PREDICTIVE FACTORS FOR THE PROGRESSION OF CHRONIC CHAGAS CARDIOMYOPATHY IN PATIENTS WITHOUT LEFT VENTRICULAR DYSFUNCTION

The identification of predictors for the progression of chronic Chagas cardiomyopathy (CCC) is essential to ensure adequate patient management. This study looked into a non-concurrent cohort of 165 CCC patients between 1985 and 2010 for independent predictors for CCC progression. The outcomes were worsening of the CCC scores and the onset of left ventricular dysfunction assessed by means of echo-Doppler cardiography. Patients were analyzed for social, demographic, epidemiologic, clinical and workup-related variables. A descriptive analysis was conducted, followed by survival curves based on univariate (Kaplan-Meier and Cox’s univariate model) and multivariate (Cox regression model) analysis. Patients were followed from two to 20 years (mean: 8.2). Their mean age was 44.8 years (20-77). Comparing both iterations of the study, in the second there was a statistically significant increase in the PR interval and in the QRS duration, despite a reduction in heart rates (Wilcoxon < 0.01). The predictors for CCC progression in the final regression model were male gender (HR = 2.81), Holter monitoring showing pauses equal to or greater than two seconds (HR = 3.02) increased cardiothoracic ratio (HR = 7.87) and time of use of digitalis (HR = 1.41). Patients with multiple predictive factors require stricter follow-up and treatment.

Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.

Exploring the predictive power of Google searches over the US stock market

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

Predictive markers for hepatitis C virus infection among Brazilian inmates

Hepatitis C virus (HCV) infection has quite high prevalence in the prison system, reaching rates of up to 40%. This survey aimed to estimate the prevalence of HCV infection and evaluate risk factors for this exposure among male inmates at the Ribeirão Preto Prison, State of São Paulo, Brazil, between May and August 2003. A total of 333 participants were interviewed using a standardized questionnaire and underwent immunoenzymatic assaying to investigate anti-HCV. The prevalence of HCV infection among the inmates was 8.7% (95% CI: 5.7-11.7). The participants'mean age was 30.1 years, and the prevalence was predominantly among individuals over 30 years of age. Multivariate analysis showed that the variables that were independently associated with HCV infection were age > 30 years, tattooing, history of previous hepatitis, previous injection drug use and previous needle-sharing.

Predictive factors of post-discharge surgical site infections among patients from a teaching hospital

Introduction Surgical site infections (SSIs) often manifest after patients are discharged and are missed by hospital-based surveillance. Methods We conducted a case-reference study nested in a prospective cohort of patients from six surgical specialties in a teaching hospital. The factors related to SSI were compared for cases identified during the hospital stay and after discharge. Results Among 3,427 patients, 222 (6.4%) acquired an SSI. In 138 of these patients, the onset of the SSI occurred after discharge. Neurological surgery and the use of steroids were independently associated with a greater likelihood of SSI diagnosis during the hospital stay. Conclusions Our results support the idea of a specialty-based strategy for post-discharge SSI surveillance.

Evolutionary dynamics of Chlamydia trachomatis genome and identification of molecular patterns of hypothetical protein coding genes

The obligate intracellular bacterium Chlamydia trachomatis is a human pathogen of major public health significance. Strains can be classified into 15 main serovars (A to L3) that preferentially cause ocular infections (A-C), genital infections (D-K) or lymphogranuloma venereum (LGV) (L1-L3), but the molecular basis behind their distinct tropism, ecological success and pathogenicity is not welldefined. Most chlamydial research demands culture in eukaryotic cell lines, but it is not known if stains become laboratory adapted. By essentially using genomics and transcriptomics, we aimed to investigate the evolutionary patterns underlying the adaptation of C. trachomatis to the different human tissues, given emphasis to the identification of molecular patterns of genes encoding hypothetical proteins, and to understand the adaptive process behind the C. trachomatis in vivo to in vitro transition. Our results highlight a positive selection-driven evolution of C. trachomatis towards nichespecific adaptation, essentially targeting host-interacting proteins, namely effectors and inclusion membrane proteins, where some of them also displayed niche-specific expression patterns. We also identified potential "ocular-specific" pseudogenes, and pointed out the major gene targets of adaptive mutations associated with LGV infections. We further observed that the in vivo-derived genetic makeup of C. trachomatis is not significantly compromised by its long-term laboratory propagation. In opposition, its introduction in vitro has the potential to affect the phenotype, likely yielding virulence attenuation. In fact, we observed a "genital-specific" rampant inactivation of the virulence gene CT135, which may impact the interpretation of data derived from studies requiring culture. Globally, the findings presented in this Ph.D. thesis contribute for the understanding of C.trachomatis adaptive evolution and provides new insights into the biological role of C. trachomatishypothetical proteins. They also launch research questions for future functional studies aiming toclarify the determinants of tissue tropism, virulence or pathogenic dissimilarities among C. trachomatisstrains.

Evaluation of the predictive indices for candidemia in an adult intensive care unit

INTRODUCTION: To evaluate predictive indices for candidemia in an adult intensive care unit (ICU) and to propose a new index. METHODS: A prospective cohort study was conducted between January 2011 and December 2012. This study was performed in an ICU in a tertiary care hospital at a public university and included 114 patients staying in the adult ICU for at least 48 hours. The association of patient variables with candidemia was analyzed. RESULTS: There were 18 (15.8%) proven cases of candidemia and 96 (84.2%) cases without candidemia. Univariate analysis revealed the following risk factors: parenteral nutrition, severe sepsis, surgical procedure, dialysis, pancreatitis, acute renal failure, and an APACHE II score higher than 20. For the Candida score index, the odds ratio was 8.50 (95% CI, 2.57 to 28.09); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.78, 0.71, 0.33, and 0.94, respectively. With respect to the clinical predictor index, the odds ratio was 9.45 (95%CI, 2.06 to 43.39); the sensitivity, specificity, positive predictive value, and negative predictive value were 0.89, 0.54, 0.27, and 0.96, respectively. The proposed candidemia index cutoff was 8.5; the sensitivity, specificity, positive predictive value, and negative predictive value were 0.77, 0.70, 0.33, and 0.94, respectively. CONCLUSIONS: The Candida score and clinical predictor index excluded candidemia satisfactorily. The effectiveness of the candidemia index was comparable to that of the Candida score.

Predictive factors for Leishmania infantum infection in dogs examined at a veterinary teaching hospital in Teresina, State of Piauí, Brazil

Abstract: INTRODUCTION: In Brazil, culling of seropositive dogs is one of the recommended strategies to control visceral leishmaniasis. Since infectiousness is correlated with clinical signs, control measures targeting symptomatic dogs could be more effective. METHODS: A cross-sectional study was carried out among 1,410 dogs, predictive models were developed based on clinical signs and an indirect immunofluorescence antibody test. RESULTS: The validated predictive model showed sensitivity and specificity of 86.5% and 70.0%, respectively. CONCLUSIONS: Predictive models could be used as tools to aid control programs in focusing on a smaller fraction of dogs contributing more to infection dissemination.

Predictive value of the ankle-brachial index in the evaluation of intermittent claudication

The purpose of this study was to determine whether the ankle-brachial index (ABI) could be used to predict the prognosis for a patient with intermittent claudication (IC). We studied 611 patients prospectively during 28 months of follow-up. We analyzed the predictive power of using various levels of ABI - 0.30 to 0.70 at 0.05 increments - in terms of the measure's specificity (association with a favorable outcome after exercise rehabilitation therapy) and sensitivity (association with a poor outcome after exercise rehabilitation therapy). We found that using an ABI of 0.30 as a cut-off value produced the lowest margin of error overall, but the predictive power was still low with respect to identifying the patients with a poor prognosis after non-aggressive therapeutic treatment. Further study is needed to perhaps identify a second factor that could increase the sensitivity of the test.

Predictive control of a current-source inverter for solar photovoltaic grid interface

Solar photovoltaic systems are an increasing option for electricity production, since they produce electrical energy from a clean renewable energy resource, and over the years, as a result of the research, their efficiency has been increasing. For the interface between the dc photovoltaic solar array and the ac electrical grid is necessary the use of an inverter (dc-ac converter), which should be optimized to extract the maximum power from the photovoltaic solar array. In this paper is presented a solution based on a current-source inverter (CSI) using continuous control set model predictive control (CCS-MPC). All the power circuits and respective control systems are described in detail along the paper and were tested and validated performing computer simulations. The paper shows the simulation results and are drawn several conclusions.

Paving the way for predictive diagnostics and personalized treatment of invasive aspergillosis

Invasive aspergillosis (IA) is a life-threatening fungal disease commonly diagnosed among individuals with immunological deficits, namely hematological patients undergoing chemotherapy or allogeneic hematopoietic stem cell transplantation. Vaccines are not available, and despite the improved diagnosis and antifungal therapy, the treatment of IA is associated with a poor outcome. Importantly, the risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and microbiological exposure. Recent insights into antifungal immunity have further highlighted the complexity of host-fungus interactions and the multiple pathogen-sensing systems activated to control infection. How to decode this information into clinical practice remains however, a challenging issue in medical mycology. Here, we address recent advances in our understanding of the host-fungus interaction and discuss the application of this knowledge in potential strategies with the aim of moving toward personalized diagnostics and treatment (theranostics) in immunocompromised patients. Ultimately, the integration of individual traits into a clinically applicable process to predict the risk and progression of disease, and the efficacy of antifungal prophylaxis and therapy, holds the promise of a pioneering innovation benefiting patients at risk of IA.

Predictive value of clinical and electrophysiological variables in patients with chronic chagasic cardiomyopathy and nonsustained ventricular tachycardia

OBJECTIVE: Risk stratification of patients with nonsustained ventricular tachycardia (NSVT) and chronic chagasic cardiomyopathy (CCC). METHODS: Seventy eight patients with CCC and NSVT were consecutively and prospectively studied. All patients underwent to 24-hour Holter monitoring, radioisotopic ventriculography, left ventricular angiography, and electrophysiologic study. With programmed ventricular stimulation. RESULTS: Sustained monomorphic ventricular tachycardia (SMVT) was induced in 25 patients (32%), NSVT in 20 (25.6%) and ventricular fibrillation in 4 (5.1%). In 29 patients (37.2%) no arrhythmia was inducible. During a 55.7-month-follow-up, 22 (28.2%) patients died, 16 due to sudden death, 2 due to nonsudden cardiac death and 4 due to noncardiac death. Logistic regression analysis showed that induction was the independent and main variable that predicted the occurrence of subsequent events and cardiac death (probability of 2.56 and 2.17, respectively). The Mantel-Haenszel chi-square test showed that survival probability was significantly lower in the inducible group than in the noninductible group. The percentage of patients free of events was significantly higher in the noninducible group. CONCLUSION: Induction of SMVT during programmed ventricular stimulation was a predictor of arrhythmia occurrence cardiac death and general mortality in patients with CCC and NSVT.

Arrhythmogenic cardiomyopathy of the right ventricle. Predictive value of QT interval dispersion to assess arrhythmogenic risk and sudden death

OBJECTIVE: To determine in arrhythmogenic right ventricular cardiomyopathy the value of QT interval dispersion for identifying the induction of sustained ventricular tachycardia in the electrophysiological study or the risk of sudden cardiac death. METHODS: We assessed QT interval dispersion in the 12-lead electrocardiogram of 26 patients with arrhythmogenic right ventricular cardiomyopathy. We analyzed its association with sustained ventricular tachycardia and sudden cardiac death, and in 16 controls similar in age and sex. RESULTS: (mean ± SD). QT interval dispersion: patients = 53.8±14.1ms; control group = 35.0±10.6ms, p=0.001. Patients with induction of ventricular tachycardia: 52.5±13.8ms; without induction of ventricular tachycardia: 57.5±12.8ms, p=0.420. In a mean follow-up period of 41±11 months, five sudden cardiac deaths occurred. QT interval dispersion in this group was 62.0±17.8, and in the others it was 51.9±12.8ms, p=0.852. Using a cutoff > or = 60ms to define an increase in the degree of the QT interval dispersion, we were able to identify patients at risk of sudden cardiac death with a sensitivity of 60%, a specificity of 57%, and positive and negative predictive values of 25% and 85%, respectively. CONCLUSION: Patients with arrhythmogenic right ventricular cardiomyopathy have a significant increase in the degree of QT interval dispersion when compared with the healthy population. However it, did not identify patients with induction of ventricular tachycardia in the electrophysiological study, showing a very low predictive value for defining the risk of sudden cardiac death in the population studied.

Experimental validation of a proposed single-phase five-level active rectifier operating with model predictive current control

This paper presents a model predictive current control applied to a proposed single-phase five-level active rectifier (FLAR). This current control strategy uses the discrete-time nature of the active rectifier to define its state in each sampling interval. Although the switching frequency is not constant, this current control strategy allows to follow the reference with low total harmonic distortion (THDF). The implementation of the active rectifier that was used to obtain the experimental results is described in detail along the paper, presenting the circuit topology, the principle of operation, the power theory, and the current control strategy. The experimental results confirm the robustness and good performance (with low current THDF and controlled output voltage) of the proposed single-phase FLAR operating with model predictive current control.