-risk, with an NPV of 98.6% and a sensitivity of 92.0%. When the risk model was used in isolation (i.e. without the first step), 60.5% of PUL were classified as low-risk with 99.1% NPV and 94.9% sensitivity.The two-step protocol can efficiently classify PUL into being at high or low risk of complications

A core outcome set for trials in miscarriage management and prevention: an international consensus development study.

OBJECTIVE: To develop core outcome sets (COS) for miscarriage management and prevention. DESIGN: Modified Delphi survey combined with a consensus development meeting. SETTING: International. POPULATION: Stakeholder groups included healthcare providers, international experts, researchers, charities and couples with lived experience of miscarriage from 15 countries: 129 stakeholders for miscarriage management and 437 for miscarriage prevention. METHODS: Modified Delphi method and modified nominal group technique. RESULTS: The final COS for miscarriage management comprises six outcomes: efficacy of treatment, heavy vaginal bleeding, pelvic infection, maternal death, treatment or procedure-related complications, and patient satisfaction. The final COS for miscarriage prevention comprises 12 outcomes: pregnancy loss <24 weeks' gestation, live birth, gestation at birth, pre-term birth, congenital abnormalities, fetal growth restriction, maternal (antenatal) complications, compliance with intervention, patient satisfaction, maternal hospitalisation, neonatal or infant hospitalisation, and neonatal or infant death. Other outcomes identified as important were mental health-related outcomes, future fertility and health economic outcomes. CONCLUSIONS: This study has developed two core outcome sets, through robust methodology, that should be implemented across future randomised trials and systematic reviews in miscarriage management and prevention. This work will help to standardise outcome selection, collection and reporting, and improve the quality and safety of future studies in miscarriage

The METEX study: Methotrexate versus expectant management in women with ectopic pregnancy: A randomised controlled trial

Background: Patients with ectopic pregnancy (EP) and low serum hCG concentrations and women with a pregnancy of unknown location (PUL) and plateauing serum hCG levels are commonly treated with systemic methotrexate (MTX). However, there is no evidence that treatment in these particular subgroups of women is necessary as many of these early EPs may resolve spontaneously. The aim of this study is whether expectant management in women with EP or PUL and with low but plateauing serum hCG concentrations is an alternative to MTX treatment in terms of treatment success, future pregnancy, health related quality of life and costs. Methods/Design: A multicentre randomised controlled trial in TheNetherlands. Hemodynamically stable patients with an EP visible on transvaginal ultrasound and a plateauing serum hCG concentration < 1,500 IU/L or with a persisting PUL with plateauing serum hCG concentrations < 2,000 IU/L are eligible for the trial. Patients with a viable EP, signs of tubal rupture/abdominal bleeding, or a contra-indication for MTX will not be included. Expectant management is compared with systemic MTX in a single dose intramuscular regimen (1 mg/ kg) in an outpatient setting. Serum hCG levels are monitored weekly; in case of inadequately declining, systemic MTX is installed or continued. In case of hemodynamic instability and/or signs of tubal rupture, surgery is performed. The primary outcome measure is an uneventful decline of serum hCG to an undetectable level by the initial intervention. Secondary outcomes are (re)interventions (additional systemic MTX injections and/or surgery), treatment complications, health related quality of life, financial costs, and future fertility. Analysis is performed according to the intention to treat principle. Quality of life is assessed by questionnaires before and at three time points after randomisation. Costs are expressed as direct costs with data on costs and used resources in the participating centres. Fertility is assessed by questionnaires after 6, 12, 18 and 24 months. Patients' preferences will be assessed using a discrete choice experiment. Discussion: This trial will provide guidance on the present management dilemmas in women with EPs and PULs with low and plateauing serum hCG concentrations

The ultrasound use of simulators, current view, and perspectives: Requirements and technical aspects (WFUMB state of the art paper)

Simulation has been shown to improve clinical learning outcomes, speed up the learning process and improve learner confidence, whilst initially taking pressure off busy clinical lists. The World Federation for Ultrasound in Medicine and Biology (WFUMB) state of the art paper on the use of simulators in ultrasound education introduces ultrasound simulation, its advantages and challenges. It describes different simulator types, including low and high-fidelity simulators, the requirements and technical aspects of simulators, followed by the clinical applications of ultrasound simulation. The paper discusses the role of ultrasound simulation in ultrasound clinical training, referencing established literature. Requirements for successful ultrasound simulation acceptance into educational structures are explored. Despite being in its infancy, ultrasound simulation already offers a wide range of training opportunities and likely holds the key to a broader point of care ultrasound education for medical students, practicing doctors, and other health care professionals. Despite the drawbacks of simulation, there are also many advantages, which are expanding rapidly as the technology evolves

L2-norm multiple kernel learning and its application to biomedical data fusion

<p>Abstract</p> <p>Background</p> <p>This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields different extensions of multiple kernel learning (MKL) such as <it>L</it>_∞, <it>L</it>₁, and <it>L</it>₂MKL. In particular, <it>L</it>₂MKL is a novel method that leads to non-sparse optimal kernel coefficients, which is different from the sparse kernel coefficients optimized by the existing <it>L</it>_∞MKL method. In real biomedical applications, <it>L</it>₂MKL may have more advantages over sparse integration method for thoroughly combining complementary information in heterogeneous data sources.</p> <p>Results</p> <p>We provide a theoretical analysis of the relationship between the <it>L</it>₂optimization of kernels in the dual problem with the <it>L</it>₂coefficient regularization in the primal problem. Understanding the dual <it>L</it>₂problem grants a unified view on MKL and enables us to extend the <it>L</it>₂method to a wide range of machine learning problems. We implement <it>L</it>₂MKL for ranking and classification problems and compare its performance with the sparse <it>L</it>_∞and the averaging <it>L</it>₁MKL methods. The experiments are carried out on six real biomedical data sets and two large scale UCI data sets. <it>L</it>₂MKL yields better performance on most of the benchmark data sets. In particular, we propose a novel <it>L</it>₂MKL least squares support vector machine (LSSVM) algorithm, which is shown to be an efficient and promising classifier for large scale data sets processing.</p> <p>Conclusions</p> <p>This paper extends the statistical framework of genomic data fusion based on MKL. Allowing non-sparse weights on the data sources is an attractive option in settings where we believe most data sources to be relevant to the problem at hand and want to avoid a "winner-takes-all" effect seen in <it>L</it>_∞MKL, which can be detrimental to the performance in prospective studies. The notion of optimizing <it>L</it>₂kernels can be straightforwardly extended to ranking, classification, regression, and clustering algorithms. To tackle the computational burden of MKL, this paper proposes several novel LSSVM based MKL algorithms. Systematic comparison on real data sets shows that LSSVM MKL has comparable performance as the conventional SVM MKL algorithms. Moreover, large scale numerical experiments indicate that when cast as semi-infinite programming, LSSVM MKL can be solved more efficiently than SVM MKL.</p> <p>Availability</p> <p>The MATLAB code of algorithms implemented in this paper is downloadable from <url>http://homes.esat.kuleuven.be/~sistawww/bioi/syu/l2lssvm.html</url>.</p

Shotgun Proteomics Identifies Serum Fibronectin as a Candidate Diagnostic Biomarker for Inclusion in Future Multiplex Tests for Ectopic Pregnancy

Ectopic pregnancy (EP) is difficult to diagnose early and accurately. Women often present at emergency departments in early pregnancy with a 'pregnancy of unknown location' (PUL), and diagnosis and exclusion of EP is challenging due to a lack of reliable biomarkers. The objective of this study was to identify novel diagnostic biomarkers for EP. Shotgun proteomics, incorporating combinatorial-ligand library pre-fractionation, was used to interrogate pooled sera (n = 40) from women undergoing surgery for EP, termination of viable intrauterine pregnancy and management of non-viable intrauterine pregnancy. Western blot was used to validate results in individual sera. ELISAs were developed to interrogate sera from women with PUL (n = 120). Sera were collected at time of first symptomatic presentation and categorized according to pregnancy outcome. The main outcome measures were differences between groups and area under the receiver operating curve (ROC). Proteomics identified six biomarker candidates. Western blot detected significant differences in levels of two of these candidates. ELISA of sera from second cohort revealed that these differences were only significant for one of these candidates, fibronectin. ROC analysis of ability of fibronectin to discriminate EP from other pregnancy outcomes suggested that fibronectin has diagnostic potential (ROC 0.6439; 95% CI 0.5090 to 0.7788; P>0.05), becoming significant when 'ambiguous' medically managed PUL excluded from analysis (ROC 0.6538; 95% CI 0.5158 to 0.7918; P<0.05). Fibronectin may make a useful adjunct to future multiplex EP diagnostic tests