Clinical predictors for fatal pulmonary embolism in 15520 patients with venous thromboembolism - Findings from the Registro Informatizado de la Enfermedad TromboEmbolica venosa (RIETE) registry

BACKGROUND Clinical predictors for fatal pulmonary embolism (PE) in patients with venous thromboembolism have never been studied. METHODS AND RESULTS Using data from the international prospective Registro Informatizado de la Enfermedad TromboEmbolica venosa (RIETE) registry about patients with objectively confirmed symptomatic acute venous thromboembolism, we determined independent predictive factors for fatal PE. Between March 2001 and July 2006, 15520 consecutive patients (mean age+/-SD, 66.3+/-16.9 years; 49.7% men) with acute venous thromboembolism were included. Symptomatic deep-vein thrombosis without symptomatic PE was observed in 58.0% (n=9008) of patients, symptomatic nonmassive PE in 40.4% (n=6264), and symptomatic massive PE in 1.6% (n=248). At 3 months, the cumulative rates of overall mortality and fatal PE were 8.65% and 1.68%, respectively. On multivariable analysis, patients with symptomatic nonmassive PE at presentation exhibited a 5.42-fold higher risk of fatal PE compared with patients with deep-vein thrombosis without symptomatic PE (P<0.001). The risk of fatal PE was multiplied by 17.5 in patients presenting with a symptomatic massive PE. Other clinical factors independently associated with an increased risk of fatal PE were immobilization for neurological disease, age >75 years, and cancer. CONCLUSIONS PE remains a potentially fatal disease. The clinical predictors identified in the present study should be included in any clinical risk stratification scheme to optimally adapt the treatment of PE to the risk of the fatal outcome.

Evaluation of a mixed approach combining stationary and wearable systems to monitor gait over long distance.

Thanks to decades of research, gait analysis has become an efficient tool. However, mainly due to the price of the motion capture systems, standard gait laboratories have the capability to measure only a few consecutive steps of ground walking. Recently, wearable systems were proposed to measure human motion without volume limitation. Although accurate, these systems are incompatible with most of existing calibration procedures and several years of research will be necessary for their validation. A new approach consisting of using a stationary system with a small capture volume for the calibration procedure and then to measure gait using a wearable system could be very advantageous. It could benefit from the knowledge related to stationary systems, allow long distance monitoring and provide new descriptive parameters. The aim of this study was to demonstrate the potential of this approach. Thus, a combined system was proposed to measure the 3D lower body joints angles and segmental angular velocities. It was then assessed in terms of reliability towards the calibration procedure, repeatability and concurrent validity. The dispersion of the joint angles across calibrations was comparable to those of stationary systems and good reliability was obtained for the angular velocities. The repeatability results confirmed that mean cycle kinematics of long distance walks could be used for subjects' comparison and pointed out an interest for the variability between cycles. Finally, kinematics differences were observed between participants with different ankle conditions. In conclusion, this study demonstrated the potential of a mixed approach for human movement analysis.

Soluble inflammatory markers as predictors of virological response in patients with chronic hepatitis C virus infection treated with interferon-α plus ribavirin

The host immune response plays an important role in viral clearance in patients who are chronically infected with hepatitis C virus (HCV) and are treated with interferon and ribavirin. Activation of the immune system involves the release of pro and anti-inflammatory molecules that can be measured in plasma samples. The present study aimed to evaluate the association between pretreatment plasma levels of chemokines and soluble tumor necrosis factor receptors (sTNF-R) and the virological response in treated patients with chronic hepatitis C infection. Forty-one chronically-infected HCV patients that were being treated with interferon-α (IFN-α) plus ribavirin were included in the study. Socio-demographic, clinical and laboratory data were collected and pretreatment plasma levels of chemokine CCL2, CCL3, CCL11, CCL24, chemokine CXCL9, CXCL10, sTNF-R1 and sTNF-R2 were measured. The virological response was assessed at treatment week 12, at the end of treatment and 24 weeks after treatment. Pretreatment CXCL10 levels were significantly higher in patients without an early virological response (EVR) or sustained virological response (SVR) compared to responders [512.9 pg/mL vs. 179.1 pg/mL (p = 0.011) and 289.9 pg/mL vs. 142.7 pg/mL (p = 0.045), respectively]. The accuracy of CXCL10 as a predictor of the absence of EVR and SVR was 0.79 [confidence interval (CI) 95%: 0.59-0.99] and 0.69 (CI 95%: 0.51-0.87), respectively. Pretreatment plasma levels of the other soluble inflammatory markers evaluated were not associated with a treatment response. Pretreatment CXCL10 levels were predictive of both EVR and SVR to IFN-α and ribavirin and may be useful in the evaluation of candidates for therapy.

Predicting spatial patterns of plant biodiversity : from species to communities

Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study.

BACKGROUND: Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood. METHODS: Data on self-reported missed doses of cART was collected every 6 months in Swiss HIV Cohort Study participants. We identified behavioral groups associated with specific cART adherence patterns using trajectory analyses. Repeated measures logistic regression identified predictors of changes in adherence between consecutive visits. RESULTS: Six thousand seven hundred nine individuals completed 49,071 adherence questionnaires [median 8 (interquartile range: 5-10)] during a median follow-up time of 4.5 years (interquartile range: 2.4-5.1). Individuals were clustered into 4 adherence groups: good (51.8%), worsening (17.4%), improving (17.6%), and poor adherence (13.2%). Independent predictors of worsening adherence were younger age, basic education, loss of a roommate, starting intravenous drug use, increasing alcohol intake, depression, longer time with HIV, onset of lipodystrophy, and changing care provider. Independent predictors of improvements in adherence were regimen simplification, changing class of cART, less time on cART, and starting comedications. CONCLUSIONS: Treatment, behavioral changes, and life events influence patterns of drug intake in HIV patients. Clinical care providers should routinely monitor factors related to worsening adherence and intervene early to reduce the risk of treatment failure and drug resistance.

Rate and predictors of service disengagement in an epidemiological first-episode psychosis cohort.

OBJECTIVES: To assess the prevalence and predictors of service disengagement in a treated epidemiological cohort of first-episode psychosis (FEP) patients. METHODS: The Early Psychosis Prevention and Intervention Centre (EPPIC) in Australia admitted 786 FEP patients from January 1998 to December 2000. Treatment at EPPIC is scheduled for 18 months. Data were collected from patients' files using a standardized questionnaire. Seven hundred four files were available; 44 were excluded, because of a non-psychotic diagnosis at endpoint (n=43) or missing data on service disengagement (n=1). Rate of service disengagement was the outcome of interest, as well as pre-treatment, baseline, and treatment predictors of service disengagement, which were examined via Cox proportional hazards models. RESULTS: 154 patients (23.3%) disengaged from service. A past forensic history (Hazard ratio [HR]=1.69; 95%CI 1.17-2.45), lower severity of illness at baseline (HR=0.59; 95%CI 0.48-0.72), living without family at discharge (HR=1.75; 95%CI 1.22-2.50) and persistence of substance use disorder during treatment (HR=2.30; 95%CI 1.45-3.66) were significant predictors of disengagement from service. CONCLUSIONS: While engagement strategies are a core element in the treatment of first-episode psychosis, particular attention should be paid to these factors associated with disengagement. Involvement of the family in the treatment process, and focusing on reduction of substance use, need to be pursued in early intervention services.

Predictors of local malaria outbreaks: an approach to the development of an early warning system in Colombia

Risk factor surveillance is a complementary tool of morbidity and mortality surveillance that improves the likelihood that public health interventions are implemented in a timely fashion. The aim of this study was to identify population predictors of malaria outbreaks in endemic municipalities of Colombia with the goal of developing an early warning system for malaria outbreaks. We conducted a multiple-group, exploratory, ecological study at the municipal level. Each of the 290 municipalities with endemic malaria that we studied was classified according to the presence or absence of outbreaks. The measurement of variables was based on historic registries and logistic regression was performed to analyse the data. Altitude above sea level [odds ratio (OR) 3.65, 95% confidence interval (CI) 1.34-9.98], variability in rainfall (OR 1.85, 95% CI 1.40-2.44) and the proportion of inhabitants over 45 years of age (OR 0.17, 95% CI 0.08-0.38) were factors associated with malaria outbreaks in Colombian municipalities. The results suggest that environmental and demographic factors could have a significant ability to predict malaria outbreaks on the municipal level in Colombia. To advance the development of an early warning system, it will be necessary to adjust and standardise the collection of required data and to evaluate the accuracy of the forecast models.

A pilot study combining individual-based smoking cessation counseling, pharmacotherapy, and dental hygiene intervention.

BACKGROUND: Dentists are in a unique position to advise smokers to quit by providing effective counseling on the various aspects of tobacco-induced diseases. The present study assessed the feasibility and acceptability of integrating dentists in a medical smoking cessation intervention. METHODS: Smokers willing to quit underwent an 8-week smoking cessation intervention combining individual-based counseling and nicotine replacement therapy and/or bupropion, provided by a general internist. In addition, a dentist performed a dental exam, followed by an oral hygiene treatment and gave information about chronic effects of smoking on oral health. Outcomes were acceptability, global satisfaction of the dentist's intervention, and smoking abstinence at 6-month. RESULTS: 39 adult smokers were included, and 27 (69%) completed the study. Global acceptability of the dental intervention was very high (94% yes, 6% mostly yes). Annoyances at the dental exam were described as acceptable by participants (61% yes, 23% mostly yes, 6%, mostly no, 10% no). Participants provided very positive qualitative comments about the dentist counseling, the oral exam, and the resulting motivational effect, emphasizing the feeling of oral cleanliness and health that encouraged smoking abstinence. At the end of the intervention (week 8), 17 (44%) participants reported smoking abstinence. After 6 months, 6 (15%, 95% CI 3.5 to 27.2) reported a confirmed continuous smoking abstinence. DISCUSSION: We explored a new multi-disciplinary approach to smoking cessation, which included medical and dental interventions. Despite the small sample size and non-controlled study design, the observed rate was similar to that found in standard medical care. In terms of acceptability and feasibility, our results support further investigations in this field. TRIAL REGISTRATION NUMBER: ISRCTN67470159.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Syphilis in HIV-infected patients: Predictors for serological failure and serofast state.

Purpose: HIV-infected patients treated for syphilis may be at increased risk for serological failure and serofast state. Our aim was to analyse serological response to treatment in HIV-infected patients diagnosed with syphilis, and factors associated with serological cure and serofast state. Methods: Open-label, no controlled study of a series of HIV- patients diagnosed with syphilis during 2004-2011. Patients were categorized by rapid plasma reagin titer (RPR) into success (4-fold decrease in RPR by 12 or 24 months after treatment of early or late syphilis), serofast (success with persistently stable reactive RPR), and failure/ re-infection ( failure to decrease 4-fold in RPR by 12 or 24 months after treatment or sustained 4-fold increase in RPR after treatment response). Results: 141 HIV- patients were diagnosed with syphilis during the study period (104 early syphilis, 36 late or indeterminate latent syphilis). The mean age was 36.3 years, 98.5% were male, and 87.2% homosexual men. In 46 (32.6%) cases, HIV and syphilis infection diagnosis were coincident (mean CD4 457/mm3 and HIV-VL 4.72 log10). Among patients with prior known HIV infection, 65 were on antiretroviral therapy (ART) at syphilis diagnosis (mean CD4 469/ mm3, 76.9% undetectable HIV-VL). 116 patients satisfied criteria for serological response analysis (89 early, 24 late/indeterminate). At 12 months of early syphilis treatment (89.2% penicillin) there were 16 (18%) failures, and at 24 months of late/indeterminate syphilis (91.7% penicillin) there were 5 (18.5%) failures. Overall, 36 (31.0%) patients presented serofast state. Treatment failure was related with lower CD4 count (295 vs 510/μL; p=0.045) only in patients with coincident diagnosis. Serofast state was related with older age (41 vs 36 years; p=0.024), and lower CD4 count (391 vs 513/mm3; p=0.026). Conclusions: In this series of HIV-infected patients, with many patients on ART and with good immunological and virological parameters, serological failure and serofast state were frequent. Immunological status, and age could influence on serological response to syphilis treatment in HIV-infected patients.

Tumour necrosis factor -308 and -238 promoter polymorphisms are predictors of a null virological response in the treatment of Brazilian hepatitis C patients

Certain host single nucleotide polymorphisms (SNPs) affect the likelihood of a sustained virological response (SVR) to treatment in subjects infected with hepatitis C virus (HCV). SNPs in the promoters of interleukin (IL)-10 (-1082 A/G, rs1800896), myxovirus resistance protein 1 (-123 C/A, rs17000900 and -88 G/T, rs2071430) and tumour necrosis factor (TNF) (-308 G/A, rs1800629 and -238 G/A, rs361525) genes and the outcome of PEGylated α-interferon plus ribavirin therapy were investigated. This analysis was performed in 114 Brazilian, HCV genotype 1-infected patients who had a SVR and in 85 non-responders and 64 relapsers. A significantly increased risk of having a null virological response was observed in patients carrying at least one A allele at positions -308 [odds ratios (OR) = 2.58, 95% confidence intervals (CI) = 1.44-4.63, p = 0.001] or -238 (OR = 7.33, 95% CI = 3.59-14.93, p < 0.001) in the TNF promoter. The risk of relapsing was also elevated (-308: OR = 2.87, 95% CI = 1.51-5.44, p = 0.001; -238: OR = 4.20, 95% CI = 1.93-9.10, p < 0.001). Multiple logistic regression of TNF diplotypes showed that patients with at least two copies of the A allele had an even higher risk of having a null virological response (OR = 16.43, 95% CI = 5.70-47.34, p < 0.001) or relapsing (OR = 6.71, 95% CI = 2.18-20.66, p = 0.001). No statistically significant association was found between the other SNPs under study and anti-HCV therapy response.

An interdisciplinary HIV-adherence program combining motivational interviewing and electronic antiretroviral drug monitoring.

To ensure successful treatment, HIV patients must maintain a high degree of medication adherence over time. Since August 2004, patients who are (or are at risk of) experiencing problems with their HIV antiretroviral therapy (ART) have been referred by their physicians to an interdisciplinary HIV-adherence program. The program consists of a multifactorial intervention along with electronic drug monitoring (MEMS(TM)). The pharmacists organize individualized semi-structured motivational interviews based on cognitive, emotional, behavioral, and social issues. At the end of each session, the patient brings an adherence report to the physician. This enables the physician to use the adherence results to evaluate the treatment plan. The aim of this study was to retrospectively analyze this on-going interdisciplinary HIV-adherence program. All patients who were included between August 2004 and the end of April 2008 were analyzed. One hundred and four patients were included (59% women, median age 39 (31.0, 46.0) years, 42% black ethnicity). Eighty (77%) patients were ART-experienced patients and 59% had a protease inhibitor-based treatment. The retention rate was high (92%) in the program. Patient inclusion in this HIV-adherence program was determined by patient issues for naive patients and by nonadherence or suboptimal clinical outcomes for ART-experienced patients. The median time spent by a subject at the pharmacy was 35 (25.0, 48.0) minutes, half for the medication handling and half for the interview. The adherence results showed a persistence of 87% and an execution of 88%. Proportion of undetectable subjects increased during study. In conclusion, retention and persistence rates were high in this highly selected problematic population.

Combining rimonabant and fentanyl in a single entity: preparation and pharmacological results.

Based on numerous pharmacological studies that have revealed an interaction between cannabinoid and opioid systems at the molecular, neurochemical, and behavioral levels, a new series of hybrid molecules has been prepared by coupling the molecular features of two wellknown drugs, ie, rimonabant and fentanyl. The new compounds have been tested for their affinity and functionality regarding CB1 and CB2 cannabinoid and μ opioid receptors. In [(35)S]-GTPγS (guanosine 5'-O-[gamma-thio]triphosphate) binding assays from the post-mortem human frontal cortex, they proved to be CB1 cannabinoid antagonists and μ opioid antagonists. Interestingly, in vivo, the new compounds exhibited a significant dual antagonist action on the endocannabinoid and opioid systems.