Radiologic Assessment of Knee Phenotypes Based on the Coronal Plane Alignment of the Knee Classification in a Korean Population.

Background: The Coronal Plane Alignment of the Knee (CPAK) classification system has been developed as a comprehensive system that describes 9 coronal plane phenotypes based on constitutional limb alignment and joint line obliquity (JLO). Due to the characteristics of Asian populations, which show more varus and wider distribution in lower limb alignment than other populations, modification of the boundaries of the arithmetic hip-knee-ankle angle (aHKA) and JLO should be considered. The purpose of this study was to determine the knee phenotype in a Korean population based on the original CPAK and modified CPAK classification systems. Methods: We reviewed prospectively collected data of 500 healthy and 500 osteoarthritic knees between 2021 and 2023 using radiographic analysis and divided them based on the modified CPAK classification system by widening the neutral boundaries of the aHKA to 0° ± 3° and using the actual JLO as a new variable. Using long-leg standing weight-bearing radiographs, 6 radiographic parameters were measured to evaluate the CPAK type: the mechanical HKA angle, medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), aHKA, JLO, and actual JLO. Results: From 2 cohorts of 1,000 knees, the frequency distribution representing all CPAK types was different between the healthy and arthritic groups. The most common categories were type II (38.2%) in the healthy group and type I (53.8%) in the arthritic group based on the original CPAK classification. The left and upward shift in the distribution of knee phenotypes in the original classification was corrected evenly after re-establishing the boundaries of a neutral aHKA and the actual JLO. According to the modified CPAK classification system, the most common categories were type II (35.2%) in the healthy group and type I (38.0%) in the arthritic group. Conclusions: Although the modified CPAK classification corrected the uneven distribution seen when applying the original classification system in a Korean population, the most common category was type I in Korean patients with osteoarthritic knees in both classification systems. Furthermore, there were different frequencies of knee phenotypes among healthy and arthritic knees.

Windkessel model of hemodynamic state supported by a pulsatile ventricular assist device in premature ventricle contraction.

BACKGROUND: Counter-pulsation control (CPC) by ventricular assist devices (VADs) is believed to reduce cardiac load and increase coronary perfusion. However, patients with VADs have a higher risk of arrhythmia, which may cause the CPC to fail. Consequently, CPC has not been applied by VADs in clinical practice. The phase-locked loop (PLL) algorithm for CPC is readily implemented in VADs; however, it requires a normal, consistent heartbeat for adequate performance. When an arrhythmia occurs, the algorithm maintains a constant pumping rate despite the unstable heartbeat. Therefore, to apply the PLL algorithm to CPC, the hemodynamic effects of abnormal heartbeats must be analyzed. OBJECTIVES: This study sought to predict the hemodynamic effects in patients undergoing CPC using VADs, based on electrocardiogram (ECG) data, including a wide range of heart rate (HR) changes caused by premature ventricular contraction (PVC) or other reasons. METHODS: A four-element Windkessel hemodynamic model was used to reproduce the patient's aortic blood pressure in this study. ECG data from 15 patients with severe congestive heart failure were used to assess the effect of the CPC on the patients' hemodynamic state. The input and output flow characteristics of the pulsatile VAD (LibraHeart I, Cervika, Korea) were measured using an ultrasound blood flow meter (TS410, Transonic, USA), with the aortic pressure maintained at 80-120 mmHg. All other patient conditions were also reproduced. RESULTS: In patients with PVCs or normal heartbeats, CPC controlled by a VAD reduced the cardiac load by 20 and 40%, respectively. When the HR was greater for other reasons, such as sinus tachycardia, simultaneous ejection from the heart and VAD was observed; however, the cardiac load was not increased by rapid cardiac contractions resulting from decreased left ventricle volume. These data suggest that the PLL algorithm reduces the cardiac load and maintains consistent hemodynamic changes.