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  • 2005-2009  (37)
  • 1915-1919  (5)
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  • 1
    Electronic Resource
    Electronic Resource
    Association between congenital toxoplasmosis and preterm birth, low birthweight and small for gestational age birth (2005)
    Oxford, UK and Malden, USA : Blackwell Science Ltd
    BJOG 112 (2005), S. 0 
    Details
    ISSN: 1471-0528
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Objective  To determine the association between congenital toxoplasmosis and preterm birth, low birthweight and small for gestational age birth.Design  Multicentre prospective cohort study.Setting  Ten European centres offering prenatal screening for toxoplasmosis.Population  Deliveries after 23 weeks of gestation in 386 women with singleton pregnancies who seroconverted to toxoplasma infection before 20 weeks of gestation. Deliveries after 36 weeks in 234 women who seroconverted at 20 weeks or later, and tested positive before 37 weeks.Methods  Comparison of infected and uninfected births, adjusted for parity and country of birth.Main outcome measures  Differences in gestational age at birth, birthweight and birthweight centile.Results  Infected babies were born or delivered earlier than uninfected babies: the mean difference for seroconverters before 20 weeks was −5.4 days (95% CI: −1.4, −9.4), and at 20 weeks or more, −2.6 days (95% CI: −0.5, −4.7). Congenital infection was associated with an increased risk of preterm delivery when seroconversion occurred before 20 weeks (OR 4.71; 95% CI: 2.03, 10.9). No significant differences were detected for birthweight or birthweight centile.Conclusion  Babies with congenital toxoplasmosis were born earlier than uninfected babies but the mechanism leading to shorter length of gestation is unknown. Congenital infection could precipitate early delivery or prompt caesarean section or induction of delivery. We found no evidence for a significant association between congenital toxoplasmosis and reduced birthweight or small for gestational age birth.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1471-0528.2004.00299.x
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  • 2
    Electronic Resource
    Electronic Resource
    Endocannabinoid metabolism in human glioblastomas and meningiomas compared to human non-tumour brain tissue (2005)
    Oxford, UK : Blackwell Science Ltd
    Journal of neurochemistry 93 (2005), S. 0 
    Details
    ISSN: 1471-4159
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: The endogenous levels of the two cannabinoid receptor ligands 2-arachidonoyl glycerol and anandamide, and their respective congeners, monoacyl glycerols and N-acylethanolamines, as well as the phospholipid precursors of N-acylethanolamines, were measured by gas chromatography-mass spectrometry in glioblastoma (WHO grade IV) tissue and meningioma (WHO grade I) tissue and compared with human non-tumour brain tissue. Furthermore, the metabolic turnover of N-acylethanolamines was compared by measurements of the enzymatic activity of N-acyltransferase, N-acylphosphatidylethanolamine-hydrolysing phospholipase D and fatty acid amide hydrolase in the same three types of tissue. Glioblastomas were characterized by enhanced levels of N-acylethanolamines (eightfold, 128 ± 59 pmol/μmol lipid phosphorus) including anandamide (17-fold, 4.6 ± 3.1pmol/μmol lipid phosphorus) and several species of N-acylphosphatidylethanolamines (three to eightfold). This was accompanied by a more than 60% reduction in the enzyme activities of N-acylphosphatidylethanolamine-hydrolysing phospholipase D and fatty acid amide hydrolase. By contrast, meningiomas were characterized by a massively enhanced level of 2-monoacyl glycerols (20-fold, 2293 ± 361 pmol/μmol lipid phosphorus) including 2-arachidonoyl glycerol (20-fold, 1524 ± 361 pmol/μmol lipid phosphorus). This was accompanied by an enhanced in vitro conversion of phosphatidylcholine to monoacyl glycerol (fivefold). The enhanced level of the 2-arachidonoyl glycerol, anandamide and other N-acylethanolamines detected in the two types of tumour tissue may possibly act as endogenous anti-tumour mediators by stimulation of both cannabinoid and non-cannabinoid receptor-mediated mechanisms.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1471-4159.2005.03013.x
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  • 3
    Electronic Resource
    Electronic Resource
    Validation of Dual-Chamber Pacemaker Diagnostic Data Using Dual-Channel Stored Electrograms (2005)
    350 Main Street , Malden , MA 02148-5018 , USA and 9600 Garsington Road , Oxford OX4 2DQ , UK . : Blackwell Science Inc
    Pacing and clinical electrophysiology 28 (2005), S. 0 
    Details
    ISSN: 1540-8159
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Background: Pacemaker diagnostic counters are used to guide device programming and patient management. However, these data are susceptible to inappropriate classification of events. The aim of this multicenter study was to evaluate pacemaker diagnostic data using stored intracardiac electrograms (EGMs). Methods: The study included 351 patients (191 males, aged 71 ± 10 years) with standard indications for dual-chamber pacemaker implantation. EGM triggers were atrial tachycardia (AT), ventricular tachycardia (VT), sudden bradycardia response (SBR), and pacemaker-mediated tachycardia (PMT). For this study, the devices could store up to 5 EGMs of 8s each (with marker annotation and onset recording). After 3 months, the EGMs were analyzed and classified as “confirmed” if the EGM validated the trigger and as “false positive” if the EGM showed an event different from the trigger. Results: Of the 1,003 EGMs available, the triggers were AT in 640 EGMs, VT in 76, SBR in 105, and PMT in 178 EGMs. Four EGMs were triggered by magnet application. The trigger was confirmed in 614 EGMs (62%): 62% of AT episodes, 18% of VT episodes, 100% of SBR episodes, and 54% of PMT episodes. In 385 cases (45%), the EGMs revealed false-positive events due to far-field sensing (39%), noise and myopotential sensing (26%), sinus tachycardias (21%), double counting (9%), exit block (4%), and undersensing (1%). Conclusion: This large-scale study of stored EGMs revealed their value in validating diagnostic counter data. Therapeutic decisions should not be based on diagnostic counters alone; they should be validated by sophisticated tools like stored EGMs.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1540-8159.2005.00159.x
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  • 4
    Electronic Resource
    Electronic Resource
    Causal Effect Models for Realistic Individualized Treatment and Intention to Treat Rules (2007)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 3 (2007), S. 3 
    Details
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Marginal structural models (MSM) are an important class of models in causal inference. Given a longitudinal data structure observed on a sample of n independent and identically distributed experimental units, MSM model the counterfactual outcome distribution corresponding with a static treatment intervention, conditional on user-supplied baseline covariates. Identification of a static treatment regimen-specific outcome distribution based on observational data requires, beyond the standard sequential randomization assumption, the assumption that each experimental unit has positive probability of following the static treatment regimen. The latter assumption is called the experimental treatment assignment (ETA) assumption, and is parameter-specific. In many studies the ETA is violated because some of the static treatment interventions to be compared cannot be followed by all experimental units, due either to baseline characteristics or to the occurrence of certain events over time. For example, the development of adverse effects or contraindications can force a subject to stop an assigned treatment regimen.In this article we propose causal effect models for a user-supplied set of realistic individualized treatment rules. Realistic individualized treatment rules are defined as treatment rules which always map into the set of possible treatment options. Thus, causal effect models for realistic treatment rules do not rely on the ETA assumption and are fully identifiable from the data. Further, these models can be chosen to generalize marginal structural models for static treatment interventions. The estimating function methodology of Robins and Rotnitzky (1992) (analogue to its application in Murphy, et. al. (2001) for a single treatment rule) provides us with the corresponding locally efficient double robust inverse probability of treatment weighted estimator. In addition, we define causal effect models for "intention-to-treat" regimens. The proposed intention-to-treat interventions enforce a static intervention until the time point at which the next treatment does not belong to the set of possible treatment options, at which point the intervention is stopped. We provide locally efficient estimators of such intention-to-treat causal effects.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/ijb/vol3/iss1/3
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  • 5
    Electronic Resource
    Electronic Resource
    Statistical Learning of Origin-Specific Statically Optimal Individualized Treatment Rules (2007)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 3 (2007), S. 6 
    Details
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Consider a longitudinal observational or controlled study in which one collects chronological data over time on a random sample of subjects. The time-dependent process one observes on each subject contains time-dependent covariates, time-dependent treatment actions, and an outcome process or single final outcome of interest. A statically optimal individualized treatment rule (as introduced in van der Laan et. al. (2005), Petersen et. al. (2007)) is a treatment rule which at any point in time conditions on a user-supplied subset of the past, computes the future static treatment regimen that maximizes a (conditional) mean future outcome of interest, and applies the first treatment action of the latter regimen. In particular, Petersen et. al. (2007) clarified that, in order to be statically optimal, an individualized treatment rule should not depend on the observed treatment mechanism. Petersen et. al. (2007) further developed estimators of statically optimal individualized treatment rules based on a past capturing all confounding of past treatment history on outcome. In practice, however, one typically wishes to find individualized treatment rules responding to a user-supplied subset of the complete observed history, which may not be sufficient to capture all confounding. The current article provides an important advance on Petersen et. al. (2007) by developing locally efficient double robust estimators of statically optimal individualized treatment rules responding to such a user-supplied subset of the past. However, failure to capture all confounding comes at a price; the static optimality of the resulting rules becomes origin-specific. We explain origin-specific static optimality, and discuss the practical importance of the proposed methodology. We further present the results of a data analysis in which we estimate a statically optimal rule for switching antiretroviral therapy among patients infected with resistant HIV virus.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/ijb/vol3/iss1/6
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  • 6
    Electronic Resource
    Electronic Resource
    Identification of an obeche (Triplochiton scleroxylon) wood allergen as a class I chitinase (2005)
    Oxford, UK : Munksgaard International Publishers
    Allergy 60 (2005), S. 0 
    Details
    ISSN: 1398-9995
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine
    Notes: Background:  Wood dust is known to cause allergic occupational asthma and obeche (Triplochiton scleroxylon) is a prominent exponent in this field. However, the knowledge about wood allergens is still limited. The aim of this study was to identify and characterize obeche wood allergens.Methods:  Obeche extracts were prepared from freshly ground in comparison to 7 years stored wood dust and investigated by Sodium dodecyl sulfate-polyacrylamid gel electrophoresis, enzyme-linked allergosorbent test and immunoglobulin (Ig)E-immunoblot. Allergens were detected by specific IgE of seven obeche allergic patients’ sera and protein analysis was performed by mass spectrometry. Cross-reactivity was demonstrated by ImmunoCAP-inhibition with sera of seven obeche and four latex-allergic patients.Results:  Obeche extracts showed different protein pattern and IgE-binding capacities depend on the age of the wood dust. A 38 kDa protein was identified as major obeche wood allergen, detected by six of seven (85%) obeche allergic patients’ sera and was entitled as Trip s 1. Trip s 1 is homologous to plant class I chitinases and exhibited enzyme activity demonstrated by chitinolysis. Co-recognition or cross-reactivity of Trip s 1 according to structural similarity was seen in sera of latex allergic patients. IgE inhibition studies with obeche as solid phase and Trip s 1 and latex hevein as inhibitor demonstrated that Trip s 1 was a more effective inhibitor in obeche as well as in latex allergic patients’ sera.Conclusions:  Trip s 1 is a new obeche wood allergen of the plant class I chitinase family. This finding may explain the dominant role of obeche in sensitization against wood dust.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1398-9995.2005.00794.x
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  • 7
    Electronic Resource
    Electronic Resource
    Denmark as an International Actor 706-2006 (2006)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    World Political Science Review 2.2006, 3, art2 
    Details
    ISSN: 1935-6226
    Source: Berkeley Electronic Press Academic Journals
    Topics: Political Science
    Notes: During its long history, Denmark was able to pursue dominant foreign policy in her historical great power roles, while balancing normally was linked with her roles as a medium power. Until the 17th century, a policy of moderate dominance was the prevailing foreign policy mode, to be followed by a balancing mode, which lasted till 1864. The stunning defeat in that war reduced Danish option to a difficult choice between acquiescence and quiescence. Both are typical small state postures because of the lack of influence, but they differ on the sensitivity variable. The sensitive small state must adapt actively or passively to outside pressures, while the less sensitive small state may succeed in dodging situations where acquiescent adaptation would be required.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/wpsr/vol2/iss3/art2
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  • 8
    Electronic Resource
    Electronic Resource
    History-Adjusted Marginal Structural Models and Statically-Optimal Dynamic Treatment Regimens (2005)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 1 (2005), S. 4 
    Details
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a treatment. These models, introduced by Robins, model the marginal distributions of treatment-specific counterfactual outcomes, possibly conditional on a subset of the baseline covariates. Marginal structural models are particularly useful in the context of longitudinal data structures, in which each subject's treatment and covariate history are measured over time, and an outcome is recorded at a final time point. However, the utility of these models for some applications has been limited by their inability to incorporate modification of the causal effect of treatment by time-varying covariates. Particularly in the context of clinical decision making, such time-varying effect modifiers are often of considerable or even primary interest, as they are used in practice to guide treatment decisions for an individual. In this article we propose a generalization of marginal structural models, which we call history-adjusted marginal structural models (HA-MSM). These models allow estimation of adjusted causal effects of treatment, given the observed past, and are therefore more suitable for making treatment decisions at the individual level and for identification of time-dependent effect modifiers. Specifically, a HA-MSM models the conditional distribution of treatment-specific counterfactual outcomes, conditional on the whole or a subset of the observed past up till a time-point, simultaneously for all time-points. Double robust inverse probability of treatment weighted estimators have been developed and studied in detail for standard MSM. We extend these results by proposing a class of double robust inverse probability of treatment weighted estimators for the unknown parameters of the HA-MSM. In addition, we show that HA-MSM provide a natural approach to identifying the dynamic treatment regimen which follows, at each time-point, the history-adjusted (up till the most recent time point) optimal static treatment regimen. We illustrate our results using an example drawn from the treatment of HIV infection.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/ijb/vol1/iss1/4
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  • 9
    Electronic Resource
    Electronic Resource
    Super Learning: An Application to the Prediction of HIV-1 Drug Resistance (2007)
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art7 
    Details
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Many alternative data-adaptive algorithms can be used to learn a predictor based on observed data. Examples of such learners include decision trees, neural networks, support vector regression, least angle regression, logic regression, and the Deletion/Substitution/Addition algorithm. The optimal learner for prediction will vary depending on the underlying data-generating distribution. In this article we introduce the "super learner", a prediction algorithm that applies any set of candidate learners and uses cross-validation to select between them. Theory shows that asymptotically the super learner performs essentially as well as or better than any of the candidate learners. In this article we present the theory behind the super learner, and illustrate its performance using simulations. We further apply the super learner to a data example, in which we predict the phenotypic antiretroviral susceptibility of HIV based on viral genotype. Specifically, we apply the super learner to predict susceptibility to a specific protease inhibitor, nelfinavir, using a set of database-derived non-polymorphic treatment-selected mutations.
    Type of Medium: Electronic Resource
    URL: http://www.bepress.com/sagmb/vol6/iss1/art7
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  • 10
    Electronic Resource
    Electronic Resource
    Mental disorders in current and former heavy ecstasy (MDMA) users (2005)
    Oxford, UK : Blackwell Science Ltd
    Addiction 100 (2005), S. 0 
    Details
    ISSN: 1360-0443
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Medicine , Psychology
    Notes: Background  Ecstasy use has often been found to be associated with psychopathology, yet this research has so far been based largely on subjective symptom ratings.Aims  To investigate whether ecstasy users suffered from long-term psychopathological consequences.Measurements  We compared the prevalence of Diagnostic and Statistical Manual version IV (DSM-IV) mental disorders in 30 current and 29 former ecstasy users, 29 polydrug and 30 drug-naive controls. Groups were approximately matched by age, gender and level of education. The current ecstasy users reported a life-time dose of an average of 821 and the former ecstasy users of 768 ecstasy tablets.Findings  Ecstasy users did not significantly differ from controls in the prevalence of mental disorders, except those related to substance use. Substance-induced affective, anxiety and cognitive disorders occurred more frequently among ecstasy users than polydrug controls. The life-time prevalence of ecstasy dependence amounted to 73% in the ecstasy user groups. More than half of the former ecstasy users and nearly half of the current ecstasy users met the criteria of substance-induced cognitive disorders at the time of testing. Logistic regression analyses showed the estimated life-time doses of ecstasy to be predictive of cognitive disorders, both current and life-time.Conclusions  The motivation for ecstasy use is not likely to be self-medication of pre-existing depressive or anxiety disorders as these did not occur more frequently in the ecstasy users than in control groups or in the general population. Cognitive disorders still present after over 5 months of ecstasy abstinence may well be functional consequences of serotonergic neurotoxicity of 3,4-methylenedioxymethamphetamine (MDMA).
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1360-0443.2005.01180.x
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