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.

Predictive factors of in-hospital mortality and of severe perioperative complications in myocardial revascularization surgery

OBJECTIVE: To investigate preoperative predictive factors of severe perioperative intercurrent events and in-hospital mortality in coronary artery bypass graft (CABG) surgery and to develop specific models of risk prediction for these events, mainly those that can undergo changes in the preoperative period. METHODS: We prospectively studied 453 patients who had undergone CABG. Factors independently associated with the events of interest were determined with multiple logistic regression and Cox proportional hazards regression model. RESULTS: The mortality rate was 11.3% (51/453), and 21.2% of the patients had 1 or more perioperative intercurrent events. In the final model, the following variables remained associated with the risk of intercurrent events: age ³ 70 years, female sex, hospitalization via SUS (Sistema Único de Saúde - the Brazilian public health system), cardiogenic shock, ischemia, and dependence on dialysis. Using multiple logistic regression for in-hospital mortality, the following variables participated in the model of risk prediction: age ³ 70 years, female sex, hospitalization via SUS, diabetes, renal dysfunction, and cardiogenic shock. According to the Cox regression model for death within the 7 days following surgery, the following variables remained associated with mortality: age ³ 70 years, female sex, cardiogenic shock, and hospitalization via SUS. CONCLUSION: The aspects linked to the structure of the Brazilian health system, such as factors of great impact on the results obtained, indicate that the events investigated also depend on factors that do not relate to the patient's intrinsic condition.

Predictive factors of complications after coronary stent implantation

OBJECTIVE: To analyze the predictive factors of complications after implantation of coronary stents in a consecutive cohort study. METHODS: Clinical and angiographic characteristics related to the procedure were analyzed, and the incidence of major cardiovascular complications (myocardial infarction, urgent surgery, new angioplasty, death) in the in-hospital phase were recorded. Data were stored in an Access database and analyzed by using the SPSS 6.0 statistical program and a stepwise backwards multiple logistic regression model. RESULTS: One thousand eighteen (mean age of 61±11 years, 29% females) patients underwent 1,070 stent implantations. The rate of angiographic success was 96.8%, the rate of clinical success was 91%, and the incidence of major cardiovascular complications was 7.9%. The variables independently associated with major cardiovascular complications, with their respective odds ratio (OR) were: rescue stent, OR = 5.1 (2.7-9.6); filamentary stent, OR = 4.5 (2.2-9.1); first-generation tubular stent, OR = 2.4 (1.2-4.6); multiple stents, OR = 3 (1.6-5.6); complexity of the lesion, OR = 2.4 (1.1-5.1); thrombus, OR = 2 (1.1-3.5). CONCLUSION: The results stress the importance of angiographic variables and techniques in the risk of complications and draw attention to the influence of the stent's design on the result of the procedure.

Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

Background: End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. Objective: To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Methods: Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. Results: The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34%) and infections (15%). Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038), TT angiotensinogen (p = 0.08261), and family income greater than five times the minimum wage (p = 0.03089), the latter being a protective factor. Conclusions: The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene.

A Novel Algorithm to Quantify Coronary Remodeling Using Inferred Normal Dimensions

Background:Vascular remodeling, the dynamic dimensional change in face of stress, can assume different directions as well as magnitudes in atherosclerotic disease. Classical measurements rely on reference to segments at a distance, risking inappropriate comparison between dislike vessel portions.Objective:to explore a new method for quantifying vessel remodeling, based on the comparison between a given target segment and its inferred normal dimensions.Methods:Geometric parameters and plaque composition were determined in 67 patients using three-vessel intravascular ultrasound with virtual histology (IVUS-VH). Coronary vessel remodeling at cross-section (n = 27.639) and lesion (n = 618) levels was assessed using classical metrics and a novel analytic algorithm based on the fractional vessel remodeling index (FVRI), which quantifies the total change in arterial wall dimensions related to the estimated normal dimension of the vessel. A prediction model was built to estimate the normal dimension of the vessel for calculation of FVRI.Results:According to the new algorithm, “Ectatic” remodeling pattern was least common, “Complete compensatory” remodeling was present in approximately half of the instances, and “Negative” and “Incomplete compensatory” remodeling types were detected in the remaining. Compared to a traditional diagnostic scheme, FVRI-based classification seemed to better discriminate plaque composition by IVUS-VH.Conclusion:Quantitative assessment of coronary remodeling using target segment dimensions offers a promising approach to evaluate the vessel response to plaque growth/regression.

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

Predictive value of the acid fast smear for detection of Mycobacterium tuberculosis in respiratory specimens in a Reference Center of HIV/Aids in Rio de Janeiro, Brazil

In order to evaluate the predictive value of acid fast bacilii (AFB) smear for the diagnosis of Mycobacterium tuberculosis in respiratory specimens in a setting with a high prevalence of Aids and an unknown prevalence of nontuberculous mycobacteria (NTM), we retrospectively examined specimens cultured for mycobacteria between 1 September 1993 and 30 September 1994 and medical records of patients with positive culture in a General Hospital, Aids reference in Rio de Janeiro, Brazil. Seventy three per cent (1517/2077) of samples were respiratory specimens and mycobacteria were recovered from 20.6% (313/1517) of these. M. tuberculosis was identified in 94.2% (295/313) and NTM in 5.8% (18/313). The yield of positive AFB smear and of positive culture was 6.1% (93/1517) and 20.6% (313/1517), respectively. The positive predictive value (PPV) of AFB for M. tuberculosis was 98.4% in expectorated sputum and 96.4% in bronchoalveolar lavage. Forty four percent (130/295) of specimens with positive culture for M. tuberculosis and 66.7% (12/18) for NTM were from patients HIV positive. The conclusion was that in our study population, the PPV of AFB for M. tuberculosis in respiratory specimens was high and the prevalence of NTM was low despite the high prevalence of HIV positive.

Chagas disease in Mexico: an analysis of geographical distribution during the past 76 years - A review

Literature from 1928 through 2004 was compiled from different document sources published in Mexico or elsewhere. From these 907 publications, we found 19 different topics of Chagas disease study in Mexico. The publications were arranged by decade and also by state. This information was used to construct maps describing the distribution of Chagas disease according to different criteria: the disease, vectors, reservoirs, and strains. One of the major problems confronting study of this zoonotic disease is the great biodiversity of the vector species; there are 30 different species, with at least 10 playing a major role in human infection. The high variability of climates and biogeographic regions further complicate study and understanding of the dynamics of this disease in each region of the country. We used a desktop Genetic Algorithm for Rule-Set Prediction procedure to provide ecological models of organism niches, offering improved flexibility for choosing predictive environmental and ecological data. This approach may help to identify regions at risk of disease, plan vector-control programs, and explore parasitic reservoir association. With this collected information, we have constructed a data base: CHAGMEX, available online in html format.

Bonafide, type-specific human papillomavirus persistence among HIV-positive pregnant women: predictive value for cytological abnormalities, a longitudinal cohort study

This study investigated the rate of human papillomavirus (HPV) persistence, associated risk factors, and predictors of cytological alteration outcomes in a cohort of human immunodeficiency virus-infected pregnant women over an 18-month period. HPV was typed through L1 gene sequencing in cervical smears collected during gestation and at 12 months after delivery. Outcomes were defined as nonpersistence (clearance of the HPV in the 2nd sample), re-infection (detection of different types of HPV in the 2 samples), and type-specific HPV persistence (the same HPV type found in both samples). An unfavourable cytological outcome was considered when the second exam showed progression to squamous intraepithelial lesion or high squamous intraepithelial lesion. Ninety patients were studied. HPV DNA persistence occurred in 50% of the cases composed of type-specific persistence (30%) or re-infection (20%). A low CD4+T-cell count at entry was a risk factor for type-specific, re-infection, or HPV DNA persistence. The odds ratio (OR) was almost three times higher in the type-specific group when compared with the re-infection group (OR = 2.8; 95% confidence interval: 0.43-22.79). Our findings show that bonafide (type-specific) HPV persistence is a stronger predictor for the development of cytological abnormalities, highlighting the need for HPV typing as opposed to HPV DNA testing in the clinical setting.

Building predictive models of soil particle-size distribution

Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Positive predictive values of Breast Imaging Reporting and Data System (BI-RADS®) categories 3, 4 and 5 in breast lesions submitted to percutaneous biopsy

Objective To evaluate the BI-RADS as a predictive factor of suspicion for malignancy in breast lesions by correlating radiological with histological results and calculating the positive predictive value for categories 3, 4 and 5 in a breast cancer reference center in the city of São Paulo. Materials and Methods Retrospective, analytical and cross-sectional study including 725 patients with mammographic and/or sonographic findings classified as BI-RADS categories 3, 4 and 5 who were referred to the authors' institution to undergo percutaneous biopsy. The tests results were reviewed and the positive predictive value was calculated by means of a specific mathematical equation. Results Positive predictive values found for categories 3, 4 and 5 were respectively the following: 0.74%, 33.08% and 92.95%, for cases submitted to ultrasound-guided biopsy, and 0.00%, 14.90% and 100% for cases submitted to stereotactic biopsy. Conclusion The present study demonstrated high suspicion for malignancy in lesions classified as category 5 and low risk for category 3. As regards category 4, the need for systematic biopsies was observed.

Axillary ultrasound and fine-needle aspiration in preoperative staging of axillary lymph nodes in patients with invasive breast cancer

Abstract Objective: To propose an algorithm to determine the necessity for ultrasonography-guided fine-needle aspiration (US-FNA) in preoperative axillary lymph node staging of patients with invasive breast cancer. Materials and Methods: Prospective study developed at National Cancer Institute. The study sample included 100 female patients with breast cancer referred for axillary staging by US-FNA. Results: The overall US-FNA sensitivity was set at 79.4%. The positive predictive value was calculated to be 100%, and the negative predictive value, 69.5%. The US-FNA sensitivity for lymph nodes with normal sonographic features was 0%, while for indeterminate lymph nodes it was 80% and, for suspicious lymph nodes, 90.5%. In the assessment of invasive breast tumors stages T1, T2 and T3, the sensitivity was respectively 69.6%, 83.7% and 100%. US-FNA could avoid sentinel node biopsy in 54% of cases. Conclusion: Axillary ultrasonography should be included in the preoperative staging of all patients with invasive breast cancer. The addition of US-FNA in cases of lymph nodes suspicious for malignancy may prevent more than 50% of sentinel lymphadenectomies, significantly shortening the time interval to definitive therapy.

Software for calculation of reservoir active capacity with the sequent-peak algorithm

It is presented a software developed with Delphi programming language to compute the reservoir's annual regulated active storage, based on the sequent-peak algorithm. Mathematical models used for that purpose generally require extended hydrological series. Usually, the analysis of those series is performed with spreadsheets or graphical representations. Based on that, it was developed a software for calculation of reservoir active capacity. An example calculation is shown by 30-years (from 1977 to 2009) monthly mean flow historical data, from Corrente River, located at São Francisco River Basin, Brazil. As an additional tool, an interface was developed to manage water resources, helping to manipulate data and to point out information that it would be of interest to the user. Moreover, with that interface irrigation districts where water consumption is higher can be analyzed as a function of specific seasonal water demands situations. From a practical application, it is possible to conclude that the program provides the calculation originally proposed. It was designed to keep information organized and retrievable at any time, and to show simulation on seasonal water demands throughout the year, contributing with the elements of study concerning reservoir projects. This program, with its functionality, is an important tool for decision making in the water resources management.