Predictive Validity of the Braden Scale for Pressure Ulcer Risk in Elderly Residents of Long-Term Care Facilities

The aim of this study was to evaluate the predictive validity of the Braden Scale for Predicting Pressure Sore Risk in elderly residents of long-term care facilities (LTCFs) in Brazil. The determination of the cutoff score for the Brazilian population is important for the comparison between Brazilian and international studies and establishment of guidelines for prevention of pressure ulcers in our health care facilities. This is the first study of its kind in Brazil. This was a secondary analysis of a prospective cohort study conducted with 233 LTCF residents aged 60 and over who underwent complete skin examination and Braden Scale rating every 2 days for 3 months. Two groups of patients were considered: the total group (N = 233) and risk group (n = 94, total scores <= 18). Data from the first and last assessments were analyzed for sensitivity, specificity, and likelihood ratios. The best results were obtained for the total group, with cutoff scores of 18 and 17, sensitivity of 75.9% and 74.1%, specificity of 70.3% and 75.4%, and area under the receiver operating characteristic curve (AUC-ROC) of 0.79 and 0.81 at the first and last assessments, respectively. For the risk group, the cutoff scores of 16 (first assessment) and 13 (last assessment) were associated with a smaller AUC-ROC and, therefore, lower predictive accuracy. The Braden Scale showed good predictive validity in elderly LTCF residents. (Geriatr Nurs 2010;31:95-104)

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.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Equivalence between hot tensile and creep testing data for Kanthal A1 alloy

Hot tensile and creep tests were carried out on Kanthal A1 alloy in the temperature range from 600 to 800 degrees C. Each of these sets of data were analyzed separately according to their own methodologies, but an attempt was made to find a correlation between them. A new criterion proposed for converting hot tensile data to creep data, makes possible the analysis of the two kinds of results according to usual creep relations like: Norton, Monkman-Grant, Larson-Miller and others. The remarkable compatibility verified between both sets of data by this procedure strongly suggests that hot tensile data can be converted to creep data and vice-versa for Kanthal A1 alloy, as verified previously for other metallic materials.

Sensorless synchronization method for thin-film direct optical broadband monitoring system

Optical monitoring systems are necessary to manufacture multilayer thin-film optical filters with low tolerance on spectrum specification. Furthermore, to have better accuracy on the measurement of film thickness, direct monitoring is a must. Direct monitoring implies acquiring spectrum data from the optical component undergoing the film deposition itself, in real time. In making film depositions on surfaces of optical components, the high vacuum evaporator chamber is the most popular equipment. Inside the evaporator, at the top of the chamber, there is a metallic support with several holes where the optical components are assembled. This metallic support has rotary motion to promote film homogenization. To acquire a measurement of the spectrum of the film in deposition, it is necessary to pass a light beam through a glass witness undergoing the film deposition process, and collect a sample of the light beam using a spectrometer. As both the light beam and the light collector are stationary, a synchronization system is required to identify the moment at which the optical component passes through the light beam.

High accuracy and fast acquisition time of polarisation nulling-based OSNR monitor

A technique for improving the performance of an OSNR monitor based on a polarisation nulling method with the downhill simplex algorithm is demonstrated. Establishing a compromise between accuracy and acquisition time, the monitor has been calibrated to 0.72 dB/390 ms and 0.98 dB/320 ms, over a range of nearly 21 dB. As far as is known, these are the best values achieved with such an OSNR monitoring method.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

Robot measuring form errors

This work presents an automated system for the measurement of form errors of mechanical components using an industrial robot. A three-probe error separation technique was employed to allow decoupling between the measured form error and errors introduced by the robotic system. A mathematical model of the measuring system was developed to provide inspection results by means of the solution of a system of linear equations. A new self-calibration procedure, which employs redundant data from several runs, minimizes the influence of probes zero-adjustment on the final result. Experimental tests applied to the measurement of straightness errors of mechanical components were accomplished and demonstrated the effectiveness of the employed methodology. (C) 2007 Elsevier Ltd. All rights reserved.

STRESS-STRAIN CURVES FOR STEEL FIBER-REINFORCED CONCRETE IN COMPRESSION

This paper presents a study on the compressive behavior of steel fiber-reinforced concrete. In this study, an analytical model for stress-strain curve for steel fiber-reinforced concrete is derived for concretes with strengths of 40 MPa and 60 MPa at the age of 28 days. Those concretes were reinforced with steel fibers with hooked ends 35 mm long and with aspect ratio of 65. The analytical model was compared with some experimental stress-strain curves and with some models reported in technical literature. Also, the accuracy of the proposed stress-strain curve was evaluated by comparison of the area under stress-strain curve. The results showed good agreement between analytical and experimental data and the benefits of the using of fibers in the compressive behavior of concrete.

Determination of in situ uniaxial compressive strength of coal seams based on geophysical data

The central issue for pillar design in underground coal mining is the in situ uniaxial compressive strength (sigma (cm)). The paper proposes a new method for estimating in situ uniaxial compressive strength in coal seams based on laboratory strength and P wave propagation velocity. It describes the collection of samples in the Bonito coal seam, Fontanella Mine, southern Brazil, the techniques used for the structural mapping of the coal seam and determination of seismic wave propagation velocity as well as the laboratory procedures used to determine the strength and ultrasonic wave velocity. The results obtained using the new methodology are compared with those from seven other techniques for estimating in situ rock mass uniaxial compressive strength.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Leak detection by inverse transient analysis in an experimental PVC pipe system

Leakage reduction in water supply systems and distribution networks has been an increasingly important issue in the water industry since leaks and ruptures result in major physical and economic losses. Hydraulic transient solvers can be used in the system operational diagnosis, namely for leak detection purposes, due to their capability to describe the dynamic behaviour of the systems and to provide substantial amounts of data. In this research work, the association of hydraulic transient analysis with an optimisation model, through inverse transient analysis (ITA), has been used for leak detection and its location in an experimental facility containing PVC pipes. Observed transient pressure data have been used for testing ITA. A key factor for the success of the leak detection technique used is the accurate calibration of the transient solver, namely adequate boundary conditions and the description of energy dissipation effects since PVC pipes are characterised by a viscoelastic mechanical response. Results have shown that leaks were located with an accuracy between 4-15% of the total length of the pipeline, depending on the discretisation of the system model.

Adaptable Strut-and-Tie Model for Design and Verification of Four-Pile Caps

A large percentage of pile caps support only one column, and the pile caps in turn are supported by only a few piles. These are typically short and deep members with overall span-depth ratios of less than 1.5. Codes of practice do not provide uniform treatment for the design of these types of pile caps. These members have traditionally been designed as beams spanning between piles with the depth selected to avoid shear failures and the amount of longitudinal reinforcement selected to provide sufficient flexural capacity as calculated by the engineering beam theory. More recently, the strut-and-tie method has been used for the design of pile caps (disturbed or D-region) in which the load path is envisaged to be a three-dimensional truss, with compressive forces being supported by concrete compressive struts between the column and piles and tensile forces being carried by reinforcing steel located between piles. Both of these models have not provided uniform factors of safety against failure or been able to predict whether failure will occur by flexure (ductile mode) or shear (fragile mode). In this paper, an analytical model based on the strut-and-tie approach is presented. The proposed model has been calibrated using an extensive experimental database of pile caps subjected to compression and evaluated analytically for more complex loading conditions. It has been proven to be applicable across a broad range of test data and can predict the failures modes, cracking, yielding, and failure loads of four-pile caps with reasonable accuracy.

Short-term experimental data of drying shrinkage of ground granulated blast-furnace slag cement concrete

This paper presents results of laboratory testing of unrestrained drying shrinkage during a period of 154 days of different concrete mixtures from the Brazilian production line that utilize ground granulated blast-furnace slag in their compositions. Three concrete mixtures with water/cement ratio of 0.78(M1), 0.41(M2), and 0.37(M3) were studied. The obtained experimental data were compared with the analytical results from prediction models available in the literature: the ACI 209 model (ACI), the B3 model (B3), the Eurocode 2 model (EC2), the GL 2000 model (GL), and the Brazilian NBR 6118 model (NBR), and an analysis of the efficacy of these models was conducted utilizing these experimental data. In addition, the development of the mechanical properties (compressive strength and modulus of elasticity) of the studied concrete mixtures was also measured in the laboratory until 126 days. From this study, it could be concluded that the ACI and the GL were the models that most approximated the experimental drying shrinkage data measured during the analyzed period of time.