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General beliefs about medicines among doctors and nurses in out-patient care: a cross-sectional study

BMC FAMILY PRACTICE 2009年第1期10卷 35-35页

作者： Mardby, Ann-Charlotte Akerlind, Ingemar Hedenrud, Tove Univ Gothenburg Dept Publ Hlth & Community Med Gothenburg Sweden Malardalen Univ Sch Hlth Care & Social Welf Vasteras Sweden

Background: Doctors and nurses are two natural partners in the healthcare team, but theyusually differ in their perspectives on how to work for increased health. These professions may also have different beliefs about medicines, a factor important for adherence to medicines. The aim was to explore general beliefs about medicines among doctors and nurses. Methods: Questionnaires were sent to 306 private practitioners (PPs), 298 general practitioners (GPs) and 303 nurses in the county of Vastra Gotaland, Sweden. The questionnaire included sociodemographic questions and the general part of the Beliefs about Medicines Questionnaire (BMQ), which measures the beliefs people have about medicines in general. General beliefs about medicines in relation to background variables were explored with independent t-tests and ANOVA analyses. Differences between occupations and influences of interaction variables were analysed with multiple linear regression models for general beliefs about medicines. Results: The data collection resulted in 616 questionnaires (62.1% PPs;61.6% GPs;80.5% nurses). The majority of the PPs and 40% of the GPs were male but most of the nurses were female. The GPs' mean age was 47 years, PPs' 60 years and nurses' 52 years. Few nurses originated from non-Nordic countries while 15% of the PPs and 25% of the GPs did. Nurses saw medicines as more harmful and less beneficial than did PPs and GPs. These differences could not be explained by the included interaction variables. GPs with a Nordic background saw medicines as more beneficial and less harmful than did GPs with a non-Nordic background. Furthermore, GPs of non-Nordic origin were most likely to believe that medicines were overprescribed by doctors. Conclusion: Doctors were more positive about medicines than nurses. The differences in beliefs about medicines found between doctors and nurses could not be explained by any of the included interaction variables. These differences in beliefs may be useful in di

关键词： Nordic Country multiple linear regression model General Belief Interaction Variable Professional Experience

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Application of Artificial Neural Networks to Estimate Wastewater Treatment Plant Inlet Biochemical Oxygen Demand

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ENVIRONMENTAL PROGRESS 2008年第4期27卷 439-446页

作者： Dogan, Emrah Ates, Asude Yilmaz, Ece Ceren Eren, Beytullah Sakarya Univ Dept Civil Engn TR-54187 Sakarya Turkey Sakarya Univ Dept Environm Engn TR-54187 Sakarya Turkey

Biochemical oxygen demand (BOD) has been shown to be an important variable in water quality management and planning. However, BOD is difficult to measure and needs longer time periods (5 days) to get results. Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resource variables. The objective of this research was to develop an ANNs model to estimate daily BOD in the inlet of wastewater biochemical treatment plants. The plantscale data set (364 daily records of the year 2005) was obtained from a local wastewater treatment plant. Various combinations of daily water quality data, namely chemical oxygen demand (COD), water discharge (Q,,), suspended solid (SS), total nitrogen (N), and total phosphorus (P) are used as inputs into the ANN so as to evaluate the degree of effect of each of these variables on the daily inlet BOD. The results of the ANN model are compared with the multiple linear regression model (MLR). Mean square error, average absolute relative error, and coefficient of determination statistics are used as comparison criteria for the evaluation of the model performance. The ANN technique whose inputs are COD, Q,v, SS, A, and P gave mean square errors of 708.01, average absolute relative errors of 10.03%, and a coefficient of determination 0.919, respectively. On the basis of the comparisons, it was found that the ANN model could be employed successfully in estimating the daily BOD in the inlet of wastewater biochemical treatment plants. (C) 2008 American Institute of Chemical Engineers Environ Prog, 27: 439-446, 2008

关键词： water quality artificial neural network wastewater treatment plant multiple linear regression model

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regression-Based Limits for Multivariate Poisson Control Chart

Regression-Based Limits for Multivariate Poisson Control Cha...

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International Conference on Industrial Engineering and Engineering Management

作者： Kuo, T. I. Chiu, J. E. Natl Kinmen Inst Technol Dept Business Adm Kinmen Taiwan Natl Yunlin Univ Sci & Technol Dept Ind Engn & Management Touliu Yunlin Taiwan

ISBN: (纸本)9781424426294

C-charts and U-charts are widely applied for Poisson distribution to monitor the number of defects in the univariate process. More than one quality characteristic for attribute data with Poisson distribution is of interest in many industrial applications. A control chart is constructed for monitoring multivariate Poisson count data, called the MP chart. The MP chart is constructed based on the sum of defects or nonconformities in one single control chart. In this study, the control limits in the multivariate Poisson process are estimated by using multiple linear regression model since the calculation of control limits is complicated. Two examples are provided to illustrate the effectiveness of this approach.

关键词： Attribute control chart multivariate Poisson distribution multiple linear regression model

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Reproducibility of exhaled nitric oxide in smokers and non-smokers: Relevance for longitudinal studies

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BMC Pulmonary Medicine 2008年第1期8卷 1-7页

作者： Bohadana, Abraham Michaely, Jean-Pierre Teculescu, Dan Wild, Pascal Institut National de la Santé et de la Recherche Médicale INSERM ERI 11 54505 Vandoeuvre-lès-Nancy France Service de Pneumologie Centre Hospitalier Universitaire de Nancy 54511 Vandoeuvre-lès-Nancy France Département Epidémiologie en Entreprises INRS 54511 Vandoeuvre-lès-Nancy France

Background: Currently, there is much interest in measuring fractional exhaled nitric oxide (FENO) in populations. We evaluated the reproducibility of FENO in healthy subjects and determined the number of subjects nece... 详细信息

Background: Currently, there is much interest in measuring fractional exhaled nitric oxide (FE_NO) in populations. We evaluated the reproducibility of FE_NO in healthy subjects and determined the number of subjects necessary to carry out a longitudinal survey of FE_NO in a population containing smokers and non-smokers, based on the assessed reproducibility. Methods: The reproducibility of FENO was examined in 18 healthy smokers and 21 non-smokers. FE_NO was assessed once at 9 AM on five consecutive days;in the last day this measurement was repeated at 2 PM. Respiratory symptoms and medical history were assessed by questionnaire. The within- and between-session repeatability of FE_NO and log-transformed FE_NO was described. The power of a longitudinal study based on a relative increase in FE_NO was estimated using a bilateral t-test of the log-transformed FENO using the between-session variance of the assay. Results: FE_NO measurements were highly reproducible throughout the study. FE_NO was significantly higher in males than females regardless of smoking status. FE_NO was positively associated with height (p < 0.001), gender (p < 0.034), smoking (p < 0.0001) and percent FEV1/FVC (p < 0.001) but not with age (p = 0.987). The between-session standard deviation was roughly constant on the log scale. Assuming the between-session standard deviation is equal to its longitudinal equivalent, either 111 or 29 subjects would be necessary to achieve an 80% power in detecting a 3% or a 10% increase in FE_NO respectively. Conclusion: The good reproducibility of FENO is not influenced by gender or smoking habits. In a well controlled, longitudinal study it should allow detecting even small increases in FENO with a reasonable population size. © 2008 Bohadana et al;licensee BioMed Central Ltd.

关键词： Force Vital Capacity Airway Inflammation multiple linear regression model Atopic Subject Bronchial Provocation Test

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Financing demand forecast and analysis for China logistics industry

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Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology 2008年第11期30卷 172-175页

作者： Liu, Wei-Hua School of Management Tianjin University Tianjin 300072 China

The current issues of financial demand for China logistics industry was analyzed, the importance to forecast financial demand was put forward. With the multiple linear regression model, the regression equations among GDP increasing rate, bank financing and stock financing in East China, Middle China and West China were given respectively. By calculating the increments of bank financing and stock financing of logistics industry, the annual and total financing demand amount for each province were brought out. The total financing demand amount for China logistics industry from 2008 to 2015 was discussed, the financing demand proportions for different regions was also explained. Some useful policies to meet China logistics industry financing demand were suggested at last.

关键词： Financing demand Forecast Logistics industry multiple linear regression model

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Use of selected chemical markers in combination with a multiple regression model to assess the contribution of domesticated animal sources of fecal pollution in the environment

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CHEMOSPHERE 2007年第10期69卷 1617-1624页

作者： Tyagi, Punam Edwards, Dwayne R. Coyne, Mark S. Univ Kentucky Coll Agr Biosyst & Agr Engn Dept Lexington KY 40546 USA Univ Kentucky Coll Agr Plant Soil Sci Dept Lexington KY 40546 USA

Human and animal wastes are major sources of environmental pollution. Reliable methods of identifying waste sources are necessary to specify the types and locations of measures that best prevent and mitigate pollution. This investigation demonstrates the use of chemical markers (fecal sterols and bile acids) to identify selected sources of fecal pollution in the environment. Fecal sterols and bile acids were determined for pig, horse, cow, and chicken feces (10 - 26 feces samples for each animal). Concentrations of major fecal sterols (coprostanol, epicoprostanol, cholesterol, cholestanol, stigmastanol, and stigmasterol) and bile acids (lithocholic acid, deoxycholic acid, cholic acid, chenodeoxycholic acid, ursodeoxycholic acid, and hyodeoxycholic acid) were determined using a gas chromatography and mass spectrometer (GC - MS) technique. The fecal sterol and bile acid concentration data were used to estimate parameters of a multiple linear regression model for fecal source identification. The regression model was calibrated using 75% of the available data validated against the remaining 25% of the data points in a jackknife process that was repeated 15 times. The regression results were very favorable in the validation data set, with an overall coefficient of determination between predicted and actual fecal source of 0.971. To check the potential of the proposed model, it was applied on a set of simulated runoff data in predicting the specific animal sources. Almost 100% accuracy was obtained between the actual and predicted fecal sources. While additional work using polluted water (as opposed to fresh fecal samples) as well as multiple pollution sources are needed, results of this study clearly indicate the potential of this model to be useful in identifying the individual sources of fecal pollution. Published by Elsevier Ltd.

关键词： bile acids fecal samples GC-MS multiple linear regression model runoff sterols

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Carbon stock and organic carbon dynamics in soils of Rajasthan, India

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JOURNAL OF ARID ENVIRONMENTS 2007年第3期68卷 408-421页

作者： Singh, S. K. Singh, A. K. Sharma, B. K. Tarafdar, J. C. Cent Arid Zone Res Inst Jodhpur 343003 Rajasthan India

Soil carbon stock (CS), was estimated in the 0-25 and 0-100 cm soil depths of and and semi-arid regions of Rajasthan. Carbon stock was 2.13 Pg in the 0-100cm soil depth, of which 1.23 Pg was soil organic carbon and 0.90 Pg was soil inorganic carbon. The surface horizon (0-25 cm) stored 31% of the soil carbon stock. Soil carbon stocks were higher in Entisols (0.72 Pg or 33.6% of CS on 43.6% of the land area) and Aridisols (0.70Pg or 32.7% of CS on 28.9% of the land area) than in Inceptisols(0.61 Pg or 28.6% of CS on 24.01% of the land area), Alfisols (0.015 Pg or 0.007% of CS on 0.76% of the land area) and Verisols (0.105 Pg or 0.005% of the CS on the 3.2% of the land area). Torripsamments, Haplocambids and Haplustepts together held 80% of CS and 86.9% of soil organic carbon stock, whereas Haplocambids, Petrocalcids and Haplustepts comprised 72% inorganic carbon stock. Soil organic carbon density (SOC) ranged from 4000 to 7000 kg/km(2) in Haplustalfs, Haplusterts, Haplustepts and Torripsamments, while its inorganic counterpart 4200-4600 kg/km(2)/year SOC could be sequestered in untilled soils of the and region, which have year-round canopy cover. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： multiple linear regression model soil organic and inorganic carbon density soil organic carbon dynamics

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A novel approach for prediction of tacrolimus blood concentration in liver transplantation patients in the intensive care unit through support vector regression

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CRITICAL CARE 2007年第4期11卷 1-7页

作者： Van Looy, Stijn Verplancke, Thierry Benoit, Dominique Hoste, Eric Van Maele, Georges De Turck, Filip Decruyenaere, Johan Ghent Univ Hosp Dept Intens Care Ghent Belgium Univ Ghent Dept Informat Technol INTEC Ghent Belgium Univ Ghent Dept Med Stat Ghent Belgium

Introduction Tacrolimus is an important immunosuppressive drug for organ transplantation patients. It has a narrow therapeutic range, toxic side effects, and a blood concentration with wide intra-and interindividual variability. Hence, it is of the utmost importance to monitor tacrolimus blood concentration, thereby ensuring clinical effect and avoiding toxic side effects. Prediction models for tacrolimus blood concentration can improve clinical care by optimizing monitoring of these concentrations, especially in the initial phase after transplantation during intensive care unit (ICU) stay. This is the first study in the ICU in which support vector machines, as a new data modeling technique, are investigated and tested in their prediction capabilities of tacrolimus blood concentration. linear support vector regression (SVR) and nonlinear radial basis function (RBF) SVR are compared with multiple linear regression (MLR). Methods Tacrolimus blood concentrations, together with 35 other relevant variables from 50 liver transplantation patients, were extracted from our ICU database. This resulted in a dataset of 457 blood samples, on average between 9 and 10 samples per patient, finally resulting in a database of more than 16,000 data values. Nonlinear RBF SVR, linear SVR, and MLR were performed after selection of clinically relevant input variables and model parameters. Differences between observed and predicted tacrolimus blood concentrations were calculated. Prediction accuracy of the three methods was compared after fivefold cross-validation (Friedman test and Wilcoxon signed rank analysis). Results linear SVR and nonlinear RBF SVR had mean absolute differences between observed and predicted tacrolimus blood concentrations of 2.31 ng/ml (standard deviation [SD] 2.47) and 2.38 ng/ml (SD 2.49), respectively. MLR had a mean absolute difference of 2.73 ng/ml (SD 3.79). The difference between linear SVR and MLR was statistically significant (p < 0.001). RBF SVR had the ad

关键词： Tacrolimus multiple linear regression Support Vector regression multiple linear regression model Support Vector regression model

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Respiratory distress syndrome-associated inflammation is related to early but not late peri/intraventricular hemorrhage in preterm infants

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JOURNAL OF PEDIATRICS 2006年第6期148卷 740-746页

作者： Krediet, Tannette G. Kavelaars, Annemieke Vreman, Hendrik J. Heijnen, Cobi J. van Bel, Frank Univ Utrecht Wilhelmina Childrens Hosp Dept Neonatol Med Ctr NL-3508 AB Utrecht Netherlands Univ Utrecht Wilhelmina Childrens Hosp Lab Psychoneuroimmunol & Perinatol Med Ctr NL-3508 AB Utrecht Netherlands Stanford Univ Sch Med Dept Neonatol Stanford CA 94305 USA

Objective To investigate whether or not peri/intraventricular hemorrhages (PIVHs) occurring in the first 12 hours of life (early PIVHs) are related to respiratory distress syndrome (RDS)-associated inflammatory factors in contrast to PIVHs -developing after 12 hours of life (late PIVHs). Study design Blood samples obtained at 0 to 12 hours, 48 to 72 hours, and 168 hours of life were evaluated for determination of the proinflammatory cytokines interleukin (IL)-8 and IL-6, tumor necrosis factor (TNF)-alpha, and malondialdehyde (MDA) as measures of lipid peroxidation. Simultaneously, cranial ultrasonography was performed in 114 neonates under 32 weeks gestational age. Results Out of the total study group of 114 neonates, 67 (59%) had RDS. Early PIVH occurred in 16 neonates, 14 of whom (88%) had RDS. Late PIVHs occurred in 12 neonates. Neonates with RDS had higher IL-8 and IL-6 levels at 0 to 12 hours (P <.0001;<.0001) and at 48 to 72 hours (P <.001;<.01) than those without RDS. Neonates with early PIVH had higher IL-8 (P <.02), IL-6 (P <.02), and MDA (P <.01) levels at 0 to 12 hours than those With late PIVH or no PIVH. Those with early PIVH had higher IL-8 levels at 48 to 72 hours than those without PIVH (P <.02). multiple linear regression revealed an association between RDS/early PIVH and IL-8, IL-6, and MDA levels. Conclusions An RDS-associated increase in proinflammatory cytokine and MDA levels was associated with early PIVHs, but not with late PIVHs, suggesting a different etiopathogenesis in early versus late PIVHs.

关键词： CPAP Continuous positive airway pressure IL Interleukin LPS Lipopolysaccharide MDA Malondialdehyde MLR multiple linear regression model PIVH Peri/intraventricular hemorrhage RDS Respiratory distress syndrome TNF Tumor necrosis factor

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Selection of optimal recording sites for limited lead body surface potential mapping: A sequential selection based approach

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BMC Medical Informatics and Decision Making 2006年第1期6卷 1-9页

作者： Finlay, Dewar D. Nugent, Chris D. Donnelly, Mark P. Lux, Robert L. McCullagh, Paul J. Black, Norman D. School of Computing and Mathematics Faculty of Engineering University of Ulster Belfast United Kingdom Nora Eccles Harrison Cardiovascular Research and Training Institute University of Utah Slat Lake City United States

Background: In this study we propose the development of a new algorithm for selecting optimal recording sites for limited lead body surface potential mapping. The proposed algorithm differs from previously reported methods in that it is based upon a simple and intuitive data driven technique that does not make any presumptions about deterministic characteristics of the data. It uses a forward selection based search technique to find the best combination of electrocardiographic leads. Methods: The study was conducted using a dataset consisting of body surface potential maps (BSPM) recorded from 116 subjects which included 59 normals and 57 subjects exhibiting evidence of old Myocardial Infarction (MI). The performance of the algorithm was evaluated using spatial RMS voltage error and correlation coefficient to compare original and reconstructed map frames. Results: In all, three configurations of the algorithm were evaluated and it was concluded that there was little difference in the performance of the various configurations. In addition to observing the performance of the selection algorithm, several lead subsets of 32 electrodes as chosen by the various configurations of the algorithm were evaluated. The rationale for choosing this number of recording sites was to allow comparison with a previous study that used a different algorithm, where 32 leads were deemed to provide an acceptable level of reconstruction performance. Conclusion: It was observed that although the lead configurations suggested in this study were not identical to that suggested in the previous work, the systems did bear similar characteristics in that recording sites were chosen with greatest density in the precordial region. © 2006 Finlay et al;licensee BioMed Central Ltd.

关键词： multiple linear regression model Feature Subset Recording Site Reconstruction Performance Transformation Coefficient

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