981 resultados para Simple linear regression


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Tese de Doutoramento em Engenharia Civil.

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Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.

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The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

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BACKGROUND Available screening tests for dementia are of limited usefulness because they are influenced by the patient's culture and educational level. The Eurotest, an instrument based on the knowledge and handling of money, was designed to overcome these limitations. The objective of this study was to evaluate the diagnostic accuracy of the Eurotest in identifying dementia in customary clinical practice. METHODS A cross-sectional, multi-center, naturalistic phase II study was conducted. The Eurotest was administered to consecutive patients, older than 60 years, in general neurology clinics. The patients' condition was classified as dementia or no dementia according to DSM-IV diagnostic criteria. We calculated sensitivity (Sn), specificity (Sp) and area under the ROC curves (aROC) with 95% confidence intervals. The influence of social and educational factors on scores was evaluated with multiple linear regression analysis, and the influence of these factors on diagnostic accuracy was evaluated with logistic regression. RESULTS Sixteen neurologists recruited a total of 516 participants: 101 with dementia, 380 without dementia, and 35 who were excluded. Of the 481 participants who took the Eurotest, 38.7% were totally or functionally illiterate and 45.5% had received no formal education. Mean time needed to administer the test was 8.2+/-2.0 minutes. The best cut-off point was 20/21, with Sn = 0.91 (0.84-0.96), Sp = 0.82 (0.77-0.85), and aROC = 0.93 (0.91-0.95). Neither the scores on the Eurotest nor its diagnostic accuracy were influenced by social or educational factors. CONCLUSION This naturalistic and pragmatic study shows that the Eurotest is a rapid, simple and useful screening instrument, which is free from educational influences, and has appropriate internal and external validity.

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ABSTRACT: BACKGROUND: The ability of different obesity indices to predict cardiovascular risk is still debated in youth and few data are available in sub Saharan Africa. We compared the associations between several indices of obesity and cardiovascular risk factors (CVRFs) in late adolescence in the Seychelles. METHODS: We measured body mass index (BMI), waist circumference, waist/hip ratio (WHiR), waist/height ratio (WHtR) and percent fat mass (by bioimpedance) and 6 CVRFs (blood pressure, LDL-cholesterol, HDL-cholesterol, triglycerides, fasting blood glucose and uric acid) in 423 youths aged 19-20 years from the general population. RESULTS: The prevalence of overweight/obesity and several CVRFs was high, with substantial sex differences. Except for glucose in males and LDL-cholesterol in females, all obesity indices were associated with CVRFs. BMI consistently predicted CVRFs at least as well as the other indices. Linear regression on BMI had standardized regression coefficients of 0.25-0.36 for most CVRFs (p<0.01) and ROC analysis had an AUC between 60%-75% for most CVRFs. BMI also predicted well various combinations of CVRFs: 36% of male and 16% of female lean subjects (BMI P90). CONCLUSION: There was an elevated prevalence of obesity and of several CVRFs in youths in Seychelles. BMI predicted single or combined CVRFs at least as well as other simple obesity indices.

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We introduce several exact nonparametric tests for finite sample multivariatelinear regressions, and compare their powers. This fills an important gap inthe literature where the only known nonparametric tests are either asymptotic,or assume one covariate only.

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Random coefficient regression models have been applied in differentfields and they constitute a unifying setup for many statisticalproblems. The nonparametric study of this model started with Beranand Hall (1992) and it has become a fruitful framework. In thispaper we propose and study statistics for testing a basic hypothesisconcerning this model: the constancy of coefficients. The asymptoticbehavior of the statistics is investigated and bootstrapapproximations are used in order to determine the critical values ofthe test statistics. A simulation study illustrates the performanceof the proposals.

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OBJECTIVE: Best long-term practice in primary HIV-1 infection (PHI) remains unknown for the individual. A risk-based scoring system associated with surrogate markers of HIV-1 disease progression could be helpful to stratify patients with PHI at highest risk for HIV-1 disease progression. METHODS: We prospectively enrolled 290 individuals with well-documented PHI in the Zurich Primary HIV-1 Infection Study, an open-label, non-randomized, observational, single-center study. Patients could choose to undergo early antiretroviral treatment (eART) and stop it after one year of undetectable viremia, to go on with treatment indefinitely, or to defer treatment. For each patient we calculated an a priori defined "Acute Retroviral Syndrome Severity Score" (ARSSS), consisting of clinical and basic laboratory variables, ranging from zero to ten points. We used linear regression models to assess the association between ARSSS and log baseline viral load (VL), baseline CD4+ cell count, and log viral setpoint (sVL) (i.e. VL measured ≥90 days after infection or treatment interruption). RESULTS: Mean ARSSS was 2.89. CD4+ cell count at baseline was negatively correlated with ARSSS (p = 0.03, n = 289), whereas HIV-RNA levels at baseline showed a strong positive correlation with ARSSS (p<0.001, n = 290). In the regression models, a 1-point increase in the score corresponded to a 0.10 log increase in baseline VL and a CD4+cell count decline of 12/µl, respectively. In patients with PHI and not undergoing eART, higher ARSSS were significantly associated with higher sVL (p = 0.029, n = 64). In contrast, in patients undergoing eART with subsequent structured treatment interruption, no correlation was found between sVL and ARSSS (p = 0.28, n = 40). CONCLUSION: The ARSSS is a simple clinical score that correlates with the best-validated surrogate markers of HIV-1 disease progression. In regions where ART is not universally available and eART is not standard this score may help identifying patients who will profit the most from early antiretroviral therapy.

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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

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OBJECTIVES: in a retrospective study, attempts have been made to identify individual organ-dysfunction risk profiles influencing the outcome after surgery for ruptured abdominal aortic aneurysms. METHODS: out of 235 patients undergoing graft replacement for abdominal aortic aneurysms, 57 (53 men, four women, mean age 72 years [s.d. 8.8]) were treated for ruptured aneurysms in a 3-year period. Forty-eight preoperative, 13 intraoperative and 34 postoperative variables were evaluated statistically. A simple multi-organ dysfunction (MOD) score was adopted. RESULTS: the perioperative mortality was 32%. Three patients died intraoperatively, four within 48 h and 11 died later. A significant influence for pre-existing risk factors was identified only for cardiovascular diseases. Multiple linear-regression analysis indicated that a haemoglobin <90 g/l, systolic blood pressure <80 mmHg and ECG signs of ischaemia at admission were highly significant risk factors. The cause of death for patients, who died more than 48 h postoperatively, was mainly MOD. All patients with a MOD score >/=4 died (n=7). These patients required 27% of the intensive-care unit (ICU) days of all patients and 72% of the ICU days of the non-survivors. CONCLUSION: patients with ruptured aortic aneurysms from treatment should not be excluded. However, a physiological scoring system after 48 h appears justifiable in order to decide on the appropriateness of continual ICU support.

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The unifying objective of Phases I and II of this study was to determine the feasibility of the post-tensioning strengthening method and to implement the technique on two composite bridges in Iowa. Following completion of these two phases, Phase III was undertaken and is documented in this report. The basic objectives of Phase III were further monitoring bridge behavior (both during and after post-tensioning) and developing a practical design methodology for designing the strengthening system under investigation. Specific objectives were: to develop strain and force transducers to facilitate the collection of field data; to investigate further the existence and effects of the end restraint on the post-tensioning process; to determine the amount of post-tensioning force loss that occurred during the time between the initial testing and the retesting of the existing bridges; to determine the significance of any temporary temperature-induced post-tensioning force change; and to develop a simplified design methodology that would incorporate various variables such as span length, angle-of-skew, beam spacing, and concrete strength. Experimental field results obtained during Phases II and III were compared to the theoretical results and to each other. Conclusions from this research are as follows: (1) Strengthening single-span composite bridges by post-tensioning is a viable, economical strengthening technique. (2) Behavior of both bridges was similar to the behavior observed from the bridges during field tests conducted under Phase II. (3) The strain transducers were very accurate at measuring mid-span strain. (4) The force transducers gave excellent results under laboratory conditions, but were found to be less effective when used in actual bridge tests. (5) Loss of post-tensioning force due to temperature effects in any particular steel beam post-tensioning tendon system were found to be small. (6) Loss of post-tensioning force over a two-year period was minimal. (7) Significant end restraint was measured in both bridges, caused primarily by reinforcing steel being continuous from the deck into the abutments. This end restraint reduced the effectiveness of the post-tensioning but also reduced midspan strains due to truck loadings. (8) The SAP IV finite element model is capable of accurately modeling the behavior of a post-tensioned bridge, if guardrails and end restraints are included in the model. (9) Post-tensioning distribution should be separated into distributions for the axial force and moment components of an eccentric post-tensioning force. (10) Skews of 45 deg or less have a minor influence on post-tensioning distribution. (11) For typical Iowa three-beam and four-beam composite bridges, simple regression-derived formulas for force and moment fractions can be used to estimate post-tensioning distribution at midspan. At other locations, a simple linear interpolation gives approximately correct results. (12) A simple analytical model can accurately estimate the flexural strength of an isolated post-tensioned composite beam.

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Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

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The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

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Summary: Particulate air pollution is associated with increased cardiovascular risk. The induction of systemic inflammation following particle inhalation represents a plausible mechanistic pathway. The purpose of this study was to assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers in 6183 adults in Lausanne, Switzerland. The results show that short-term exposure to PM10 was associated with higher levels of circulating IL-6 and TNF-α. The positive association of PM10 with markers of systemic inflammation materializes the link between air pollution and cardiovascular risk. Background: Variations in short-term exposure to particulate matters (PM) have been repeatedly associated with daily all-cause mortality. Particle-induced inflammation has been postulated to be one of the important mechanisms for increased cardiovascular risk. Experimental in-vitro, in-vivo and controlled human studies suggest that interleukin 6 (IL-6) and tumor-necrosis-factor alpha (TNF-α) could represent key mediators of the inflammatory response to PM. The associations of short-term exposure to ambient PM with circulating inflammatory markers have been inconsistent in studies including specific subgroups so far. The epidemiological evidence linking short-term exposure to ambient PM and systemic inflammation in the general population is scarce. So far, large-scale population-based studies have not explored important inflammatory markers such as IL-6, IL-1β or TNF-α. We therefore analyzed the associations between short-term exposure to ambient PM10 and circulating levels of high-sensitive CRP (hs-CRP), IL-6, IL-1β and TNF-α in the population-based CoLaus study. Objectives: To assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers, including hs-CRP, IL-6, IL-1β and TNF-α, in adults aged 35 to 75 years from the general population. Methodology: All study subjects were participants to the CoLaus study (www.colaus.ch) and the baseline examination was carried out from 2003 to 2006. Overall, 6184 participants were included. For the present analysis, 6183 participants had data on at least one of the four measured circulating inflammatory markers. The monitoring data was obtained from the website of Swiss National Air Pollution Monitoring Network (NABEL). We analyzed data on PM10 as well as outside air temperature, pressure and humidity. Hourly concentrations of PM10 were collected from 1 January 2003 to 31 December 2006. Robust linear regression (PROC ROBUSTREG) was used to evaluate the relationship between cytokine inflammatory and PM10. We adjusted all analyses for age, sex, body mass index, smoking status, alcohol consumption, diabetes status, hypertension status, education levels, zip code, and statin intake. All data were adjusted for the effects of weather by including temperature, barometric pressure, and season as covariates in the adjusted models. We performed simple and multiple logistic regression analyses. Descriptive statistical analysis used the Wilcoxon rank sum test (for medians). All data analyses were performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA), and a two-sided significance level of 5% was used. Results: PM10 levels averaged over 24 hours were significantly and positively associated with continuous IL-6 and TNF-α levels, in the whole study population both in unadjusted and adjusted analyses. For each cytokine, there was a similar seasonal pattern, with wider confidence intervals in summer than during the other seasons, which might partly be due to the smaller number of participants examined in summer. The associations of PM10 with IL-6 and TNF-α were also found after having dichotomized these cytokines into high versus low levels, which suggests that the associations of PM10 with the continuous cytokine levels are very robust to any distributional assumption and to potential outlier values. In contrast with what we observed for continuous IL-1β levels, high PM10 levels were significantly associated with high IL-1β. PM10 was significantly associated with IL-6 and TNF-α in men, but with TNF-α only in women. However, there was no significant statistical interaction between PM10 and sex. For IL-6 and TNF-α, the associations tended to be stronger in younger people, with a significant interaction between PM10 and age groups for IL-6. PM10 was significantly associated with IL-6 and TNF-α in the healthy group and also in the "non-healthy" group, although the statistical interaction between healthy status and PM10 was not significant. Conclusion: In summary, we found significant independent positive associations of short-term exposure to PM10 with circulating levels of IL-6 and TNF-α in the adult population of Lausanne. Our findings strongly support the idea that short-term exposure to PM10 is sufficient to induce systemic inflammation on a broad scale in the general population. From a public health perspective, the reported association of elevated inflammatory cytokines with short-term exposure to PM10 in a city with relatively clean air such as Lausanne supports the importance of limiting urban air pollution levels.

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It is generally accepted that between 70 and 80% of manufacturing costs can be attributed to design. Nevertheless, it is difficult for the designer to estimate manufacturing costs accurately, especially when alternative constructions are compared at the conceptual design phase, because of the lack of cost information and appropriate tools. In general, previous reports concerning optimisation of a welded structure have used the mass of the product as the basis for the cost comparison. However, it can easily be shown using a simple example that the use of product mass as the sole manufacturing cost estimator is unsatisfactory. This study describes a method of formulating welding time models for cost calculation, and presents the results of the models for particular sections, based on typical costs in Finland. This was achieved by collecting information concerning welded products from different companies. The data included 71 different welded assemblies taken from the mechanical engineering and construction industries. The welded assemblies contained in total 1 589 welded parts, 4 257 separate welds, and a total welded length of 3 188 metres. The data were modelled for statistical calculations, and models of welding time were derived by using linear regression analysis. Themodels were tested by using appropriate statistical methods, and were found to be accurate. General welding time models have been developed, valid for welding in Finland, as well as specific, more accurate models for particular companies. The models are presented in such a form that they can be used easily by a designer, enabling the cost calculation to be automated.