STATIC RADIOLOGICAL MEASURES ARE NOT INDICATORS OF THE KNEE DYNAMIC ALIGNMENT AND KINEMATIC BEHAVIOUR PRE- AND POST-TOTAL KNEE ARTHROPLASTY
Bibliographic record
Abstract
Static radiographic measures, such as arithmetic hip-knee-ankle angle (aHKA; i.e., angle between tibia and femur anatomic axis) and joint line obliquity (JLO) are parameters of interest in surgical planning for total knee arthroplasty (TKA) to define realignment targets. While mechanical HKA (i.e., angle between tibia anatomic and knee-hip centers axis) has been reported to be associated with one biomechanical marker (i.e., frontal plane alignment during the terminal stance phase of gait), it is insufficient to use it as an indicator of the knee dynamic behavior. It is still unknown if other radiographic measures could provide more valuable information to predict dynamic alignment behavior, thus the aim of this study was to assess the associations between three-dimensional (3D) kinematic biomechanical markers and both aHKA and JLO pre- and post-TKA. This was a secondary data analysis from a prospective TKA study with nineteen patients. All patients gave their informed consent to participate, 63.2% were women and the mean age was 61 years (95%CI: 57.9;63.3). Eight patients (42.1%) received a posterior-stabilized implant while the others had a bicruciate-retaining design. All participants underwent a knee kinesiography exam before and 1-year after surgery. This exam allows to quantify kinematic biomechanical markers in the three planes of movement while the patient is walking on a treadmill (see Figure 1). From a standardized full-length weight-bearing lower limb radiograph, a senior orthopaedic surgeon measured the lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA), used to calculate aHKA (MPTA-LDFA) and JLO (MPTA+LDFA). Bivariate Pearson correlations were calculated between 11 specific 3D kinematic biomechanical markers and both aHKA and JLO, before and 1-year after TKA. Detailed results are presented in Table 1. Out of the 44 evaluated associations, only one was statistically significant (i.e., p<0.05) in pre-TKA patients, between JLO and the frontal (i.e., varus-valgus) alignment at heel strike. A smaller JLO (i.e., towards a knee in apex distal) was associated with a more varus knee at heel strike (p=0.04). However, this association was moderate as it explained less than 25% of the variance (r=−0.482). Interestingly, aHKA was not significantly associated with any 3D kinematic biomechanical marker before nor after TKA. Results show that aHKA and JLO are not significantly associated with 3D knee kinematic biomechanical markers before nor after TKA. This suggests that these static radiographic alignment measures should not be used as indicators of the knee dynamic alignment or kinematic behavior in TKA patients. Therefore, to adequately consider the knee dynamic behavior to restore joint function with TKA, surgeons must integrate more objective measures related to function in their surgical planning. Further research with larger cohorts should be carried out to control the influence of implant designs and soft tissue balancing on kinematic biomechanical markers post-surgery to better understand the impact of TKA intervention on the knee dynamic behavior and achieve more functional knee dynamic alignment and better outcomes post-surgery. For any figures or tables, please contact the authors directly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".