Abstract Background In robotic-assisted total knee arthroplasty (TKA), achieving soft-tissue balance requires repeated intraoperative plan adjustment and remains experience-dependent. Predictive models may support planning, but their clinical value depends on whether model-generated plans approximate predefined target gaps within the robotic workflow. This study assessed the software-based concordance between model-generated plans and predefined target gaps in robotic-assisted TKA. The predefined target gaps were planning set points established within the robotic software rather than measured intraoperative gaps. Methods This retrospective software-based concordance study included 209 complete-case knees undergoing robotic-assisted TKA. A machine-learning-based predictive model generated a bone-resection plan, which was imported into the robotic planning software to calculate software-derived medial and lateral gaps in extension and flexion. These software-derived gaps were compared with predefined target gaps, which were planning set points rather than measured values and were 18 mm in 819 of 836 gap-level observations (98.0%). The primary analysis focused on target gap deviation, defined as the software-derived gap minus the predefined target gap. As a benchmark, the deviation of the preadjustment gaps from the same targets was used as a preadjustment reference. Results A total of 836 gap-level observations were analyzed. The overall mean target gap deviation was −0.142 mm (SD, 1.411 mm), with a mean absolute error of 1.016 mm. Overall, 77.6% of software-derived gaps were within ±1 mm of target, and 93.4% were within ±2 mm. Bland–Altman analysis showed a small overall bias of −0.142 mm, with 95% limits of agreement from −2.91 to +2.62 mm. At the knee level, only 43.1% of knees had all software-derived gaps within ±1 mm of target. Gap-level deviations ranged from −7 mm to +5 mm, and 16.3% of knees (34/209) had at least one gap with an absolute deviation > 2 mm. Compared with the preadjustment reference (MAE 2.002 mm, 49.4% within ±1 mm), the model substantially reduced deviation (MAE 1.016 mm, 77.6% within ±1 mm, p < 0.001). Conclusions In this software-based concordance analysis, the predictive planning model generated surgical plans whose robotic software-derived gaps approximated predefined target gaps with a mean absolute deviation of approximately 1 mm. The model-generated plan reduced target-gap deviation relative to the initial preadjustment plan within this target-conditioned workflow. However, because the targets were near-uniform (98.0% at 18 mm) and all measurements were software-derived, compartment-specific bias, moderate whole-knee consistency (43.1%), and occasional outlier deviations indicate that the model should be used as a surgeon-supervised decision support tool rather than as an autonomous planner. Prospective validation against measured intraoperative and postoperative gaps is required before clinical effectiveness can be claimed.
Knee osteoarthritis (OA) is a heterogeneous disease with varying progression rates among patients within the same severity grade. This study aimed to identify clinically interpretable radiographic phenotypes among knees with baseline Kellgren and Lawrence (KL) grade 2 osteoarthritis and to compare their 4-year radiographic progression patterns using baseline radiographic features, lifetime exercise patterns, and demographic characteristics. Data of patients with baseline KL grade 2 from the Osteoarthritis Initiative database were retrieved. Unsupervised clustering was performed using uniform manifold approximation and projection (UMAP) for dimensionality reduction, followed by hierarchical density-based spatial clustering of applications with noise (HDBSCAN) to identify distinct subgroups. The proportion of knees progressing to KL grade ≥ 3 within 4 years was compared between subgroups, followed by a survival analysis until knee replacement or progression to KL grade 4. A total of 1997 knees with a mean follow-up of 103.3 months (maximum, 108 months) were included. A total of seven subgroups were identified and classified into accelerated osteoarthritis progression (AOP) group and slow osteoarthritis progression (SOP) group according to whether their 4-year KL grade progression proportions were above or below the training-set average. In a supportive long-term survival analysis, the AOP group also showed significantly earlier progression to knee replacement or KL grade 4 than the SOP group (training set, P < 0.001; test set, P = 0.049), although the absolute difference in mean survival time was modest (8.3 versus 8.5 years in the training set; 8.4 versus 8.6 years in the test set). The AOP group was characterized mainly by lateral joint space narrowing (JSN) and medial JSN with subchondral sclerosis, whereas the SOP group was characterized by medial JSN without subchondral sclerosis, osteophyte-dominant patterns without JSN, or chondrocalcinosis-dominant patterns; these differences were statistically significant across clusters. Within baseline KL grade 2 knees, clinically interpretable radiographic phenotypes, including lateral JSN, medial JSN with subchondral sclerosis, osteophyte-dominant changes without JSN, and chondrocalcinosis-dominant patterns, were associated with different 4-year KL grade progression rates. These findings support viewing KL grade 2 knee OA as a heterogeneous radiographic stage that may be further stratified into phenotype-based subgroups with different short-term radiographic prognoses.
Abstract Background Posterior tibial slope (PTS) has been identified as an important anatomical risk factor for medial meniscus posterior root tear (MMPRT). However, prior studies have primarily focused on the medial slope. The primary aim of this study was to measure medial and lateral PTS on magnetic resonance imaging (MRI) and to determine whether medial–lateral slope asymmetry is associated with MMPRT. Methods This multicenter retrospective study included patients aged 50–75 years who underwent knee MRI for knee pain at two institutions. Patients with osteoarthritis (Kellgren–Lawrence grade 3 or 4) were excluded. MMPRT was diagnosed on MRI. The medial PTS (MPTS), lateral PTS (LPTS), medial proximal tibial angle (MPTA), and lateral distal femoral angle (LDFA) were measured, and ΔPTS was defined as MPTS − LPTS. Groups were compared before and after 1:1 propensity score (PS) matching for age, sex, and body mass index. Multivariable logistic regression and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the association and discriminative ability of ΔPTS. Results A total of 120 knees were included, of which 26 (21.7%) demonstrated MMPRT. MPTS did not differ significantly between groups, whereas the MMPRT group showed a significantly smaller LPTS ( p < 0.001) and larger ΔPTS ( p < 0.001). These findings remained consistent after 1:1 PS matching (22 matched pairs), with ΔPTS remaining significantly greater in the MMPRT group ( p < 0.001). In multivariable analysis, ΔPTS was independently associated with MMPRT (odds ratio 2.17 per 1°, 95% CI 1.56–3.02, p < 0.001). ROC curve analysis demonstrated good discriminative performance of ΔPTS for identifying MMPRT (area under the curve [AUC] = 0.87, 95% CI 0.79–0.95), which exceeded that of LPTS (0.73) and MPTS (0.54) (DeLong p = 0.006 and p < 0.001, respectively). The exploratory cutoff value was 4.0°, yielding a sensitivity of 80.8% and a specificity of 81.9%. Conclusions Knees with MMPRT exhibited a smaller LPTS and greater ΔPTS compared with knees without MMPRT, which remained significant after PS matching. ROC analysis demonstrated good discriminative performance, and a ΔPTS of 4.0° or greater may serve as an exploratory threshold. PTS asymmetry may represent a morphological factor associated with MMPRT. Level of evidence III.
Purpose This study aimed to investigate the longitudinal relationship between postoperative medial proximal tibial angle (pMPTA) and joint space narrowing or osteophyte formation during a 3-year follow-up period after medial open-wedge high tibial osteotomy (MOWHTO). Methods This retrospective cohort study included 133 knees of 101 patients (58 female patients; 77 female knees) who underwent MOWHTO [mean age: 57.5 ± 7.9 years; body mass index: 26.3 ± 4.0 kg/m 2 ; 32 patients (19 female patients) underwent bilateral surgeries]. On the basis of plain radiograph until 1 month postoperatively (Post Op), pMPTA and change in MPTA (ΔMPTA) (i.e., [pMPTA] − [preoperative MPTA]) were measured. Additionally, the medial and lateral femorotibial joint space widths (MJSW/LJSW) and osteophyte area (MOPA/LOPA) were measured at Post Op, and the JSW and OPA were remeasured at 3-year follow-up (3Y). Amount of changes in JSW and OPA were measured using the following formula: Δ = [JSW 3Y or OPA 3Y ] − [JSW Post Op or OPA Post Op ]. If ΔMJSW was ≤ −0.3 mm, we defined medial knee osteoarthritis as progressed (p-mOA). Results Forty-seven (35.3%) patients were diagnosed with p-mOA. Both pMPTA and ΔMPTA positively correlated with ΔMJSW. Receiver operating characteristic curves of pMPTA detected p-mOA, and the cut-off of pMPTA was 90°. Generalized estimation equations revealed that those with < 90° of correction for pMPTA demonstrated higher odds ratio of p-mOA (odds ratio: 3.300; 95% confidence interval: 1.327–8.198, p -value: 0.010), as compared with those with ≥ 90° correction. This finding was more robust in patients with preoperative Kellgren–Lawrence grade 0 or 1 (odds ratio: 5.408; 95% confidence interval: 1.400–20.905, p -value: 0.014), and ΔLJSW did not correlate with both pMPTA and ΔMPTA. Both the MOPA and LOPA increased during the 3-year follow-up period. However, there was no correlation between ΔOPA and pMPTA or ΔMPTA. Conclusions Only in those with nonradiographic OA, correcting pMPTA with < 90° demonstrated a higher odds ratio of medial femorotibial joint space narrowing after MOWHTO when compared with those having ≥ 90° correction in the current short-term follow-up. Level of evidence : III.
Recovery after anterior cruciate ligament (ACL) reconstruction is typically monitored through patient-reported outcomes and periodic clinical assessments, which may not fully capture real-world functional performance. Smartphone-derived mobility data provide a passive and objective approach for evaluating daily activity and recovery. To examine associations between smartphone-derived mobility metrics and recovery outcomes in adults 3–12 months after primary ACL reconstruction and to identify distinct recovery phenotypes using mobility-based clustering. This cross-sectional study included 120 adults who were 3–12 months post-primary ACL reconstruction and had at least 14 days of retrospective smartphone mobility data. Mobility variables included daily step count, activity volume and intensity (e.g., active minutes and walking bout duration), sedentary behavior, and walking-related metrics. Outcomes included pain (Numeric Rating Scale [NRS]), functional status (Knee Injury and Osteoarthritis Outcome Score [KOOS] Pain, Activities of Daily Living, and Sport/Recreation subscales), knee-related quality of life (ACL Quality of Life questionnaire [ACL-QoL]), and psychological measures including the Pain Catastrophizing Scale (PCS), Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder-7 (GAD-7). Associations were evaluated using Pearson correlation and multivariable linear regression analyses. Recovery phenotypes were identified using unsupervised k-means clustering of mobility metrics. Higher daily step counts were independently associated with better KOOS-ADL scores (β = 0.48, p < 0.001), higher ACL-QoL scores (β = 0.45, p < 0.001), and lower pain intensity (β = − 0.39, p = 0.001). Three recovery phenotypes emerged: a high-activity/low-pain phenotype with superior function and minimal psychological distress, a moderate-activity/moderate-pain phenotype with intermediate outcomes, and a low-activity/high-pain phenotype characterized by reduced mobility, poorer function, greater pain, and higher pain catastrophizing. Significant gradients were observed across phenotypes for pain (NRS: 1.72–5.01), function (KOOS-Pain: 88.94–62.37), and pain catastrophizing (PCS: 8.52–24.91; all p < 0.001). Smartphone-derived mobility metrics were significantly associated with recovery outcomes following ACL reconstruction. Mobility-based clustering identified distinct recovery phenotypes associated with meaningful differences in pain, function, and pain catastrophizing, highlighting the potential of passive mobility monitoring to support personalized rehabilitation strategies. However, given the variability in evaluation periods and uncontrolled surgical factors, future research employing standardized, long-term follow-ups is warranted.
