Meta-analysis : subclinical thyroid dysfunction and the risk for coronary heart disease and mortality

Rapport de synthèse : Description : ce travail de thèse évalue de façon systématique les études sur l'association entre les dysfonctions thyroïdiennes infracliniques d'une part, et la maladie coronarienne et la mortalité d'autre part. Les hypothyroïdies infracliniques affectent environ 4-5% de la population adulte alors que la prévalence de l'hyperthyroïdie infraclinique est inférieure (environ 1%). L'éventuelle association entre elles pourrait justifier un dépistage systématique des dysfonctions thyroïdiennes infracliniques. Les précédentes études sur l'association entre l'hypothyroïdie infraclinique et la maladie coronarienne ont donné des résultats conflictuels. La parution de nouveaux articles récents basés sur de grandes cohortes prospectives nous a permis d'effectuer une méta-analyse basée uniquement sur des études de cohorte prospectives, augmentant ainsi la validité des résultats. Résultats: 10 des 12 études identifiées pour notre revue systématique sont basées sur des cohortes issues de la population générale («population-based »), regroupant en tout 14 449 participants. Ces 10 études examinent toutes le risque associé à l'hypothyroïdie infraclinique (avec 2134 événements coronariens et 2822 décès), alors que 5 étudient également le risque associé à l'hyperthyroïdie infraclinique (avec 1392 événements coronariens et 1993 décès). En utilisant un modèle statistique de type random-effect model, le risque relatif [RR] lié à l'hypothyroïdie infraclinique pour la maladie coronarienne est de 1.20 (intervalle de confiance [IC] de 95%, 0.97 à 1.49). Le risque diminue lorsque l'on regroupe uniquement les études de meilleure qualité (RR compris entre 1.02 et 1.08). Il est plus élevé parmi les participants de moins de 65 ans (RR, 1.51 [IC, 1.09 à 2.09] et 1.05 [IC, 0.90 à 1.22] pour les études dont l'âge moyen des participants est >_ 65 ans). Le RR de la mortalité cardiovasculaire est de 1.18 (IC, 0.98 à 1.42) et de 1.12 (IC, 0.99 à 1.26) pour la mortalité totale. En cas d'hyperthyroïdie infraclinique, les RR de la maladie coronarienne sont de 1.21 (IC, 0.88 à 1.68), de 1.19 (IC, 0.81 à 1.76) pour la mortalité cardiovasculaire, et de 1.12 (IC, 0.89 à 1.42) pour la mortalité totale. Conclusions et perspectives : nos résultats montrent que les dysfonctions thyroïdiennes infracliniques (hypothyroïdie et hyperthyroïdie infracliniques) représentent un facteur de risque modifiable, bien que modéré, de la maladie coronarienne et de la mortalité. L'efficacité du traitement de ces dysfonctions thyroïdiennes infracliniques doit encore être prouvée du point de vue cardiovasculaire et de la mortalité. Il est nécessaire d'effectuer des études contrôlées contre placebo avec le risque cardiovasculaire et la mortalité comme critères d'efficacité, avant de pouvoir proposer des recommandations sur le dépistage des ces dysfonctions thyroïdiennes dans la population adulte.

Effects of Three Types of Exercise Interventions on Healthy Old Adults' Gait Speed : A Systematic Review and Meta-Analysis.

BACKGROUND: Habitual walking speed predicts many clinical conditions later in life, but it declines with age. However, which particular exercise intervention can minimize the age-related gait speed loss is unclear. PURPOSE: Our objective was to determine the effects of strength, power, coordination, and multimodal exercise training on healthy old adults' habitual and fast gait speed. METHODS: We performed a computerized systematic literature search in PubMed and Web of Knowledge from January 1984 up to December 2014. Search terms included 'Resistance training', 'power training', 'coordination training', 'multimodal training', and 'gait speed (outcome term). Inclusion criteria were articles available in full text, publication period over past 30 years, human species, journal articles, clinical trials, randomized controlled trials, English as publication language, and subject age ≥65 years. The methodological quality of all eligible intervention studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. We computed weighted average standardized mean differences of the intervention-induced adaptations in gait speed using a random-effects model and tested for overall and individual intervention effects relative to no-exercise controls. RESULTS: A total of 42 studies (mean PEDro score of 5.0 ± 1.2) were included in the analyses (2495 healthy old adults; age 74.2 years [64.4-82.7]; body mass 69.9 ± 4.9 kg, height 1.64 ± 0.05 m, body mass index 26.4 ± 1.9 kg/m(2), and gait speed 1.22 ± 0.18 m/s). The search identified only one power training study, therefore the subsequent analyses focused only on the effects of resistance, coordination, and multimodal training on gait speed. The three types of intervention improved gait speed in the three experimental groups combined (n = 1297) by 0.10 m/s (±0.12) or 8.4 % (±9.7), with a large effect size (ES) of 0.84. Resistance (24 studies; n = 613; 0.11 m/s; 9.3 %; ES: 0.84), coordination (eight studies, n = 198; 0.09 m/s; 7.6 %; ES: 0.76), and multimodal training (19 studies; n = 486; 0.09 m/s; 8.4 %, ES: 0.86) increased gait speed statistically and similarly. CONCLUSIONS: Commonly used exercise interventions can functionally and clinically increase habitual and fast gait speed and help slow the loss of gait speed or delay its onset.

Chronic disease management programmes for adults with asthma (intervention Review)

BACKGROUND: The burden of asthma on patients and healthcare systems is substantial. Interventions have been developed to overcome difficulties in asthma management. These include chronic disease management programmes, which are more than simple patient education, encompassing a set of coherent interventions that centre on the patients' needs, encouraging the co-ordination and integration of health services provided by a variety of healthcare professionals, and emphasising patient self-management as well as patient education. OBJECTIVES: To evaluate the effectiveness of chronic disease management programmes for adults with asthma. SEARCH METHODS: Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register, MEDLINE (MEDLINE In-Process and Other Non-Indexed Citations), EMBASE, CINAHL, and PsycINFO were searched up to June 2014. We also handsearched selected journals from 2000 to 2012 and scanned reference lists of relevant reviews. SELECTION CRITERIA: We included individual or cluster-randomised controlled trials, non-randomised controlled trials, and controlled before-after studies comparing chronic disease management programmes with usual care in adults over 16 years of age with a diagnosis of asthma. The chronic disease management programmes had to satisfy at least the following five criteria: an organisational component targeting patients; an organisational component targeting healthcare professionals or the healthcare system, or both; patient education or self-management support, or both; active involvement of two or more healthcare professionals in patient care; a minimum duration of three months. DATA COLLECTION AND ANALYSIS: After an initial screen of the titles, two review authors working independently assessed the studies for eligibility and study quality; they also extracted the data. We contacted authors to obtain missing information and additional data, where necessary. We pooled results using the random-effects model and reported the pooled mean or standardised mean differences (SMDs). MAIN RESULTS: A total of 20 studies including 81,746 patients (median 129.5) were included in this review, with a follow-up ranging from 3 to more than 12 months. Patients' mean age was 42.5 years, 60% were female, and their asthma was mostly rated as moderate to severe. Overall the studies were of moderate to low methodological quality, because of limitations in their design and the wide confidence intervals for certain results.Compared with usual care, chronic disease management programmes resulted in improvements in asthma-specific quality of life (SMD 0.22, 95% confidence interval (CI) 0.08 to 0.37), asthma severity scores (SMD 0.18, 95% CI 0.05 to 0.30), and lung function tests (SMD 0.19, 95% CI 0.09 to 0.30). The data for improvement in self-efficacy scores were inconclusive (SMD 0.51, 95% CI -0.08 to 1.11). Results on hospitalisations and emergency department or unscheduled visits could not be combined in a meta-analysis because the data were too heterogeneous; results from the individual studies were inconclusive overall. Only a few studies reported results on asthma exacerbations, days off work or school, use of an action plan, and patient satisfaction. Meta-analyses could not be performed for these outcomes. AUTHORS' CONCLUSIONS: There is moderate to low quality evidence that chronic disease management programmes for adults with asthma can improve asthma-specific quality of life, asthma severity, and lung function tests. Overall, these results provide encouraging evidence of the potential effectiveness of these programmes in adults with asthma when compared with usual care. However, the optimal composition of asthma chronic disease management programmes and their added value, compared with education or self-management alone that is usually offered to patients with asthma, need further investigation.

Impact of Aldosterone Antagonists on Sudden Cardiac Death Prevention in Heart Failure and Post-Myocardial Infarction Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND AND OBJECTIVES: Sudden cardiac death (SCD) is a severe burden of modern medicine. Aldosterone antagonist is publicized as effective in reducing mortality in patients with heart failure (HF) or post myocardial infarction (MI). Our study aimed to assess the efficacy of AAs on mortality including SCD, hospitalization admission and several common adverse effects. METHODS: We searched Embase, PubMed, Web of Science, Cochrane library and clinicaltrial.gov for randomized controlled trials (RCTs) assigning AAs in patients with HF or post MI through May 2015. The comparator included standard medication or placebo, or both. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Event rates were compared using a random effects model. Prospective RCTs of AAs with durations of at least 8 weeks were selected if they included at least one of the following outcomes: SCD, all-cause/cardiovascular mortality, all-cause/cardiovascular hospitalization and common side effects (hyperkalemia, renal function degradation and gynecomastia). RESULTS: Data from 19,333 patients enrolled in 25 trials were included. In patients with HF, this treatment significantly reduced the risk of SCD by 19% (RR 0.81; 95% CI, 0.67-0.98; p = 0.03); all-cause mortality by 19% (RR 0.81; 95% CI, 0.74-0.88, p<0.00001) and cardiovascular death by 21% (RR 0.79; 95% CI, 0.70-0.89, p<0.00001). In patients with post-MI, the matching reduced risks were 20% (RR 0.80; 95% CI, 0.66-0.98; p = 0.03), 15% (RR 0.85; 95% CI, 0.76-0.95, p = 0.003) and 17% (RR 0.83; 95% CI, 0.74-0.94, p = 0.003), respectively. Concerning both subgroups, the relative risks respectively decreased by 19% (RR 0.81; 95% CI, 0.71-0.92; p = 0.002) for SCD, 18% (RR 0.82; 95% CI, 0.77-0.88, p < 0.0001) for all-cause mortality and 20% (RR 0.80; 95% CI, 0.74-0.87, p < 0.0001) for cardiovascular mortality in patients treated with AAs. As well, hospitalizations were significantly reduced, while common adverse effects were significantly increased. CONCLUSION: Aldosterone antagonists appear to be effective in reducing SCD and other mortality events, compared with placebo or standard medication in patients with HF and/or after a MI.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Random mating with a finite number of matings.

Random mating is the null model central to population genetics. One assumption behind random mating is that individuals mate an infinite number of times. This is obviously unrealistic. Here we show that when each female mates a finite number of times, the effective size of the population is substantially decreased.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

The average inter-crossing number of equilateral random walks and polygons

In this paper, we study the average inter-crossing number between two random walks and two random polygons in the three-dimensional space. The random walks and polygons in this paper are the so-called equilateral random walks and polygons in which each segment of the walk or polygon is of unit length. We show that the mean average inter-crossing number ICN between two equilateral random walks of the same length n is approximately linear in terms of n and we were able to determine the prefactor of the linear term, which is a = (3 In 2)/(8) approximate to 0.2599. In the case of two random polygons of length n, the mean average inter-crossing number ICN is also linear, but the prefactor of the linear term is different from that of the random walks. These approximations apply when the starting points of the random walks and polygons are of a distance p apart and p is small compared to n. We propose a fitting model that would capture the theoretical asymptotic behaviour of the mean average ICN for large values of p. Our simulation result shows that the model in fact works very well for the entire range of p. We also study the mean ICN between two equilateral random walks and polygons of different lengths. An interesting result is that even if one random walk (polygon) has a fixed length, the mean average ICN between the two random walks (polygons) would still approach infinity if the length of the other random walk (polygon) approached infinity. The data provided by our simulations match our theoretical predictions very well.

A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

Randomized observation periods for the compound Poisson risk model: Dividends

In the framework of the classical compound Poisson process in collective risk theory, we study a modification of the horizontal dividend barrier strategy by introducing random observation times at which dividends can be paid and ruin can be observed. This model contains both the continuous-time and the discrete-time risk model as a limit and represents a certain type of bridge between them which still enables the explicit calculation of moments of total discounted dividend payments until ruin. Numerical illustrations for several sets of parameters are given and the effect of random observation times on the performance of the dividend strategy is studied.

Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

The influence of Bone Morphogenic Protein-2 on the consolidation phase in a distraction osteogenesis model.

We asked whether locally applied recombinant-Bone Morphogenic Protein-2 (rh-BMP-2) with an absorbable Type I collagen sponge (ACS) carrier could enhance the consolidation phase in a callotasis model. We performed unilateral transverse osteotomy of the tibia in 21 immature male rabbits. After a latency period of 7 days, a 3-weeks distraction was begun at a rate of 0.5mm/12h. At the end of the distraction period (Day 28) animals were randomly divided into three groups and underwent a second surgical procedure: 6 rabbits in Group I (Control group; the callus was exposed and nothing was added), 6 rabbits in Group II (ACS group; receiving the absorbable collagen sponge soaked with saline) and 9 rabbits in Group III (rh-BMP-2/ACS group; receiving the ACS soaked with 100μg/kg of rh-BMP-2, Inductos(®), Medtronic). Starting at Day 28 we assessed quantitative and qualitative radiographic parameters as well as densitometric parameters every two weeks (Days 28, 42, 56, 70 and 84). Animals were sacrificed after 8 weeks of consolidation (Day 84). Qualitative radiographic evaluation revealed hypertrophic calluses in the Group III animals. The rh-BMP-2/ACS also influenced the development of the cortex of the calluses as shown by the modified radiographic patterns in Group III when compared to Groups I and II. Densitometric analysis revealed the bone mineral content (BMC) was significantly higher in the rh-BMP-2/ACS treated animals (Group III).