Association of increased time from chemoradiation (CRT) to esophagectomy (E) with increased surgical complications (Cx) in esophageal cancer (EC).

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 77-77
Author(s):  
Joshua E. Meyer ◽  
Alan Thomay ◽  
Karen J. Ruth ◽  
Talha Shaikh ◽  
Andre A. Konski ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Multivariable Analysis ◽  
Optimal Timing ◽  
Time Interval ◽  
Data Set ◽  
Estimated Blood Loss ◽  
The Mean

77 Background: EC is often treated with CRT followed by E. E is typically performed 6 weeks after completion of CRT, but the optimal timing is unknown. Previous work has shown that a longer time interval (TI) between CRT and E resulted in a higher percentage of patients (pts) with pathologic complete response. This study was undertaken to determine whether this improved response comes at the expense of increased surgical Cx. Methods: Complete records were available for 85 pts who underwent CRT and subsequent E at a single academic center from 2001-2011. Surgical Cx were collected. Univariable and multivariable analyses were performed to investigate the association between length of TI from CRT to E and Cx, adjusting for age, gender, and surgery type. Multiple linear regression was performed to examine the association of length of stay (LOS) and estimated blood loss (EBL) with TI, adjusting for covariates. Results: Of 85 patients, 72 were male and the histology was adenocarcinoma in 72. The median age was 61 (range: 36-80), the most common clinical stage was T3N1 and 60% of pts had ECOG performance status of 1 (range 0-2). The median length of CRT (most commonly Cisplatin, 5FU and 50.4 Gy) was 37 days and median TI from initiation of CRT to E was 89 days (range: 64-242). 59 pts (69%) experienced at least 1 complication. The mean TIs for pts with and without Cx were 97 and 87 days (P=0.019). When specific Cx were examined, the mean TI for pulmonary Cx was greater (107 v. 89 days; P=0.018). Patients experiencing anastamotic leaks had shorter mean TIs (83 v. 96 days; P=0.022). Multiple linear regression showed a positive association between LOS and TI (p=0.0027) but none with EBL. On multivariable analysis, increased TI predicted for pulmonary complications (OR 1.05, P=0.0061) and LOS (OR 1.03, P=0.033). Increased TI predicted for decreased risk of anastamotic leak (OR 0.94, P=0.063). Conclusions: In this retrospective data set, we demonstrated an association between longer TI from CRT to E and pulmonary toxicity in EC pts. Longer TI was also associated with increased LOS. In contrast, anastamotic leaks were associated with shorter TIs. These data suggest TI from CRT to E may impact the risk of Cx.

Breastfeeding Self-Efficacy and Its Relationship with the Perceived Stress and the Breastfeeding Performance in Iranian Mothers with Late Preterm Infants, 2019

2020 ◽  
Author(s):  
Akram Kahforoushan ◽  
Shirin Hasanpour ◽  
Mojgan Mirghafourvand
Keyword(s):  
Standard Deviation ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Preterm Infants ◽  
Perceived Stress ◽  
Self Efficacy ◽  
Short Form ◽  
Late Preterm ◽  
Late Preterm Infants ◽  
The Mean

Abstract BackgroundLate preterm infants suffer from many short-term and long-term problems after birth. The key factor in fighting these problems is effective breastfeeding. The present study aimedto determine the breastfeeding self-efficacy and its relationship with the perceived stress and breastfeeding performance in mothers with late preterm infants. MethodsIn this prospective study, 171 nursing mothers with late preterm infants born in Alzahra Medical Center of Tabriz, Iran, who met the conditions of this study were selected through convenience sampling. The Breastfeeding Self-Efficacy Scale-Short Form (BSES- SF) was employed to measure breastfeeding self-efficacy and 14-item Perceived Stress Scale (PSS14) was used to measure the perceived stress during 24 hours after giving birth and when the child was 4 months old the breastfeeding performance was measured by the standard breastfeeding performance questionnaire. The data were analyzed by Pearson and Spearman’s correlation tests, independent t-test, one-way ANOVA, and Multiple Linear Regression.ResultsThe mean (standard deviation) of breastfeeding self-efficacy equaled 50.0 (7.8) from the scores ranging between13-65 and the mean (standard deviation) of the perceived stress equaled to 26.5 (8.8) from the scores ranging between 0-56. The median (25-75 percentiles) of breastfeeding performance score in the mothers equaled 2.0 (1.0 to 3.0) from the scores ranging between 0-6. On the basis of multiple linear regression and through adjusting the personal-social characteristic, by increasing the score of the breastfeeding self-efficacy, the perceived stress was decreased to a statistically significant amount (B=-0.1, 95%CI=-0.3 to 0.0), however, there was no statistically significant relationship between breastfeeding self-efficacy and breastfeeding performance (p=0.418). ConclusionDue to the modifiable variability of breastfeeding self-efficacy and its role in perceived maternal stress, the development of appropriate strategies to further increase breastfeeding self-efficacy and provide more support to these mothers and infants is of particular importance.

Personal Adaptive Method to Assess Mental Tension during Daily Life Using Heart Rate Variability

2012 ◽  
Vol 51 (01) ◽  
pp. 39-44 ◽  
Author(s):  
K. Matsuoka ◽  
K. Yoshino
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Test Data ◽  
Daily Life ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Training Data ◽  
Data Set

SummaryObjectives: The aim of this study is to present a method of assessing psychological tension that is optimized to every individual on the basis of the heart rate variability (HRV) data which, to eliminate the influence of the inter-individual variability, are measured in a long time period during daily life.Methods: HRV and body accelerations were recorded from nine normal subjects for two months of normal daily life. Fourteen HRV indices were calculated with the HRV data at 512 seconds prior to the time of every mental tension level report. Data to be analyzed were limited to those with body accelerations of 30 mG (0.294 m/s2) and lower. Further, the differences from the reference values in the same time zone were calculated with both the mental tension score (Δtension) and HRV index values (ΔHRVI). The multiple linear regression model that estimates Δtension from the scores for principal components of ΔHRVI were then constructed for each individual. The data were divided into training data set and test data set in accordance with the twofold cross validation method. Multiple linear regression coefficients were determined using the training data set, and with the optimized model its generalization capability was checked using the test data set.Results: The subjects’ mean Pearson correlation coefficient was 0.52 with the training data set and 0.40 with the test data set. The subjects’ mean coefficient of determination was 0.28 with the training data set and 0.11 with the test data set.Conclusion: We proposed a method of assessing psychological tension that is optimized to every individual based on HRV data measured over a long period of daily life.

scholarly journals Taking into account latency, amplitude, and morphology: improved estimation of single-trial ERPs by wavelet filtering and multiple linear regression

2011 ◽  
Vol 106 (6) ◽  
pp. 3216-3229 ◽  
Author(s):  
L. Hu ◽  
M. Liang ◽  
A. Mouraux ◽  
R. G. Wise ◽  
Y. Hu ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Pain Perception ◽  
Event Related Potentials ◽  
Relevant Information ◽  
Single Trial ◽  
Data Set ◽  
Wavelet Filtering ◽  
Sensory Stimuli ◽  
Related Potentials

Across-trial averaging is a widely used approach to enhance the signal-to-noise ratio (SNR) of event-related potentials (ERPs). However, across-trial variability of ERP latency and amplitude may contain physiologically relevant information that is lost by across-trial averaging. Hence, we aimed to develop a novel method that uses 1) wavelet filtering (WF) to enhance the SNR of ERPs and 2) a multiple linear regression with a dispersion term (MLRd) that takes into account shape distortions to estimate the single-trial latency and amplitude of ERP peaks. Using simulated ERP data sets containing different levels of noise, we provide evidence that, compared with other approaches, the proposed WF+MLRd method yields the most accurate estimate of single-trial ERP features. When applied to a real laser-evoked potential data set, the WF+MLRd approach provides reliable estimation of single-trial latency, amplitude, and morphology of ERPs and thereby allows performing meaningful correlations at single-trial level. We obtained three main findings. First, WF significantly enhances the SNR of single-trial ERPs. Second, MLRd effectively captures and measures the variability in the morphology of single-trial ERPs, thus providing an accurate and unbiased estimate of their peak latency and amplitude. Third, intensity of pain perception significantly correlates with the single-trial estimates of N2 and P2 amplitude. These results indicate that WF+MLRd can be used to explore the dynamics between different ERP features, behavioral variables, and other neuroimaging measures of brain activity, thus providing new insights into the functional significance of the different brain processes underlying the brain responses to sensory stimuli.

scholarly journals Comparison of Methods for Harvest Prediction in ‘Gigante’ Cactus Pear

2019 ◽  
Vol 11 (14) ◽  
pp. 216 ◽  
Author(s):  
Bruno V. C. Guimarães ◽  
Sérgio L. R. Donato ◽  
Ignacio Aspiazú ◽  
Alcinei M. Azevedo ◽  
Abner J. de Carvalho
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Coefficient Of Determination ◽  
Cactus Pear ◽  
Federal Institute ◽  
The Mean ◽  
Artificial Neural

Behavior analysis and plant expression are the answers the researcher needs to construct predictive models that minimize the effects of the uncertainties of field production. The objective of this study was to compare the simple and multiple linear regression methods and the artificial neural networks to allow the maximum security in the prediction of harvest in ‘Gigante’ cactus pear. The uniformity test was conducted at the Federal Institute of Bahia, Campus Guanambi, Bahia, Brazil, coordinates 14°13′30″ S, 42°46′53″ W and altitude of 525 m. At 930 days after planting, we evaluated 384 basic units, in which were measured the following variables: plant height (PH); cladode length (CL), width (CW) and thickness (CT); cladode number (CN); total cladode area (TCA); cladode area (CA) and cladode yield (Y). For the comparison between the artificial neural networks (ANN) and regression models (single and multiple-SLR and MLR), we considered the mean prediction error (MPE), the mean quadratic error (MQE), the mean square of deviation (MSD) and the coefficient of determination (R2).The values estimated by the ANN 7-5-1 showed the best proximity to the data obtained in field conditions, followed by ANN 6-2-1, MLR (TCA and CT), SLR (TCA) and SLR (CN). In this way, the ANN models with the topologies 7-2-1 and 6-2-1, MLR with the variables total cladode area and cladode thickness and SLR with the isolated descriptors total cladode area and cladode number, explain 85.1; 81.5; 76.3; 74.09 and 65.87%, respectively, of the yield variation. The ANNs were more efficient at predicting the yield of the ‘Gigante’ cactus pear when compared to the simple and multiple linear regression models.

scholarly journals Choroidal Remodeling Distribution Pattern in the Macular Region in Chinese Young Patients with Myopia

2021 ◽  
Author(s):  
Jun Wang ◽  
Xin Ye ◽  
Xiangjun She ◽  
Jiahao Xu ◽  
Yiqi Chen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Distribution Pattern ◽  
Young Patients ◽  
Enhanced Depth Imaging ◽  
Potential Marker ◽  
Luminal Area ◽  
The Mean ◽  
Foveal Center ◽  
The Relationship

Abstract Background: The pathogenesis of myopia has been found to be associated with the blood supply of the choroid. This study aimed to determine the relationship between distribution pattern of the choroidal remodeling and the degree of myopia in young patients.Methods: Young patients (age < 18 years) with spherical equivalent of less than -12 diopters (D) were included. Spectral-domain optical coherence tomography (SD-OCT) with enhanced depth imaging (EDI) modality was used to measure the choroidal thickness (CT) and choroidal vascularity index (CVI) in the macular regions. CVI was calculated as the proportion of luminal area to choroidal area and was measured within 1 mm and 3 mm nasal (N1 and N3), temporal (T1 and T3), superior (S1 and S3), and inferior (I1 and I3) to the foveal center. CT and CVI were compared across different ages (i.e., 5~9 years, 10~13 years, and 14~18 years), axial lengths (ALs) (i.e., 21.00~25.00mm and 25.01~29.00mm), and spherical equivalents (SEs) (i.e., SE>-0.5D, -0.5~-3.0D, -3.01~-6.0D, and <-6.0D). Multiple linear regression was applied to examine the associations amongst age, AL, SE, and CVI of different locations.Results: 164 of 172 eyes from 85 volunteers were included. The mean CT in the central foveal was 269.87 ± 63.32µm (ranging from 93.00µm to 443.00µm). The mean sub foveal-CVI was 67.66 ± 2.40% (ranging from 57.84% to 79.60%). Multiple linear regression results revealed significant correlations between SE and T1-CVI (p < 0.05, r2= 0.082, β= 0.194), N1-CVI (p < 0.05, r2= 0.039, β= 0.212). Simple linear regression results revealed that T1-CVI (p < 0.05, r2 = 0.09) and T3-CVI (p < 0.05, r2 = 0.05) were negatively correlated with SE; N1-CVI (p < 0.05, r2 = 0.05) and N3-CVI (p < 0.05, r2 = 0.04) were negatively correlated with SE. Conclusions and Relevance: CVI in the horizontal meridian underwent the largest change as myopia worsened. Temporal and nasal CVIs within the r =1mm and r=3mm sub foveal range were positively associated with degree of myopia in young patients. The CVI value may be used to assess the vascular status of the choroid and be a potential marker of myopic progression.

scholarly journals Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations

2021 ◽  
pp. 278-281
Author(s):  
O. G. Obadina ◽  
Adedayo Funmi Adedotuun ◽  
O. A. Odusanya
Keyword(s):  
Monte Carlo ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Error ◽  
Ordinary Least Squares ◽  
Linear Regression Coefficient ◽  
Monte Carlo Simulation Technique ◽  
Independent Variables ◽  
Average Mean Square Error ◽  
The Mean

The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coefficient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rose, the AMSE decreased. The MRR and LKM both outperformed the LSM. At random error of variance 10, the MRR is the most suitable for all circumstances.

scholarly journals Housing Price Prediction Based on Multiple Linear Regression

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qingqi Zhang
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Housing Prices ◽  
Housing Price ◽  
Multiple Linear Regression Model ◽  
Data Set ◽  
Factors Affecting ◽  
Price Prediction

In this paper, the author first analyzes the major factors affecting housing prices with Spearman correlation coefficient, selects significant factors influencing general housing prices, and conducts a combined analysis algorithm. Then, the author establishes a multiple linear regression model for housing price prediction and applies the data set of real estate prices in Boston to test the method. Through the data analysis and test in this paper, it can be summarized that the multiple linear regression model can effectively predict and analyze the housing price to some extent, while the algorithm can still be improved through more advanced machine learning methods.

scholarly journals Long term dynamics of OH<sup>∗</sup> temperatures over Middle Europe: Trends and solar correlations

2016 ◽  
Author(s):  
Christoph Kalicinsky ◽  
Peter Knieling ◽  
Ralf Koppmann ◽  
Dirk Offermann ◽  
Wolfgang Steinbrecht ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Trend ◽  
Temperature Time Series ◽  
Time Interval ◽  
Radio Flux ◽  
Solar Radio Flux ◽  
Temperature Time

Abstract. We present the analysis of annual average OH∗ temperatures in the mesopause region derived from measurements of the GRound based Infrared P-branch Spectrometer (GRIPS) at Wuppertal (51° N, 7° E) in the time interval 1988 to 2015. The current study uses a 7 year longer temperature time series compared to the latest analysis regarding the long term dynamics of OH* temperatures measured at Wuppertal. This additional time of observation leads to a change in characterisation of the observed long term dynamics. We perform a multiple linear regression using the solar radio flux F10.7cm (11-year cycle of solar activity) and time to describe the temperature evolution. The analysis leads to a linear trend of (−0.089&amp;pm;0.055) K year−1 and a sensitivity to the solar activity of (4.2&amp;pm;0.9) K (100 SFU)−1 (r2 of fit 0.6). However, one linear trend in combination with the 11-year solar cycle is not sufficient to explain all observed long term dynamics. Actually we find a clear trend break in the temperature time series in middle of 2006. Before this break point there is an explicit negative linear trend of (−0.22&amp;pm;0.08) K year−1 and after 2006 the linear trend turns positive with a value of (0.38&amp;pm;0.23) K year−1. This apparent trend break can also be described using a long periodic oscillation. One possibility is to use the 22-year solar cycle that describes the reversal of the solar magnetic field (Hale cycle). A multiple linear regression using the solar radio flux and the solar polar magnetic field as parameters leads to the regression coefficients Csolar = (5.0&amp;pm;0.7) K (100 SFU)−1 and Chale = (1.8&amp;pm;0.5) K (100 µT)−1 (r2 = 0.71). But the best way to describe the OH* temperature time series is to use the solar radio flux and a 24-year oscillation. A multiple linear regression using these parameters leads to a sensitivity to the solar activity of (4.3&amp;pm;0.7) K (100 SFU)−1 and an amplitude of the 24-year oscillation A = (1.95&amp;pm;0.43) K (r2 = 0.77). The most important finding here is that using these parameters for the multiple linear regression an additional linear trend is no longer needed. Moreover, with the knowledge of this 24-year oscillation the linear trends derived in this and in a former study of the Wuppertal data series can be reproduced by just fitting a line to the corresponding part (time interval) of the oscillation. This actually means that depending on the analysed time interval completely different linear trends with respect to magnitude and sign can be observed. This fact is of essential importance for any comparison between different observations and model simulations. After detrending the temperature time series regarding the 11-year solar cycle and the 24-year oscillation multi-annual oscillations (MAOs) remain. A harmonic analysis finds three pronounced oscillations with periods of (2.69&amp;pm;0.06) years, (3.15&amp;pm;0.07) years, and (4.54&amp;pm;0.17) years. The corresponding amplitudes are (1.03&amp;pm;0.33) K, (1.03&amp;pm;0.33) K, and (0.91&amp;pm;0.36) K, respectively.

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