New evaluation indices for rotational knee angles in standing anteroposterior knee radiographs

2020 ◽  
pp. 1-15
Author(s):  
Takahiro Mori ◽  
Tomoharu Mochizuki ◽  
Yoshio Koga ◽  
Hiroshi Koga ◽  
Koichi Kobayashi ◽  
...  
Keyword(s):  
Time Course ◽  
Femoral Condyle ◽  
Standing Position ◽  
Regression Equation ◽  
Regression Equations ◽  
Lateral Edge ◽  
Fibula Head ◽  
Healthy Elderly ◽  
Posterior Femoral Condyle ◽  
Medial Eminence

BACKGROUND: Identifying the time course of rotational knee alignment is crucial for elucidating the etiology in knee osteoarthritis. OBJECTIVE: The aim of this study was to propose new rotational indices for calculating the change in relative rotational angles between the femur and tibia in standing anteroposterior (AP) radiographs. METHODS: Forty healthy elderly volunteers (20 women and 20 men; mean age, 70 ± 6 years) were assessed. The evaluation parameters were as follows: (1) femoral rotational index: the distance between the sphere center of the medial posterior femoral condyle and the lateral edge of the patella, and (2) tibial rotational index: the distance between the medial eminence of the tibia and the lateral edge of the fibula head. The indices were standardized by the diameter of the sphere of the medial posterior femoral condyle. This study (1) identified the relationship between changes in rotational indices and the simulated rotational knee angles in the standing position, (2) proposed a regression equation for the change in relative rotational angles between the femur and tibia in standing AP radiographs, and (3) verified the accuracy of the regression equation. RESULTS: The rotational indices increased in direct proportion to simulated rotational knee angles (femoral index: r > 0.9,p < 0.0001; tibial index: r > 0.9, p < 0.0001). Based on the results, the regression equation with the accuracy of 0.45 ± 0.26° was determined. CONCLUSIONS: The proposed regression equations can potentially predict the change in relative rotational angles between the femur and tibia in a pair of standing AP radiographs taken at different dates in longitudinal studies.

THE MODEL FOR MANAGING INVESTMENTS IN THE MOSCOW ENVIRONMENT BASED ON A POWER REGRESSION EQUATION

2020 ◽  
Vol 2 (7) ◽  
pp. 91-99
Author(s):  
E. V. KOSTYRIN ◽  
◽  
M. S. SINODSKAYA ◽  
Keyword(s):  
Solid Waste ◽  
Influencing Factors ◽  
Pair Correlation ◽  
Approximation Error ◽  
Regression Equation ◽  
Regression Equations ◽  
The Impact ◽  
The Relationship ◽  
Average Approximation ◽  
Average Approximation Error

The article analyzes the impact of certain factors on the volume of investments in the environment. Regression equations describing the relationship between the volume of investment in the environment and each of the influencing factors are constructed, the coefficients of the Pearson pair correlation between the dependent variable and the influencing factors, as well as pairwise between the influencing factors, are calculated. The average approximation error for each regression equation is determined. A correlation matrix is constructed and a conclusion is made. The developed econometric model is implemented in the program of separate collection of municipal solid waste (MSW) in Moscow. The efficiency of the model of investment management in the environment is evaluated on the example of the growth of planned investments in the activities of companies specializing in the export and processing of solid waste.

The time course of passive stiffness responses following an acute bout of static stretching in healthy, elderly men

2020 ◽  
pp. 1-9
Author(s):  
Ty B. Palmer ◽  
Ahalee C. Farrow ◽  
Chinonye C. Agu-Udemba ◽  
Ethan A. Mitchell
Keyword(s):  
Time Course ◽  
Static Stretching ◽  
Passive Stiffness ◽  
Elderly Men ◽  
Acute Bout ◽  
Healthy Elderly

scholarly journals Sacral incidence to pubis: a novel and alternative morphologic radiological parameter to pelvic incidence in assessing spinopelvic sagittal alignment

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yasuhito Takahashi ◽  
Kei Watanabe ◽  
Masashi Okamoto ◽  
Shun Hatsushikano ◽  
Kazuhiro Hasegawa ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Pelvic Incidence ◽  
Sagittal Alignment ◽  
Intraclass Correlation ◽  
Hip Dislocation ◽  
Standing Position ◽  
Regression Equation ◽  
Whole Body ◽  
Spinopelvic Parameters ◽  
Pelvic Inclination

Abstract Background Although pelvic incidence (PI) is a key morphologic parameter in assessing spinopelvic sagittal alignment, accurate measurements of PI become difficult in patients with severe hip dislocation or femoral head deformities. This study aimed to investigate the reliability of our novel morphologic parameters and the correlations with established sagittal spinopelvic parameters. Methods One hundred healthy volunteers (25 male and 75 female), with an average age of 38.9 years, were analysed. Whole-body alignment in the standing position was measured using a slot-scanning X-ray imager. We measured the established spinopelvic sagittal parameters and a novel parameter: the sacral incidence to pubis (SIP). The correlation coefficient of each parameter, regression equation of PI using SIP, and regression equation of lumbar lordosis (LL) using PI or SIP were obtained. The intraclass correlation coefficient (ICC) was calculated as an evaluation of the measurement reliability. Results Reliability analysis showed high intra- and inter-rater agreements in all the spinopelvic parameters, with ICCs > 0.9. The SIP and pelvic inclination angle (PIA) demonstrated strong correlation with PI (R = 0.96) and pelvic tilt (PT) (R = 0.92). PI could be predicted according to the regression equation: PI = − 9.92 + 0.905 * SIP (R = 0.9596, p < 0.0001). The ideal LL could be predicted using the following equation using PI and age: ideal LL = 32.33 + 0.623 * PI – 0.280 * age (R = 0.6033, p < 0.001) and using SIP and age: ideal LL = 24.29 + 0.609 * SIP – 0.309 * age (R = 0.6177, p < 0.001). Conclusions Both SIP and PIA were reliable parameters for determining the morphology and orientation of the pelvis, respectively. Ideal LL was accurately predicted using the SIP with equal accuracy as the PI. Our findings will assist clinicians in the assessment of spinopelvic sagittal alignment. Trial registration This study was retrospectively registered with the UMIN Clinical Trials Registry (UMIN000042979; January 13, 2021).

scholarly journals Volunteer activities of reading picture books and cognitive function in healthy elderly: (10) time course analysis in word fluency tasks in 7-year longitudinal study

2015 ◽  
Vol 79 (0) ◽  
pp. 2EV-068-2EV-068
Author(s):  
Hiroyuki Suzuki ◽  
Susumu Ogawa ◽  
Yuko Ohgami ◽  
Shino Otsuka ◽  
Yu Saito ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
Cognitive Function ◽  
Picture Books ◽  
Time Course ◽  
Word Fluency ◽  
Healthy Elderly

scholarly journals Prediksi Tinggi Badan Ditentukan dari Panjang Rentang Lengan dan Panjang Telapak Kaki Pada Mongoloid Feminina Khususnya Etnis Jawa

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Nur Mujaddidah Mochtar
Keyword(s):  
Clinical Medicine ◽  
Pearson Correlation ◽  
Body Height ◽  
Regression Equation ◽  
The Body ◽  
Regression Equations ◽  
Foot Length ◽  
Arm Span ◽  
Knee Height ◽  
The Mean

Background: There are various circumstances where measurements are not actually possible, replacement parameters can be used to estimate body height. Many characteristics of body height measurement and how to measure it. These include anthropometric measurements that can be used for the identification of medicolegal-forensic processes. Body height in clinical medicine and in the field of scientific research can be easily estimated using various anthropometric parameters such as arm span, knee height, foot length and foot breadth, and others. The arm span and foot length has proved to be one of the most reliable predictors. This study was conducted to estimate of body height from arm span and foot length using the regression equation and to determine the correlation between the body height and arm span and foot length.Methods: This study was conducted at Universitas Muhammadiyah Surabaya with 182 Javanese female students. Stature, arm span and foot length measured directly using anthropometric technique and measuring tape. The data obtained were then analyzed with SPSS version 16. The regression equation was derived for the estimate of body height and the relationship between stature, arm span and foot length determined by the Pearson correlation.               Results: We found that the mean body height of Javanese women was 1534,45 ± 47,623  mm, mean of arm span 1543,25 ± 60,468 mm and the mean of foot length 226,14 ± 9,586 mm. The correlation between stature and arm span was positive and significant (r = 0,715  , p <0,05). The correlation between stature and foot length was positive and significant (r = 0,726 , p <0,05). The correlation between stature and arm span and foot length was positive and significant (r = 0,798, p <0,05).               Conclusion: Body height correlates well with the arm span and foot length so that it can be used as a reliable marker for high estimates using regression equations.

scholarly journals PROBLEMS FOR ANTI-CRISIS ANALYTICAL PROCEDURES OF FINANCIAL STABILITY OF TRADE ENTERPRISES

2020 ◽  
Author(s):  
Ludmila Anipko ◽  
◽  
Irina Klimovych ◽  
Keyword(s):  
Financial Stability ◽  
Regression Equation ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Financial Condition ◽  
Financial Audit ◽  
Analytical Procedures ◽  
Financial Monitoring ◽  
Complex Indicators

Anti-crisis analytical procedures the financial stability of trade enterprises (hereinafter – AP FS) are part of the internal financial audit of economic activity. The system of financial monitoring is practically acceptable for the implementation of AP FS. The developed classification allows to determine the ability of the enterprise to implement AP FS. An analytical method has been developed that allows, based on the analysis of the financial condition and multivariate forecast, to develop measures to ensure the financial stability of the trade enterprise continuously. By interpolation, the study of the current financial situation, and extrapolation – a multivariate forecast, the numerical value of the integrated (complex) indicator that characterizes financial stability is determined by the regression equation, including factors listed in the classification, the significance of which is determined by regression equations. Based on the analysis of the numerical values of the regression coefficients, it is possible to determine the most important factors that affect the financial stability of trade enterprises, and those that have almost no effect on it. Components with significantly small numerical values of the regression coefficients can be generally discarded. This will reduce the number of indicators that affect financial stability and thus, you can reduce the number of components in the regression equation to the two three most important, which allows you to solve the problem of optimization. The expediency of using integrated and complex indicators is shown. The obtained results are only an information basis for the economic administration of the trade enterprise in making management decisions, the formation of long-term plans. The developed approaches to assessing the financial stability of enterprises are universal and can be used for enterprises in other sectors of the economy.

Decreasing Posterior Femoral Condyle Offset Improves Intraoperative Correction of Flexion Contracture in Total Knee Arthroplasty

2020 ◽  
Author(s):  
Murilo Anderson Leie ◽  
Antonio Klasan ◽  
Wei Wang Yeo ◽  
Dylan Misso ◽  
Myles Coolican
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Femoral Condyle ◽  
Knee Extension ◽  
Flexion Contracture ◽  
Level Of Evidence ◽  
Full Extension ◽  
Time Of Surgery ◽  
Posterior Femoral Condyle ◽  
Total Knee

AbstractMultiple intraoperative strategies are described to achieve full extension in total knee arthroplasty, but only a few studies have assessed the effect of the flexion gap on intraoperative improvement in flexion contracture. The aim of this study was to determine whether posterior condylar offset, in isolation, independently affects extension at the time of total knee arthroplasty.Two hundred and seventy-eight patients who underwent total knee arthroplasty for knee osteoarthritis and flexion contracture ≥ 5 degrees between January 2008 and July 2018 were included in this study. Patients with other factors that could affect knee extension at the time of surgery were excluded. We recorded the thickness of posterior femoral condyle bone resected as well as the thickness of the posterior femoral component chosen for each patient. Patients' knee extension was recorded under anesthetic, prior to resection and intraoperatively after total knee replacement.Average thickness of bone resection for the posteromedial femur was 12.64  ± 1.65 mm and for the posterolateral femur was 10.38  ± 1.52 mm. Using a linear regression model, we found that changes in posterior offset and implant downsizing influenced correction of fixed flexion deformity at the time of surgery. When patients had a combined posteromedial and posterolateral offset 2 mm thinner than the thickness of bone resected, there was an average correction of 3.5 degrees of flexion contracture.Our study demonstrated that posterior femoral condyle offset is an independent variable affecting correction of flexion contracture at the time of surgery in a gap balanced cruciate-retaining total knee arthroplasty. Level of evidence Level IV evidence

Osteochondritis Dissecans of the Posterior Femoral Condyle

1983 ◽  
Vol &NA; (175) ◽  
pp. 120???129 ◽  
Author(s):  
R. E. OUTERBRIDGE
Keyword(s):  
Osteochondritis Dissecans ◽  
Femoral Condyle ◽  
Posterior Femoral Condyle

scholarly journals Identifying the Driving Factors of Black Bloom in Lake Bay through Bayesian LASSO

2019 ◽  
Vol 16 (14) ◽  
pp. 2492 ◽  
Author(s):  
Wang ◽  
Wang ◽  
Cheng ◽  
Cheng
Keyword(s):  
Policy Development ◽  
Sediment Concentration ◽  
Ordinary Least Squares ◽  
Complex Problem ◽  
Regression Equation ◽  
Management Policy ◽  
Major Influence ◽  
Chaohu Lake ◽  
Regression Equations ◽  
Lasso Regression

Black blooms are a serious and complex problem for lake bays, with far-reaching implications for water quality and drinking safety. While Fe(II) and S(−II) have been reported as the most important triggers of this phenomenon, little effort has been devoted in investigating the relationships between Fe(II) and S(−II) and the host of potentially important aquatic factors. However, a model involving many putative predictors and their interactions will be oversaturated and ill-defined, making ordinary least squares (OLS) estimation unfeasible. In such a case, sparsity assumption is typically required to exclude the redundant predictors from the model, either through variable selection or regularization. In this study, Bayesian least absolute shrinkage and selection operator (LASSO) regression was employed to identify the major influence variables from 11 aquatic factors for Fe(II), S(−II), and suspended sediment concentration (SSC) in the Chaohu Lake (Eastern of China) bay during black bloom maintenance. Both the main effects and the interactions between these factors were studied. The method successfully screened the most important variables from many items. The determination coefficients (R2) and adjusted determination coefficients (Adjust R2) showed that all regression equations for Fe(II), S(-II), and SSC were in good agreement with the situation observed in the Chaohu Lake. The outcome of correlation and LASSO regression indicated that total phosphorus (TP) was the single most important factor for Fe(II), S(-II), and SSC in black bloom with explanation ratios (ERs) of 76.1% , 37.0%, and 12.9%, respectively. The regression results showed that the interaction items previously deemed negligible have significant effects on Fe(II), S(−II), and SSC. For the Fe(II) equation, total nitrogen (TN) × dissolved oxygen (DO) and chlorophyll a (CHLA) × oxidation reduction potential (ORP), which contributed 10.6% and 13.3% ERs, respectively, were important interaction variables. TP emerged in each key interaction item of the regression equation for S(−II). Water depth (DEP) × Fe(II) (30.7% ER) was not only the main interaction item, but DEP (5.6% ER) was also an important single factor for the SSC regression equation. It also indicated that the sediment in shallow bay is an important source for SSC in water. The uncertainty of these relationships was also estimated by the posterior distribution and coefficient of variation (CV) of these items. Overall, our results suggest that TP concentration is the most important driver of black blooms in a lake bay, whereas the other factors, such as DO, DEP, and CHLA act in concert with other aquatic factors. There results provide a basis for the further control and management policy development of black blooms.

Cross-Validation of Regression Equations to Predict Performance in a Pursuit Tracking Task

1978 ◽  
Vol 22 (1) ◽  
pp. 369-372
Author(s):  
Ricky E. Savage ◽  
Robert C. Williges ◽  
Beverly H. Williges
Keyword(s):  
Cross Validation ◽  
Regression Equation ◽  
Tracking Task ◽  
Training Condition ◽  
Regression Equations ◽  
Training Time ◽  
Pooled Data ◽  
Pursuit Tracking ◽  
Validation Procedure ◽  
Time To Learn

A double, cross-validation procedure was used to validate regression equations which predict training time to learn a two-dimensional pursuit tracking task. Motor skill and information processing tasks were used as predictors. The results yielded a reliable regression equation for each training condition, and these equations were quite similar in cross-validation. Subsequently, a regression equation based on pooled data from the original and cross-validation sample was calculated for each training condition. To establish the usefulness of a regression approach for selecting training strategies, these equations will be used in a future study where students will be matched, mismatched, and randomly assigned to various training alternatives.

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