scholarly journals Reduced left atrial strain in magnetic resonance imaging is associated with abnormal P-waves in patients after acute myocardial infarction

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
M Wester ◽  
J Pec ◽  
C Fisser ◽  
K Debl ◽  
O Hamer ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Linear Regression ◽  
Left Atrial ◽  
Regression Models ◽  
Linear Regression Analysis ◽  
P Wave ◽  
P Value ◽  
Linear Regression Models ◽  
The Relationship

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): ReForM-B-Program Background Abnormal P-wave terminal force in lead V1 (PTFV1) is associated with atrial remodeling. The relationship between PTFV1 and atrial function after acute myocardial injury is insufficiently understood and may be elucidated by detailed feature tracking (FT) strain analysis of cardiac magnetic resonance images (CMR). Purpose We investigated the relationship between PTFV1 and left atrial (LA) strain (measured by CMR) in a patient cohort presenting with acute myocardial infarction (MI). Methods 56 patients with acute MI underwent CMR within 3-5 days after MI. PTFV1 was measured as the product of negative P-wave amplitude and duration in lead V1 (Fig. A). A PTFV1 >4000 ms*µV was defined as abnormal. CMR cine data were retrospectively analyzed using a dedicated FT software. LA strain (ε) and strain rate (SR) for atrial reservoir ([εs]; [SRs]), conduit ([εe]; [SRe]) and booster function ([εa]; [SRa]) were measured in two long-axis views (Fig. A). Results Patients with abnormal PTFV1 had significantly reduced LA conduit function εe and SRe (Fig. B + D). There was a significant negative correlation between the extent of PTFV1 and both εe and SRe (Fig. C + E). In univariate and multivariate regression models, both PTFV1 and age predicted atrial conduit function. In contrast, multiple clinical co-factors had no significant influence on εe (Table). Interestingly, linear regression models revealed only mild dependency of PTFV1 on conventional parameters of cardiac function such as left ventricular ejection fraction (p = 0.059; R²(adj.)=0.047), and no dependency on structural parameters such as LA area (p = 0.639; R²(adj.)=0.016), or LA fractional area change (p = 0.825; R²(adj.)=0.020). Conclusion Abnormal PTFV1 was associated with reduced LA function independent from numerous clinical co-factors in patients presenting with acute myocardial infarction. Table N = 56 Linear Regression Analysis Multiple Linear Regression Analysis (R2 (adj.)=0.376, p = 0.016) Variable B 95% CI P value R2 (adj.) B 95% CI P value PTFV1 [µV*ms] -1.628 17085.298 to 27210.854 0.013 0.092 -1.315 -2.614 to -0.016 0.047 Age [y] -425.775 24985.168 to 54634.995 0.002 0.145 -610.815 -982.78 to -238.849 0.001 Body mass indes [kg/m2] -185.653 -3259.187 to 47020.775 0.671 -0.015 -506.096 -1327.357 to 315.165 0.219 Creatinine kinase [U/l] -1.571 14806.991 to 24842.272 0.121 0.027 -1.791 -3.72 to 0.138 0.067 Male sex -893.28 10701.206 to 23504.066 0.802 -0.017 4275.631 -3842.517 to 12393.78 0.292 Estimated glomerular filtration rate [ml/min/1.73m2] 88.617 -4564.177 to 21395.361 0.202 0.012 -163.981 -331.343 to 3.381 0.054 Systolic blood pressure [mmHg] -2.001 14045.786 to 22037.253 0.095 0.038 29.331 -108.243 to 166.906 0.668 nt-pro brain natriuretic peptide [pg/ml] 24.629 -4060.804 to 30920.828 0.716 -0.016 1.015 -1.778 to 3.809 0.466 Univariate and multivariate linear regression models for left atrial conduit strain Abstract Figure

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

BAYESIAN IDENTIFICATION OF OUTLIERS AND CHANGE-POINTS IN MEASUREMENT ERROR MODELS

2005 ◽  
Vol 08 (04) ◽  
pp. 433-449 ◽  
Author(s):  
FERNANDO A. QUINTANA ◽  
PILAR L. IGLESIAS ◽  
HELENO BOLFARINE
Keyword(s):  
Linear Regression ◽  
Outlier Detection ◽  
Change Point ◽  
Regression Models ◽  
Point Problem ◽  
Linear Regression Models ◽  
Outlier Identification ◽  
Change Point Problem ◽  
Error In Variables ◽  
The Relationship

The problem of outlier and change-point identification has received considerable attention in traditional linear regression models from both, classical and Bayesian standpoints. In contrast, for the case of regression models with measurement errors, also known as error-in-variables models, the corresponding literature is scarce and largely focused on classical solutions for the normal case. The main object of this paper is to propose clustering algorithms for outlier detection and change-point identification in scale mixture of error-in-variables models. We propose an approach based on product partition models (PPMs) which allows one to study clustering for the models under consideration. This includes the change-point problem and outlier detection as special cases. The outlier identification problem is approached by adapting the algorithms developed by Quintana and Iglesias [32] for simple linear regression models. A special algorithm is developed for the change-point problem which can be applied in a more general setup. The methods are illustrated with two applications: (i) outlier identification in a problem involving the relationship between two methods for measuring serum kanamycin in blood samples from babies, and (ii) change-point identification in the relationship between the monthly dollar volume of sales on the Boston Stock Exchange and the combined monthly dollar volumes for the New York and American Stock Exchanges.

scholarly journals Factors associated with parasite dominance in fishes from Brazil

2016 ◽  
Vol 25 (2) ◽  
pp. 225-230
Author(s):  
Cristina Fernandes do Amarante ◽  
Wagner de Souza Tassinari ◽  
Jose Luis Luque ◽  
Maria Julia Salim Pereira
Keyword(s):  
Linear Regression ◽  
Body Length ◽  
Regression Models ◽  
Mixed Model ◽  
Multiple Linear Regression Model ◽  
Mixed Effects ◽  
The Body ◽  
Linear Regression Models ◽  
Biological Aspects ◽  
The Relationship

Abstract The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

scholarly journals “The inflammation link between periodontal disease and coronary atherosclerosis in patients with acute coronary syndromes - case-control study”.

2020 ◽  
Author(s):  
Agnieszka Wojtkowska ◽  
Tomasz Zapolski ◽  
Joanna Wysokinska-Miszczuk ◽  
Andrzej P. Wysokinski
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Coronary Heart Disease ◽  
Regression Analysis ◽  
Heart Disease ◽  
Linear Regression ◽  
Periodontal Disease ◽  
Coronary Atherosclerosis ◽  
Linear Regression Analysis ◽  
Pocket Depth

Abstract Background Coronary atherosclerosis and periodontal disease, due to their prevalence, are a serious epidemiological problem. Pathophysiological evidence points to their possible common inflammatory etiopathological background. The aim of the study was to analyze the relationship between the presence and severity of periodontitis, systemic inflammation and selected parameters of myocardial injury and heart function in patients with acute myocardial infarction. Methods The study group consisted of 71 patients 54.22(7.05) - year - old hospitalized due to acute myocardial infarction. The patients underwent a coronary angiographic examination and echocardiography. The following laboratory parameters were determined: blood morphology, hsCRP (high sensitivity C-reactive protein), ESR (erythrocyte sedimentation rate), fibrinogen, troponin I, CK-MB (creatine kinase myocardial band), BNP (brain natriuretic peptide), lipidogram, glucose, creatinine, GFR (glomerular filtration rate), TSH (thyroid stymulating hormone), HbA1c (glikolize hemoglobin). Dental assessment of the patients was performed and the following indicators were included: the number of teeth preserved, approximal plaque index (API), bleeding on probing (BoP), pocket depth (PD), the number of bleeding periodontal pockets ≥ 4 mm in depth (NoPD≥4 mm), the percentage of bleeding periodontal pockets ≥ 4 mm in depth (%PD≥4 mm), clinical attachment loss (CAL). The control consisted of 40 patients 52 (± 8.43)- year-old without a history of coronary heart disease. These patients were subjected to a periodontal examination using the above parameters and classification methods. The following statistical tests were implemented: Shapiro-Wilk test, Levene's test, Mann Whitney's U analysis, Univariate Analysis of Variance (ANOVA); the post-hoc analysis was performed with the use of Tukey's honest significant difference test (HSD), Kruskal-Wallis's non-parametric test, Spearman's rank correlation, logistic regression analysis, linear regression analysis and ROC analysis. Results The BI (bleeding index) significantly correlated with fibrynogen (R-0,36; p-0,006). All indices regarding the pocket depth correlated significantly with the number of leukocytes: PD (R-0,27; p-0,02), NoPD≥4mm (R- 0,28, p-0,02),% PD4≥mm (R-0,27; p-0,02). PD (R-0,28; p-0,01) and NoPD≥4mm (R-0,24; p-0,04) were also associated significantly with the level of hsCRP. The BI is correlated closely with the levels of BNP (R-0,29, p-0,02). The multifactorial analysis showed that significant predictors of myocardial infarction are API and BI. The analysis showed that API and BI are important predictors of troponin levels. Linear regression analysis showed that only CAL is a significant predictor of BNP. Conclusions Patients with acute myocardial infarction have worse periodontal status compared to people without coronary heart disease. Higher severity of periodontal disease, poorer oral hygiene and increased activity of the periodontitis leads to greater manifestation of systemic inflammation in patients with acute myocardial infarction. Periodontitis is a risk factor for myocardial infarction and also affects the degree of post-infarction left ventricular damage, which means that there is an inflammatory link between these two diseases.

scholarly journals The inflammation link between periodontal disease and coronary atherosclerosis in patients with acute coronary syndromes: case–control study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Agnieszka Wojtkowska ◽  
Tomasz Zapolski ◽  
Joanna Wysokińska-Miszczuk ◽  
Andrzej P. Wysokiński
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Coronary Heart Disease ◽  
Regression Analysis ◽  
Heart Disease ◽  
Linear Regression ◽  
Coronary Atherosclerosis ◽  
Linear Regression Analysis ◽  
Pocket Depth ◽  
Bleeding On Probing

Abstract Background Coronary atherosclerosis and periodontal disease, due to their prevalence, are a serious epidemiological problem. Pathophysiological evidence points to their possible common inflammatory etiopathological background. The aim of the study was to analyze the relationship between the presence and severity of periodontitis, systemic inflammation and selected parameters of myocardial injury and heart function in patients with acute myocardial infarction. Methods The study group consisted of 71 patients 54.22 (7.05)-year-old hospitalized due to acute myocardial infarction. The patients underwent a coronary angiographic examination and echocardiography. The following laboratory parameters were determined: blood morphology, high sensitivity C-reactive protein (hsCRP), erythrocyte sedimentation rate (ESR), fibrinogen, troponin I, creatine kinase myocardial band (CK-MB), brain natriuretic peptide (BNP), lipidogram, glucose, creatinine, glomerular filtration rate (GFR), thyroid stymulating hormone (TSH), glycated hemoglobin (HbA1c). Dental assessment of the patients was performed and the following indicators were included: the number of teeth preserved, approximal plaque index (API), bleeding on probing (BoP), pocket depth (PD), the number of bleeding periodontal pockets ≥ 4 mm in depth (NoPD ≥ 4 mm), the percentage of bleeding periodontal pockets ≥ 4 mm in depth (%PD ≥ 4 mm), clinical attachment loss (CAL). The control consisted of 40 patients 52 (± 8.43)-year-old without a history of coronary heart disease. These patients were subjected to a periodontal examination using the above parameters and classification methods. The following statistical tests were implemented: Shapiro–Wilk test, Levene's test, Mann Whitney's U analysis, Univariate Analysis of Variance (ANOVA); the post-hoc analysis was performed with the use of Tukey's honest significant difference test (HSD), Kruskal–Wallis's non-parametric test, Spearman's rank correlation, logistic regression analysis, linear regression analysis and ROC analysis. Results The BoP (bleeding on probing) significantly correlated with fibrynogen (R-0.36; p-0.006). All indices regarding the pocket depth correlated significantly with the number of leukocytes: PD (R-0.27; p-0.02), NoPD ≥ 4 mm (R-0.28, p-0.02), %PD ≥ 4 mm (R-0.27; p-0.02). PD (R-0.28; p-0.01) and NoPD ≥ 4 mm (R-0.24; p-0.04) were also associated significantly with the level of hsCRP. The BoP is correlated closely with the levels of BNP (R-0.29, p-0.02). The multifactorial analysis showed that significant predictors of myocardial infarction are API and BoP. The analysis showed that API and BoP are important predictors of troponin levels. Linear regression analysis showed that only CAL is a significant predictor of BNP. Conclusions Patients with acute myocardial infarction have worse periodontal status compared to people without coronary heart disease. Greater severity of periodontitis, plaque accumulation and bleeding on probing are associated with acute myocardial infarction. Periodontitis is a risk factor for myocardial infarction and also affects the degree of post-infarction left ventricular damage, which means that there is an inflammatory link between these two diseases.

scholarly journals A study on factors related to readership of scientific articles

2017 ◽  
Vol 3 (2) ◽  
pp. 1-15 ◽  
Author(s):  
Tony Xu ◽  
Shayan Khalili ◽  
Cynthia Deng
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Scientific Research ◽  
The Other ◽  
Linear Regression Models ◽  
Research Papers ◽  
Scatter Plots ◽  
The Subject ◽  
Moderate Effect ◽  
The Relationship

This paper analyzes the relationship between the number of Twitter and Mendeley readers with the article’s subject, publisher, journal, and title length. It also looks at which country has the greatest number of readers to see if researchers can garner more visibility by publishing an article relevant to issues in those countries. The purpose of this report is to help researchers improve the visibility and impact value of their research. The data was gathered from 550,000 scientific research papers published between January 1st and July 1st of 2016. Python’s built-in JSON library was used to extract the number of Twitter and Mendeley readers, as well as the article count for each factor. The correlation between readers per article and each factor was then visualized using bubble graphs, linear regression models, and scatter plots. This paper concludes that the length of the title is the strongest factor affecting readership. In particular, titles with lengths between 51 and 90 characters have the greatest number of readers. Moreover, articles relevant to issues in countries with a higher GDP have the highest overall readership. On the other hand, the publisher and the journal did not have a significant effect on readership, while the subject of the article had a moderate effect on readership.

scholarly journals Comparison of Simple and Segmented Linear Regression Models on the Effect of Sea Depth toward the Sea Temperature

2021 ◽  
Vol 1 (2) ◽  
pp. 68-75
Author(s):  
Muhammad Bayu Nirwana ◽  
Dewi Wulandari
Keyword(s):  
Linear Regression ◽  
Linear Regression Model ◽  
Change Point ◽  
Regression Models ◽  
Linear Regression Models ◽  
Likelihood Estimator ◽  
Sea Temperature ◽  
Independent Variables ◽  
Modeling Data ◽  
The Relationship

The linear regression model is employed when it is identified a linear relationship between the dependent and independent variables. In some cases, the relationship between the two variables does not generate a linear line, that is, there is a change point at a certain point. Therefore, themaximum likelihood estimator for the linear regression does not produce an accurate model. The objective of this study is to presents the performance of simple linear and segmented linear regression models in which there are breakpoints in the data. The modeling is performed onthe data of depth and sea temperature. The model results display that the segmented linear regression is better in modeling data which contain changing points than the classical one.Received September 1, 2021Revised November 2, 2021Accepted November 11, 2021

Electoral Participation, Disagreement, and Diversity in Social Networks: A Matter of Intimacy?

2018 ◽  
Vol 47 (7) ◽  
pp. 1056-1078 ◽  
Author(s):  
Riccardo Ladini ◽  
Moreno Mancosu ◽  
Cristiano Vezzoni
Keyword(s):  
Social Networks ◽  
Linear Regression ◽  
Regression Models ◽  
Electoral Participation ◽  
Linear Regression Models ◽  
Election Study ◽  
Significant Evidence ◽  
Political Views ◽  
National Election Study ◽  
The Relationship

General consensus concerning the nature of the relationship between political disagreement and turnout has not yet been reached: while several studies have demonstrated the demobilizing effect of disagreement, others have found no significant evidence for this. Recently, scholars have argued that diversity — a situation in which some people are in agreement with ego and some are not — can boost electoral participation. The present article argues that the insights of previous studies are the result of two differentiated effects that depend on the level of intimacy of the discussants to which one is exposed. By employing a set of linear regression models on Italian National Election Study 2013 pre-electoral survey ( N > 8,000), we show that mixed political views among friends boost electoral participation. For what concerns relatives, the likelihood to vote decreases linearly with increasing disagreement.

scholarly journals Hubungan Kualitas Tidur Dengan Status Hemodinamik Pada Pasien IMA Di Ruang ICVCU RSUD Dr. Moewardi Tahun 2016

2018 ◽  
Vol 3 (1) ◽  
Author(s):  
Syifa Mutia Desiani
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Heart Rate ◽  
Sleep Quality ◽  
Respiratory Rate ◽  
Sleep Problems ◽  
P Value ◽  
Hemodynamic Status ◽  
Spearman Test ◽  
The Relationship

Background. Acute Myocardial Infraction can have unique manifestations in individual patients, such as shortness of breath, pale, headache, nausea, vomiting, and the most common presenting symptoms of myocardial infarction is chest pain. The clinical symptoms of a patient with Acute Myocardial Infarction (AMI) can cause a nursing problem and basic human problem. For example, chest pain can cause sleep problems. Sleep problems can influence the hemodynamics of a patient. The goal of this research is to find of correlation between sleep quality with a hemodynamic status of a patient with AMI. Methods. The research used descriptive analytic with the cross-sectional approach. The total sample is 30 respondents, assessing the quality of sleep using questioners sheet and to measure hemodynamic by observation sheet. Analysis of correlation data used a Spearman test. The Results. The result of research obtained 43,3% had mild sleep problems, 50% had moderate sleep problems, 6,7% had severe sleep problems. The result of analysis statistic with Spearman test shows that relationship between sleep quality with MAP obtained significance (p-value) 0,003, the relationship between sleep quality with heart rate obtained significance (p-value) 0,0001, and the relationship between sleep quality with respiratory rate obtained significance (p-value) 0,0001. Based on significance value there is a correlation between sleep quality with hemodynamic status (MAP, heart rate, respiratory rate) of patients with Acute Myocardial Infarction (AMI). Conclusion. There is a correlation between sleep quality with hemodynamic status (MAP, heart rate, and respiratory rate) of patients with Acute Myocardial Infarction (AMI) in ICVCU Dr.Moewardi Hospital.

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