Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Swallowed topical corticosteroids reduce the risk for long-lasting bolus impactions in eosinophilic esophagitis.

BACKGROUND: Long-lasting food impactions requiring endoscopic bolus removal occur frequently in patients with eosinophilic esophagitis (EoE) and harbor a risk for severe esophageal injuries. We evaluated whether treatment with swallowed topical corticosteroids is able to reduce the risk of occurrence of this complication. METHODS: We analyzed data from the Swiss EoE Cohort Study. Patients with yearly clinic visits, during which standardized assessment of symptoms, endoscopic, histologic, and laboratory findings was carried out, were included. RESULTS: A total of 206 patients (157 males) were analyzed. The median follow-up time was 5 years with a total of 703 visits (mean 3.41 visits/patient). During the follow-up period, 33 patients (16 % of the cohort) experienced 42 impactions requiring endoscopic bolus removal. We evaluated the following factors regarding the outcome 'bolus impaction' by univariate logistic regression modeling: swallowed topical corticosteroid therapy (OR 0.503, 95%-CI 0.255-0.993, P = 0.048), presence of EoE symptoms (OR 1.150, 95%-CI 0.4668-2.835, P = 0.761), esophageal stricture (OR 2.832, 95%-CI 1.508-5.321, P = 0.001), peak eosinophil count >10 eosinophils/HPF (OR 0.724, 95%-CI 0.324-1.621, P = 0.433), blood eosinophilia (OR 1.532, 95%-CI 0.569-4.118, P = 0.398), and esophageal dilation (OR 1.852, 95%-CI 1.034-3.755, P = 0.017). In the multivariate model, the following factors were significantly associated with bolus impaction: swallowed topical corticosteroid therapy (OR 0.411, 95%-CI 0.203-0.835, P = 0.014) and esophageal stricture (OR 2.666, 95%-CI 1.259-5.645, P = 0.01). Increasing frequency of use of swallowed topical steroids was associated with a lower risk for bolus impactions. CONCLUSIONS: Treatment of EoE with swallowed topical corticosteroids significantly reduces the risk for long-lasting bolus impactions.

Predicting outcome after acute basilar artery occlusion based on admission characteristics.

OBJECTIVE: To develop a simple prognostic model to predict outcome at 1 month after acute basilar artery occlusion (BAO) with readily available predictors. METHODS: The Basilar Artery International Cooperation Study (BASICS) is a prospective, observational, international registry of consecutive patients who presented with an acute symptomatic and radiologically confirmed BAO. We considered predictors available at hospital admission in multivariable logistic regression models to predict poor outcome (modified Rankin Scale [mRS] score 4-5 or death) at 1 month. We used receiver operator characteristic curves to assess the discriminatory performance of the models. RESULTS: Of the 619 patients, 429 (69%) had a poor outcome at 1 month: 74 (12%) had a mRS score of 4, 115 (19%) had a mRS score of 5, and 240 (39%) had died. The main predictors of poor outcome were older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIH Stroke Scale (NIHSS) score, and longer time to treatment. A prognostic model that combined demographic data and stroke risk factors had an area under the receiver operating characteristic curve (AUC) of 0.64. This performance improved by including findings from the neurologic examination (AUC 0.79) and CT imaging (AUC 0.80). A risk chart showed predictions of poor outcome at 1 month varying from 25 to 96%. CONCLUSION: Poor outcome after BAO can be reliably predicted by a simple model that includes older age, absence of hyperlipidemia, presence of prodromal minor stroke, higher NIHSS score, and longer time to treatment.

Spatial modelling of Lutzomyia (Nyssomyia) whitmani s.l. (Antunes & Coutinho, 1939) (Diptera: Psychodidae: Phlebotominae) habitat suitability in the state of Mato Grosso, Brazil

Lutzomyia (Nyssomyia) whitmani s.l.is the main vector of cutaneous leishmaniasis in state of Mato Grosso, but little is known about environmental determinants of its spatial distribution on a regional scale. Entomologic surveys of this sand fly species, conducted between 1996 and 2001 in 41 state municipalities, were used to investigate the relationships between environmental factors and the presence of the species, and to develop a spatial model of habitat suitability. The relationship between averaged CDC light trap indexes and 15 environmental and socio-economic factors were tested by logistic regression (LR) analysis. Spatial layers of deforestation tax and the Brazilian index of gross net production (IGNP) were identified as significant explanatory variables for vector presence in the LR model, and these were then overlaid with habitat maps. The highest habitat suitability in 2001 was obtained for the heavily deforested areas in the Central-North, South, East, and Southwest of Mato Grosso, particularly in municipalities with lower IGNP values.

Prognostic factors in left-sided endocarditis: results from the andalusian multicenter cohort

Despite medical advances, mortality in infective endocarditis (IE) is still very high. Previous studies on prognosis in IE have observed conflicting results. The aim of this study was to identify predictors of in-hospital mortality in a large multicenter cohort of left-sided IE.Methods An observational multicenter study was conducted from January 1984 to December 2006 in seven hospitals in Andalusia, Spain. Seven hundred and five left-side IE patients were included. The main outcome measure was in-hospital mortality. Several prognostic factors were analysed by univariate tests and then by multilogistic regression model. Results.The overall mortality was 29.5% (25.5% from 1984 to 1995 and 31.9% from 1996 to 2006; Odds Ratio 1.25; 95% Confidence Interval: 0.97-1.60; p = 0.07). In univariate analysis, age, comorbidity, especially chronic liver disease, prosthetic valve, virulent microorganism such as Staphylococcus aureus, Streptococcus agalactiae and fungi, and complications (septic shock, severe heart failure, renal insufficiency, neurologic manifestations and perivalvular extension) were related with higher mortality. Independent factors for mortality in multivariate analysis were: Charlson comorbidity score (OR: 1.2; 95% CI: 1.1-1.3), prosthetic endocarditis (OR: 1.9; CI: 1.2-3.1), Staphylococcus aureus aetiology (OR: 2.1; CI: 1.3-3.5), severe heart failure (OR: 5.4; CI: 3.3-8.8), neurologic manifestations (OR: 1.9; CI: 1.2-2.9), septic shock (OR: 4.2; CI: 2.3-7.7), perivalvular extension (OR: 2.4; CI: 1.3-4.5) and acute renal failure (OR: 1.69; CI: 1.0-2.6). Conversely, Streptococcus viridans group etiology (OR: 0.4; CI: 0.2-0.7) and surgical treatment (OR: 0.5; CI: 0.3-0.8) were protective factors.Conclusions Several characteristics of left-sided endocarditis enable selection of a patient group at higher risk of mortality. This group may benefit from more specialised attention in referral centers and should help to identify those patients who might benefit from more aggressive diagnostic and/or therapeutic procedures.

Acute imaging does not improve ASTRAL score's accuracy despite having a prognostic value.

BACKGROUND: The ASTRAL score was recently shown to reliably predict three-month functional outcome in patients with acute ischemic stroke. AIM: The study aims to investigate whether information from multimodal imaging increases ASTRAL score's accuracy. METHODS: All patients registered in the ASTRAL registry until March 2011 were included. In multivariate logistic-regression analyses, we added covariates derived from parenchymal, vascular, and perfusion imaging to the 6-parameter model of the ASTRAL score. If a specific imaging covariate remained an independent predictor of three-month modified Rankin score > 2, the area-under-the-curve (AUC) of this new model was calculated and compared with ASTRAL score's AUC. We also performed similar logistic regression analyses in arbitrarily chosen patient subgroups. RESULTS: When added to the ASTRAL score, the following covariates on admission computed tomography/magnetic resonance imaging-based multimodal imaging were not significant predictors of outcome: any stroke-related acute lesion, any nonstroke-related lesions, chronic/subacute stroke, leukoaraiosis, significant arterial pathology in ischemic territory on computed tomography angiography/magnetic resonance angiography/Doppler, significant intracranial arterial pathology in ischemic territory, and focal hypoperfusion on perfusion-computed tomography. The Alberta Stroke Program Early CT score on plain imaging and any significant extracranial arterial pathology on computed tomography angiography/magnetic resonance angiography/Doppler were independent predictors of outcome (odds ratio: 0·93, 95% CI: 0·87-0·99 and odds ratio: 1·49, 95% CI: 1·08-2·05, respectively) but did not increase ASTRAL score's AUC (0·849 vs. 0·850, and 0·8563 vs. 0·8564, respectively). In exploratory analyses in subgroups of different prognosis, age or stroke severity, no covariate was found to increase ASTRAL score's AUC, either. CONCLUSIONS: The addition of information derived from multimodal imaging does not increase ASTRAL score's accuracy to predict functional outcome despite having an independent prognostic value. More selected radiological parameters applied in specific subgroups of stroke patients may add prognostic value of multimodal imaging.

Influence of deep sternal wound infection on long-term survival after cardiac surgery.

BACKGROUND: This study aimed to investigate the influence of deep sternal wound infection on long-term survival following cardiac surgery. MATERIAL AND METHODS: In our institutional database we retrospectively evaluated medical records of 4732 adult patients who received open-heart surgery from January 1995 through December 2005. The predictive factors for DSWI were determined using logistic regression analysis. Then, each patient with deep sternal wound infection (DSWI) was matched with 2 controls without DSWI, according to the risk factors identified previously. After checking balance resulting from matching, short-term mortality was compared between groups using a paired test, and long-term survival was compared using Kaplan-Meier analysis and a Cox proportional hazard model. RESULTS: Overall, 4732 records were analyzed. The mean age of the investigated population was 69.3±12.8 years. DSWI occurred in 74 (1.56%) patients. Significant independent predictive factors for deep sternal infections were active smoking (OR 2.19, CI95 1.35-3.53, p=0.001), obesity (OR 1.96, CI95 1.20-3.21, p=0.007), and insulin-dependent diabetes mellitus (OR 2.09, CI95 1.05-10.06, p=0.016). Mean follow-up in the matched set was 125 months, IQR 99-162. After matching, in-hospital mortality was higher in the DSWI group (8.1% vs. 2.7% p=0.03), but DSWI was not an independent predictor of long-term survival (adjusted HR 1.5, CI95 0.7-3.2, p=0.33). CONCLUSIONS: The results presented in this report clearly show that post-sternotomy deep wound infection does not influence long-term survival in an adult general cardio-surgical patient population.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

Recanalization and Collaterals Predict Outcome in Proximal MCA Occlusion, but neither Penumbra nor Core of Stroke

Data on new predictors of outcome include penumbra core or collaterals.Objective: To test the predictive value of recanalization, collaterals, penumbra and core of ischemia for functional outcome in a large group of patients with MCA occlusion. Method: Consecutive events included prospectively in the Acute Stroke Registry and Analysis of Lausanne from April 2002 to April 2009 with an acute stroke due to proximal MCA occlusion (M1) were considered for analysis. Acute CTA were reviewed to grade the collaterals (dichotomized in poor __50% or good _50% compared to the normal side) and localization of M1 occlusion (proximal or mid-distal). Acute CTP were reviewed and reconstructed to determine penumbra, core and stroke index (penumbra/penumbra_core) of brain ischemia. Good outcome was defined by mRS 0-2 at 3 months.Results: Among 242 events (115 male, mean NIHSS 18.1, SD 5.8, mean age 66, SD 15), 42% were treated with intravenous thrombolysis, and 3% with intraarterial thrombolysis. Collateral status was rated as poor in 53% of events and proximal M1 occlusion was present in 64%. Recanalization determined at 24 hours with CTA was complete in 26% events and partial/absent in 54%.CTP was available for 212 events. Mean penumbra was 88.6 cm3 (median 84.4, SD 53.8), mean core was 54.1 cm3 (median 46.2, SD 45.7) and stroke index was 64% (median 68%, SD 25%). Good outcome was observed in 87 events (36%) and was associated in multivariate logistic regression with thrombolysis (p_0.02, OR_2.5, 95% CI 1.2-5.4), recanalization (p_0.001, OR_4.1, 95% CI 1.9-8.9), lower NIHSS (p_0.001, OR_0.84, 95% CI 0.78-0.91), male gender (p_0.01, OR_2.8, 95% CI 1.3-5.9), mRS prior to stroke (p_0.02, OR_0.5, 95% CI 0.28-0.9) and good collateral status (p_0.005, OR_3, 95% CI 1.4-6.4). Nor penumbra, nor core, nor stroke index were significant in the multivariate model, even if an association was present in the univariate model between good functional outcome and penumbra (p_0.004, OR_1.008, 95% CI 1.003-1.01), core (p_0.001, OR_0.98, 95% CI 0.976-0.99) and strokeindex (p_0.001, OR_16.7, 95% CI 4.6 59.9).Conclusion: MCA recanalization is the best predictor for good functional outcome, followed by collateral status. CTP data did not predict the functional outcome in our large group of M1 occlusion. Author Disclosures: C. Odier: None. P. Michel: Research Grant; Significant; Paion, Lundbeck. Speakers; Modest; Boehringer-Ingelheim. Consultant/Advisory Board; Modest; Boehringer- Ingelheim. Consultant/Advisory Board; Significant; Servier, Lundbeck.

Relationship of imatinib-free plasma levels and target genotype with efficacy and tolerability

Imatinib has revolutionised the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumours (GIST). Using a nonlinear mixed effects population model, individual estimates of pharmacokinetic parameters were derived and used to estimate imatinib exposure (area under the curve, AUC) in 58 patients. Plasma-free concentration was deduced from a model incorporating plasma levels of alpha(1)-acid glycoprotein. Associations between AUC (or clearance) and response or incidence of side effects were explored by logistic regression analysis. Influence of KIT genotype was also assessed in GIST patients. Both total (in GIST) and free drug exposure (in CML and GIST) correlated with the occurrence and number of side effects (e.g. odds ratio 2.7+/-0.6 for a two-fold free AUC increase in GIST; P<0.001). Higher free AUC also predicted a higher probability of therapeutic response in GIST (odds ratio 2.6+/-1.1; P=0.026) when taking into account tumour KIT genotype (strongest association in patients harbouring exon 9 mutation or wild-type KIT, known to decrease tumour sensitivity towards imatinib). In CML, no straightforward concentration-response relationships were obtained. Our findings represent additional arguments to further evaluate the usefulness of individualizing imatinib prescription based on a therapeutic drug monitoring programme, possibly associated with target genotype profiling of patients.

Cannabis dependence in Swiss adolescents: An exploration of the role of anxiety, coping styles and psychosocial difficulties

This naturalistic cross-sectional study explores how and to what extent cannabis dependence was associated with intrapersonal aspects (anxiety, coping styles) and interpersonal aspects of adolescent functioning (school status, family relationships, peer relationships, social life). A convenience sample of 110 adolescents (aged 12 to 19) was recruited and subdivided into two groups (38 with a cannabis dependence and 72 nondependent) according to DSM-IV-TR criteria for cannabis dependence. Participants completed the State-Trait Anxiety Inventory (STAI-Y), the Coping Across Situations Questionnaire (CASQ), and the Adolescent Drug Abuse Diagnosis (ADAD) interview investigating psychosocial and interpersonal problems in an adolescent's life. Factors associated with cannabis dependence were explored with logistic regression analyses. The results indicated that severity of problems in social life and peer relationships (OR = 1.68, 95% CI = 1.21 - 2.33) and avoidantcoping (OR = 4.22, 95% CI = 1.01 - 17.73) were the only discriminatory factors for cannabis dependence. This model correctly classified 84.5% of the adolescents. These findings are partially consistent with the "self-medication hypothesis" and underlined the importance of peer relationships and dysfunctional coping strategies in cannabis dependence in adolescence. Limitations of the study and implications for clinical work with adolescents are discussed.

Evaluating thermal treeline indicators based on air and soil temperature using an air-to-soil temperature transfer model

In recent research, both soil (root-zone) and air temperature have been used as predictors for the treeline position worldwide. In this study, we intended to (a) test the proposed temperature limitation at the treeline, and (b) investigate effects of season length for both heat sum and mean temperature variables in the Swiss Alps. As soil temperature data are available for a limited number of sites only, we developed an air-to-soil transfer model (ASTRAMO). The air-to-soil transfer model predicts daily mean root-zone temperatures (10cm below the surface) at the treeline exclusively from daily mean air temperatures. The model using calibrated air and root-zone temperature measurements at nine treeline sites in the Swiss Alps incorporates time lags to account for the damping effect between air and soil temperatures as well as the temporal autocorrelations typical for such chronological data sets. Based on the measured and modeled root-zone temperatures we analyzed. the suitability of the thermal treeline indicators seasonal mean and degree-days to describe the Alpine treeline position. The root-zone indicators were then compared to the respective indicators based on measured air temperatures, with all indicators calculated for two different indicator period lengths. For both temperature types (root-zone and air) and both indicator periods, seasonal mean temperature was the indicator with the lowest variation across all treeline sites. The resulting indicator values were 7.0 degrees C +/- 0.4 SD (short indicator period), respectively 7.1 degrees C +/- 0.5 SD (long indicator period) for root-zone temperature, and 8.0 degrees C +/- 0.6 SD (short indicator period), respectively 8.8 degrees C +/- 0.8 SD (long indicator period) for air temperature. Generally, a higher variation was found for all air based treeline indicators when compared to the root-zone temperature indicators. Despite this, we showed that treeline indicators calculated from both air and root-zone temperatures can be used to describe the Alpine treeline position.

Gender inequality in health among elderly people in a combined framework of socioeconomic position, family characteristics and social support

This study analyses gender inequalities in health among elderly people in Catalonia (Spain) by adopting a conceptual framework that globally considers three dimensions of health determinants : socio-economic position, family characteristics and social support. Data came from the 2006 Catalonian Health Survey. For the purposes of this study a sub-sample of people aged 65–85 years with no paid job was selected (1,113 men and 1,484 women). The health outcomes analysed were self-perceived health status, poor mental health status and long-standing limiting illness. Multiple logistic regression models separated by sex were fitted and a hierarchical model was fitted in three steps. Health status among elderly women was poorer than among the men for the three outcomes analysed. Whereas living with disabled people was positively related to the three health outcomes and confidant social support was negatively associated with all of them in both sexes, there were gender differences in other social determinants of health. Our results emphasise the importance of using an integrated approach for the analysis of health inequalities among elderly people, simultaneously considering socio-economic position, family characteristics and social support, as well as different health indicators, in order fully to understand the social determinants of the health status of older men and women.

Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.