Can risk prediction models help us individualise stillbirth prevention? A systematic review and critical appraisal of published risk models.

BACKGROUND: Stillbirth prevention is an international priority - risk prediction models could individualise care and reduce unnecessary intervention, but their use requires evaluation. OBJECTIVES: To identify risk prediction models for stillbirth, and assess their potential accuracy and clinical benefit in practice. SEARCH STRATEGY: MEDLINE, Embase, DH-DATA and AMED databases were searched from inception to June 2019 using terms relevant to stillbirth, perinatal mortality and prediction models. The search was compliant with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. SELECTION CRITERIA: Studies developing and/or validating prediction models for risk of stillbirth developed for application during pregnancy. DATA COLLECTION AND ANALYSIS: Study screening and data extraction were conducted in duplicate, using the CHARMS checklist. Risk of bias was appraised using the PROBAST tool. RESULTS: The search identified 2751 citations. Fourteen studies reporting development of 69 models were included. Variables consistently included were: ethnicity, body mass index, uterine artery Doppler, pregnancy-associated plasma protein and placental growth factor. For almost all models there were significant concerns about risk of bias. Apparent model performance (i.e. in the development dataset) was highest in models developed for use later in pregnancy and including maternal characteristics, and ultrasound and biochemical variables, but few were internally validated and none were externally validated. CONCLUSIONS: Almost all models identified were at high risk of bias. There are first-trimester models of possible clinical benefit in early risk stratification; these require validation and clinical evaluation. There were few later pregnancy models but, if validated, these could be most relevant to individualised discussions around timing of birth. TWEETABLE ABSTRACT: Prediction models using maternal factors, blood tests and ultrasound could individualise stillbirth prevention, but existing models are at high risk of bias.The authors are collaborators in the IPPIC (International Prediction of Pregnancy Complications) stillbirth project, funded by Sands (the Stillbirth and Neonatal Death Society)

Development and validation of prediction models for risk of adverse outcomes in women with early-onset pre-eclampsia: protocol of the prospective cohort PREP study.

Background: Early-onset pre-eclampsia with raised blood pressure and protein in the urine before 34 weeks' gestation is one of the leading causes of maternal deaths in the UK. The benefits to the child from prolonging the pregnancy need to be balanced against the risk of maternal deterioration. Accurate prediction models of risks are needed to plan management. Methods: We aim to undertake a multicentre prospective cohort study (Prediction of Risks in Early onset Pre-eclampsia (PREP)) to develop clinical prediction models in women with early-onset pre-eclampsia, for risk of adverse maternal outcomes by 48 h and by discharge. We will externally validate the models in two independent cohorts with 634 and 216 women. In the secondary analyses, we will assess risk of adverse fetal and neonatal outcomes at birth and by discharge. Discussion: The PREP study will quantify the risk of maternal complications at various time points and provide individualised estimates of overall risk in women with early-onset pre-eclampsia to plan the management. Trial registration: ISRCTN registry, ISRCTN40384046

Quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 1: Individual participant data meta-analysis and health economic analysis.

INTRODUCTION: The aim of the QUIDS study is to develop a decision support tool for the management of women with symptoms and signs of preterm labour, based on a validated prognostic model using quantitative fetal fibronectin (qfFN) concentration, in combination with clinical risk factors. METHODS AND ANALYSIS: The study will evaluate the Rapid fFN 10Q System (Hologic, Marlborough, Massachusetts) which quantifies fFN in a vaginal swab. In part 1 of the study, we will develop and internally validate a prognostic model using an individual participant data (IPD) meta-analysis of existing studies containing women with symptoms of preterm labour alongside fFN measurements and pregnancy outcome. An economic analysis will be undertaken to assess potential cost-effectiveness of the qfFN prognostic model. The primary endpoint will be the ability of the prognostic model to rule out spontaneous preterm birth within 7 days. Six eligible studies were identified by systematic review of the literature and five agreed to provide their IPD (n=5 studies, 1783 women and 139 events of preterm delivery within 7 days of testing). ETHICS AND DISSEMINATION: The study is funded by the National Institute of Healthcare Research Health Technology Assessment (HTA 14/32/01). It has been approved by the West of Scotland Research Ethics Committee (16/WS/0068). PROSPERO REGISTRATION NUMBER: CRD42015027590. VERSION: Protocol version 2, date 1 November 2016

Exercise therapy for chronic low back pain:protocol for an individual participant data meta-analysis

<p>Abstract</p> <p>Background</p> <p>Low back pain (LBP) is one of the leading causes of disability and has a major socioeconomic impact. Despite a large amount of research in the field, there remains uncertainty about the best treatment approach for chronic LBP, and identification of relevant patient subgroups is an important goal. Exercise therapy is a commonly used strategy to treat chronic low back pain and is one of several interventions that evidence suggests is moderately effective.</p> <p>In parallel with an update of the 2005 Cochrane review, we will undertake an individual participant data (IPD) meta-analysis, which will allow us to standardize analyses across studies and directly derive results, and to examine differential treatment effects across individuals to estimate how patients’ characteristics modify treatment benefit.</p> <p>Methods/design</p> <p>We will use standard systematic review methods advocated by the Cochrane Collaboration to identify relevant trials. We will include trials evaluating exercise therapy compared to any or no other interventions in adult non-specific chronic LBP. Our primary outcomes of interest include pain, functional status, and return-to-work/absenteeism. We will assess potential risk of bias for each study meeting selection criteria, using criteria and methods recommended by the Cochrane BRG.</p> <p>The original individual participant data will be requested from the authors of selected trials having moderate to low risk of bias. We will test original data and compile a master dataset with information about each trial mapped on a pre-specified framework, including reported characteristics of the study sample, exercise therapy characteristics, individual patient characteristics at baseline and all follow-up periods, subgroup and treatment effect modifiers investigated. Our analyses will include descriptive, study-level meta-analysis and meta-regression analyses of the overall treatment effect, and individual-level IPD meta-analyses of treatment effect modification. IPD meta-analyses will be conducted using a one-step approach where the IPD from all studies are modeled simultaneously while accounting for the clustering of participants with studies.</p> <p>Discussion</p> <p>We will analyze IPD across a large number of LBP trials. The resulting larger sample size and consistent presentation of data will allow additional analyses to explore patient-level heterogeneity in treatment outcomes and prognosis of chronic LBP.</p

Belowground DNA-based techniques: untangling the network of plant root interactions

Contains fulltext : 91591.pdf (publisher's version ) (Closed access)7 p

Zoonotic Transfer of Clostridium difficile Harboring Antimicrobial Resistance between Farm Animals and Humans.

The emergence of Clostridium difficile as a significant human diarrheal pathogen is associated with the production of highly transmissible spores and the acquisition of antimicrobial resistance genes (ARGs) and virulence factors. Unlike the hospital-associated C. difficile RT027 lineage, the community-associated C. difficile RT078 lineage is isolated from both humans and farm animals; however, the geographical population structure and transmission networks remain unknown. Here, we applied whole-genome phylogenetic analysis of 248 C. difficile RT078 strains from 22 countries. Our results demonstrate limited geographical clustering for C. difficile RT078 and extensive coclustering of human and animal strains, thereby revealing a highly linked intercontinental transmission network between humans and animals. Comparative whole-genome analysis reveals indistinguishable accessory genomes between human and animal strains and a variety of antimicrobial resistance genes in the pangenome of C. difficile RT078. Thus, bidirectional spread of C. difficile RT078 between farm animals and humans may represent an unappreciated route disseminating antimicrobial resistance genes between humans and animals. These results highlight the importance of the "One Health" concept to monitor infectious disease emergence and the dissemination of antimicrobial resistance genes

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Precision Measurement of the Mass of the h_c(1P1) State of Charmonium

A precision measurement of the mass of the h_c(1P1) state of charmonium has been made using a sample of 24.5 million psi(2S) events produced in e+e- annihilation at CESR. The reaction used was psi(2S) -> pi0 h_c, pi0 -> gamma gamma, h_c -> gamma eta_c, and the reaction products were detected in the CLEO-c detector. Data have been analyzed both for the inclusive reaction and for the exclusive reactions in which eta_c decays are reconstructed in fifteen hadronic decay channels. Consistent results are obtained in the two analyses. The averaged results of the present measurements are M(h_c)=3525.28+-0.19 (stat)+-0.12(syst) MeV, and B(psi(2S) -> pi0 h_c)xB(h_c -> gamma eta_c)= (4.19+-0.32+-0.45)x10^-4. Using the 3PJ centroid mass, Delta M_hf(1P)= - M(h_c) = +0.02+-0.19+-0.13 MeV.Comment: 9 pages, available through http://www.lns.cornell.edu/public/CLNS/, submitted to PR

Precision Measurement of B(D+ -> mu+ nu) and the Pseudoscalar Decay Constant fD+

We measure the branching ratio of the purely leptonic decay of the D+ meson with unprecedented precision as B(D+ -> mu+ nu) = (3.82 +/- 0.32 +/- 0.09)x10^(-4), using 818/pb of data taken on the psi(3770) resonance with the CLEO-c detector at the CESR collider. We use this determination to derive a value for the pseudoscalar decay constant fD+, combining with measurements of the D+ lifetime and assuming |Vcd| = |Vus|. We find fD+ = (205.8 +/- 8.5 +/- 2.5) MeV. The decay rate asymmetry [B(D+ -> mu+ nu)-B(D- -> mu- nu)]/[B(D+ -> mu+ nu)+B(D- -> mu- nu)] = 0.08 +/- 0.08, consistent with no CP violation. We also set 90% confidence level upper limits on B(D+ -> tau+ nu) < 1.2x10^(-3) and B(D+ -> e+ nu) < 8.8x10^(-6).Comment: 24 pages, 11 figures and 6 tables, v2 replaced some figure vertical axis scales, v3 corrections from PRD revie

J/psi and psi(2S) Radiative Transitions to eta_c

Using 24.5 million psi(2S) decays collected with the CLEO-c detector at CESR we present the most precise measurements of magnetic dipole transitions in the charmonium system. We measure B(psi(2S)->gamma eta_c) = (4.32+/-0.16+/-0.60)x10^-3, B(J/psi->gamma eta_c)/B(psi(2S)->gamma eta_c) = 4.59+/-0.23+/-0.64, and B(J/psi->gamma eta_c) = (1.98+/-0.09+/-0.30)%. We observe a distortion in the eta_c line shape due to the photon-energy dependence of the magnetic dipole transition rate. We find that measurements of the eta_c mass are sensitive to the line shape, suggesting an explanation for the discrepancy between measurements of the eta_c mass in radiative transitions and other production mechanisms.Comment: 11 pages, 3 figure