Robotic-Assisted Joint Replacement — Current Evidence

Robotic-assisted joint replacement combines pre-operative 3D imaging-based planning with intraoperative robotic guidance to achieve highly precise implant positioning and bone preparation. Unlike passive navigation systems (which guide but do not constrain the surgeon), robotic platforms actively control or restrict the surgical instruments — either by providing haptic feedback that resists movement outside a pre-defined boundary (semi-active systems) or by autonomously executing bone cuts within the surgical plan (active systems). Robotic arthroplasty has seen rapid adoption globally, particularly in the USA, and is now available for TKA, UKA, and THA. The technology promises greater precision and reproducibility than conventional or navigated surgery, but robust evidence demonstrating superior long-term clinical outcomes and cost-effectiveness is still emerging.

• Classification of robotic systems: Active systems (the robot autonomously executes the surgical plan; the surgeon supervises but does not directly control the cutting; example — ROBODOC, which is now largely obsolete due to high complication rates including nerve injury from rigid registration pins); Semi-active (haptic) systems (the most widely used category; the surgeon controls the instrument but the robotic arm provides haptic resistance at the boundary of the pre-defined resection zone — the surgeon cannot move outside the `bone sculpting` boundary without overriding the system; examples — MAKO SmartRobotics [Stryker] for TKA, UKA, and THA; NAVIO [Smith & Nephew] for UKA and TKA); Passive systems (robotic systems that assist positioning without actively constraining the cut — essentially advanced navigation with robotic assistance)
• Pre-operative CT planning: most robotic platforms (particularly MAKO) require a pre-operative CT scan of the hip and knee (for TKA) or just the knee (for UKA); the CT is used to create a patient-specific 3D bone model; the surgeon plans the implant size, position, and alignment on the 3D model pre-operatively; this plan is uploaded to the robotic system; intraoperatively, the patient`s anatomy is registered to the CT model, and the robotic arm executes the plan
• The MAKO system: currently the most widely used robotic platform globally; uses haptic technology (RIO — Robotic Arm Interactive Orthopedic System); cleared by the FDA for TKA, UKA, and THA; requires pre-operative CT; allows pre-operative implant planning and intraoperative plan modification based on soft tissue balance; the saw or burr is constrained within the pre-planned resection zone by haptic feedback

• UKA is where robotic assistance has the strongest evidence base: conventional UKA has a higher revision rate than conventional TKA in most registries; component malalignment is a major driver of UKA failure (aseptic loosening, wear, and progression of OA are all accelerated by malaligned components); robotic UKA (primarily MAKO and NAVIO platforms) consistently demonstrates superior component positioning accuracy compared to conventional UKA; registry data (AOANJRR, NJR) are now showing lower revision rates for robotic UKA compared to conventional UKA, and robotic UKA revision rates are approaching those of TKA — addressing one of the historical disadvantages of UKA
• MAKO UKA outcomes: Pearle et al. (2010) demonstrated significantly reduced tibial component outliers with MAKO vs conventional UKA; the AOANJRR 2022 report showed robotic UKA had a statistically significant lower revision rate than conventional UKA at 5 years; the NAVIO system has shown equivalent accuracy to MAKO with CT-free planning (using intraoperative surface mapping)
• The `surgeon learning curve` is compressed with robotic UKA: early studies showed that the accuracy advantage of robotic UKA was consistent even in surgeons who performed relatively few UKAs — the robotic system compensates for lower case volume experience; this is potentially important for low-volume surgeons and surgical trainees

• Component positioning accuracy: multiple studies demonstrate that robotic TKA (MAKO) achieves significantly more accurate component positioning than conventional TKA — reducing outliers in coronal alignment, sagittal alignment, and tibial component rotation; the MAKO system`s ability to dynamically assess soft tissue balance intraoperatively (the `knee balance` function — measuring gap symmetry in extension and flexion) and adjust the plan to optimise balance is a unique advantage over conventional and navigated TKA
• Clinical outcomes: the RACER-TKA RCT (Kayani et al., JBJS 2021) — the largest RCT of robotic vs conventional TKA — demonstrated superior functional recovery at 6 weeks (earlier return to straight leg raise, earlier ambulation, lower pain scores) with robotic TKA; no significant difference in clinical outcomes at 1 year; the 2-year outcomes from this trial and others are awaited; PROMs (OKS, KOOS, WOMAC) at 1 year are equivalent in most studies
• Bone preservation: robotic precision allows more conservative bone resection (closer to the planned resection with less inadvertent over-cutting); this may preserve more bone stock for future revision surgery — an important consideration given the increasing number of young patients undergoing TKA
• Kinematic alignment with robotics: the MAKO system enables precise execution of a kinematic alignment plan (personalised component positioning based on native anatomy); robotic assistance improves the accuracy of KA execution vs conventional KA — the robotic system can execute a plan that would be very difficult to reproduce manually with standard jigs

• Cup positioning consistency: the MAKO THA system uses pre-operative CT-based planning and intraoperative haptic guidance to position the acetabular cup within the Lewinnek safe zone (inclination 40° ± 10°; anteversion 15° ± 10°); multiple studies demonstrate that robotic THA achieves cup positioning within the safe zone in >95% of cases, compared to approximately 60–80% with conventional THA; improved cup positioning consistency reduces dislocation risk and edge loading
• Leg length and offset accuracy: robotic THA also enables more precise restoration of leg length and femoral offset — two important determinants of hip biomechanics, abductor function, and long-term implant survival; intraoperative adjustment of the plan based on templated targets is facilitated by the robotic system
• Functional cup positioning and the spine-hip relationship: the MAKO THA system allows pre-operative planning of `functional` cup orientation accounting for the patient`s individual pelvic tilt in standing and sitting (using pre-operative EOS imaging or CT-based spino-pelvic measurement); this is particularly valuable in patients with lumbar spine pathology or prior lumbar fusion — the most challenging group for THA dislocation prevention

• Cost and cost-effectiveness: robotic systems represent a significant capital investment (the MAKO system costs approximately £0.5–1 million); ongoing costs include disposable instruments, maintenance contracts, and the pre-operative CT scan (for MAKO); cost-effectiveness analyses have not consistently demonstrated that the improved outcomes justify the additional cost at the current level of evidence; the cost per quality-adjusted life year (QALY) gained is a subject of ongoing health economic research; NHS adoption has been limited compared to the private sector; the cost argument may change as long-term revision rate data mature (fewer revisions = cost savings)
• The training and adoption curve: robotic systems have a learning curve — both in terms of pre-operative planning and intraoperative workflow; however, the learning curve is typically shorter than for conventional arthroplasty (the robotic system compensates for technical variability); studies show that robotic TKA outcomes are consistent from the first case in a surgeon`s experience, whereas conventional TKA shows a clear learning curve effect on outcomes; this has implications for surgical training and early career surgeons
• Limitations and failure modes: registration accuracy is critical — errors in bone surface registration propagate to all subsequent robotic guidance; CT metal artefact (from prior implants) can degrade the bone model quality; intraoperative plan modification is possible but requires re-registration; the robotic arm itself can malfunction (hardware failure); the surgeon must always be able to complete the procedure safely without the robotic system in the event of failure

• Robotic arthroplasty: active (autonomous execution — ROBODOC, now largely obsolete); semi-active/haptic (surgeon controls but robotic arm constrains within boundary — MAKO, NAVIO); passive (robotic guidance without constraint)
• MAKO: most widely used; Stryker; haptic semi-active; pre-operative CT-based 3D planning; available for UKA, TKA, THA; intraoperative soft tissue balance assessment (knee balance function in TKA)
• Robotic UKA: strongest evidence base; consistent superior component positioning vs conventional; AOANJRR showing lower revision rates for robotic UKA approaching TKA rates; addresses historical UKA disadvantage; learning curve compressed
• Robotic TKA: superior component positioning accuracy; soft tissue balance assessment; RACER-TKA RCT (Kayani 2021) — faster early functional recovery at 6 weeks; equivalent PROMs at 1 year; more conservative bone resection
• Robotic THA: cup within Lewinnek safe zone in >95% (vs ~70% conventional); accurate leg length + offset restoration; functional cup positioning for spine-hip pathology patients; valuable in prior lumbar fusion patients
• Cost: ~£0.5–1 million capital; cost-effectiveness not yet clearly demonstrated; NHS adoption limited; long-term revision savings may change the calculus
• Learning curve: robotic systems shorten the learning curve; consistent outcomes from case 1; advantage for low-volume surgeons and trainees
• Registration accuracy: `garbage in, garbage out` — robotic guidance is only as accurate as bone surface registration; CT artefact from prior metal implants degrades bone model; surgeon must always be able to proceed without robotic system
• Kinematic alignment execution: robotics enables precise execution of KA plans that are difficult to reproduce manually; MAKO + KA is an active area of clinical development