Predictive Validity of Waterlow Scale for Pressure Ulcer Development Risk in Hospitalized Patients

AIM: We sought to evaluate the predictive validity of the Waterlow Scale in hospitalized patients. SUBJECTS AND SETTING: The study was conducted at a general private hospital with 220 beds and a mean time of hospitalization of 7.4 days and a mean occupation rate of approximately 80%. Adult patients with a Braden Scale score of 18 or less and a Waterlow Scale score of 16 or more were studied. The sample consisted of 98 patients with a mean age of 71.1 +/- 15.5 years. METHODS: Skin assessment and scoring by using the Waterlow and Braden scales were completed on alternate days. Patients were examined at least 3 times to be considered for analysis. The data were submitted to sensitivity and specificity analysis by using receiver operating characteristic (ROC) curves and positive (+LR) and negative (-LR) likelihood ratios. RESULTS: The cutoff scores were 17, 20, and 20 in the first, second, and third assessment, respectively. Sensitivity was 71.4%, 85.7%, and 85.7% and specificity was 67.0%, 40.7%, and 32.9%, respectively. Analysis of the area under the ROC curve revealed good accuracy (0.64, 95% confidence interval [CI]: 0.35-0.93) only for the cutoff score 17 in the first assessment. The results also showed probabilities of 14%, 10%, and 9% for the development of pressure ulcer when the test results were positive (+LR) and of 3% (-LR) when the test results were negative for the cutoff scores in the first, second, and third assessment, respectively. CONCLUSION: The Waterlow Scale achieved good predictive validity in predicting pressure ulcer in hospitalized patients when a cutoff score of 17 was used in the first assessment.

Risk factors for neonatal transfers from the Sapopemba free-standing birth centre to a hospital in Sao Paulo, Brazil

Objective: to identify risk factors associated with neonatal transfers from a free-standing birth centre to a hospital. Design: epidemiological case-control study. Setting: midwifery-led free-standing birth centre in Sao Paulo, Brazil. Participants: 96 newborns were selected from 2840 births between September 1998 and August 2005. Cases were defined as all new borns transferred from the birth centre to a hospital (n = 32), and controls were defined as new borns delivered at the same birth centre, during the same time period, and who had not been transferred to a hospital (n = 64). Measurements and findings: data were collected from medical records available at the birth centre. Univariate and multivariate analyses were performed using logistic regression. The multivariate analysis included outcomes with p<0.25, specifically: smoking during pregnancy, prenatal care appointments, labour complications, weight in relation to gestational age, and one-minute Apgar score. Of the foregoing outcomes, those that remained in the full regression model as a risk factor associated with neonatal transfer were: smoking during pregnancy [p = 0.009, odds ratio (OR) = 4.1,95% confidence interval (CI) 1.03-16.33], labour complications (p<0.001, OR = 5.5, 95% CI 1.06-28.26) and one-minute Apgar score <= 7 (p<0.001, OR = 7.8,95% CI 1.62-37.03). Key conclusions and implications for practice: smoking during pregnancy, labour complications and one-minute Apgar score <= 7 were confirmed as risk factors for neonatal transfer from the birth centre to a hospital. The identified risk factors can help to improve institutional protocols and formulate hypotheses for other studies. (C) 2009 Elsevier Ltd. All rights reserved.

Evaluation of biologic occupational risk control practices: Quality indicators development and validation

Background: There is growing demand for the adoption of qualification systems for health care practices. This study is aimed at describing the development and validation of indicators for evaluation of biologic occupational risk control programs. Methods: The study involved 3 stages: (1) setting up a research team, (2) development of indicators, and (3) validation of the indicators by a team of specialists recruited to validate each attribute of the developed indicators. The content validation method was used for the validation, and a psychometric scale was developed for the specialists` assessment. A consensus technique was used, and every attribute that obtained a Content Validity Index of at least 0.75 was approved. Results: Eight indicators were developed for the evaluation of the biologic occupational risk prevention program, with emphasis on accidents caused by sharp instruments and occupational tuberculosis prevention. The indicators included evaluation of the structure, process, and results at the prevention and biologic risk control levels. The majority of indicators achieved a favorable consensus regarding all validated attributes. Conclusion: The developed indicators were considered validated, and the method used for construction and validation proved to be effective.

Relative frequency of knowledge of results and task complexity in the motor skill acqusition

The aim of this study was to investigate the effects of knowledge of results (KR) frequency and task complexity on motor skill acquisition. The task consisted of throwing a bocha ball to place it as close as possible to the target ball. 120 students ages 11 to 73 years were assigned to one of eight experimental groups according to knowledge of results frequency (25, 50, 75, and 100%) and task complexity (simple and complex). Subjects performed 90 trials in the acquisition phase and 10 trials in the transfer test. The results showed that knowledge of results given at a frequency of 25% resulted in an inferior absolute error than 50% and inferior variable error than 50, 75, and 100 I frequencies, but no effect of task complexity was found.

Altered left ventricular diastolic function in subjects with spinal cord injury

Study design: This is cross-sectional study. Objectives: The aim of this study is to investigate the cardiac structure and function of subjects with spinal cord injury (SCI) and the impact of metabolic, hemodynamic and inflammatory factors on these parameters. Setting: Sao Paulo, Brazil. Methods: Sixty-five nondiabetic, nonhypertensive, sedentary, nonsmoker men (34 with SCI and 31 healthy subjects) were evaluated by medical history, anthropometry, laboratory tests, analysis of hemodynamic and inflammatory parameters and echocardiography. Results: Subjects with SCI had lower systolic blood pressure and higher levels of C-reactive protein and tumor necrosis factor receptors than the healthy ones. Echocardiography data showed that the SCI group presented similar left ventricular (LV) structural and systolic parameters, but lower initial diastolic velocity (Em) (9.2 +/- 0.5 vs 12.3 +/- 0.5 cm s(-1); P<0.001) and higher peak early inflow velocity (E)/Em ratio (7.7 +/- 0.5 vs 6.1 +/- 0.3; P = 0.009) compared with the able-bodied group, even after adjustment for systolic blood pressure and C-reactive protein levels. Furthermore, injured subjects with E/Em >8 had lower peak spectral longitudinal contraction (Sm) (9.0 +/- 0.7 vs 11.6 +/- 0.4cm s(-1); P<0.001) and cardiac output (4.2 +/- 0.2 vs 5.0 +/- 0.21 min(-1); P = 0.029), as well as higher relative wall thickness (0.38 +/- 0.01 vs 0.35 +/- 0.01; P = 0.005), than individuals with SCI with E/Em<8, but similar age, body mass index, blood pressure, injury level, metabolic parameters and inflammatory marker levels. Conclusion: Subjects with SCI presented impaired LV diastolic function in comparison with able-bodied ones. Moreover, worse LV diastolic function was associated with a pattern of LV concentric remodeling and subclinical decreases in systolic function among injured subjects. Overall, these findings might contribute to explain the increased cardiovascular risk reported for individuals with SCI. Spinal Cord (2011) 49, 65-69; doi: 10.1038/sc.2010.88; published online 27 July 2010

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

Fuzzy risk index for power transformer failures due to external short-circuits

A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

Reproductive Activity and Survivorship of Liriomyza sativae (Diptera: Agromyzidae) at Different Temperatures and Relative Humidity Levels

We studied a population of Liriomyza sativae Blanchard (Diptera: Agromyzidae) identified by morphological and molecular techniques from the semiarid region of the Brazilian northeast. The influence of temperature and relative humidity on the survival and reproductive parameters of L. sativae in cowpeas (Vigna unguiculata L. Walp.) (Fabales: Fabaceae) was evaluated. We used temperatures of 18, 20, 22, 25, 28, 30, and 32 +/- 1 degrees C (50 +/- 10% RH) and relative humidity values of 30,50,70, and 90 +/- 10% (25 +/- 1 degrees C) under a 14 L:10 D photoperiod. Adult longevity decreased as temperature and relative humidity increased and was greater, in general, for females. The preoviposition and oviposition periods also decreased as temperature increased, whereas relative humidity only caused reductions in the oviposition period at higher levels. Fecundity was similar in the range from 18 to 30 degrees C but decreased at 32 degrees C with respect to relative humidity; the best performances of L. sativae occurred at lower levels. The pattern of oviposition rate changed with temperature and relative humidity. Regardless of temperature and relative humidity, L, sativae laid between 75 and 92% of its eggs on the adaxial surface of the cowpea leaves. This information will be highly useful to design a leafminer production system aimed at the multiplication of natural enemies, as well as for pest management in the field.

Definition of priority areas for forest conservation through the ordered weighted averaging method

The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads: distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns. (C) 2008 Elsevier B.V. All rights reserved.

Suitability of relative humidity as an estimator of leaf wetness duration

Leaf wetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates. Because LWD is not widely measured, several methods have been developed to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles of dew formation and dew and/or rain evaporation have shown good portability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empirical models use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimate LWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained from Ames, IA (USA), Elora, Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sao Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH >= 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH >= 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH >= 90% model performed best, presenting the highest general fraction of correct estimates (F(C)), between 0.87 and 0.92, and the lowest false alarm ratio (F(AR)), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, even when independent data were used; MAE ranged from 1.23 to 1.89 h, which is very similar to errors obtained with published physical models for LWD estimation. Based on these results, we concluded that, if calibrated locally, LWD can be estimated with acceptable accuracy by RH above a specific threshold, and that the EXT_RH method was unsuitable for estimating LWD at the locations used in this study. (C) 2007 Elsevier B.V. All rights reserved.

Optimal irrigation depth for bean crops considering water constraints and farmer`s risk aversion level

Nowadays, the rising competition for the use of water and environmental resources with consequent restrictions for farmers should change the paradigm in terms of irrigation concepts, or rather, in order to attain economical efficiency other than to supply water requirement for the crop. Therefore, taking into account the social and economical role of bean activity in Brazil, as well as the risk inherent to crop due to its high sensibility to both deficit and excessive water, the optimization methods regarding to irrigation management have become more interesting and essential. This study intends to present a way to determine the optimal water supply, considering different combinations between desired bean yield and level of risk, bringing as a result a graph with the former associated with the latter, depending on different water depths.

ECONOMICAL OCCUPATION OF AGRICULTURAL AREA OF PIRACICABA (SAO PAULO STATE, BRAZIL), INCLUDING RISK THROUGH LINEAR PROGRAMMING

The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.

Adaptation of an apple sooty blotch and flyspeck warning system for the Upper Midwest United States

A warning system for sooty blotch and flyspeck (SBFS) of apple, developed in the southeastern United States, uses cumulative hours of leaf wetness duration (LWD) to predict the timing of the first appearance of signs. In the Upper Midwest United States, however, this warning system has resulted in sporadic disease control failures. The purpose of the present study was to determine whether the warning system`s algorithm could be modified to provide more reliable assessment of SBFS risk. Hourly LWD, rainfall, relative humidity (RH), and temperature data were collected from orchards in Iowa, North Carolina, and Wisconsin in 2005 and 2006. Timing of the first appearance of SBFS signs was determined by weekly scouting. Preliminary analysis using scatterplots and boxplots suggested that Cumulative hours of RH >= 97% could be a useful predictor of SBFS appearance. Receiver operating characteristic curve analysis was used to compare the predictive performance of cumulative LWD and cumulative hours of RH >= 97%. Cumulative hours of RH >= 97% was a more conservative and accurate predictor than cumulative LWD for 15 site years in the Upper Midwest, but not for four site years in North Carolina. Performance of the SBFS warning system in the Upper Midwest and climatically similar regions may be improved if cumulative hours of RH >= 97% were substituted for cumulative LWD to predict the first appearance of SBFS.