scholarly journals Novel ideas for the comprehensive evaluation of varus knee osteoarthritis: radiological measurements of the morphology of the lateral knee joint

2021 ◽  
Author(s):  
Wenru Ma ◽  
Fengkun Wang ◽  
Shengnan Sun ◽  
Zengshuai Han ◽  
Lei Ding ◽  
...  
Keyword(s):  
Linear Regression ◽  
Knee Joint ◽  
Morphological Characteristics ◽  
Principal Component ◽  
Varus Deformity ◽  
Principal Component Score ◽  
Varus Knee ◽  
Proximal Fibula ◽  
Component Score ◽  
Knee Oa

Abstract BackgroundThe lateral anatomical and morphological characteristics of knees with varus knee osteoarthritis (OA) have not received sufficient attention. This study used several radiological parameters to describe the morphological characteristics of the lateral knee with OA to determine whether there are relationships between varus knee OA and parameters such as lateral plateau widening (LPW), proximal fibula curvature (PFC), and fibula height (FH).MethodsThe study retrospectively analyzed 1072 subjects [376 males, 696 females; mean age 66.84 ± 7.04 (range 46–83) years; mean body mass index (BMI) 26.98 ± 3.22 kg/m²] who underwent standard radiography for diagnosing or evaluating symptomatic knee joint disease. The 163 Kellgren and Lawrence (K-L) grades 0 and I knees were categorized into the no-knee-OA group, and the 909 K-L grades II–IV knees were classified into the knee-OA group. The medial proximal tibial angle (MPTA), joint line convergence angle (JLCA), and hip-knee-ankle angle (HKAA) were measured to investigate varus knee deformity. The LPW, PFC, and FH were measured. T-tests and chi-square tests were used to compare each index between the two groups. Binary logistic regression was performed to examine the correlation between indexes and knee OA occurrence. Principal component analysis was used to calculate the comprehensive principal component score of varus deformity, which was used to comprehensively evaluate the knee varus deformity degree by reducing the original data's dimension. Multiple logistic and linear regression analyses were performed to examine the correlations between the three parameters and K-L grades and the comprehensive principal component score of varus deformit.ResultsLPW and PFC were significantly greater and FH was significantly smaller in the knee-OA group than in the no-knee-OA group. LPW, PFC, and FH were correlated with knee OA occurrence. One principal component, named the comprehensive principal component score of varus deformity, was extracted from the three indexes, and the total variance of the principal component interpretation was 76.60%. Multivariate logistics and linear regression analysis showed that after adjusting for age and BMI, LPW and PFC were positively correlated with K-L grading and varus deformity. FH was significantly and negatively associatedwith K-L grading and varus deformity (all P < 0.05).ConclusionsRegular morphological changes take place in the lateral knee with varus OA, including lateral dislocation of the tibial plateau, proximal fibula bending, and upward movement of the fibular head. Changes in LPW, PFC, and FH could enable a more comprehensive assessment of varus knee OA occurrence, severity, and deformity.Level of EvidenceRetrospective Study Level III

scholarly journals Effects of quantitative and qualitative principal component score strategies on the structure of coffee, rubber tree, rice and sorghum core collections

1998 ◽  
Vol 30 (Suppl 1) ◽  
pp. S237 ◽  
Author(s):  
Serge Hamon ◽  
Stéphane Dussert ◽  
Monique Deu ◽  
Perla Hamon ◽  
Marc Seguin ◽  
...  
Keyword(s):  
Rubber Tree ◽  
Principal Component ◽  
Principal Component Score ◽  
Core Collections ◽  
Component Score

Relationship Between Low Bone Mineral Density and Varus Deformity in Postmenopausal Women with Knee Osteoarthritis

2009 ◽  
Vol 36 (3) ◽  
pp. 592-597 ◽  
Author(s):  
YASUSHI AKAMATSU ◽  
NAOTO MITSUGI ◽  
NAOYA TAKI ◽  
RYOHEI TAKEUCHI ◽  
TOMOYUKI SAITO
Keyword(s):  
Bone Mineral Density ◽  
Lumbar Spine ◽  
Knee Osteoarthritis ◽  
Structural Changes ◽  
Tibial Plateau ◽  
Varus Deformity ◽  
Varus Knee ◽  
Mineral Density ◽  
Femorotibial Angle ◽  
Knee Oa

Objective.To assess the relationship between bone mineral density (BMD) and varus deformity arising from bone structural changes caused by knee osteoarthritis (OA) in postmenopausal women.Methods.This cross-sectional study involved 135 consecutive postmenopausal female patients who had varus knee OA and a Kellgren-Lawrence grade ≥ 2. Knee radiographs were obtained with the patient standing on one leg, and subjects were classified into 3 tertile groups according to femorotibial angle, which was taken as a measure of varus knee OA severity. We also measured the 3 subangles that make up the femorotibial angle, and focused on the varus inclination of the tibial plateau. BMD was measured in the lumbar spine, femoral neck, and medial and lateral tibial condyles using dual-energy X-ray absorptiometry. Differences between femorotibial angle tertile groups were assessed, and associations between femorotibial sub-angles and BMD values at various points were evaluated.Results.After adjustment for age and body mass index, there was no significant association between the varus inclination of the tibial plateau and lumbar spine BMD. A weak but statistically significant negative correlation existed between varus inclination of the tibial plateau and BMD at the ipsilateral proximal femur and lateral tibial condyle.Conclusion.Varus inclination of the tibial plateau was significantly more severe in the femorotibial angle tertile 3 group, and in patients with lower BMD in the ipsilateral lower limb. Varus knee OA may result not only from cartilage loss but also from structural changes of the bone.

Integrating principal component score strategy with power core method for development of core collection in Indian soybean germplasm

2015 ◽  
Vol 15 (3) ◽  
pp. 230-238 ◽  
Author(s):  
C. Gireesh ◽  
S. M. Husain ◽  
M. Shivakumar ◽  
G. K. Satpute ◽  
Giriraj Kumawat ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Core Collection ◽  
Principal Component ◽  
Oilseed Crop ◽  
Principal Component Score ◽  
Core Collections ◽  
Component Score ◽  
Soybean Germplasm ◽  
Mini Core Collection ◽  
Core Method

Soybean is a leading oilseed crop in India, which contains about 40% of protein and 20% of oil. Core collection will accelerate the management and utilization of soybean genetic resources in breeding programmes. In the present study, eight agromorphological traits of 3443 soybean germplasm were analysed for the development of core collection using the principal component score (PCS) strategy and the power core method. The PCS strategy yielded core collection (CC1) of 576 accessions, which accounted for 16.72% of the entire collection (EC). The analysis based on the power core programme resulted in CC2 of 402 accessions, which accounted for 11.67% of the EC. Statistical analysis showed similar trends for the mean and range estimated in both core collections and EC. In addition, the variance, standard deviation and coefficient of variance were in general higher in core collections than in the EC. The correlations observed in the EC in general were preserved in core collections. A total of 311 and 137 unique accessions were found in CC1 and CC2 in addition to 265 accessions that were found to be common in both core collections. These 265 common accessions were the most diverse core sets, which accounted for 7.64% of the EC. We proposed to constitute an integrated core collection (ICC) by integrating both common and unique accessions. The ICC comprised 713 accessions, which accounted for about 20.62% of the EC. Statistical analysis indicated that the ICC captured maximum variation than CC1 and CC2. Therefore, the ICC can be extensively evaluated for a large number of economically important traits for the identification of desirable genotypes and for the development of mini core collection in soybean.

scholarly journals The Effect of Correction Algorithms on Knee Kinematics and Kinetics during Gait of Patients with Knee Osteoarthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Hanna Ulbricht ◽  
Meijin Hou ◽  
Xiangbin Wang ◽  
Jian He ◽  
Yanxin Zhang
Keyword(s):  
Knee Joint ◽  
Knee Osteoarthritis ◽  
Gait Analysis ◽  
Clinical Decision Making ◽  
Knee Kinematics ◽  
Principal Component ◽  
Clinical Decision ◽  
Joint Angles ◽  
Knee Oa ◽  
Flexion Moment

In gait analysis, the accuracy of knee joint angles and moments is critical for clinical decision-making. The purpose of this study was to determine the efficacy of two existing algorithms for knee joint axis correction under pathological conditions. Gait data from 20 healthy participants and 20 patients with knee osteoarthritis (OA) were collected using a motion capture system. An algorithm based on Principal Component Analysis (PCA) and a functional joint-based algorithm (FJA) were used to define the knee joint flexion axis. The results show that PCA decreased crosstalk for both groups, and FJA reduced crosstalk in patients with knee OA only. PCA decreased the range of motions of patients with knee OA in the direction of abduction/adduction significantly. There was a significant increase in the maximum knee flexion moment of patients with knee OA by FJA. The results indicate that both algorithms can efficiently reduce crosstalk for gait from patients with knee OA, which can further influence the results of knee joint angles and moments. We recommend that the correction algorithms be applied in clinical gait analysis with patients with knee OA.

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