As advancements in total knee arthroplasty progress at an exciting pace, two areas are of special interest, as they directly impact implant design and surgical decision making. Knee morphometry considers the three-dimensional shape of the articulating surfaces within the knee joint, and knee phenotyping provides the ability to categorize alignment into practical groupings that can be used in both clinical and research settings. This annotation discusses the details of these concepts, and the ways in which they are helping us better understand the individual subtleties of each patient’s knee. Cite this article:
The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
Methods
Robotic arm-assisted surgery offers accurate and reproducible guidance in component positioning and assessment of soft-tissue tensioning during knee arthroplasty, but the feasibility and early outcomes when using this technology for revision surgery remain unknown. The objective of this study was to compare the outcomes of robotic arm-assisted revision of unicompartmental knee arthroplasty (UKA) to total knee arthroplasty (TKA) versus primary robotic arm-assisted TKA at short-term follow-up. This prospective study included 16 patients undergoing robotic arm-assisted revision of UKA to TKA versus 35 matched patients receiving robotic arm-assisted primary TKA. In all study patients, the following data were recorded: operating time, polyethylene liner size, change in haemoglobin concentration (g/dl), length of inpatient stay, postoperative complications, and hip-knee-ankle (HKA) alignment. All procedures were performed using the principles of functional alignment. At most recent follow-up, range of motion (ROM), Forgotten Joint Score (FJS), and Oxford Knee Score (OKS) were collected. Mean follow-up time was 21 months (6 to 36).Aims
Methods
The aim of mechanical alignment in total knee arthroplasty is to align all knees into a fixed neutral position, even though not all knees are the same. As a result, mechanical alignment often alters a patient’s constitutional alignment and joint line obliquity, resulting in soft-tissue imbalance. This annotation provides an overview of how the Coronal Plane Alignment of the Knee (CPAK) classification can be used to predict imbalance with mechanical alignment, and then offers practical guidance for bone balancing, minimizing the need for soft-tissue releases. Cite this article:
Total knee arthroplasty (TKA) may provoke ankle symptoms. The aim of this study was to validate the impact of the preoperative mechanical tibiofemoral angle (mTFA), the talar tilt (TT) on ankle symptoms after TKA, and assess changes in the range of motion (ROM) of the subtalar joint, foot posture, and ankle laxity. Patients who underwent TKA from September 2020 to September 2021 were prospectively included. Inclusion criteria were primary end-stage osteoarthritis (Kellgren-Lawrence stage IV) of the knee. Exclusion criteria were missed follow-up visit, post-traumatic pathologies of the foot, and neurological disorders. Radiological angles measured included the mTFA, hindfoot alignment view angle, and TT. The Foot Function Index (FFI) score was assessed. Gait analyses were conducted to measure mediolateral changes of the gait line and ankle laxity was tested using an ankle arthrometer. All parameters were acquired one week pre- and three months postoperatively.Aims
Methods
Orthopaedic surgeons are currently faced with an overwhelming number of choices surrounding total knee arthroplasty (TKA), not only with the latest technologies and prostheses, but also fundamental decisions on alignment philosophies. From ‘mechanical’ to ‘adjusted mechanical’ to ‘restricted kinematic’ to ‘unrestricted kinematic’ — and how constitutional alignment relates to these — there is potential for ambiguity when thinking about and discussing such concepts. This annotation summarizes the various
Intraoperative pressure sensors allow surgeons to quantify soft-tissue balance during total knee arthroplasty (TKA). The aim of this study was to determine whether using sensors to achieve soft-tissue balance was more effective than manual balancing in improving outcomes in TKA. A multicentre randomized trial compared the outcomes of sensor balancing (SB) with manual balancing (MB) in 250 patients (285 TKAs). The primary outcome measure was the mean difference in the four Knee injury and Osteoarthritis Outcome Score subscales (ΔKOOS4) in the two groups, comparing the preoperative and two-year scores. Secondary outcomes included intraoperative balance data, additional patient-reported outcome measures (PROMs), and functional measures.Aims
Methods
This systematic review aims to compare the precision of component positioning, patient-reported outcome measures (PROMs), complications, survivorship, cost-effectiveness, and learning curves of MAKO robotic arm-assisted unicompartmental knee arthroplasty (RAUKA) with manual medial unicompartmental knee arthroplasty (mUKA). Searches of PubMed, MEDLINE, and Google Scholar were performed in November 2021 according to the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “robotic”, “unicompartmental”, “knee”, and “arthroplasty”. Published clinical research articles reporting the learning curves and cost-effectiveness of MAKO RAUKA, and those comparing the component precision, functional outcomes, survivorship, or complications with mUKA, were included for analysis.Aims
Methods
The goal of the current systematic review was to assess the impact of implant placement accuracy on outcomes following total knee arthroplasty (TKA). A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the Ovid Medline, Embase, Cochrane Central, and Web of Science databases in order to assess the impact of the patient-reported outcomes measures (PROMs) and implant placement accuracy on outcomes following TKA. Studies assessing the impact of implant alignment, rotation, size, overhang, or condylar offset were included. Study quality was assessed, evidence was graded (one-star: no evidence, two-star: limited evidence, three-star: moderate evidence, four-star: strong evidence), and recommendations were made based on the available evidence.Aims
Methods
A comprehensive classification for coronal lower limb alignment with predictive capabilities for knee balance would be beneficial in total knee arthroplasty (TKA). This paper describes the Coronal Plane Alignment of the Knee (CPAK) classification and examines its utility in preoperative soft tissue balance prediction, comparing kinematic alignment (KA) to mechanical alignment (MA). A radiological analysis of 500 healthy and 500 osteoarthritic (OA) knees was used to assess the applicability of the CPAK classification. CPAK comprises nine phenotypes based on the arithmetic HKA (aHKA) that estimates constitutional limb alignment and joint line obliquity (JLO). Intraoperative balance was compared within each phenotype in a cohort of 138 computer-assisted TKAs randomized to KA or MA. Primary outcomes included descriptive analyses of healthy and OA groups per CPAK type, and comparison of balance at 10° of flexion within each type. Secondary outcomes assessed balance at 45° and 90° and bone recuts required to achieve final knee balance within each CPAK type.Aims
Methods
It is unknown whether kinematic alignment (KA) objectively improves knee balance in total knee arthroplasty (TKA), despite this being the biomechanical rationale for its use. This study aimed to determine whether restoring the constitutional alignment using a restrictive KA protocol resulted in better quantitative knee balance than mechanical alignment (MA). We conducted a randomized superiority trial comparing patients undergoing TKA assigned to KA within a restrictive safe zone or MA. Optimal knee balance was defined as an intercompartmental pressure difference (ICPD) of 15 psi or less using a pressure sensor. The primary endpoint was the mean intraoperative ICPD at 10° of flexion prior to knee balancing. Secondary outcomes included balance at 45° and 90°, requirements for balancing procedures, and presence of tibiofemoral lift-off.Aims
Methods
Modern healthcare contracting is shifting the
responsibility for improving quality, enhancing community health
and controlling the total cost of care for patient populations from
payers to providers. Population-based contracting involves capitated
risk taken across an entire population, such that any included services
within the contract are paid for by the risk-bearing entity throughout
the term of the agreement. Under such contracts, a risk-bearing entity,
which may be a provider group, a hospital or another payer, administers
the contract and assumes risk for contractually defined services.
These contracts can be structured in various ways, from professional
fee capitation to full global per member per month diagnosis-based
risk. The entity contracting with the payer must have downstream
network contracts to provide the care and facilities that it has
agreed to provide. Population health is a very powerful model to
reduce waste and costs. It requires a deep understanding of the nuances
of such contracting and the appropriate infrastructure to manage
both networks and risk. Cite this article:
