Guidance Techniques in Knee Replacement

Few topics in knee replacement generate as much curiosity, and as much marketing, as the technology used in the operating room. Patients arrive in the office having seen a billboard, a television ad, or a hospital brochure, and they want to know whether a robot will be doing their knee replacement, and whether that means a better result.

The answer has three parts. First, a robot is not doing your knee replacement; your surgeon is. Every commercially available robotic system in routine use today is a precision tool the surgeon operates under direct hands-on control, and in no case is the robot making surgical decisions on its own. Second, these technologies improve one specific thing very reliably: the accuracy with which the implant is placed, relative to a chosen surgical plan. Whether that accuracy translates into a knee that feels, functions, or lasts better than one done with conventional instruments is a separate question, and it is the one the orthopedic community is still working to answer. Third, and most easily missed, the technology executes a plan. What plan it executes depends on the surgeon's choice of alignment philosophy, which is discussed in detail on the companion page on knee alignment techniquesknee alignment techniques.

The Plan and the Execution

That third point is important and needs to be addressed. Alignment is the plan: whether the goal is a straight mechanical axis, a restoration of your own pre-arthritic anatomy, or a position determined by how your ligaments balance. Guidance is the execution: how the surgeon actually directs the bone cuts, positions the components, and assesses the soft tissues to deliver that plan. They are different decisions, and confusing them is a common source of misunderstanding in this area.

Guidance is one of four linked decisions in a knee replacement, alongside the surgical approachsurgical approach, the alignment philosophy, and the implantimplant itself. Each is covered in its own article, and the overview article on knee replacement surgeryknee replacement surgery covers how the four fit together.

There are four guidance techniques1 in current knee replacement practice. Manual instrumentation uses mechanical jigs and positioners to align the cutting guides. Patient-specific instrumentation uses custom guides manufactured in advance from your own imaging. Computer navigation uses real-time tracking to inform the surgeon where the guides align. Robotic assistance uses a robotic platform to guide or constrain the bone preparation directly. Most of the current research attention and marketing is in robotics. However, the traditional instrumented techniques still play an important role in most surgeries.

Manual Instrumentation

Manual instrumentation2 is the technique against which everything else is measured. The surgeon uses mechanical alignment jigs with referencing rods placed inside or outside the femur and the tibia. These jigs position the cutting blocks3 on both bones. The cuts are made with an oscillating saw through slots in those blocks. Ligament balance can be assessed with spacer blocks or tensioners and adjusted by releasing tight structures or by recutting bone.

Mechanical alignment, kinematic alignment, and inverse kinematic alignment are all achievable with instrumentation, provided the instruments and the implant are designed for the task. However, functional alignment requires more data than traditional manual instruments can provide.

Manual instrumentation remains the most widely used approach to knee replacement worldwide; it is what the great majority of the long-term survivorship data in the literature is built on, and its results are durable. When you read that a knee replacement has roughly a ninety percent chance of still functioning at twenty years, that figure comes overwhelmingly from knees implanted with manual instruments.

Patient-Specific Instrumentation

Patient-specific instrumentation4, usually abbreviated PSI, is the one technique on this list whose story is largely over.

The concept was appealing. Weeks before surgery, the patient has a CT or MRI scan. That imaging is used to build a three-dimensional model of the knee, a surgical plan is generated from the model, and single-use cutting guides are manufactured to match the patient's individual bone surfaces. In the operating room the guides seat onto the bone in one position, the surgeon pins them and cuts, and the large mechanical alignment jigs are never needed. Less instrumentation, no rods placed inside the femur, shorter operative time, and in theory a cut positioned exactly where the preoperative plan intended.

There is a genuinely interesting historical detail here. The earliest patient-specific systems, developed in the mid-2000s, were built explicitly around kinematic alignment principles, restoring the patient's own joint surfaces rather than imposing a neutral mechanical axis. That was several years before kinematic alignment gained meaningful acceptance in the wider orthopedic community. The idea arrived before the field was ready to evaluate it, and the technology was ultimately judged on the standards of its era rather than on the philosophy behind it.

The technique's peak was the first half of the 2010s, when every major implant manufacturer offered a patient-specific system and the literature filled with comparative trials. The verdict arrived steadily over the decade that followed. Thienpont and colleagues, in a 2014 meta-analysis and again in a larger 2017 analysis, found that patient-specific guides improved some individual measures of component position while increasing the risk of outliers in others, with the differences in operative time and blood loss too small to justify routine use on their own. In 2023, the American Academy of Orthopaedic Surgeons issued a Strong Recommendation against the use of patient-specific instrumentation, the most forceful negative position it took on any technology in that guideline.

The most complete assessment arrived in January 2026, when a Cochrane review by Zhao and colleagues pooled forty-four randomized trials and 3,664 patients. It found no meaningful differences between patient-specific guides and conventional instruments in implant survival, function, pain, complications, or reoperation, and no meaningful improvement in the precision of overall limb alignment. Compared with computer navigation, patient-specific guides may actually produce alignment less precisely.

Patient-specific instrumentation still has a place, particularly in knees with unusual anatomy or retained hardware where a conventional alignment rod cannot be used. But as a general technique for routine knee replacement, the evidence does not support it.

Computer Navigation

Computer navigation5 preceded robotics by roughly a decade and remains in use today. Small tracker pins are placed in the femur and tibia, the surgeon touches anatomic landmarks with a probe so the computer learns where the bones sit in space, and the system then displays, in real time, the position of the leg, the orientation of the cutting guides, and the accuracy of each cut before and after it is made.

The distinction between navigation and robotics is important because the two are frequently confused. Navigation provides information. It does not physically guide the instrument. The surgeon still positions conventional cutting guides and uses a standard saw, and the computer tells them what they have done and what they are about to do. Robotic assistance goes one step further and adds a physical element that constrains where the cutting tool can go. Navigation tells you where you are. Robotics tells you where you are and helps keep the cut inside the plan.

Across the comparative literature, navigation reduces alignment outliers relative to manual instrumentation, and research analyses that compare all four guidance techniques against one another consistently place navigation second only to robotics for alignment accuracy, and ahead of both patient-specific and conventional instruments. It also gives the surgeon quantitative gap and balance data, which is why navigated systems have been used successfully to execute functional alignment.

What navigation has not shown, across a very large body of evidence accumulated over more than two decades, is a difference in what patients experience. The 2023 AAOS guideline concluded there was no difference in outcomes, function, or pain compared with conventional technique, and issued a Moderate Recommendation to that effect. Long-term studies that include navigated arms alongside robotic and conventional groups have found essentially identical implant survival across all three at ten years.

This history is the most useful thing to know about navigation, because it is the closest available precedent for robotics. A technology that measurably improved the accuracy of the operation, was studied extensively, and did not translate that accuracy into a measurable difference in how patients felt or how long their implants lasted. Whether robotics follows the same trajectory or diverges from it is still being studied, and answering it will take another decade of follow-up.

Robotic Assistance

A modern robotic-assisted system6 is built from three components. First, a way of building a three-dimensional map of your knee, either from a CT scan taken weeks before surgery or from intraoperative mapping in which the surgeon touches bony landmarks with a probe. Second, a planning interface, a screen on which the surgeon can visualize and adjust the size, position, and rotation of the components before and after the bone cuts are made. Third, a physical tool that guides or constrains the bone cuts so they match the plan.

From your perspective the operation is very similar to a conventional one. Depending on the system and the surgeon's technique, the tracker pins may sit within the main incision or in small separate incisions away from it. The surgeon registers the anatomic landmarks with a probe, reviews the plan on screen, and adjusts the component position based on the anatomy, the alignment, and how the soft tissues balance through the range of motion.

Operative times are modestly longer for robotic cases in the published literature, though in experienced hands the difference is small enough to be clinically unimportant. There is a learning curve for the surgeon when adopting this technique. The literature describes operative efficiency improving over roughly seven to eleven cases, while the accuracy of the bone cuts stays consistent from the first case forward.

The Platforms

At least six robotic platforms have meaningful market presence. They differ in how they build their model of your knee and how they guide the cuts. No study has shown definitively that any one of them produces better clinical outcomes than any other.

Mako, from Stryker, has the longest track record and by most accounts the largest installed base; it uses a preoperative CT and a surgeon-guided robotic arm that provides tactile resistance at the boundary of the planned cut. ROSA, from Zimmer Biomet, can work imageless or from converted preoperative X-rays, and uses its arm to position a conventional cutting jig through which the surgeon saws. VELYS, from DePuy Synthes, is imageless and positions a saw within the planned resection plane.

CORI, from Smith and Nephew, uses no arm at all, instead employing a handheld burr that slows or retracts near the planned boundary, giving it the smallest footprint of the major platforms. OMNIBotics, from Corin, mounts its robotically positioned jig directly to the bone and pairs it with an automated ligament tensioning device that generates continuous gap data through the range of motion. TMINI, from THINK Surgical, is a handheld wireless device that drives bone pins along precisely planned planes, with conventional cutting guides then attached to those pins.

Nearly every platform is a closed system, designed to work with a specific implant family from the same manufacturer. The implant carries its own design characteristics, including its articular geometry and the range of alignment its manufacturer has tested and approved, and those characteristics determine which alignment philosophies the surgeon can practically execute. The choice of robot, the choice of implant, and the choice of alignment strategy are therefore not independent decisions. TMINI is the notable exception, cleared for use with implants from nine separate companies, which keeps implant choice independent of the decision to use the robot.

What the Evidence Actually Shows

In 2023 the American Academy of Orthopaedic Surgeons published its updated Clinical Practice Guideline on the Surgical Management of Osteoarthritis of the Knee. It is the most authoritative specialty society document addressing the technologies beyond manual instrumentation.

The guideline grades each conclusion by the quality of the evidence behind it. Strong and Moderate grades produce a recommendation, which directs practice either toward a technology or away from it. A Limited grade produces an option, meaning the evidence was not strong enough to recommend the technology, but neither did it show harm.

Patient-specific instrumentation received a Strong Recommendation against its use. Computer navigation received a Moderate Recommendation, concluding no difference in outcomes, function, or pain compared with conventional technique. Robotic assistance was classified as an Option with Limited strength, on the basis that evidence suggested no significant difference in function, outcomes, or complications in the short term. Robotic assistance therefore occupies a middle position, permitted but not endorsed.

The guideline co-chair noted at publication that mid-term and long-term robotic data had not yet matured and would be available for the next update, anticipated around 2028.

To understand the orthopedic outcome literature it helps to know that we measure knee function and satisfaction with validated scoring systems like WOMAC, KOOS, and the Forgotten Joint Score (FJS). A difference between two groups on these scales can be statistically significant, meaning unlikely to be due to chance, but still too small for a patient to feel. The threshold at which a difference becomes noticeable to a real person is called the minimal clinically important difference, roughly nine to twelve points for WOMAC and eight to ten for KOOS subscales. A great deal of what you will read about these technologies reports differences that clear statistical significance and fall well below that threshold.

Where the evidence is strong. Robotic assistance improves the accuracy of implant alignment and reduces alignment outliers, defined as cases deviating more than three degrees from the plan. A 2025 meta-analysis by Mostafa and colleagues pooling twenty-one randomized trials and 2,692 patients found the risk of alignment outliers reduced by roughly two-thirds. A separate 2025 systematic review spanning two decades of randomized trials found a ten to twenty-four percent reduction, regardless of whether the surgeon used mechanical or personalized alignment. Research analyses comparing all four guidance techniques rank robotics first for alignment accuracy, with navigation close behind. This finding is reproduced consistently across authors, systems, and populations.

Where the evidence is modest. Robotic assistance appears to produce small short-term advantages in the first weeks. Systematic reviews have reported shorter hospital stays, lower early pain scores, and faster achievement of functional milestones, and a 2023 meta-analysis by Hoeffel and colleagues found a fourteen percent reduction in length of stay and a greater likelihood of discharge directly home. These findings carry one large caveat: modern recovery protocols, multimodal pain management, and outpatient pathways have independently improved early recovery for all knee replacement patients regardless of technology. Separating the effect of the robot from the effect of the surrounding care is genuinely difficult.

Where the evidence is weak or absent. Beyond the first few weeks, the advantages largely disappear. A 2024 meta-analysis by Fu and colleagues found that functional advantages visible at three months had diminished by six months and were no longer significant thereafter. A 2024 systematic review by Hoveidaei and colleagues found no significant difference in patient satisfaction, ninety-five percent versus ninety-one percent.

Regarding implant survival, the most important long-term question, a 2025 analysis of the American Joint Replacement Registry found that navigation or robotics at the time of primary surgery did not reduce the need for revision at five years. A ten-year single-institution study and a 2025 meta-analysis of twenty comparative studies both found survivorship essentially identical between robotic and conventional knees.

The largest cross-technique analysis available reinforces this. Zheng and colleagues, pooling 112 randomized trials and nearly fifteen thousand knee replacements across all four guidance techniques, ranked robotics first for alignment accuracy and found no difference among the four techniques in most clinical outcomes, at either short-term or medium-to-long-term follow-up, including complications.

Complications. Overall complication rates are broadly comparable, but the technologies introduce a small number of risks that do not exist with manual instruments. Tracker pin sites placed through separate skin incisions can cause pain, drainage, infection, or rarely a fracture through the pin hole, a risk largely eliminated when pins are placed within the main incision. A 2022 analysis of the FDA adverse event database identified unexpected robotic arm movement, retained foreign objects, and cases converted to manual technique mid-procedure because of equipment failure.

A 2026 population-based study from Ontario examined the adoption of robotic knee replacement across an entire health system. Among 74,359 knee replacements at 62 hospitals, 1,613 were robotic. After matching, major surgical complications within one year occurred in 2.0 percent of robotic cases against 1.0 percent of conventional ones, an absolute difference of about one per hundred patients that the authors described as modest. They attributed it to both learning curve effects and risks intrinsic to current-generation platforms. The study did not identify which robotic systems were used.

The Alignment Variable

There is a subtlety in all of this that is usually missing from the conversation, and it returns to the distinction between the plan and the execution.

Almost every study comparing robotic to conventional knee replacement holds the alignment philosophy constant in both arms, typically mechanical alignment. The question those studies were designed to answer is whether executing a mechanical alignment plan more precisely produces a different result than executing the same plan with conventional instruments. The literature has answered that reasonably clearly: the precision is better, the patient-level result is similar. But that is a different question from whether the alignment philosophy itself influences the result, and a growing body of evidence suggests it does.

A 2022 head-to-head study from the Hospital for Special Surgery compared two hundred patients, half kinematically aligned and half mechanically aligned, using the same robotic system and the same implant, varying only the alignment target. The kinematic group reported lower pain scores in the first six weeks and significantly higher Forgotten Joint Scores at one and two years. A 2025 randomized trial comparing mechanical and functional alignment on the same robotic platform found that mechanical alignment required a soft-tissue release in about sixty-five percent of cases against sixteen percent for functional alignment, a substantially different surgical experience driven entirely by the alignment choice, though patient-reported outcomes at two years were similar between the groups.

Studies that isolate alignment as the variable are a growing part of the literature. Recent meta-analyses comparing alignment philosophies have generally found the differences real but small at the population level, often at or below the minimal clinically important difference. Neither the alignment question nor the technology question has yet produced a finding dramatic enough to reshape how most knees are replaced.

What This Means for You as a Patient

The guidance technique your surgeon uses is one piece of a larger picture, and on the current evidence it is not the piece that determines your result. Robotics reliably makes the bone cuts more accurate. Navigation does so as well, to a slightly lesser degree. Patient-specific instrumentation is not generally recommended other than for specific uses. Manual instrumentation, in experienced hands, produces durable results.

If your surgeon uses robotic assistance and is experienced with it, that is a reasonable choice. If your surgeon uses instruments and has excellent results, that is also a reasonable choice. Neither should be the primary basis for deciding where to have your surgery. Surgeon experience, surgical judgment, implant selection, alignment philosophy, and the quality of your perioperative care all contribute to the outcome.

When you meet with your surgeon, these questions are worth asking:

What guidance technique will you use for my knee, and why did you choose it for my case? Your surgeon's reasoning tells you more about the likely quality of your care than the specific technology does.

What alignment philosophy will you use, and how does that fit with the implant and the tools you have chosen? This is the question most patients do not know to ask, and it may be the most important one on this list. A surgeon who can explain how mechanical, kinematic, or functional alignment applies to your anatomy, and how the implant works within that philosophy, is a surgeon thinking fundamentally about the operation.

How many knee replacements have you personally performed with this system? The workflow learning curve for robotic technology is short, roughly seven to eleven cases, and cut accuracy tends to be consistent from the first case. The Ontario data suggest the curve for avoiding complications may run longer than that. Experience still matters.

Will the procedure require a preoperative CT or MRI scan? Some systems do, some do not. If one is needed, your surgeon or hospital can explain the timing, the radiation exposure, and any additional cost.

What happens if the technology has a technical problem during my surgery? Every surgeon performing robotic or navigated knee replacement can convert to conventional technique if the equipment fails. It is a reasonable question to ask.

The research has told us clearly that robotics makes cuts more accurate. It has not yet told us clearly whether that accuracy changes how your knee feels five or ten years from now, and a growing line of evidence suggests that the alignment philosophy your surgeon applies, and the match between that philosophy and the implant they choose, may matter as much as the tool used to execute it.

References

Bellemans, Vandenneucker, and Vanlauwe (2007): Robot-assisted total knee arthroplasty. Clinical Orthopaedics and Related Research 2007;464:111-116. A foundational review documenting the early experience with active robotic systems and the clinical concerns that led to their withdrawal.

Thienpont, Schwab, and Fennema (2014): A systematic review and meta-analysis of patient-specific instrumentation for improving alignment of the components in total knee replacement. Bone and Joint Journal 2014;96-B(8):1052-1061. A meta-analysis of randomized controlled trials and cohort studies examining the effect of patient-specific instruments on radiological outcomes including mechanical axis alignment and component malalignment at a threshold of more than three degrees from neutral.

Roche (2015): Robotic-assisted unicompartmental knee arthroplasty: the MAKO experience. Orthopedic Clinics of North America 2015;46(1):125-131. An early clinical description of the Mako system, documenting its initial application in partial knee replacement before expansion to total knee arthroplasty.

Thienpont, Schwab, and Fennema (2017): Efficacy of patient-specific instruments in total knee arthroplasty: a systematic review and meta-analysis. Journal of Bone and Joint Surgery (American) 2017;99(6):521-530. A larger follow-up meta-analysis finding that patient-specific instrumentation improved the accuracy of femoral component alignment and global mechanical alignment but at the cost of an increased risk of tibial component outliers, with differences in operative time and blood loss described by the authors as minimal and not in themselves a substantial justification for routine use.

Kayani, Konan, Tahmassebi, Pietrzak, and Haddad (2018): Robotic-arm assisted total knee arthroplasty is associated with improved early functional recovery and reduced time to hospital discharge compared with conventional jig-based total knee arthroplasty: a prospective cohort study. The Bone and Joint Journal 2018;100-B(7):930-937. A prospective comparison of forty consecutive jig-based and forty consecutive robotic-arm assisted knee replacements by a single surgeon, showing reduced postoperative pain, decreased analgesia requirements, and faster achievement of functional milestones with robotic assistance.

Kayani, Konan, Pietrzak, and Haddad (2018): Iatrogenic bone and soft tissue trauma in robotic-arm assisted total knee arthroplasty compared with conventional jig-based total knee arthroplasty: a prospective cohort study and validation of a new classification system. The Journal of Arthroplasty 2018;33(8):2496-2501. A comparative study documenting differences in iatrogenic tissue injury between robotic-assisted and conventional knee replacement, and introducing the MASTI classification system for macroscopic soft tissue injury.

Kayani, Konan, Huq, Tahmassebi, and Haddad (2019): Robotic-arm assisted total knee arthroplasty has a learning curve of seven cases for integration into the surgical workflow but no learning curve effect for accuracy of implant positioning. Knee Surgery, Sports Traumatology, Arthroscopy 2019;27(4):1132-1141. A prospective study of sixty consecutive conventional and sixty consecutive robotic-assisted knee replacements establishing that the operative-time learning curve plateaus after approximately seven cases, while bone cut accuracy is consistent from the first case.

Kayani and Haddad (2019): Robotic total knee arthroplasty: clinical outcomes and directions for future research. Bone and Joint Research 2019;8(10):438-442. An editorial overview framing the state of robotic knee arthroplasty and identifying the key evidence gaps that future research needs to address.

Batailler, Fernandez, Swan, and colleagues (2021): MAKO CT-based robotic arm-assisted system is a reliable procedure for total knee arthroplasty: a systematic review. Knee Surgery, Sports Traumatology, Arthroscopy 2021;29(11):3585-3598. A PRISMA systematic review of twenty-six studies of Mako knee replacement outcomes reporting shorter hospital stays, lower pain scores, and improved early functional metrics compared with conventional technique.

Elbuluk, Jerabek, Suhardi, Sculco, Ast, and Vigdorchik (2022): Head-to-head comparison of kinematic alignment versus mechanical alignment for total knee arthroplasty. The Journal of Arthroplasty 2022;37(8S):S849-S851. A 1:1 matched study of two hundred patients from the Hospital for Special Surgery in which the same robotic technology and implant were used, varying only the alignment target. Kinematic alignment was associated with lower visual analog pain scores during the first six weeks and significantly higher Forgotten Joint Scores at one and two years, demonstrating that alignment philosophy can influence patient-reported outcomes independently of the technology used to execute it.

Hua and Salcedo (2022): Cost-effectiveness analysis of robotic-arm assisted total knee arthroplasty. PLoS ONE 2022;17(11):e0277980. A Markov decision-analytic model concluding that robotic assistance is cost-effective at a fifty thousand dollar per quality-adjusted life year threshold only at centers performing more than forty-nine robotic cases annually.

Kort, Stirling, Pilot, and Müller (2022): Robot-assisted knee arthroplasty improves component positioning and alignment, but results are inconclusive on whether it improves clinical scores or reduces complications and revisions: a systematic overview of meta-analyses. Knee Surgery, Sports Traumatology, Arthroscopy 2022;30(8):2639-2653. An umbrella review of ten meta-analyses cautioning that alignment improvements have not been clearly shown to translate into better clinical outcomes, with notable methodological concerns about the quality of the underlying literature.

Lei, Liu, Chen, Feng, Yang, and Guo (2022): Navigation and robotics improved alignment compared with PSI and conventional instrument, while clinical outcomes were similar in TKA: a network meta-analysis. Knee Surgery, Sports Traumatology, Arthroscopy 2022;30(3):721-733. A PRISMA network meta-analysis of seventy-three randomized controlled trials and 4,209 knee replacements finding that navigation and robotics significantly reduced malalignment and malposition compared with patient-specific and conventional instruments, with robotics ranking first for alignment accuracy and navigation second, while clinical outcomes were similar across the four techniques.

Pagani, Menendez, Moverman, Puzzitiello, and Gordon (2022): Adverse events associated with robotic-assisted joint arthroplasty: an analysis of the US Food and Drug Administration MAUDE database. The Journal of Arthroplasty 2022;37(8):1526-1533. An analysis of 263 adverse event reports identifying equipment-related incidents specific to robotic-assisted arthroplasty. Unexpected robotic arm movement was the most frequent finding in knee cases, and thirty-one cases required conversion to manual technique.

Vermue, Luyckx, Winnock de Grave, and colleagues (2022): Robot-assisted total knee arthroplasty is associated with a learning curve for surgical time but not for component alignment, limb alignment and gap balancing. Knee Surgery, Sports Traumatology, Arthroscopy 2022;30(2):593-602. An independent confirmation across six surgeons that operative efficiency requires a learning period, modulated by surgical volume, while component alignment and gap balancing accuracy remain consistent from the outset.

Zhang, Ndou, Ng, and colleagues (2022): Robotic-arm assisted total knee arthroplasty is associated with improved accuracy and patient reported outcomes: a systematic review and meta-analysis. Knee Surgery, Sports Traumatology, Arthroscopy 2022;30(8):2677-2695. A systematic review and meta-analysis of sixteen studies examining accuracy and patient-reported outcomes, including a learning-curve sub-analysis finding a range of seven to eleven cases for operative time with no learning curve for component positioning accuracy.

Griffin, Davis, Parsons, and colleagues (2023): Robotic Arthroplasty Clinical and cost Effectiveness Randomised controlled trial (RACER-knee): a study protocol. BMJ Open 2023;13(6):e068255. The published protocol for the RACER-Knee trial, a 332-patient participant- and assessor-blinded randomized controlled trial comparing Mako robotic-assisted knee replacement with conventional technique, using sham incisions and blinded operation notes, with follow-up planned to ten years and an embedded cost-effectiveness analysis.

Hoeffel, Goldstein, Intwala, and colleagues (2023): Systematic review and meta-analysis of economic and healthcare resource utilization outcomes for robotic versus manual total knee arthroplasty. Journal of Robotic Surgery 2023;17(6):2899-2910. A meta-analysis of fifty studies finding a fourteen percent reduction in hospital length of stay, a seventy-four percent greater likelihood of discharge to home, and a seventeen percent lower likelihood of ninety-day readmission with robotic-assisted knee replacement, along with modestly longer operative times.

Lee, Kim, Lee, Song, and Seon (2023): No difference in clinical outcomes and survivorship for robotic, navigational, and conventional primary total knee arthroplasty with a minimum follow-up of 10 years. Clinics in Orthopedic Surgery 2023;15(1):82-91. A single-institution study with minimum ten-year follow-up showing satisfactory and essentially identical survival rates across robotic, navigational, and conventional knee replacement groups.

Nogalo, Meena, Abermann, and Fink (2023): Complications and downsides of the robotic total knee arthroplasty: a systematic review. Knee Surgery, Sports Traumatology, Arthroscopy 2023;31(3):736-750. A PRISMA systematic review of twenty-one studies cataloging the specific complication profile of robotic knee replacement, including pin-hole fracture, pin-related infection, iatrogenic soft tissue and bony injury, and intraoperative abandonment of the robotic workflow.

Srivastava and the Surgical Management of Osteoarthritis of the Knee Work Group (2023): American Academy of Orthopaedic Surgeons clinical practice guideline summary of surgical management of osteoarthritis of the knee. Journal of the American Academy of Orthopaedic Surgeons 2023;31(24):1211-1220. The published journal summary of the AAOS SMOAK2 guideline, containing sixteen recommendations and seven options, and the citable scholarly form of the guideline's conclusions on patient-specific instrumentation, computer navigation, and robotic assistance.

Walgrave and Oussedik (2023): Comparative assessment of current robotic-assisted systems in primary total knee arthroplasty. Bone and Joint Open 2023;4(1):13-18. The most comprehensive comparative review of the major robotic platforms available for total knee replacement, describing the mechanical and workflow differences between systems.

Zhang, Chen, Tay, and colleagues (2023): Cost-effectiveness of robot-assisted total knee arthroplasty: a Markov decision analysis. The Journal of Arthroplasty 2023;38(8):1434-1437. A decision analysis using a pay-per-use contract model reaching the opposite conclusion to Hua and Salcedo, finding that robotic-assisted knee replacement was not cost-effective under its modeling assumptions.

Daoub, Qayum, Patel, Selim, and Banerjee (2024): Robotic assisted versus conventional total knee arthroplasty: a systematic review and meta-analysis of randomised controlled trials. Journal of Robotic Surgery 2024;18(1):364. A meta-analysis of nine randomized controlled trials finding significant advantages for robotic assistance in mechanical alignment, WOMAC score, and femoral coronal plane outliers, with no difference in functional Knee Society or Hospital for Special Surgery scores.

Fu, She, Jin, and colleagues (2024): Comparison of robotic-assisted total knee arthroplasty: an updated systematic review and meta-analysis. Journal of Robotic Surgery 2024;18(1):292. An updated meta-analysis showing that early functional score advantages diminish by six months and are no longer significant at longer follow-up, with no long-term functional superiority.

Hoveidaei, Esmaeili, and colleagues (2024): Robotic assisted total knee arthroplasty is not associated with increased patient satisfaction: a systematic review and meta-analysis. International Orthopaedics 2024;48(7):1771-1784. A pooled analysis of seventeen articles and 1,148 patients finding no statistically significant difference in patient satisfaction between robotic-assisted and conventional knee replacement, ninety-five percent against ninety-one percent.

Sah (2024): In my experience: the use and value of the novel, handheld, wireless, implant-agnostic robotic. Journal of Orthopaedic Experience and Innovation 2024;5(2). DOI 10.60118/001c.125418. A surgeon's perspective on the TMINI platform describing the practical workflow advantages of a handheld, sterile, wireless robotic device and the implications of an open implant library for matching alignment philosophy with implant design.

Zheng, Li, Yuan, Geng, and Tian (2024): Comparison of the accuracy and efficacy of different assistive techniques in primary total knee arthroplasty: a network meta-analysis. Journal of Experimental Orthopaedics 2024;11(4):e70098. A Bayesian network meta-analysis of 112 randomized controlled trials and 14,968 total knee arthroplasties comparing conventional instruments, computer-assisted navigation, patient-specific instruments, and robot-assisted systems. Robotic assistance ranked highest for accurate mechanical axis alignment and component position, followed by navigation, patient-specific instruments, and conventional instruments. No difference was observed among the four techniques in most clinical outcomes at short-term or medium-and-long-term follow-up, including complications.

Alton, Severson, Ford, Leslie, and Lesko (2025): VELYS robotic-assisted total knee arthroplasty: enhanced accuracy and comparable early outcomes versus manual instrumentation during adoption. Journal of Experimental Orthopaedics 2025;12(1):e70163. A multicenter prospective non-randomized cohort study at five United States sites in which the robotic procedures were the first performed at each site, representing the adoption phase. Hip-knee-ankle accuracy was non-inferior to manual instrumentation and individual implant angle accuracy was significantly improved, with early advantages equalizing by one year. The paper describes the VELYS mechanism as a semi-active system that positions the saw blade in the plane of the planned resection and cuts power to the saw if the blade is forced outside that plane.

Boutros, Awad, Mouawad, and Mansour (2025): Kinematic versus mechanically aligned total knee arthroplasty: a meta-analysis of randomized controlled trials. The Journal of Knee Surgery 2025, online ahead of print. A systematic review of twenty-one randomized controlled trials finding that kinematic alignment produced statistically significant but small improvements in early function, joint awareness, and patient satisfaction compared with mechanical alignment, with differences generally at or below the minimal clinically important difference and no difference in complication or revision rates.

Chen, Loke, Lim, and Tan (2025): Survivorship in robotic total knee arthroplasty compared with conventional total knee arthroplasty: a systematic review and meta-analysis. Arthroplasty 2025;7(1):21. A random-effects meta-analysis of twenty comparative studies and 5,403 patients finding no significant difference in pooled implant survivorship at any time point, with ten-year survivorship of 96.9 percent for conventional and 97.8 percent for robotic knee replacement.

García-Sanz, Sosa-Reina, Jaén-Crespo, and colleagues (2025): Redefining knee arthroplasty: does robotic assistance improve outcomes beyond alignment? An evidence-based umbrella review. Journal of Clinical Medicine 2025;14(8):2588. An umbrella review of ten systematic reviews concluding that while robotic assistance improves surgical precision and may offer short-term benefits, long-term superiority over conventional technique remains unproven, with cost and operative time limiting adoption.

Mostafa, Malik, and colleagues (2025): Robotic-assisted versus conventional total knee arthroplasty: a systematic review and meta-analysis of alignment accuracy and clinical outcomes. Annals of Medicine and Surgery 2025;87(2):867-879. A meta-analysis of twenty-one randomized controlled trials involving 2,692 patients, finding that robotic-assisted knee replacement significantly reduced mechanical alignment outliers compared with conventional instrumentation.

Pius, Sporer, Sterling, and colleagues (2025): Navigated and robotic total knee arthroplasty do not confer improved 5-year survivorship compared to conventional total knee arthroplasty: an analysis from the American Joint Replacement Registry. The Journal of Arthroplasty 2025;40(7S1):S130-S139. A large registry analysis of Medicare patients aged sixty-five and older finding that navigation and robotics at the time of primary knee replacement did not reduce the need for revision at five years.

Sacco, Tecame, Lalevée, and colleagues (2025): Robotic vs. conventional total knee arthroplasty over two decades: evolving trends toward personalised alignment without significant clinical superiority in predominantly mild varus deformity. A systematic review of RCTs. Journal of Experimental Orthopaedics 2025;12(4):e70452. A PRISMA systematic review spanning two decades of randomized trials, finding that robotic assistance reduced alignment outliers by ten to twenty-four percent compared with conventional technique regardless of the alignment strategy used, without corresponding clinical superiority.

Young, Tay, Kawaguchi, and colleagues (2025): The John N. Insall Award: functional versus mechanical alignment in total knee arthroplasty: a randomized controlled trial. The Journal of Arthroplasty 2025;40(7S1):S20-S30.e2. A prospective randomized controlled trial of 244 patients using the same robotic system and implant, in which mechanical alignment required a soft-tissue release in approximately sixty-five percent of cases compared with approximately sixteen percent for functional alignment, illustrating how profoundly the alignment philosophy changes the surgical experience even when the technology is held constant. At two years the primary outcome and most patient-reported outcomes were similar between groups.

Böhle, Bauer, Woiczinski, and Matziolis (2026): Are current total knee arthroplasty implants tested and approved for personalised alignment? Knee Surgery, Sports Traumatology, Arthroscopy 2026;34(1):174-182. An independent academic study that systematically contacted implant manufacturers regarding their regulatory-approved deviation tolerances, with eleven of thirteen responding. It documents that the range of alignment each implant is tested and approved for varies substantially between systems, which constrains which alignment philosophies can be executed with a given implant.

Morrison, Hall, Clement, Walmsley, Gee, and Clarke (2026): Use of the VELYS Robotic-Assisted Solution in knee arthroplasty: a scoping review. Journal of Experimental Orthopaedics 2026;13(2):e70726. A PRISMA-ScR scoping review of the evidence base for the VELYS platform, noting that unlike systems employing formal haptic boundaries, VELYS achieves protection of surrounding soft tissue structures through visual feedback to the surgeon while controlling the resection plane for accuracy.

Pincus, Ekhtiari, Lex, Schemitsch, Ruangsomboon, Paterson, and Ravi (2026): Association between adoption of robotic total knee arthroplasty in Canada and major surgical complications. The Journal of Arthroplasty 2026;41(7):S141-S146. DOI 10.1016/j.arth.2026.03.077. Published in the Proceedings of the Knee Society 2025. A population-based propensity score-matched cohort study using Ontario health administrative data covering 74,359 primary knee replacements performed by 345 surgeons at 62 hospitals between April 2019 and October 2023, of which 1,613 were robotic-assisted. In the matched cohort of 1,584 robotic and 6,218 conventional cases, major surgical complications within one year occurred in 2.0 percent against 1.0 percent, an absolute risk difference of 0.99 percent and a hazard ratio of 2.01. Secondary outcomes were individually non-significant and interpreted as exploratory. The authors attribute the finding to a combination of learning-curve effects and risks intrinsic to current-generation robotic platforms, and note that implant types and specific robotic platforms were not identified in the data.

Zhao, Jefferies, Marimuthu, Kumar, Chen, Harris, and MacDessi (2026): Patient-specific cutting guides for total knee arthroplasty. Cochrane Database of Systematic Reviews 2026;1(1):CD012589. A Cochrane review of forty-four randomized controlled trials and 3,664 participants finding low-certainty evidence of no meaningful differences between patient-specific cutting guides and either conventional instrumentation or computer-assisted navigation with regard to implant survival, reoperation rate, adverse events, function, or pain, and no meaningful improvement in the precision of overall limb alignment. Compared with navigation, patient-specific guides may result in worse alignment precision.