High Correlation between Ethanol Concentrations in Postmortem Femoral Blood and in Alternative Biological Specimens, but Large Uncertainty When the Linear Regression Model Was Used for Prediction in Individual Cases

2020 ◽  
Vol 44 (5) ◽  
pp. 415-421 ◽  
Author(s):  
G Thelander ◽  
F C Kugelberg ◽  
A W Jones
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Pleural Cavity ◽  
Medical Examiner ◽  
Outcome Variable ◽  
Large Uncertainty ◽  
Lung Fluid ◽  
Femoral Blood ◽  
The Mean ◽  
Alternative Specimen

Abstract In connection with medicolegal autopsies peripheral blood (e.g. from a femoral vein) is the specimen of choice for toxicological analysis, although alternative specimens are also sometimes submitted, such as bile, cerebrospinal fluid (CSF), vitreous humor (VH), bladder urine, pleural effusions and/or lung fluid. Ethanol concentrations were determined in duplicate in femoral blood and in various alternative biological specimens by headspace gas chromatography. The analysis was carried out on two different fused silica capillary columns furnishing different retention times for ethanol and both n-propanol and t-butanol were used as internal standards. The results were evaluated by linear regression using blood alcohol concentration (BAC) as dependent or outcome variable and the concentrations in an alternative specimen as independent or predictor variable. The Pearson correlation coefficients were all statistically highly significant (P < 0.001); r = 0.94 (bile), r = 0.98 (CSF), r = 0.97 (VH), r = 0.92 (urine), r = 0.94 (lung fluid) and r = 0.96 (pleural cavity effusions). When the regression model was used to predict femoral BAC from the mean concentration in an alternative specimen the mean and 95% prediction intervals were 1.12 ± 0.824 g/L (bile), 1.41 ± 0.546 g/L (CSF), 1.15 ± 0.42 g/L (VH), 1.29 ± 0.780 g/L (urine), 1.25 ± 0.772 g/L (lung fluid) and 0.68 ± 0.564 g/L (pleural cavity effusions). This large uncertainty for a single new observation needs to be considered when alcohol-related deaths are evaluated and interpreted. However, the analysis of alternative specimens is recommended in medical examiner cases to provide supporting evidence with regard to the origin of ethanol, whether this reflects antemortem (AM) ingestion or postmortem (PM) synthesis.

scholarly journals A Novel S-Regression Model on an Auto Price

2018 ◽  
Vol 7 (2.29) ◽  
pp. 912
Author(s):  
Fadzilah Salim ◽  
Nur Azman Abu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Mean Squared Error ◽  
Squared Error ◽  
Curve Model ◽  
Used Car ◽  
Independent Variable ◽  
The Mean ◽  
Used Cars ◽  
The Relationship

A simple linear regression model is useful in a prediction model. A general linear regression beyond a single independent variable is still not popular. A nonlinear regression can be easily produced a better predictive model but it is difficult to construct. The objective of this paper is to propose a technique for predicting the price of used cars in Malaysia using S-shaped curve model. In this paper, the S-shaped Membership Function [SMF] is used as the basis to develop a novel S-Regression model. Comparisons between linear regression, cubic regression and S-Regression have been made on the used car prices. The mean squared error of S-Regression model is found to be closer to cubic regression than the linear regression. S-Regression model is found to be quite suitable to represent the relationship between the price of a used car and the make year of a car. The result demonstrates that the S-Regression model gives better and practical estimate of the price of a used car in Malaysia.  

scholarly journals On the Stochastic Restrictedr-kClass Estimator and Stochastic Restrictedr-dClass Estimator in Linear Regression Model

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Jibo Wu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Mean Squared Error ◽  
Multiple Linear Regression Model ◽  
Error Matrix ◽  
Squared Error ◽  
The Mean ◽  
Linear Restrictions ◽  
Theoretical Results

The stochastic restrictedr-kclass estimator and stochastic restrictedr-dclass estimator are proposed for the vector of parameters in a multiple linear regression model with stochastic linear restrictions. The mean squared error matrix of the proposed estimators is derived and compared, and some properties of the proposed estimators are also discussed. Finally, a numerical example is given to show some of the theoretical results.

scholarly journals Fiducial-based image-guided SBRT for pancreatic adenocarcinoma: Does inter-and intra-fraction treatment variation warrant adaptive therapy?

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Colin S. Hill ◽  
Sarah Han-Oh ◽  
Zhi Cheng ◽  
Ken Kang-Hsin Wang ◽  
Jeffrey J. Meyer ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Pancreatic Adenocarcinoma ◽  
Linear Regression Model ◽  
Organs At Risk ◽  
Motion Management ◽  
The Mean ◽  
Adaptive Therapy ◽  
Mean Vector ◽  
Vector Shift

Abstract Purpose Variation in target positioning represents a challenge to set-up reproducibility and reliability of dose delivery with stereotactic body radiation therapy (SBRT) for pancreatic adenocarcinoma (PDAC). While on-board imaging for fiducial matching allows for daily shifts to optimize target positioning, the magnitude of the shift as a result of inter- and intra-fraction variation may directly impact target coverage and dose to organs-at-risk. Herein, we characterize the variation patterns for PDAC patients treated at a high-volume institution with SBRT. Methods We reviewed 30 consecutive patients who received SBRT using active breathing coordination (ABC). Patients were aligned to bone and then subsequently shifted to fiducials. Inter-fraction and intra-fraction scans were reviewed to quantify the mean and maximum shift along each axis, and the shift magnitude. A linear regression model was conducted to investigate the relationship between the inter- and intra-fraction shifts. Results The mean inter-fraction shift in the LR, AP, and SI axes was 3.1 ± 1.8 mm, 2.9 ± 1.7 mm, and 3.5 ± 2.2 mm, respectively, and the mean vector shift was 6.4 ± 2.3 mm. The mean intra-fraction shift in the LR, AP, and SI directions were 2.0 ± 0.9 mm, 2.0 ± 1.3 mm, and 2.3 ± 1.4 mm, respectively, and the mean vector shift was 4.3 ± 1.8 mm. A linear regression model showed a significant relationship between the inter- and intra-fraction shift in the AP and SI axis and the shift magnitude. Conclusions Clinically significant inter- and intra-fraction variation occurs during treatment of PDAC with SBRT even with a comprehensive motion management strategy that utilizes ABC. Future studies to investigate how these variations could lead to variation in the dose to the target and OAR should be investigated. Strategies to mitigate the dosimetric impact, including real time imaging and adaptive therapy, in select cases should be considered.

scholarly journals Landmark-based estimation vs. linear regression model: a retrospective comparison for prediction of optimal length of right subclavian vein catheterization in infants

2021 ◽  
Author(s):  
Chahyun Oh ◽  
Boohwi Hong ◽  
Yumin Jo ◽  
Woosuk Chung ◽  
Hoseop Kim ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Subclavian Vein ◽  
Pediatric Patients ◽  
Optimal Length ◽  
The Mean ◽  
The Right ◽  
Insertion Length ◽  
Vein Catheterization

Background: The optimal insertion length for right subclavian vein catheterization in infants has not been determined. This study retrospectively compared landmark-based and linear regression model-based estimation of optimal insertion length for right subclavian vein catheterization in pediatric patients of corrected age < 1 year. Methods: Fifty catheterizations of the right subclavian vein were analyzed. The landmark related distances were: from the needle insertion point (I) to the tip of the sternal head of the right clavicle (A) and from A to the midpoint (B) of the perpendicular line drawn from the sternal head of the right clavicle to the line connecting the nipples. The optimal length of insertion was retrospectively determined by reviewing post-procedural chest radiographs. Estimates using a landmark-based equation (IA + AB – intercept) and a linear regression model were compared with the optimal length of insertion. Results: A landmark-based equation was determined as IA + AB – 5. The mean difference between the landmark-based estimate and the optimal insertion length was 1.0 mm (95% limits of agreement –18.2 to 20.3 mm). The mean difference between the linear regression model (26.681 – 4.014 × weight + 0.576 × IA + 0.537 × AB – 0.482 × postmenstrual age) and the optimal insertion length was 0 mm (95% limits of agreement –16.7 to 16.7 mm). The difference between the estimates using these two methods was not significant. Conclusion: A simple landmark-based equation may be useful for estimating optimal insertion length in pediatric patients of corrected age < 1 year undergoing right subclavian vein catheterization.

scholarly journals A Study of Relationship Between Serum Uric Acid, and Fasting Plasma Glucose in Type 2 Diabetes Mellitus Patients

2020 ◽  
Vol 11 (4) ◽  
pp. 7229-7233
Author(s):  
Anuradha G ◽  
Santhini Gopalakrishnan S ◽  
Vinodakumar H R
Keyword(s):  
Uric Acid ◽  
Linear Regression ◽  
Regression Model ◽  
Serum Uric Acid ◽  
Plasma Glucose ◽  
Linear Regression Model ◽  
Fasting Plasma Glucose ◽  
The Mean ◽  
The Relationship

The current study was conducted to observe the relationship between serum uric acid, lipid profile and fasting plasma glucose in type 2 DM patients. It was a cross-sectional study. A total of 618 participants were included in the study (203-healthy, 206-prediabetic and 209-T2DM). One way analysis of variance was used to compare the mean between these three groups. A linear regression model was used to find the relationship between SUA and FPG in T2DM. The mean values of serum uric acid in pre-diabetes and T2DM (4.929±1.33 and 4.69±1.41 mg/dl, respectively) were lower compared to healthy (5.40±1.08 mg/dl). SUA showed a significant positive correlation with serum triglycerides in T2DM (p<0.05). The linear regression model showed that SUA was inversely associated with FPG in T2DM after adjustment for age and gender. The biological interrelationship observed in the current study raises the possibility of potential pathogenic overlap between SUA and FPG. SUA might be involved in a metabolic imbalance which in turn leads to T2DM.

Correlation between shunt series and scoliosis radiographs in children with myelomeningoceles

2012 ◽  
Vol 17 (5) ◽  
pp. 410-414 ◽  
Author(s):  
Jonathan G. Thomas ◽  
Steven W. Hwang ◽  
Todd J. Blumberg ◽  
William E. Whitehead ◽  
Daniel J. Curry ◽  
...  
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Medical Records ◽  
Clinical Suspicion ◽  
Scoliotic Curve ◽  
Radiographic Evidence ◽  
Curve Magnitude ◽  
The Mean ◽  
The Impact ◽  
Shunt Series

Object Over 85% of patients with myelomeningoceles require placement of a ventriculoperitoneal shunt for hydrocephalus, and between 25% and 85% of these patients develop scoliosis. Although most patients undergo repeated shunt series radiography to evaluate for device malfunction, scoliosis radiographs are less consistently obtained. The authors sought to determine if a correlation exists between these 2 radiographic techniques for a given patient, as shunt series are obtained with the patient supine, whereas scoliosis radiographs are acquired with the patient standing upright. The authors also endeavored to study if shunt series radiographs can reliably detect significant scoliosis. Methods The authors retrospectively reviewed a single institution's series of 593 patients with myelomeningoceles and identified all patients in whom a shunt series and scoliosis radiographs were obtained within a 6-month period. They reviewed the medical records and radiographs of these patients for demographic and radiographic parameters. They then applied a linear regression model and determined shunt series curve cutoffs to detect scoliotic curves greater than 20° and 50°. Results Of the 593 patients identified, 116 did not have radiographs available for interpretation. Of the remaining 477 patients, 201 had radiographic evidence of scoliosis (42%), and 66 had both a shunt series and a scoliosis radiographs acquired within a 6-month interval. In 4 patients, both end vertebrae of the scoliotic curve could not be visualized on a single radiograph. The mean age of the remaining cohort was 10.6 ± 5.2 years and the mean curve magnitude was 58° ± 37°. Using identical end vertebrae, the mean shunt series curve magnitude was 49° ± 35°. The mean interval between both radiographs was 2.3 ± 3.3 months. The regression model showed a strong linear association between shunt series and scoliosis series curves. A curve greater than 19° on shunt series radiographs would detect significant curves of greater than 20° on scoliosis series with 91% sensitivity and 78% specificity. A shunt series curve greater than 37° had 100% sensitivity and 93% specificity in identifying significant scoliotic curves greater than 50°. Conclusions Although shunt series radiographs may not precisely depict scoliotic curve magnitude because the impact of gravity is negated, they may be useful in helping to confirm clinical suspicion of scoliosis. The authors' results suggest a strong correlation between both types of radiographs.

scholarly journals The Performance of Some Restricted Estimators In Restricted Linear Regression Model

2021 ◽  
Vol 26 (2) ◽  
Author(s):  
Bader Aboud ◽  
Mustafa Ismaeel Naif
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Simulation Study ◽  
Linear Regression Model ◽  
Regression Estimator ◽  
Mean Square ◽  
Ridge Regression Estimator ◽  
The Mean ◽  
Biased Estimators ◽  
Better Than

In the linear regression model, the restricted biased estimation as one of important  methods to addressing the high variance and the  multicollinearity problems. In this paper, we make the simulation study of the some restricted biased estimators. The mean square error (MME) criteria are used to make a comparison  among them. According to the simulation study we observe that, the performance of the restricted modified unbiased  ridge regression estimator (RMUR) was proposed by  Bader and Alheety (2020)  is better than  of these estimators. Numerical example have been considered to illustrate the performance of the estimators.

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