Smartphone-based apps that measure step-count and patient reported outcomes (PROMs) are being increasingly used to quantify recovery in total hip arthroplasty (THA). However, optimum patient-specific activity level before and during THA early-recovery is not well characterised. This study investigated 1) correlations between step-count and PROMs and 2) how patient demographics impact step-count preoperatively and during early postoperative recovery. Smartphone step-count and PROM data from 554 THA patients was retrospectively reviewed. Mean age was 64±10yr, BMI was 29±13kg/m2, 56% were female. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and HOOS12 Function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<2500steps/day), medium (2500-5500steps/day), and high (>5500steps/day). Age >65years, BMI >30, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). HOOS12 Function correlated with step-count preoperatively and at 6wk (p<0.01). High vs low step count individuals had improved UCLA scores preoperatively (∆1.8,p<0.001), at 6wk (∆1.1,p<0.05), and 12wk (∆1.6,p<0.01), and improved HOOS12 Function scores preoperatively (∆8.4,p<0.05) and at 6wk (∆8.8,p<0.001). Younger patients had greater step-count preoperatively (4.1±3.0k vs 3.0±2.5k, p<0.01) and at 12wk (5.1±3.3k vs 3.6±2.9k, p<0.01). Males had greater step-count preoperatively (4.1±3.0k vs. 3.0±2.7k, p<0.001), at 6wk (4.5±3.2k vs 2.6±2.5k, p<0.001), and at 12wk (5.2±3.6k vs. 3.4±2.5k, p<0.001). Low BMI patients had greater step-count at 6wk (4.3±3.3k vs. 2.6±2.7k, p<0.01) and 12wk (5.0±3.6k vs. 3.6±2.6k, p<0.05). Daily step-count is significantly impacted by patient demographics and correlates with PROMs, where patients with high step count exhibit improved PROMs. Generic recovery profiles may therefore not be appropriate for benchmarking across diverse populations.
Passive smartphone-based apps are becoming more common for measuring patient progress after total knee arthroplasty (TKA). Optimum activity levels during early TKA recovery haven't been well documented. This study investigated correlations between step-count and patient reported outcome measures (PROMs) and how demographics impact step-count preoperatively and during early post-operative recovery. Smartphone capture step-count data from 357 TKA patients was retrospectively reviewed. Mean age was 68±8years. 61% were female. Mean BMI was 31±6kg/m2. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and KOOS12-function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<1500steps/day), medium (1500-4000steps/day), and high (>4000steps/day). Age >65years, BMI >30kg/m2, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups, and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). KOOS12-Function correlated with step-count at 6wk and 12wk (p<0.05). High step-count individuals had improved PROMs compared to low step-count individuals preoperatively (UCLA: ∆1.4 [p<0.001], KOOS12-Function: ∆7.3 [p<0.05]), at 6wk (UCLA: ∆1 [p<0.01], KOOS12-Function: ∆7 [p<0.05]), and at 12wk (UCLA: ∆0.8 [p<0.05], KOOS12-Function: ∆6.5 [p<0.05]). Younger patients had greater step-count preoperatively (3.8±3.0k vs. 2.5±2.3k, p<0.01), at 6wk (3.1±2.9k vs. 2.2±2.3k, p<0.05) and at 12wk (3.9±2.6k vs. 2.8±2.6k, p<0.01). Males had greater step-count preoperatively (3.7±2.6k vs. 2.5±2.6k, p<0.001), at 6wk (3.6±2.6k vs. 1.9±2.4k, p<0.001), and at 12wk (3.9±2.3 vs. 2.8±2.8k, p<0.01). No differences in step-count were observed between low and high BMI patients at any timepoint. High step count led to improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age and sex. Generic recovery profiles may not be appropriate across a diverse population.
Achieving a balanced joint with neutral alignment is not always possible in total knee arthroplasty (TKA). Intra-operative compromises such as accepting some joint imbalance, non-neutral alignment or soft-tissue release may result in worse patient outcomes, however, it is unclear which compromise will most impact outcome. In this study we investigate the impact of post-operative soft tissue balance and component alignment on postoperative pain. 135 patients were prospectively enrolled in robot assisted TKA with a digital joint tensioning tool (OMNIBotics with BalanceBot, Corin USA) (57% female; 67.0 ± 8.1 y/o; BMI: 31.9 ± 4.8 kg/m2). All surgeries were performed with a PCL sacrificing tibia or femur first techniques technique, using CR femoral components and a deep dish tibial insert (APEX, Corin USA). Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the tensioning tool inserted in place of the tibial trial. Component alignment parameters and post-operative joint gaps throughout flexion were recorded. Patients completed 1-year KOOS pain questionnaires. Spearman correlations and Mann-Whitney-U tests were used to investigate continuous and categorical data respectively. All analysis performed in R 3.5.3.Introduction
Methods
Soft-tissue balancing methods in TKA have evolved from surgeon feel to digital load-sensing tools. Such techniques allow surgeons to assess the soft-tissue envelope after bone cuts, however, these approaches are ‘after-the-fact’ and require soft-tissue release or bony re-cuts to achieve final balance. Recently, a robotic ligament tensioning device has been deployed which characterizes the soft tissue envelope through a continuous range-of-motion after just the initial tibial cut, allowing for virtual femoral resection planning to achieve a targeted gap profile throughout the range of flexion (figure-1). This study reports the first early clinical results and patient reported outcomes (PROMs) associated with this new technique and compares the outcomes with registry data. Since November 2017, 314 patients were prospectively enrolled and underwent robotic-assisted TKA using this surgical technique (mean age: 66.2 ±8.1; females: 173; BMI: 31.4±5.3). KOOS/WOMAC, UCLA, and HSS-Patient Satisfaction scores were collected pre- and post-operatively. Three, six, and twelve-month assessments were completed by 202, 141, and 63 patients, respectively, and compared to registry data from the Shared Ortech Aggregated Repository (SOAR). SOAR is a TJA PROM repository run by Ortech, an independent clinical data collection entity, and it includes data from thousands of TKAs from a diverse cross-section of participating hospitals, teaching institutions and clinics across the United States and Canada who collect outcomes data. PROMs were compared using a two-tailed t-test for non-equal variance.Introduction
Methods
Soft tissue releases are often required to correct deformity and achieve gap balance in total knee arthroplasty (TKA). However, the process of releasing soft tissues can be subjective and highly variable and is often perceived as an ‘art’ in TKA surgery. Releasing soft tissues also increases the risk of iatrogenic injury and may be detrimental to the mechanically sensitive afferent nerve fibers which participate in the regulation of knee joint stability. Measured resection TKA approaches typically rely on making bone cuts based off of generic alignment strategies and then releasing soft tissue afterwards to balance gaps. Conversely, gap-balancing techniques allow for pre-emptive adjustment of bone resections to achieve knee balance thereby potentially reducing the amount of ligament releases required. No study to our knowledge has compared the rates of soft tissue release in these two techniques, however. The objective of this study was, therefore, to compare the rates of soft tissue releases required to achieve a balanced knee in tibial-first gap-balancing versus femur-first measured-resection techniques in robotic assisted TKA, and to compare with release rates reported in the literature for conventional, measured resection TKA [1]. The number and type of soft tissue releases were documented and reviewed in 615 robotic-assisted gap-balancing and 76 robotic-assisted measured-resection TKAs as part of a multicenter study. In the robotic-assisted gap balancing group, a robotic tensioner was inserted into the knee after the tibial resection and the soft tissue envelope was characterized throughout flexion under computer-controlled tension (fig-1). Femoral bone resections were then planned using predictive ligament balance gap profiles throughout the range of motion (fig-2), and executed with a miniature robotic cutting-guide. Soft tissue releases were stratified as a function of the coronal deformity relative to the mechanical axis (varus knees: >1° varus; valgus knees: >1°). Rates of releases were compared between the two groups and to the literature data using the Fischer's exact test.Introduction
Methods
Achieving good ligament balance in total knee arthroplasty (TKA) is essential to prevent early failure and revision surgery. Poor balance and instability are well-defined, however, an ideal ligament balance target across all patients is not well-understood. In this study we investigate the achieved ligament balance using an imageless, intra-operative dynamic balancing tool and its relation to patient reported outcomes. A prospective, multi-surgeon, multi-center study investigated the use of a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform using the APEX knee (OMNI-Corin, Raynham MA). After all resections, the femoral trial and a computer-controlled tensioning device in place of the tibial tray was inserted into the knee joint. The difference in medial and lateral (ML) gaps when balancing the knee under constant load at extension (10°), mid-flexion (30°) and flexion (90°) was captured. Patients completed the KOOS questionnaire at 3 months ± 2 weeks post-surgery and considered the past 7 days as a timeframe for responses. Pearson's correlation was used to determine linear correlations between factors and ANOVA tests were used to determine differences in categorical data.Background
Methods
Achieving a well-balanced midflexion and flexion soft tissue envelope is a major goal in Total Knee Arthroplasty (TKA). The definition of soft tissue balance that results in optimal outcomes, however, is not well understood. Studies have investigated the native soft tissue envelope in cadaveric specimen and have shown loosening of the knee in flexion, particularly on the lateral side. These methods however do not reflect the post TKA environment, are invasive, and not appropriate for intra-operative use. This study utilizes a digital gap measuring tool to investigate the impact of soft tissue balance in midflexion and flexion on post-operative pain. A prospective multicenter multi-surgeon study was performed in which patients underwent TKA with a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform. All surgeries were performed with APEX implants (Corin Ltd., USA) using a variety of tibia and femur first techniques. Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the balancing tool inserted in place of the tibial trial. Patients completed KOOS pain questionnaires at 3months±2weeks post-op. Linear correlations were investigated between KOOS pain and coronal gap measurements in midflexion (30°–60°) and flexion (>70°). T-tests were used to compare outcomes between categorical data.Introduction
Methods
Intimate bone-implant contact is a requirement for achieving stable component fixation and osseo-integration of porous-coated implants in TKA. However, consistently attaining a press-fit and a tight-fitting femoral component can be problematic when using conventional instrumentation. We present a new robotic cutting-guide system that permits intra-operative adjustment of the femoral resections such that a specified amount of press-fit can be consistently attained. System Description: A.R.T. (Apex Robotic Technology) employs a miniature bone-mounted robotic cutting-guide and flexible software that permits the surgeon to adjust the anterior and posterior femoral resections in increments of 0.25 mm per resection, allowing a maximum of 1.5mm of total added press in the AP dimension. The accuracy of guide-positioning and bone-cutting with A.R.T. was assessed in bench testing on synthetic bones (SAWBONES®) using an optical comparator. The individual guide locations for 16 femoral cut positioning sequences (80 guide positions in total) were measured. Femoral resections were performed with A.R.T. on eight sawbones (two per fit-adjustment setting) and the anterior-posterior dimensions of the final cut surfaces were also measured. Eight sawbones were prepared using conventional instrumentation (jigs) as controls: four with a 0 mm press-fit block and four with a +0.5 mm specially manufactured press-fit block.Introduction
Methods
Architectural changes occurring in the proximal femur after THA continues to be a problem. Stress shielding occurs regardless of fixation method. The resultant bone loss can lead to implant loosening and breakage of the implant. A new novel tissue sparing neck-stabilised stem has been designed to address these concerns. Over 1,200 stems have been implanted since April 2010 and 2012. Patient profile showed two-thirds being female with an age range between 17 to early 90s. 90% were treated for OA. This stem has been used in all Dorr bone classification (A, B, & C). Two surgical approaches were utilised (single anterior incision and standard posterior incision). All were used with a variety of cementless acetabular components and a variety of bearing surfaces (CoC, CoP, MoM, MoP). Complications were track by surgeon Members of the Tissue Sparing Study Group of the Joint Implant Surgery and Research Foundation. Complications include first year of limited clinical release. No surgeon was permitted usage without specific cadaver / surgical training. No head diameters below 32 mm were used.Introduction
Methods
