931 resultados para multiple linear regression analysis


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Objectives The relevance of the SYNTAX score for the particular case of patients with acute ST- segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI)  has previously only been studied in the setting of post hoc analysis of large prospective randomized clinical trials. A "real-life" population approach has never been explored before. The aim of this study was to evaluate the impact of the SYNTAX score for the prediction of the myocardial infarction size, estimated by the creatin-kinase (CK) peak value, using the SYNTAX score in patients treated with primary coronary intervention for acute ST-segment elevation myocardial infarction. Methods The primary endpoint of the study was myocardial infarction size as measured by the CK peak value. The SYNTAX score was calculated retrospectively in 253 consecutive patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI) in a large tertiary referral center in Switzerland, between January 2009 and June 2010. Linear regression analysis was performed to compare myocardial infarction size with the SYNTAX score. This same endpoint was then stratified according to SYNTAX score tertiles: low <22 (n=178), intermediate [22-32] (n=60), and high >=33 (n=15). Results There were no significant differences in terms of clinical characteristics between the three groups. When stratified according to the SYNTAX score tertiles, average CK peak values of 1985 (low<22), 3336 (intermediate [22-32]) and 3684 (high>=33) were obtained with a p-value <0.0001. Bartlett's test for equal variances between the three groups was 9.999 (p-value <0.0067). A moderate Pearson product-moment correlation coefficient (r=0.4074) with a high statistical significance level (p-value <0.0001) was found. The coefficient of determination (R^2=0.1660) showed that approximately 17% of the variation of CK peak value (myocardial infarction size) could be explained by the SYNTAX score, i.e. by the coronary disease complexity. Conclusion In an all-comers population, the SYNTAX score is an additional tool in predicting myocardial infarction size in patients treated with primary percutaneous coronary intervention (PPCI). The stratification of patients in different risk groups according to SYNTAX enables to identify a high-risk population that may warrant particular patient care.

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Switzerland has the lowest adolescent fertility rate in Western Europe. According to data collected in 1993 as part of the Swiss Multicentre Adolescent Survey on Health, 5% of 1,726 sexually active adolescents in a group of 3,993 15-20-year-old women enrolled in academic or vocational classes had ever been pregnant; most of these women (80%) had terminated their pregnancy. Adolescents who had ever been pregnant did not differ significantly from those who had not by demographic characteristics. Multiple logistic regression analysis identified seven factors associated with pregnancy: having had four or more sexual partners; not having used contraceptives at first intercourse; ever use of less-effective contraceptive methods; having used illicit drugs during the last 30 days; living apart from one's parents; recently experiencing stress; and perceiving a lack of future prospects.

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Erosion is deleterious because it reduces the soil's productivity capacity for growing crops and causes sedimentation and water pollution problems. Surface and buried crop residue, as well as live and dead plant roots, play an important role in erosion control. An efficient way to assess the effectiveness of such materials in erosion reduction is by means of decomposition constants as used within the Revised Universal Soil Loss Equation - RUSLE's prior-land-use subfactor - PLU. This was investigated using simulated rainfall on a 0.12 m m-1 slope, sandy loam Paleudult soil, at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul, in Eldorado do Sul, State of Rio Grande do Sul, Brazil. The study area had been covered by native grass pasture for about fifteen years. By the middle of March 1996, the sod was mechanically mowed and the crop residue removed from the field. Late in April 1996, the sod was chemically desiccated with herbicide and, about one month later, the following treatments were established and evaluated for sod biomass decomposition and soil erosion, from June 1996 to May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) and (b) soil without tillage, with surface residue and dead roots; (c) soil without tillage, with dead roots only; (d) soil tilled conventionally every two-and-half months, with dead roots plus incorporated residue; and (e) soil tilled conventionally every six months, with dead roots plus incorporated residue. Simulated rainfall was applied with a rotating-boom rainfall simulator, at an intensity of 63.5 mm h-1 for 90 min, eight to nine times during the experimental period (about every two-and-half months). Surface and subsurface sod biomass amounts were measured before each rainfall test along with the erosion measurements of runoff rate, sediment concentration in runoff, soil loss rate, and total soil loss. Non-linear regression analysis was performed using an exponential and a power model. Surface sod biomass decomposition was better depicted by the exponential model, while subsurface sod biomass was by the power model. Subsurface sod biomass decomposed faster and more than surface sod biomass, with dead roots in untilled soil without residue on the surface decomposing more than dead roots in untilled soil with surface residue. Tillage type and frequency did not appreciably influence subsurface sod biomass decomposition. Soil loss rates increased greatly with both surface sod biomass decomposition and decomposition of subsurface sod biomass in the conventionally tilled soil, but they were minimally affected by subsurface sod biomass decomposition in the untilled soil. Runoff rates were little affected by the studied treatments. Dead roots plus incorporated residues were effective in reducing erosion in the conventionally tilled soil, while consolidation of the soil surface was important in no-till. The residual effect of the turned soil on erosion diminished gradually with time and ceased after two years.

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BACKGROUND: Several studies have reported increased levels of inflammatory biomarkers in chronic kidney disease (CKD), but data from the general population are sparse. In this study, we assessed levels of the inflammatory markers C-reactive protein (hsCRP), tumor necrosis factor α (TNF-α), interleukin (IL)-1β and IL-6 across all ranges of renal function. METHODS: We conducted a cross-sectional study in a random sample of 6,184 Caucasian subjects aged 35-75 years in Lausanne, Switzerland. Serum levels of hsCRP, TNF-α, IL-6, and IL-1β were measured in 6,067 participants (98.1%); serum creatinine-based estimated glomerular filtration rate (eGFR(creat), CKD-EPI formula) was used to assess renal function, and albumin/creatinine ratio on spot morning urine to assess microalbuminuria (MAU). RESULTS: Higher serum levels of IL-6, TNF-α and hsCRP and lower levels of IL-1β were associated with a lower renal function, CKD (eGFR(creat) <60 ml/min/1.73 m(2); n = 283), and MAU (n = 583). In multivariate linear regression analysis adjusted for age, sex, hypertension, smoking, diabetes, body mass index, lipids, antihypertensive and hypolipemic therapy, only log-transformed TNF-α remained independently associated with lower renal function (β -0.54 ±0.19). In multivariate logistic regression analysis, higher TNF-α levels were associated with CKD (OR 1.17; 95% CI 1.01-1.35), whereas higher levels of IL-6 (OR 1.09; 95% CI 1.02-1.16) and hsCRP (OR 1.21; 95% CI 1.10-1.32) were associated with MAU. CONCLUSION: We did not confirm a significant association between renal function and IL-6, IL-1β and hsCRP in the general population. However, our results demonstrate a significant association between TNF-α and renal function, suggesting a potential link between inflammation and the development of CKD. These data also confirm the association between MAU and inflammation.

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OBJECTIVE: To investigate the association between early depressive behavior after stroke onset and occurrence of poststroke depression (PSD) at 3- and 12-month follow-up evaluations. METHODS: The study prospectively included 273 patients with first-ever single uncomplicated ischemic stroke. In the stroke unit, nurses scored crying, overt sadness, and apathy daily using an observational method to include patients with comprehension deficits. The Barthel Index was used to assess disability. Follow-up evaluation at months 3 and 12 included psychiatric assessment based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition. RESULTS: Crying (19.8%), overt sadness (50.5%), and apathy (47.6%) were observed. Of the patients observed crying, 4 showed pathologic crying, 19 emotionalism, and 12 catastrophic reactions. Crying and overt sadness, but not apathy, were associated with a subjective experience of depression (p < 0.05). Thirty of 52 (58%) patients observed crying, 12 of 19 (63%) patients with emotionalism, and 5 of 12 (41%) patients with catastrophic reactions developed PSD within the first year. Multiple logistic regression analysis showed that only severe functional disability (odds ratio [OR], 4.31; 95% CI, 2.41 to 7.69), crying behaviors (OR, 2.66; 95% CI, 1.35 to 5.27), and an age <68 years (OR, 2.32; 95% CI, 1.30 to 4.13) were (p < 0.05) predictors of late PSD development (13% of the variance). CONCLUSIONS: In the stroke unit, crying and overt sadness are more reliable indicators of depressed mood than apathy. In patients with first-ever stroke, crying behaviors soon after stroke, a younger age, and severe disability are predictors of poststroke depression occurrence within the first year after stroke onset.

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In this study, we assessed whether the white-coat effect (difference between office and daytime blood pressure (BP)) is associated with nondipping (absence of BP decrease at night). Data were available in 371 individuals of African descent from 74 families selected from a population-based hypertension register in the Seychelles Islands and in 295 Caucasian individuals randomly selected from a population-based study in Switzerland. We used standard multiple linear regression in the Swiss data and generalized estimating equations to account for familial correlations in the Seychelles data. The prevalence of systolic and diastolic nondipping (<10% nocturnal BP decrease) and white-coat hypertension (WCH) was respectively 51, 46, and 4% in blacks and 33, 37, and 7% in whites. When white coat effect and nocturnal dipping were taken as continuous variables (mm Hg), systolic (SBP) and diastolic BP (DBP) dipping were associated inversely and independently with white-coat effect (P < 0.05) in both populations. Analogously, the difference between office and daytime heart rate was inversely associated with the difference between daytime and night-time heart rate in the two populations. These results did not change after adjustment for potential confounders. The white-coat effect is associated with BP nondipping. The similar associations between office-daytime values and daytime-night-time values for both BP and heart rate suggest that the sympathetic nervous system might play a role. Our findings also further stress the interest, for clinicians, of assessing the presence of a white-coat effect as a means to further identify patients at increased cardiovascular risk and guide treatment accordingly.

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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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In a recent paper A. S. Johal and D. J. Dunstan [Phys. Rev. B 73, 024106 (2006)] have applied multivariate linear regression analysis to the published data of the change in ultrasonic velocity with applied stress. The aim is to obtain the best estimates for the third-order elastic constants in cubic materials. From such an analysis they conclude that uniaxial stress data on metals turns out to be nearly useless by itself. The purpose of this comment is to point out that by a proper analysis of uniaxial stress data it is possible to obtain reliable values of third-order elastic constants in cubic metals and alloys. Cu-based shape memory alloys are used as an illustrative example.

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Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas. Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available. Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex geology.

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Detailed knowledge on water percolation into the soil in irrigated areas is fundamental for solving problems of drainage, pollution and the recharge of underground aquifers. The aim of this study was to evaluate the percolation estimated by time-domain-reflectometry (TDR) in a drainage lysimeter. We used Darcy's law with K(θ) functions determined by field and laboratory methods and by the change in water storage in the soil profile at 16 points of moisture measurement at different time intervals. A sandy clay soil was saturated and covered with plastic sheet to prevent evaporation and an internal drainage trial in a drainage lysimeter was installed. The relationship between the observed and estimated percolation values was evaluated by linear regression analysis. The results suggest that percolation in the field or laboratory can be estimated based on continuous monitoring with TDR, and at short time intervals, of the variations in soil water storage. The precision and accuracy of this approach are similar to those of the lysimeter and it has advantages over the other evaluated methods, of which the most relevant are the possibility of estimating percolation in short time intervals and exemption from the predetermination of soil hydraulic properties such as water retention and hydraulic conductivity. The estimates obtained by the Darcy-Buckingham equation for percolation levels using function K(θ) predicted by the method of Hillel et al. (1972) provided compatible water percolation estimates with those obtained in the lysimeter at time intervals greater than 1 h. The methods of Libardi et al. (1980), Sisson et al. (1980) and van Genuchten (1980) underestimated water percolation.

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Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

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Introduction: Non-operative management (NOM) of blunt splenic injuries in hemodynamically stable patients is nowadays considered the standard treatment. Material and Methods: The aim was to clarify the criteria used for primary operative management (OM) and planned NOM. Furthermore, the study aimed to identify risk factors for failure of NOM. All adult patients with blunt splenic injuries treated from 2000-2008 were reviewed and a logistic regression analysis employed. Results: There were 206 patients (146 men, 70.9%). Mean age was 38.2 ± 19.1 years. The mean Injury Severity Score (ISS) was 30.9 ± 11.6. The American Association for the Surgery of Trauma (AAST) classification of the splenic injury was: grade I, n = 43 (20.9%); grade II, n = 52 (25.2%); grade III, n = 60 (29.1%), grade IV, n = 42 (20.4%) and grade V, n = 9 (4.4%). 47 patients (22.8%) required immediate surgery (OM). More than 5 units of red cell transfusions (odds ratio [OR] 13.72, P < 0.001), a Glasgow Coma Scale < 11 (OR 9.88, P = 0.009) and age ? 55 years (OR 3.29, P = 0.038) were associated with primary OM. 159 patients (77.2%) qualified for a non-surgical approach (NOM), which was successful in 89.9% (143/159). The overall splenic salvage rate amounted to 69.4% (143/206). Multiple logistic regression analysis found age ? 40 years to be the only factor significantly and independently related to the failure of NOM (OR 13.58, P = 0.001). Conclusion: Advanced age is associated with an increased failure rate of NOM in patients with blunt splenic injuries.

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BACKGROUND: Recently, it was shown that the relation between admission glucose and functional outcome after ischemic stroke is described by a J-shaped curve, with a glucose range of 3.7-7.3 mmol/l associated with a favorable outcome. We tested the hypothesis that persistence of hyperglycemia above this threshold at 24-48 h after stroke onset impairs 3-month functional outcome. METHODS: We analyzed all patients with glucose >7.3 mmol/l on admission from the Acute STroke Registry and Analysis of Lausanne (ASTRAL). Patients were divided into two groups according to their subacute glucose level at 24-48 h after last well-being time (group 1: ≤7.3 mmol/l, group 2: >7.3 mmol/l). A favorable functional outcome was defined as a modified Rankin Score (mRS) ≤2 at 3 months. A multiple logistic regression analysis of multiple demographic, clinical, laboratory and neuroimaging covariates was performed to assess predictors of an unfavorable outcome. RESULTS: A total of 1,984 patients with ischemic stroke were admitted between January 1, 2003 and October 20, 2009, within 24 h after last well-being time. In the 421 patients (21.2%) with admission glucose >7.3 mmol/l, the proportion of patients with a favorable outcome was not statistically significantly different between the two groups (59.2 vs. 48.7%, respectively). In multiple logistic regression analysis, unfavorable outcome was significantly associated with age (odds ratio, OR: 1.06, 95% confidence interval, 95% CI: 1.03-1.08 for every 10-year increase), National Institute of Health Stroke Score, NIHSS score, on admission (OR: 1.16, 95% CI: 1.11-1.21), prehospital mRS (OR: 12.63, 95% CI: 2.61-61.10 for patients with score >0), antidiabetic drug usage (OR: 0.36, 95% CI: 0.15-0.86) and glucose on admission (OR: 1.16, 95% CI: 1.02-1.31 for every 1 mmol/l increase). No association was found between persistent hyperglycemia at 24-28 h and outcome in either diabetics or nondiabetics. CONCLUSIONS: In ischemic stroke patients with acute hyperglycemia, persistent hyperglycemia (>7.3 mmol/l) at 24-48 h after stroke onset is not associated with a worse functional outcome at 3 months whether the patient was previously diabetic or not.

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Dual-energy X-ray absorptiometry (DXA) measurement of bone mineral density (BMD) is the reference standard for diagnosing osteoporosis but does not directly reflect deterioration in bone microarchitecture. The trabecular bone score (TBS), a novel grey-level texture measurement that can be extracted from DXA images, predicts osteoporotic fractures independent of BMD. Our aim was to identify clinical factors that are associated with baseline lumbar spine TBS. In total, 29,407 women ≥50yr at the time of baseline hip and spine DXA were identified from a database containing all clinical results for the Province of Manitoba, Canada. Lumbar spine TBS was derived for each spine DXA examination blinded to clinical parameters and outcomes. Multiple linear regression and logistic regression (lowest vs highest tertile) was used to define the sensitivity of TBS to other risk factors associated with osteoporosis. Only a small component of the TBS measurement (7-11%) could be explained from BMD measurements. In multiple linear regression and logistic regression models, reduced lumbar spine TBS was associated with recent glucocorticoid use, prior major fracture, rheumatoid arthritis, chronic obstructive pulmonary disease, high alcohol intake, and higher body mass index. In contrast, recent osteoporosis therapy was associated with a significantly lower likelihood for reduced TBS. Similar findings were seen after adjustment for lumbar spine or femoral neck BMD. In conclusion, lumbar spine TBS is strongly associated with many of the risk factors that are predictive of osteoporotic fractures. Further work is needed to determine whether lumbar spine TBS can replace some of the clinical risk factors currently used in fracture risk assessment.

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ABSTRACT: INTRODUCTION: Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a circulating enzyme with pro-inflammatory and oxidative activities associated with cardiovascular disease and ischemic stroke. While high plasma Lp-PLA2 activity was reported as a risk factor for dementia in the Rotterdam study, no association between Lp-PLA2 mass and dementia or Alzheimer's disease (AD) was detected in the Framingham study. The objectives of the current study were to explore the relationship of plasma Lp-PLA2 activity with cognitive diagnoses (AD, amnestic mild cognitive impairment (aMCI), and cognitively healthy subjects), cardiovascular markers, cerebrospinal fluid (CSF) markers of AD, and apolipoprotein E (APOE) genotype. METHODS: Subjects with mild AD (n = 78) and aMCI (n = 59) were recruited from the Memory Clinic, University Hospital, Basel, Switzerland; cognitively healthy subjects (n = 66) were recruited from the community. Subjects underwent standardised medical, neurological, neuropsychological, imaging, genetic, blood and CSF evaluation. Differences in Lp-PLA2 activity between the cognitive diagnosis groups were tested with ANOVA and in multiple linear regression models with adjustment for covariates. Associations between Lp-PLA2 and markers of cardiovascular disease and AD were explored with Spearman's correlation coefficients. RESULTS: There was no significant difference in plasma Lp-PLA2 activity between AD (197.1 (standard deviation, SD 38.4) nmol/min/ml) and controls (195.4 (SD 41.9)). Gender, statin use and low-density lipoprotein cholesterol (LDL) were independently associated with Lp-PLA2 activity in multiple regression models. Lp-PLA2 activity was correlated with LDL and inversely correlated with high-density lipoprotein (HDL). AD subjects with APOE-ε4 had higher Lp-PLA2 activity (207.9 (SD 41.2)) than AD subjects lacking APOE-ε4 (181.6 (SD 26.0), P = 0.003) although this was attenuated by adjustment for LDL (P = 0.09). No strong correlations were detected for Lp-PLA2 activity and CSF markers of AD. CONCLUSION: Plasma Lp-PLA2 was not associated with a diagnosis of AD or aMCI in this cross-sectional study. The main clinical correlates of Lp-PLA2 activity in AD, aMCI and cognitively healthy subjects were variables associated with lipid metabolism.