Kriittisyysanalyysin kehittäminen kemianalan tuotantolaitokseen

Tutkimuksen tarkoituksena oli löytää menetelmä, jolla löydetään tuotannon kannalta kriittiset laitteet. Vertailu suoritettiin suomalaisen PSK 6800-standardin ja saksalaisen DIN standardin mukainen BASF:n laatiman Risk-based Maintenance concept:n välillä. Tutkimuksessa kehitettiin tehtaan tarpeisiin soveltuva kriittisyysanalyysi. Tarkoituksena oli kehittää tehtaalle ominaisilla tunnusluvuilla soveltuva analysointimenetelmä. Tehtaan kunnossapidolta kerätyn pohjatiedon avulla laadittiin kriittisyysanalyysi. PSK-6800 standardin pohjalle kehitetty kriittisyysanalyysi testattiin ja vertailtiin BASF:n mallin mukaisesti kehitetyn kriittisyysanalyysin tuloksiin. Analysointi suoritetaan tuotantoprosessin alkupään laitteistolle. Kahden kriittisyysanalyysin tulokset ovat yhtenevät. Tuotantolaitos voi valita kahdesta kriittisyysanalyysistä tarpeisiinsa sopivan analysointi menetelmän.

Stratification of the severity of critically ill patients with classification trees

Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Predicting Hospital Mortality in Critically Ill Cancer Patients according to Acute Kidney Injury Severity

Background: Acute kidney injury (AKI) is a frequent complication in hospitalized patients, especially in those in intensive care units (ICU). The RIFLE classification might be a valid prognostic factor for critically ill cancer patients. The present study aims to evaluate the discriminatory capacity of RIFLE versus other general prognostic scores in predicting hospital mortality in critically ill cancer patients. Methods: This is a single-center study conducted in a cancer-specialized ICU in Brazil. All of the 288 patients hospitalized from May 2006 to June 2008 were included. RIFLE classification, APACHE II, SOFA, and SAPS II scores were calculated and the area under receiver operating characteristic (AROC) curves and logistic multiple regression were performed using hospital mortality as the outcome. Results: AKI, defined by RIFLE criteria, was observed in 156 (54.2%) patients. The distribution of patients with any degree of AKI was: risk, n = 96 (33.3%); injury, n = 30 (10.4%), and failure, n = 30 (10.4%). Mortality was 13.6% for non-AKI patients, 49% for RIFLE `R` patients, 62.3% for RIFLE `I` patients, and 86.8% for RIFLE `F` patients (p = 0.0006). Logistic regression analysis showed that RIFLE criteria, APACHE II, SOFA, and SAPS II were independent factors for mortality in this population. The discrimination of RIFLE was good (AROC 0.801, 95% CI 0.748-0.854) but inferior compared to those of APACHE II (AROC 0.940, 95% CI 0.915-0.966), SOFA (AROC 0.910, 95% CI 0.876-0.943), and SAPS II (AROC 0.869, 95% CI 0.827-0.912). Conclusion: AKI is a frequent complication in ICU patients with cancer. RIFLE was inferior to commonly used prognostic scores for predicting mortality in this cohort of patients. Copyright (C) 2011 S. Karger AG, Basel

Evaluation of bedbath in critically ill patients: impact of water temperature on the pulse oximetry variation

This is a participant study, quasi-experimental, of a before and after type. A quantitative approach of biophysiological measures was used, represented by the saturation of oxygen measured by pulse oximeter (SpO2), and recorded on three occasions: before, during and after the bedbath in critically ill patients hospitalized at the ICU of a University Hospital in Brazil. Objective: to compare the SpO2 in various stages of the bath, with and without control of water temperature. Data collection was performed between December 2007 and April 2008 on a convenience sample consisting of 30 patients aged over 18 who had classification in TISS-28 from level II. Results show that water temperature control means a lower variation of SpO2 (p<0.05). No marked differences in variation of saturation between men and women or between age groups were established. In conclusion, heated and constant water temperature during the bedbath is able to minimize the fall of SpO2 that occurs while handling patients during procedures.

Laser therapy in pressure ulcers: evaluation by the Pressure Ulcer Scale for Healing and Nursing Outcomes Classification

AbstractOBJECTIVETo describe the pressure ulcer healing process in critically ill patients treated with conventional dressing therapy plus low-intensity laser therapy evaluated by the Pressure Ulcer Scale for Healing (PUSH) and the result of Wound Healing: Secondary Intention, according to the Nursing Outcomes Classification (NOC).METHODCase report study according to nursing process conducted with an Intensive Care Unit patient. Data were collected with an instrument containing the PUSH and the result of the NOC. In the analysis we used descriptive statistics, considering the scores obtained on the instrument.RESULTSA reduction in the size of lesions of 7cm to 1.5cm of length and 6cm to 1.1cm width, in addition to the increase of epithelial tissue and granulation, decreased secretion and odor.CONCLUSIONThere was improvement in the healing process of the lesion treated with adjuvant therapy and the use of NOC allowed a more detailed and accurate assessment than the PUSH.

Continuous electroencephalographic monitoring in critically ill patients with central nervous system infections.

OBJECTIVES: To determine the prevalence, predictors, and clinical significance of electrographic seizures (ESz) and other continuous electroencephalographic monitoring findings in critically ill patients with central nervous system infections. DESIGN: Retrospective cohort study. SETTING: Eighteen-bed neurocritical care unit. PATIENTS: We identified 42 consecutive patients with primary central nervous system infection (viral, 27 patients [64%]; bacterial, 8 patients [18%]; and fungal or parasitic, 7 patients [17%]) who underwent continuous electroencephalographic monitoring between January 1, 1996, and February 28, 2007. MAIN OUTCOME MEASURES: Presence of ESz or periodic epileptiform discharges (PEDs). RESULTS: Electrographic seizures were recorded in 14 patients (33%), and PEDs were recorded in 17 patients (40%). Twenty patients (48%) had either PEDs or ESz. Of the 14 patients with ESz, only 5 (36%) had a clinical correlate. Periodic epileptiform discharges (odds ratio=13.4; P=.001) and viral cause (odds ratio=13.0; P=.02) were independently associated with ESz. Both ESz (odds ratio=5.9; P=.02) and PEDs (odds ratio=6.1; P=.01) were independently associated with poor outcome at discharge (severe disability, vegetative state, or death). CONCLUSIONS: In patients with central nervous system infections undergoing continuous electroencephalographic monitoring, ESz and/or PEDs were frequent, occurring in 48% of our cohort. More than half of the ESz had no clinical correlate. Both ESz and PEDs were independently associated with poor outcome. Additional studies are needed to determine whether prevention or treatment of these electrographic findings improves outcome.

Multimedia selection: Allowing educators to act critically and independently

In Brazil, important portals like the Portal do Professor, or Teacher's Portal, from the Ministry of Education, offer multimedia products like audios, videos, games, animations, simulations and others with an accompanying teacher's guide. These guides in general suggest ways to prepare the students to use the products while offering indications on how to practice that knowledge after using the products in the classrooom. Despite this, portals with huge repositories that receive new products every week don't present to teachers a solution for a problem: How to select the appropriate products to use in the classroom and how to assess their use after teaching in order to check if the learning was meaningful? In this way, this paper discusses multimedia selection for meaningful learning while considering concept mapping and abstraction classification. The development of multimedia repositories has created both opportunities for easy access to digital content and areas of serious concerns since the misuse of products by teachers may lead to different problems.

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.

Causes of death and determinants of outcome in critically ill patients

INTRODUCTION: Whereas most studies focus on laboratory and clinical research, little is known about the causes of death and risk factors for death in critically ill patients. METHODS: Three thousand seven hundred patients admitted to an adult intensive care unit (ICU) were prospectively evaluated. Study endpoints were to evaluate causes of death and risk factors for death in the ICU, in the hospital after discharge from ICU, and within one year after ICU admission. Causes of death in the ICU were defined according to standard ICU practice, whereas deaths in the hospital and at one year were defined and grouped according to the ICD-10 (International Statistical Classification of Diseases and Related Health Problems) score. Stepwise logistic regression analyses were separately calculated to identify independent risk factors for death during the given time periods. RESULTS: Acute, refractory multiple organ dysfunction syndrome was the most frequent cause of death in the ICU (47%), and central nervous system failure (relative risk [RR] 16.07, 95% confidence interval [CI] 8.3 to 31.4, p < 0.001) and cardiovascular failure (RR 11.83, 95% CI 5.2 to 27.1, p < 0.001) were the two most important risk factors for death in the ICU. Malignant tumour disease and exacerbation of chronic cardiovascular disease were the most frequent causes of death in the hospital (31.3% and 19.4%, respectively) and at one year (33.2% and 16.1%, respectively). CONCLUSION: In this primarily surgical critically ill patient population, acute or chronic multiple organ dysfunction syndrome prevailed over single-organ failure or unexpected cardiac arrest as a cause of death in the ICU. Malignant tumour disease and chronic cardiovascular disease were the most important causes of death after ICU discharge.

Copeptin and arginine vasopressin concentrations in critically ill patients

CONTEXT: Determination of arginine vasopressin (AVP) concentrations may be helpful to guide therapy in critically ill patients. A new assay analyzing copeptin, a stable peptide derived from the AVP precursor, has been introduced. OBJECTIVE: Our objective was to determine plasma copeptin concentrations. DESIGN: We conducted a post hoc analysis of plasma samples and data from a prospective study. SETTING: The setting was a 12-bed general and surgical intensive care unit (ICU) in a tertiary university teaching hospital. PATIENTS: Our subjects were 70 healthy volunteers and 157 ICU patients with sepsis, with systemic inflammatory response syndrome (SIRS), and after cardiac surgery. INTERVENTIONS: There were no interventions. MAIN OUTCOME MEASURES: Copeptin plasma concentrations, demographic data, AVP plasma concentrations, and a multiple organ dysfunction syndrome score were documented 24 h after ICU admission. RESULTS: AVP (P < 0.001) and copeptin (P < 0.001) concentrations were significantly higher in ICU patients than in controls. Patients after cardiac surgery had higher AVP (P = 0.003) and copeptin (P = 0.003) concentrations than patients with sepsis or SIRS. Independent of critical illness, copeptin and AVP correlated highly significantly with each other. Critically ill patients with sepsis and SIRS exhibited a significantly higher ratio of copeptin/AVP plasma concentrations than patients after cardiac surgery (P = 0.012). The American Society of Anesthesiologists' classification (P = 0.046) and C-reactive protein concentrations (P = 0.006) were significantly correlated with the copeptin/AVP ratio. CONCLUSIONS: Plasma concentrations of copeptin and AVP in healthy volunteers and critically ill patients correlate significantly with each other. The ratio of copeptin/AVP plasma concentrations is increased in patients with sepsis and SIRS, suggesting that copeptin may overestimate AVP plasma concentrations in these patients.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

Prognostic Value of Secretoneurin in Critically Ill Patients With Infections.

OBJECTIVES Secretoneurin is produced in neuroendocrine cells, and the myocardium and circulating secretoneurin levels provide incremental prognostic information to established risk indices in cardiovascular disease. As myocardial dysfunction contributes to poor outcome in critically ill patients, we wanted to assess the prognostic value of secretoneurin in two cohorts of critically ill patients with infections. DESIGN Two prospective, observational studies. SETTING Twenty-four and twenty-five ICUs in Finland. PATIENTS A total of 232 patients with severe sepsis (cohort #1) and 94 patients with infections and respiratory failure (cohort #2). INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We measured secretoneurin levels by radioimmunoassay in samples obtained early after ICU admission and compared secretoneurin with other risk indices. In patients with severe sepsis, admission secretoneurin levels (logarithmically transformed) were associated with hospital mortality (odds ratio, 3.17 [95% CI, 1.12-9.00]; p = 0.030) and shock during the hospitalization (odds ratio, 2.17 [1.06-4.46]; p = 0.034) in analyses that adjusted for other risk factors available on ICU admission. Adding secretoneurin levels to age, which was also associated with hospital mortality in the multivariate model, improved the risk prediction as assessed by the category-free net reclassification index: 0.35 (95% CI, 0.06-0.64) (p = 0.02). In contrast, N-terminal pro-B-type natriuretic peptide levels were not associated with mortality in the multivariate model that included secretoneurin measurements, and N-terminal pro-B-type natriuretic peptide did not improve patient classification on top of age. Secretoneurin levels were also associated with hospital mortality after adjusting for other risk factors and improved patient classification in cohort #2. In both cohorts, the optimal cutoff for secretoneurin levels at ICU admission to predict hospital mortality was ≈ 175 pmol/L, and higher levels were associated with mortality also when adjusting for Simplified Acute Physiology Score II and Sequential Organ Failure Assessment scores. CONCLUSIONS Secretoneurin levels provide incremental information to established risk indices for the prediction of mortality and shock in critically ill patients with severe infections.

Risk technology in Australia: The role of the job seeker classification instrument in employment services

Promoted as the key policy response to unemployment, the Job Network constitutes an array of interlocking processes that position unemployed people as `problems' in need of remediation. Unemployment is presented as a primary risk threatening society, and unemployed people are presented as displaying various degrees of riskiness. The Job Seeker Classification Instrument (JSCI) is a `technology' employed by Centrelink to assess `risk' and to determine the type of interaction that unemployed people have with the job Network. In the first instance, we critically examine the development of the JSCI and expose issues that erode its credibility and legitimacy. Second, employing the analytical tools of discourse analysis, we show how the JSCI both assumes and imposes particular subject identities on unemployed people. The purpose of this latter analysis is to illustrate the consequences of the sorts of technologies and interventions used within the job Network.

The application of methods of uncertain reasoning to the biological classification of river water quality

This thesis presents an investigation into the application of methods of uncertain reasoning to the biological classification of river water quality. Existing biological methods for reporting river water quality are critically evaluated, and the adoption of a discrete biological classification scheme advocated. Reasoning methods for managing uncertainty are explained, in which the Bayesian and Dempster-Shafer calculi are cited as primary numerical schemes. Elicitation of qualitative knowledge on benthic invertebrates is described. The specificity of benthic response to changes in water quality leads to the adoption of a sensor model of data interpretation, in which a reference set of taxa provide probabilistic support for the biological classes. The significance of sensor states, including that of absence, is shown. Novel techniques of directly eliciting the required uncertainty measures are presented. Bayesian and Dempster-Shafer calculi were used to combine the evidence provided by the sensors. The performance of these automatic classifiers was compared with the expert's own discrete classification of sampled sites. Variations of sensor data weighting, combination order and belief representation were examined for their effect on classification performance. The behaviour of the calculi under evidential conflict and alternative combination rules was investigated. Small variations in evidential weight and the inclusion of evidence from sensors absent from a sample improved classification performance of Bayesian belief and support for singleton hypotheses. For simple support, inclusion of absent evidence decreased classification rate. The performance of Dempster-Shafer classification using consonant belief functions was comparable to Bayesian and singleton belief. Recommendations are made for further work in biological classification using uncertain reasoning methods, including the combination of multiple-expert opinion, the use of Bayesian networks, and the integration of classification software within a decision support system for water quality assessment.