Risk Prediction of Cardiovascular Complications in Pregnant Women With Heart Disease

Abstract Background: Heart disease in pregnancy is the leading cause of non- obstetric maternal death. Few Brazilian studies have assessed the impact of heart disease during pregnancy. Objective: To determine the risk factors associated with cardiovascular and neonatal complications. Methods: We evaluated 132 pregnant women with heart disease at a High-Risk Pregnancy outpatient clinic, from January 2005 to July 2010. Variables that could influence the maternal-fetal outcome were selected: age, parity, smoking, etiology and severity of the disease, previous cardiac complications, cyanosis, New York Heart Association (NYHA) functional class > II, left ventricular dysfunction/obstruction, arrhythmia, drug treatment change, time of prenatal care beginning and number of prenatal visits. The maternal-fetal risk index, Cardiac Disease in Pregnancy (CARPREG), was retrospectively calculated at the beginning of prenatal care, and patients were stratified in its three risk categories. Results: Rheumatic heart disease was the most prevalent (62.12%). The most frequent complications were heart failure (11.36%) and arrhythmias (6.82%). Factors associated with cardiovascular complications on multivariate analysis were: drug treatment change (p = 0.009), previous cardiac complications (p = 0.013) and NYHA class III on the first prenatal visit (p = 0.041). The cardiovascular complication rates were 15.22% in CARPREG 0, 16.42% in CARPREG 1, and 42.11% in CARPREG > 1, differing from those estimated by the original index: 5%, 27% and 75%, respectively. This sample had 26.36% of prematurity. Conclusion: The cardiovascular complication risk factors in this population were drug treatment change, previous cardiac complications and NYHA class III at the beginning of prenatal care. The CARPREG index used in this sample composed mainly of patients with rheumatic heart disease overestimated the number of events in pregnant women classified as CARPREG 1 and > 1, and underestimated it in low-risk patients (CARPREG 0).

Bactérias Gram-negativas com fator infeccioso de resistência a drogas, isoladas de crianças em dois hospitais do Rio de Janeiro

Enterobactérias com fator infeccioso de resistência a drogas, foram isoladas em fezes de 113 crianças internadas no Instituto de Puericultura da U.F.R.J e no Hospital Jesus nos períodos 1960-1964 e 1970-1973, verificando-se que 71,6% das crianças excretaram bactérias resistentes, das quais 41,3% a uma única droga e 58,7% a várias drogas.

The interaction of Gram negative bacteria and S. mansoni in mice with experimental Schistosomiasis

Animals (122 mice) were infected each with eighty cercariae of S. mansoni and subsequently challenged intravenously eight weeks later with the following gram-negative organisms. S. typhi, E. coli, Klebsiella-enterobacter species, Proteus mirabilis and Pseudomonas aeruginosa. Enumeration of bacteria in the liver, spleen and blood and S. mansoni from the portal sistem was performed from one to four weeks later in infected animals. A significant difference between infection produced by S. typhi and other gram negative organisms was observed: S. typhi persisted longer in the spleen and liver and could be recovered from S. mansoni worms up to three weeks following bacterial infection. Other gram negative bacteria disappeared from S. mansoni worms after two weeks of initial challenge. Additional animals (51 mice) infected with S. mansoni were given S. typhi, E. coli or sterile saline. After two weeks, animals were sacrificed and the recovery rate of worms from the portal system, and the mesenteric and hepatic oogram were determined. in animals infected with E. coli a significant decrease in the number of worms was observed compared to the saline control group; thirty worms were recovered in the control group compared to two worms in e. coli infected animals. In addition, the patterns of oviposition was significantly different in these latter animals suggesting complete inhibition of this process. Following S. typhi infection the difference in recovery of worms and pattern of oviposition was minimal. These findings suggest a difference in the interaction of various gram negative bacteria and S. mansoni and are consistent with the clinical observation of prolonged salmonella bacteremia in patients with schistosomiasis.

Bactérias gram negativas resistentes a antimicrobianos em alimentos

A partir de 154 espécimens de alimentos, representados por hortaliças (alface), leite e merenda escolar, obteve-se o isolamento e identificação de 400 amostras de bacilos Gram negativos. Esta amostragem se distribuiu em 339 enterobactérias (Escherichia, Shigella, Citrobacter, Klebsiella, Enterobacter, Serratia e Proteus) e 61 de gêneros afins (Acinetobacter, Flavobacterium, Aeromonas e Pseudomonas). Submetendo-se as culturas aos antimicrobianos: sulfadiazina (Su), estreptomicina (Sm), tetraciclina (Tc), cloranfenicol (Cm), canamicina (Km), ampicilina (Ap), ácido nalidíxico (Nal) e gentamicina (Gm), observou-se apenas seis estirpes sensíveis a todas as drogas e sensibilidade absoluta à Gm. A predominância dos modelos Su (27,6%) e Su-Ap (39,6%) incidiu nas enterobactérias, enquanto que, 18,0% para Ap e 9,8% para Su-Ap foram detectados nos gêneros afins. Para caracterização da resistência foram realizados testes de conjugação e a totalidade das culturas não revelou transferência para o gene que confere resistência ao ácido nalidíxico. Relevantes são as taxas de amostras R+ observadas nos bacilos entéricos, oscilando em torno de 90% (leite e merenda escolar) e alface, em torno de 70%

Expression of mosquito active toxin genes by a Colombian native strain of the gram-negative bacterium Asticcacaulis excentricus

Mosquito control with biological insecticides, such as Bacillus sp. toxins, has been used widely in many countries. However, rapid sedimentation away from the mosquito larvae feeding zone causes a low residual effect. In order to overcome this problem, it has been proposed to clone the Bacillus toxin genes in aquatic bacteria which are able to live in the upper part of the water column. Two strains of Asticcacaulis excentricus were chosen to introduce the B. sphaericus binary toxin gene and B. thuringiensis subsp. medellin cry11Bb gene cloned in suitable vectors. In feeding experiments with these aquatic bacteria, it was shown that Culex quinquefasciatus, Aedes aegypti, and Anopheles albimanus larvae were able to survive on a diet based on this wild bacterium. A. excentricus recombinant strains were able to express both genes, but the recombinant strain expressing the B. sphaericus binary toxin was toxic to mosquito larvae. Crude protease A. excentricus extracts did not degrade the Cry11Bb toxin. The flotability studies indicated that the recombinant A. excentricus strains remained in the upper part of the water column longer than the wild type Bacillus strains.

Application of control measures for infections caused by multi-resistant gram-negative bacteria in intensive care unit patients

Multi-resistant gram-negative rods are important pathogens in intensive care units (ICU), cause high rates of mortality, and need infection control measures to avoid spread to another patients. This study was undertaken prospectively with all of the patients hospitalized at ICU, Anesthesiology of the Hospital São Paulo, using the ICU component of the National Nosocomial Infection Surveillance System (NNIS) methodology, between March 1, 1997 and June 30, 1998. Hospital infections occurring during the first three months after the establishment of prevention and control measures (3/1/97 to 5/31/97) were compared to those of the last three months (3/1/98 to 5/31/98). In this period, 933 NNIS patients were studied, with 139 during the first period and 211 in the second period. The overall rates of infection by multi-resistant microorganisms in the first and second periods were, respectively, urinary tract infection: 3.28/1000 patients/day; 2.5/1000 patients/day; pneumonia: 2.10/1000 patients/day; 5.0/1000 patients/day; bloodstream infection: 1.09/1000 patients/day; 2.5/1000 patients/day. A comparison between overall infection rates of both periods (Wilcoxon test) showed no statistical significance (p = 0.067). The use of intervention measures effectively decreased the hospital bloodstream infection rate (p < 0.001), which shows that control measures in ICU can contribute to preventing hospital infections.

Antimicrobial susceptibility patterns of unusual nonfermentative gram-negative bacilli isolated from Latin America: report from the SENTRY Antimicrobial Surveillance Program (1997-2002)

The antimicrobial susceptibility of 176 unusual non-fermentative gram-negative bacilli (NF-GNB) collected from Latin America region through the SENTRY Program between 1997 and 2002 was evaluated by broth microdilution according to the National Committee for Clinical Laboratory Standards (NCCLS) recommendations. Nearly 74% of the NF-BGN belonged to the following genera/species: Burkholderia spp. (83), Achromobacter spp. (25), Ralstonia pickettii (16), Alcaligenes spp. (12), and Cryseobacterium spp. (12). Generally, trimethoprim/sulfamethoxazole (MIC50, < 0.5 µg/ml) was the most potent drug followed by levofloxacin (MIC50, 0.5 µg/ml), and gatifloxacin (MIC50, 1 µg/ml). The highest susceptibility rates were observed for levofloxacin (78.3%), gatifloxacin (75.6%), and meropenem (72.6%). Ceftazidime (MIC50, 4 µg/ml; 83.1% susceptible) was the most active beta-lactam against B. cepacia. Against Achromobacter spp. isolates, meropenem (MIC50, 0.25 µg/ml; 88% susceptible) was more active than imipenem (MIC50, 2 µg/ml). Cefepime (MIC50, 2 µg/ml; 81.3% susceptible), and imipenem (MIC50, 2 µg/ml; 81.3% susceptible) were more active than ceftazidime (MIC50, >16 µg/ml; 18.8% susceptible) and meropenem (MIC50, 8 µg/ml; 50% susceptible) against Ralstonia pickettii. Since selection of the most appropriate antimicrobial agents for testing and reporting has not been established by the NCCLS for many of NF-GNB species, results from large multicenter studies may help to guide the best empiric therapy.

The role of the New Trauma and Injury Severity Score (NTRISS) for survival prediction

The objective of this study was to verify if replacing the Injury Severity Score (ISS) by the New Injury Severity Score (NISS) in the original Trauma and Injury Severity Score (TRISS) form would improve the survival rate estimation. This retrospective study was performed in a level I trauma center during one year. ROC curve was used to identify the best indicator (TRISS or NTRISS) for survival probability prediction. Participants were 533 victims, with a mean age of 38±16 years. There was predominance of motor vehicle accidents (61.9%). External injuries were more frequent (63.0%), followed by head/neck injuries (55.5%). Survival rate was 76.9%. There is predominance of ISS scores ranging from 9-15 (40.0%), and NISS scores ranging from 16-24 (25.5%). Survival probability equal to or greater than 75.0% was obtained for 83.4% of the victims according to TRISS, and for 78.4% according to NTRISS. The new version (NTRISS) is better than TRISS for survival prediction in trauma patients.

Urinary incontinence in the prediction of falls in hospitalized elderly

Objective Analyzing the effect of urinary incontinence as a predictor of the incidence of falls among hospitalized elderly. Method Concurrent cohort study where 221 elderly inpatients were followed from the date of admission until discharge, death or fall. The Kaplan-Meier methods, the incidence density and the Cox regression model were used for the survival analysis and the assessment of the association between the exposure variable and the other variables. Results Urinary incontinence was a strong predictor of falls in the surveyed elderly, and was associated with shorter time until the occurrence of event. Urinary incontinence, concomitant with gait and balance dysfunction and use of antipsychotics was associated with falls. Conclusion Measures to prevent the risk of falls specific to hospitalized elderly patients who have urinary incontinence are necessary.



Runoff measurement and prediction for a watershed under natural vegetation in central Brazil

This work aimed to measure and analyze total rainfall (P), rainfall intensity and five-day antecedent rainfall effects on runoff (R); to compare measured and simulated R values using the Soil Conservation Service Curve Number method (CN) for each rainfall event; and to establish average R/P ratios for observed R values. A one-year (07/01/96 to 06/30/97) rainfall-runoff data study was carried out in the Capetinga watershed (962.4 ha), located at the Federal District of Brazil, 47° 52' longitude West and 15° 52' latitude South. Soils of the watershed were predominantly covered by natural vegetation. Total rainfall and runoff for the period were 1,744 and 52.5 mm, respectively, providing R/P of 3% and suggesting that watershed physical characteristics favored water infiltration into the soil. A multivariate regression analysis for 31 main rainfall-runoff events totaling 781.9 and 51.0 mm, respectively, indicated that the amount of runoff was only dependent upon rainfall volume. Simulated values of total runoff were underestimated about 15% when using CN method and an area-weighted average of the CN based on published values. On the other hand, when average values of CN were calculated for the watershed, total runoff was overestimated about 39%, suggesting that CN method shoud be used with care in areas under natural vegetation.

Reconsolidation of the soil surface after tillage discontinuity, with and without cultivation, related to erosion and its prediction with RUSLE

Site-specific regression coefficient values are essential for erosion prediction with empirical models. With the objective to investigate the surface-soilconsolidation factor, Cf, linked to the RUSLE's prior-land-use subfactor, PLU, an erosion experiment using simulated rainfall on a 0.075 m m-1 slope, sandy loam Paleudult soil, was conducted at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul (EEA/UFRGS), in Eldorado do Sul, State of Rio Grande do Sul, Brazil. Firstly, a row-cropped area was excluded from cultivation (March 1995), the existing crop residue removed from the field, and the soil kept clean-tilled the rest of the year (to get a degraded soil condition for the intended purpose of this research). The soil was then conventional-tilled for the last time (except for a standard plot which was kept continuously cleantilled for comparison purposes), in January 1996, and the following treatments were established and evaluated for soil reconsolidation and soil erosion until May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) fresh-tilled soil, continuously in clean-tilled fallow (unit plot); (b) reconsolidating soil without cultivation; and (c) reconsolidating soil with cultivation (a crop sequence of three corn- and two black oats cycles, continuously in no-till, removing the crop residues after each harvest for rainfall application and redistributing them on the site after that). Simulated rainfall was applied with a Swanson's type, rotating-boom rainfall simulator, at 63.5 mm h-1 intensity and 90 min duration, six times during the two-and-half years of experimental period (at the beginning of the study and after each crop harvest, with the soil in the unit plot being retilled before each rainfall test). The soil-surface-consolidation factor, Cf, was calculated by dividing soil loss values from the reconsolidating soil treatments by the average value from the fresh-tilled soil treatment (unit plot). Non-linear regression was used to fit the Cf = e b.t model through the calculated Cf-data, where t is time in days since last tillage. Values for b were -0.0020 for the reconsolidating soil without cultivation and -0.0031 for the one with cultivation, yielding Cf-values equal to 0.16 and 0.06, respectively, after two-and-half years of tillage discontinuation, compared to 1.0 for fresh-tilled soil. These estimated Cf-values correspond, respectively, to soil loss reductions of 84 and 94 %, in relation to soil loss from the fresh-tilled soil, showing that the soil surface reconsolidated intenser with cultivation than without it. Two distinct treatmentinherent soil surface conditions probably influenced the rapid decay-rate of Cf values in this study, but, as a matter of a fact, they were part of the real environmental field conditions. Cf-factor curves presented in this paper are therefore useful for predicting erosion with RUSLE, but their application is restricted to situations where both soil type and particular soil surface condition are similar to the ones investigate in this study.

Surface and subsurface decomposition of a desiccated grass pasture biomass related to erosion and its prediction with RUSLE

Erosion is deleterious because it reduces the soil's productivity capacity for growing crops and causes sedimentation and water pollution problems. Surface and buried crop residue, as well as live and dead plant roots, play an important role in erosion control. An efficient way to assess the effectiveness of such materials in erosion reduction is by means of decomposition constants as used within the Revised Universal Soil Loss Equation - RUSLE's prior-land-use subfactor - PLU. This was investigated using simulated rainfall on a 0.12 m m-1 slope, sandy loam Paleudult soil, at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul, in Eldorado do Sul, State of Rio Grande do Sul, Brazil. The study area had been covered by native grass pasture for about fifteen years. By the middle of March 1996, the sod was mechanically mowed and the crop residue removed from the field. Late in April 1996, the sod was chemically desiccated with herbicide and, about one month later, the following treatments were established and evaluated for sod biomass decomposition and soil erosion, from June 1996 to May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) and (b) soil without tillage, with surface residue and dead roots; (c) soil without tillage, with dead roots only; (d) soil tilled conventionally every two-and-half months, with dead roots plus incorporated residue; and (e) soil tilled conventionally every six months, with dead roots plus incorporated residue. Simulated rainfall was applied with a rotating-boom rainfall simulator, at an intensity of 63.5 mm h-1 for 90 min, eight to nine times during the experimental period (about every two-and-half months). Surface and subsurface sod biomass amounts were measured before each rainfall test along with the erosion measurements of runoff rate, sediment concentration in runoff, soil loss rate, and total soil loss. Non-linear regression analysis was performed using an exponential and a power model. Surface sod biomass decomposition was better depicted by the exponential model, while subsurface sod biomass was by the power model. Subsurface sod biomass decomposed faster and more than surface sod biomass, with dead roots in untilled soil without residue on the surface decomposing more than dead roots in untilled soil with surface residue. Tillage type and frequency did not appreciably influence subsurface sod biomass decomposition. Soil loss rates increased greatly with both surface sod biomass decomposition and decomposition of subsurface sod biomass in the conventionally tilled soil, but they were minimally affected by subsurface sod biomass decomposition in the untilled soil. Runoff rates were little affected by the studied treatments. Dead roots plus incorporated residues were effective in reducing erosion in the conventionally tilled soil, while consolidation of the soil surface was important in no-till. The residual effect of the turned soil on erosion diminished gradually with time and ceased after two years.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

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 %.