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PubMed2006

A cross-sectional study of the prevalence of intensity of infection with Schistosoma japonicum in 50 irrigated and rain-fed villages in Samar Province, the Philippines.

BACKGROUND: Few studies have described heterogeneity in Schistosoma japonicum infection intensity, and none were done in Philippines. The purpose of this report is to describe the village-to-village variation in the prevalence of two levels of infection intensity across 50 villages of Samar Province, the Philippines. METHODS: This cross-sectional study was conducted in 25 rain-fed and 25 irrigated villages endemic for S. japonicum between August 2003 and November 2004. Villages were selected based on irrigation and farming criteria. A maximum of 35 eligible households were selected per village. Each participant was asked to provide stool samples on three consecutive days. All those who provided at least one stool sample were included in the analysis. A Bayesian three category outcome hierarchical cumulative logit regression model with adjustment for age, sex, occupation and measurement error of the Kato-Katz technique was used for analysis. RESULTS: A total of 1427 households and 6917 individuals agreed to participate in the study. A total of 5624 (81.3%) participants provided at least one stool sample. The prevalences of those lightly and at least moderately infected varied from 0% (95% Bayesian credible interval (BCI): 0%-3.1%) to 45.2% (95% BCI: 36.5%-53.9%) and 0% to 23.0% (95% BCI: 16.4%-31.2%) from village-to-village, respectively. Using the 0-7 year old group as a reference category, the highest odds ratio (OR) among males and females were that of being aged 17-40-year old (OR = 8.76; 95% BCI: 6.03-12.47) and 11-16-year old (OR = 8.59; 95% BCI: 4.74-14.28), respectively. People who did not work on a rice farm had a lower prevalence of infection than those working full time on a rice farm. The OR for irrigated villages compared to rain-fed villages was 1.41 (95% BCI: 0.50-3.21). DISCUSSION: We found very important village-to-village variation in prevalence of infection intensity. This variation is probably due to village-level variables other than that explained by a crude classification of villages into the irrigated and non-irrigated categories. We are planning to capture this spatial heterogeneity by updating our initial transmission dynamics model with the data reported here combined with 1-year post-treatment follow-up of study participants.

Adolescent↗

PubMed2026

The genetic overlap between schizophrenia and major depression with cognitive function.

This study aimed to systematically dissect the shared genetic basis of schizophrenia (SCZ) and major depression (MD) with cognitive function. To investigate this, we integrated large-scale genome-wide association studies (GWAS) summary statistics for SCZ (N = 175,799, [cases, 74,776; controls, 101,023]), MD (N = 2,622,273 [cases, 550,355; controls, 2,071,918]) and four cognitive traits (reaction time, N = 330,069; memory, N = 112,067; verbal-numerical reasoning, N = 36,035; educational attainment, N = 111,114). Linkage disequilibrium (LD) score regression analysis revealed that SCZ showed significant negative genetic correlations with reaction time, memory, and verbal-numerical reasoning. MD showed negative genetic correlations with memory, verbal-numerical reasoning, and educational attainment. Bayesian colocalization analysis identified seven genomic regions with strong or supportive evidence between SCZ and cognitive function, and two genomic regions with supportive evidence between MD and cognitive function. Gene mapping and over representation analysis (ORA) indicated that SCZ-associated genes were primarily involved in pathways related to transport processes, and MD-associated genes were significantly enriched in pathways related to neural development. Through genetic correlation and colocalization analysis, this study elucidates the genetic overlap between SCZ and MD with cognitive function, providing a new perspective for related research.

Journal Article↗

PubMed2004

Inferring pathways and networks with a Bayesian framework.

Numerous mathematical methods have been adapted and developed to quantitatively reverse engineer biological networks, for example, signal transduction pathways, from experimental micro-array data. Compared with stochastic methods, such as Boolean networks, and deterministic methods, such as thermodynamic or differential equation-based models, Bayesian network analysis has the ability to assess, with scoring metrics, causal relations based on conditional probabilities and thus permit hypothesis testing. The goal of this paper is to illustrate the integration of several Bayesian based techniques into a unified Bayesian framework that can infer hepatocellular networks from metabolic data. Reverse engineering of pathways and networks provides a framework for predictive modeling and hypotheses testing to gain deeper insight into living organisms, disease mechanisms, and targeted therapeutics. Evaluating this methodology initially against the known biochemical network provides confidence in the networks that are uncovered from the experimental data using this framework. From the metabolic data we inferred the known sub-networks, such as the tricarboxylic acid (TCA) and urea cycles. In addition, we combined the relationships learned from the data and our current knowledge of the biological system to postulate several alternative metabolic sub-network models that can predict a particular cellular function, such as intracellular triglyceride accumulation.

Algorithms↗

PubMed2004

Bayesian isotonic regression and trend analysis.

In many applications, the mean of a response variable can be assumed to be a nondecreasing function of a continuous predictor, controlling for covariates. In such cases, interest often focuses on estimating the regression function, while also assessing evidence of an association. This article proposes a new framework for Bayesian isotonic regression and order-restricted inference. Approximating the regression function with a high-dimensional piecewise linear model, the nondecreasing constraint is incorporated through a prior distribution for the slopes consisting of a product mixture of point masses (accounting for flat regions) and truncated normal densities. To borrow information across the intervals and smooth the curve, the prior is formulated as a latent autoregressive normal process. This structure facilitates efficient posterior computation, since the full conditional distributions of the parameters have simple conjugate forms. Point and interval estimates of the regression function and posterior probabilities of an association for different regions of the predictor can be estimated from a single MCMC run. Generalizations to categorical outcomes and multiple predictors are described, and the approach is applied to an epidemiology application.

Bayes Theorem↗

PubMed2006

Bayesian variable selection for the analysis of microarray data with censored outcomes.

MOTIVATION: A common task in microarray data analysis consists of identifying genes associated with a phenotype. When the outcomes of interest are censored time-to-event data, standard approaches assess the effect of genes by fitting univariate survival models. In this paper, we propose a Bayesian variable selection approach, which allows the identification of relevant markers by jointly assessing sets of genes. We consider accelerated failure time (AFT) models with log-normal and log-t distributional assumptions. A data augmentation approach is used to impute the failure times of censored observations and mixture priors are used for the regression coefficients to identify promising subsets of variables. The proposed method provides a unified procedure for the selection of relevant genes and the prediction of survivor functions. RESULTS: We demonstrate the performance of the method on simulated examples and on several microarray datasets. For the simulation study, we consider scenarios with large number of noisy variables and different degrees of correlation between the relevant and non-relevant (noisy) variables. We are able to identify the correct covariates and obtain good prediction of the survivor functions. For the microarray applications, some of our selected genes are known to be related to the diseases under study and a few are in agreement with findings from other researchers. AVAILABILITY: The Matlab code for implementing the Bayesian variable selection method may be obtained from the corresponding author. CONTACT: mvannucci@stat.tamu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗

PubMedDate not supplied

Logistic regression and Bayesian networks to study outcomes using large data sets.

BACKGROUND: In nursing research, the interest in using large health care databases to predict nursing sensitive outcomes is growing rapidly. Traditionally, one of the most frequently used methods is logistic regression (LR), which, although powerful and familiar, has several limitations when used in the analysis of large databases. As a result, innovative approaches are required. APPROACH: To (a) introduce an innovative/alternative data analysis approach (Bayesian network), (b) discuss the constraints of LR and the complementary advantages of Bayesian networks (BNs) in working with large and multidimensional health care data, and (c) provide a fundamental understanding of the use of BNs in the nursing/health care domain. RESULTS: Studies have shown that BNs have several advantages over LR in analyzing complex and large data: (a) statistical assumptions, such as linearity and additivity, are relaxed; (b) handling of a larger number of predictors and identification of interactions among predictors is less complex; and (c) the discovery of structure, pattern, and knowledge, for example, of unknown, complex, and nonlinear relationships, in data is facilitated. CONCLUSION: Outcome studies, such as those undertaken by nurse researchers, may benefit from the examination and use of innovative approaches such as BNs to the analysis of very large and complex health care data sets.

Bayes Theorem↗

PubMed2024

Fine-mapping the CYP2A6 regional association with nicotine metabolism among African American smokers.

The nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine) is a stable biomarker for CYP2A6 enzyme activity and nicotine clearance, with demonstrated clinical utility in personalizing smoking cessation treatment. Common genetic variation in the CYP2A6 region is strongly associated with NMR in smokers. Here, we investigated this regional association in more detail. We evaluated the association of CYP2A6 single-nucleotide polymorphisms (SNPs) and * alleles with NMR among African American smokers (N = 953) from two clinical trials of smoking cessation. Stepwise conditional analysis and Bayesian fine-mapping were undertaken. Putative causal variants were incorporated into an existing African ancestry-specific genetic risk score (GRS) for NMR, and the performance of the updated GRS was evaluated in both African American (n = 953) and European ancestry smokers (n = 933) from these clinical trials. Five independent associations with NMR in the CYP2A6 region were identified using stepwise conditional analysis, including the deletion variant CYP2A6*4 (beta = -0.90, p = 1.55 × 10-11). Six putative causal variants were identified using Bayesian fine-mapping (posterior probability, PP = 0.67), with the top causal configuration including CYP2A6*4, rs116670633, CYP2A6*9, rs28399451, rs8192720, and rs10853742 (PP = 0.09). Incorporating these putative causal variants into an existing ancestry-specific GRS resulted in comparable prediction of NMR within African American smokers, and improved trans-ancestry portability of the GRS to European smokers. Our findings suggest that both * alleles and SNPs underlie the association of the CYP2A6 region with NMR among African American smokers, identify a shortlist of variants that may causally influence nicotine clearance, and suggest that portability of GRSs across populations can be improved through inclusion of putative causal variants.

Adult↗

PubMed2001

Data augmentation priors for Bayesian and semi-Bayes analyses of conditional-logistic and proportional-hazards regression.

Data augmentation priors have a long history in Bayesian data analysis. Formulae for such priors have been derived for generalized linear models, but their accuracy depends on two approximation steps. This note presents a method for using offsets as well as scaling factors to improve the accuracy of the approximations in logistic regression. This method produces an exceptionally simple form of data augmentation that allows it to be used with any standard package for conditional-logistic or proportional-hazards regression to perform Bayesian and semi-Bayes analyses of matched and survival data. The method is illustrated with an analysis of a matched case-control study of diet and breast cancer.

Algorithms↗

PubMed2002

Perils of paralogy: using HSP70 genes for inferring organismal phylogenies.

Conserved genes have found their way into the mainstream of molecular systematics. Many of these genes are members of multigene families. A difficulty with using single genes of multigene families for phylogenetic inference is that genes from one species may be paralogous to those from another taxon. We focus attention on this problem using heat shock 70 (HSP70) genes. Using polymerase chain reaction techniques with genomic DNA, we isolated and sequenced 123 distinct sequences from 12 species of sharks. Phylogenetic analysis indicated that the sequences cluster with constituitively expressed cytoplasmic heat shock-like genes. Three highly divergent gene clades were sampled. A number of similar sequences were sampled from each species within each distinct gene clade. Comparison of published species trees with an HSP70 gene tree inferred using Bayesian phylogenetic analysis revealed several cases of gene duplication and differential sorting of gene lineages within this group of sharks. Gene tree parsimony based on the objective criteria of duplication and losses showed that previously published hypotheses of species relationships and two novel hypothesis based on Bayesian phylogenetics were concordant with the history of HSP70 gene duplication and loss. By contrast, two published hypotheses based on morphological data were not significantly different from the null hypothesis of a random association between species relatedness and the HSP70 gene tree. These results suggest that gene tree parsimony using data from multigene families can be used for inferring species relationships or testing published alternative hypotheses. More importantly, the results suggest that systematic studies relying on phylogenetic inferences from HSP70 genes may by plagued by unrecognized paralogy of sampled genes. Our results underscore the distinction between gene and species trees and highlight an underappreciated source of discordance between gene trees and organismal phylogeny, i.e., unrecognized paralogy of sampled genes.

Animals↗

PubMed2000

Bayesian methods in health technology assessment: a review.

BACKGROUND: Bayesian methods may be defined as the explicit quantitative use of external evidence in the design, monitoring, analysis, interpretation and reporting of a health technology assessment. In outline, the methods involve formal combination through the use of Bayes's theorem of: 1. a prior distribution or belief about the value of a quantity of interest (for example, a treatment effect) based on evidence not derived from the study under analysis, with 2. a summary of the information concerning the same quantity available from the data collected in the study (known as the likelihood), to yield 3. an updated or posterior distribution of the quantity of interest. These methods thus directly address the question of how new evidence should change what we currently believe. They extend naturally into making predictions, synthesising evidence from multiple sources, and designing studies: in addition, if we are willing to quantify the value of different consequences as a 'loss function', Bayesian methods extend into a full decision-theoretic approach to study design, monitoring and eventual policy decision-making. Nonetheless, Bayesian methods are a controversial topic in that they may involve the explicit use of subjective judgements in what is conventionally supposed to be a rigorous scientific exercise. OBJECTIVES: This report is intended to provide: 1. a brief review of the essential ideas of Bayesian analysis 2. a full structured review of applications of Bayesian methods to randomised controlled trials, observational studies, and the synthesis of evidence, in a form which should be reasonably straightforward to update 3. a critical commentary on similarities and differences between Bayesian and conventional approaches 4. criteria for assessing the reporting of a Bayesian analysis 5. a comprehensive list of published 'three-star' examples, in which a proper prior distribution has been used for the quantity of primary interest 6. tutorial case studies of a variety of types 7. recommendations on how Bayesian methods and approaches may be assimilated into health technology assessments in a variety of contexts and by a variety of participants in the research process. METHODS: The BIDS ISI database was searched using the terms 'Bayes' or 'Bayesian'. This yielded almost 4000 papers published in the period 1990-98. All resultant abstracts were reviewed for relevance to health technology assessment; about 250 were so identified, and used as the basis for forward and backward searches. In addition EMBASE and MEDLINE databases were searched, along with websites of prominent authors, and available personal collections of references, finally yielding nearly 500 relevant references. A comprehensive review of all references describing use of 'proper' Bayesian methods in health technology assessment (those which update an informative prior distribution through the use of Bayes's theorem) has been attempted, and around 30 such papers are reported in structured form. There has been very limited use of proper Bayesian methods in practice, and relevant studies appear to be relatively easily identified. RESULTS: Bayesian methods in the health technology assessment context 1. Different contexts may demand different statistical approaches. Prior opinions are most valuable when the assessment forms part of a series of similar studies. A decision-theoretic approach may be appropriate where the consequences of a study are reasonably predictable. 2. The prior distribution is important and not unique, and so a range of options should be examined in a sensitivity analysis. Bayesian methods are best seen as a transformation from initial to final opinion, rather than providing a single 'correct' inference. 3. The use of a prior is based on judgement, and hence a degree of subjectivity cannot be avoided. However, subjective priors tend to show predictable biases, and archetypal priors may be useful for identifying a reasonable range of prior opinion.

Bayes Theorem↗

PubMed2003

Analyses for the presence of a major gene affecting uterine capacity in unilaterally ovariectomized rabbits.

The presence of a major gene for uterine capacity (UC), ovulation rate (OR), number of implanted embryos (IE), embryo survival (ES), fetal survival (FS), and prenatal survival (PS) was investigated in a population of rabbits divergently selected for UC for 10 generations. Selection was performed on estimated breeding values for UC up to four parities. UC was estimated as litter size in the remaining overcrowded horn of unilaterally ovariectomized does. OR and IE were counted by means of laparoscopy. Bartlett's test, Fain's test, and a complex segregation analysis using Bayesian methods were used to test for the presence of a major gene. All three tests showed that the data appeared consistent with the presence of a major gene affecting UC and IE. The results of the complex segregation analysis suggested the presence of a major gene with large effect on IE and ES (a > 1sigma(p)), at high frequency (p = 0.70 and 0.68, respectively), and with a large contribution to the total variance (R(g) = 0.39 and 0.47, respectively); and the presence of a major gene with moderate effect on each of OR, FS, PS, and UC. The results suggest that the studied reproductive traits are determined genetically by at least one gene of large effect.

Animals↗

PubMed2006

A posterior probability of linkage-based re-analysis of schizophrenia data yields evidence of linkage to chromosomes 1 and 17.

OBJECTIVE: Linkage analysis using 22 Canadian pedigrees identified a promising schizophrenia candidate region on 1q23 with a maximum 2-point HLOD under a recessive model of 5.8 [Brzustowicz et al. 2000]. In the current study, we revisited this data set using a Bayesian linkage analysis technique, namely the posterior probability of linkage (PPL). METHODS: The PPL has been developed as an alternative to traditional linkage analysis. It differs from both LOD scores and 'non-parametric' methods in that it directly measures the probability of linkage given the data, and incorporates prior genomic information. RESULTS: As expected, PPL results for 1q23 supported the previously observed linkage, with an estimated multipoint PPL of 99.7%. However, the PPL supported two further results: a second peak on chromosome 1 at 1p13 with a multipoint with PPL of 70% and a chromosome 17 marker (D17S784 at 17q25) with a multipoint PPL of 44%. CONCLUSIONS: The PPL-based analysis presented has the advantage over other likelihood-based linkage methods in that it avoids maximization and produces a less complex view of the strength of evidence for linkage.

Chromosomes, Human, Pair 1↗

PubMedDate not supplied

A Bayesian model for detecting past recombination events in DNA multiple alignments.

Most phylogenetic tree estimation methods assume that there is a single set of hierarchical relationships among sequences in a data set for all sites along an alignment. Mosaic sequences produced by past recombination events will violate this assumption and may lead to misleading results from a phylogenetic analysis due to the imposition of a single tree along the entire alignment. Therefore, the detection of past recombination is an important first step in an analysis. A Bayesian model for the changes in topology caused by recombination events is described here. This model relaxes the assumption of one topology for all sites in an alignment and uses the theory of Hidden Markov models to facilitate calculations, the hidden states being the underlying topologies at each site in the data set. Changes in topology along the multiple sequence alignment are estimated by means of the maximum a posteriori (MAP) estimate. The performance of the MAP estimate is assessed by application of the model to data sets of four sequences, both simulated and real.

Bayes Theorem↗

PubMed2001

Recent trends and future projections of lymphoid neoplasms--a Bayesian age-period-cohort analysis.

OBJECTIVES: A steady increase in incidence of lymphoid neoplasms has been reported, especially for non-Hodgkin's lymphoma (NHL). Using high-quality incidence data from 1973-1992 in nine population-based cancer registries (Alberta, Bombay, Denmark, Israel, New Zealand, Osaka, Oxford, Slovenia, Utah), we have examined past increases in specific lymphoid neoplasms. Further, by using a Bayesian age-period-cohort approach, we have calculated 5-, 10- and 15-year projections for each group of lymphoid neoplasms. RESULTS: NHL incidence increased in all centers by an average of 77% in men and 66% in women between 1973 and 1992. Fifteen-year projections of these rates to 2003-2007 indicate that they will increase by an average of 55% among men and 79% among women. High projected incidence rates above 15/100,000 in men and 10/100,000 in women are expected in Alberta, Denmark, Israel, New Zealand, Oxford, and Utah by 2003-2007. The one notable exception was among men from Osaka, where no increase was projected. Modest increases in leukemia and multiple myeloma rates were observed in most of the nine registries with further projected increases by 2007. Projected incidence rates of Hodgkin's disease indicated little change. CONCLUSION: Increases in NHL rates are occurring worldwide and provide no evidence of peaking. A key assumption in the projected rates is that the effect of environmental agents determining the trends during 1973-1992 will remain stable during the subsequent projection period.

Age Factors↗

PubMed2006

Phylogeography of the Western Lyresnake (Trimorphodon biscutatus): testing aridland biogeographical hypotheses across the Nearctic-Neotropical transition.

The Western Lyresnake (Trimorphodon biscutatus) is a widespread, polytypic taxon inhabiting arid regions from the warm deserts of the southwestern United States southward along the Pacific versant of Mexico to the tropical deciduous forests of Mesoamerica. This broadly distributed species provides a unique opportunity to evaluate a priori biogeographical hypotheses spanning two major distinct biogeographical realms (the Nearctic and Neotropical) that are usually treated separately in phylogeographical analyses. I investigated the phylogeography of T. biscutatus using maximum likelihood and Bayesian phylogenetic analysis of mitochondrial DNA (mtDNA) from across this species' range. Phylogenetic analyses recovered five well-supported clades whose boundaries are concordant with existing geographical barriers, a pattern consistent with a model of vicariant allopatric divergence. Assuming a vicariance model, divergence times between mitochondrial lineages were estimated using Bayesian relaxed molecular clock methods calibrated using geological information from putative vicariant events. Divergence time point estimates were bounded by broad confidence intervals, and thus these highly conservative estimates should be considered tentative hypotheses at best. Comparison of mtDNA lineages and taxa traditionally recognized as subspecies based on morphology suggest this taxon is comprised of multiple independent lineages at various stages of divergence, ranging from putative secondary contact and hybridization to sympatry of 'subspecies'.

Animals↗

PubMed2006

Adherence to antiretroviral therapy in sub-Saharan Africa and North America: a meta-analysis.

CONTEXT: Adherence to antiretroviral therapy is a powerful predictor of survival for individuals living with human immunodeficiency virus (HIV) and AIDS. Concerns about incomplete adherence among patients living in poverty have been an important consideration in expanding the access to antiretroviral therapy in sub-Saharan Africa. OBJECTIVE: To evaluate estimates of antiretroviral therapy adherence in sub-Saharan Africa and North America. DATA SOURCES: Eleven electronic databases were searched along with major conference abstract databases (inclusion dates: inception of database up until April 18, 2006) for all English-language articles and abstracts; and researchers and treatment advocacy groups were contacted. Study Selection and Data Abstraction To best reflect the general population, studies of mixed populations in both North America and Africa were selected. Studies evaluating specific populations such as men only, homeless individuals, or drug users, were excluded. The data were abstracted in duplicate on study adherence outcomes, thresholds used to determine adherence, and characteristics of the populations. A random-effects meta-analysis was performed in which heterogeneity was examined using multivariable random-effects logistic regression. A sensitivity analysis was performed using Bayesian methods. DATA SYNTHESIS: Thirty-one studies from North America (28 full-text articles and 3 abstracts) and 27 studies (9 full-text articles and 18 abstracts) from sub-Saharan Africa were included. African studies represented 12 sub-Saharan countries. Of the North American studies, 71% used patient self-report to assess adherence; this was true of 66% of the African assessments. Studies reported similar thresholds for adherence monitoring (eg, 100%, >95%, >90%, >80%). A pooled analysis of the North American studies (17,573 patients total) indicated a pooled estimate of 55% (95% confidence interval, 49%-62%; I2, 98.6%) of the populations achieving adequate levels of adherence. Our pooled analysis of African studies (12,116 patients total) indicated a pooled estimate of 77% (95% confidence interval, 68%-85%; I2, 98.4%). Study continent, adherence thresholds, and study quality were significant predictors of heterogeneity. Bayesian analysis was used as an alternative statistical method for combining adherence rates and provided similar findings. CONCLUSION: Our findings indicate that favorable levels of adherence, much of which was assessed via patient self-report, can be achieved in sub-Saharan African settings and that adherence remains a concern in North America.

Africa South of the Sahara↗

PubMed2025

Global emergence and transmission dynamics of carbapenemase-producing Citrobacter freundii sequence type 22 high-risk international clone: a retrospective, genomic, epidemiological study.

BACKGROUND: Carbapenemase-producing Citrobacter (CPC) species have recently been recognised as emerging pathogens associated with nosocomial infections in humans. The increased rate of Citrobacter freundii infections is a public health concern and there is a paucity of genomic data regarding its global transmission dynamics. We aimed to characterise the genetic features of CPC species, and their associated carbapenemase-encoding plasmids, obtained from hospitalised patients in China and from publicly available global data, with a particular focus on high-risk clones. METHODS: This was a retrospective, genomic epidemiological study of CPC species obtained from a tertiary hospital in Zhejiang Province, China, from March 5, 2013, to March 5, 2023. We used antimicrobial susceptibility testing, short-read and long-read whole-genome sequencing, phylogenomic analysis, and plasmid structure analysis. A global dataset of complete plasmid sequences encoding blaKPC, blaNDM, and blaIMP was constructed from the National Center for Biotechnology Information (NCBI) RefSeq database to provide insights into their diversity and distribution. All carbapenemase-producing Citrobacter freundii genomes from the NCBI GenBank database were incorporated in the comparative genomic analyses. Bayesian phylogeographical analysis and growth rate assays were carried out to characterise the high-risk C freundii sequence type (ST) 22 clone. FINDINGS: 1724 Citrobacter species isolates were collected from diverse clinical specimens, with 48 identified as CPC species. Citrobacter koseri (22 [46%] of 48) and C freundii (20 [42%]) were the predominant CPC species. Comparative analysis found C freundii carried significantly higher median numbers of plasmid replicons (5·0 [IQR 3·3-6·0] vs 2·0 [2·0-3·0]; p<0·0001) and acquired antimicrobial resistance genes (12·0 [7·3-15·8] vs 3·0 [3·0-5·3]; p<0·0001) than did C koseri. Molecular characterisation identified Inc-type plasmids, In823::Kl.pn.I3/In1589-like/In837-like integrons, Tn6296/Tn125/Tn5060 transposons, and insertion sequences (eg, IS26, IS3000, IS5, ISAba125, ISCR1), collectively facilitating the dissemination of carbapenemase genes. Global analysis of 3126 carbapenemase-encoding plasmids found epidemic plasmids with broad host ranges and global diversity. Phylogenetic investigation of predominant carbapenemase-encoding plasmids showed their persistence across geographical regions, temporal spans, and Enterobacterales species, exhibiting high genetic similarity to our clinical plasmids. A phylogenetic tree of 726 global carbapenemase-producing C freundii genomes showed that ST22 (227 [31·3%]) represents the predominant multidrug-resistant clone across community, health-care, and environmental niches. Transmission across continents contributes to the global predominance of the ST22 clone, which carries a high load of resistance genes (median 15·0 [IQR 11·0-17·0] vs 12·0 [3·0-16·0]; p<0·0001) and enhanced plasmid maintenance capacity (median replicons 5·0 [IQR 4·0-7·0] vs 4·0 [3·0-6·0]; p<0·0001) relative to non-ST22 clones. INTERPRETATION: Our study provides evidence to suggest that Citrobacter species are emerging carriers of carbapenem-resistance genes. These findings provide insight into the population structure of CPC species and highlight C freundii ST22 as a prominent high-risk international clone. FUNDING: National Natural Science Foundation of China, National Health Commission Scientific Research Fund-Zhejiang Provincial Major Health Science and Technology Plan Project, Zhejiang Province Natural Science Foundation Project, Outstanding Youth Foundation of Jiangsu Province of China, the Priority Academic Program Development of Jiangsu Higher Education Institutions, and Postgraduate Research and Practice Innovation Program of Jiangsu Province.

Citrobacter freundii↗

PubMed2003

A randomised trial of timed delivery for the compromised preterm fetus: short term outcomes and Bayesian interpretation.

OBJECTIVES: To compare the effect of delivering early to pre-empt terminal hypoxaemia with delaying for as long as possible to increase maturity. DESIGN: A randomized controlled trial. SETTING: 69 hospitals in 13 European countries. PARTICIPANTS: Pregnant women with fetal compromise between 24 and 36 weeks, an umbilical artery Doppler waveform recorded and clinical uncertainty whether immediate delivery was indicated. METHODS: The interventions were 'immediate delivery' or 'delay until the obstetrician is no longer uncertain'. The data monitoring and analysis were Bayesian. MAIN OUTCOME MEASURES: 'Survival to hospital discharge' and 'developmental quotient at two years of age', this latter to be reported later. RESULTS: Of 548 women (588 babies) recruited, outcomes were available on 547 mothers (587 babies). The median time-to-delivery intervals were 0.9 days in the immediate group and 4.9 days in the delay group. Total deaths prior to discharge were 29 (10%) in the immediate group versus 27 (9%) in the delay group (odds ratio 1.1, 95% CI 0.61-1.8). Total caesarean sections were 249 (91%) in the immediate group versus 217 (79%) in the delay group: (OR 2.7; 95% CI 1.6-4.5). These odds ratios were similar for those randomized at gestational ages above or below 30 weeks. INTERPRETATION: The lack of difference in overall mortality suggests that clinicians participating in this trial were on average prepared to randomize at about the correct equivocal threshold between delivery and delay. However, there was insufficient evidence to convince enthusiasts for either immediate or delayed delivery that they were wrong.

Adult↗