References

Abdelfadeel W. CT planning studies for robotic total knee arthroplasty. Bone Joint J.. 2020; 102-B:(6)79-84 https://doi.org/10.1302/0301-620X.102B6.BJJ-2019-1498.R1

Banger MS, Johnston WD, Razii N Robotic arm-assisted bi-unicompartmental knee arthroplasty maintains natural knee joint anatomy compared with total knee arthroplasty: a prospective randomized controlled trial. Bone Joint J.. 2020; 102-B:(11)1511-1518 https://doi.org/10.1302/0301-620X.102B11.BJJ-2020-1166.R1

Bautista M, Manrique J, Hozack WJ. Robotics in total knee arthroplasty. J Knee Surg.. 2019; 32:(07)600-606 https://doi.org/10.1055/s-0039-1681053

Begum FA, Kayani B, Morgan SDJ, Ahmed SS, Singh S, Haddad FS. Robotic technology: current concepts, operative techniques and emerging uses in unicompartmental knee arthroplasty. EFORT Open Rev.. 2020; 5:(5)312-318 https://doi.org/10.1302/2058-5241.5.190089

Burger JA, Kleeblad LJ, Laas N, Pearle AD. Mid-term survivorship and patient-reported outcomes of robotic-arm assisted partial knee arthroplasty. Bone Joint J.. 2020; 102-B:(1)108-116 https://doi.org/10.1302/0301-620X.102B1.BJJ-2019-0510.R1

Calatayud J, Casaña J, Ezzatvar Y, Jakobsen MD, Sundstrup E, Andersen LL. High-intensity preoperative training improves physical and functional recovery in the early post-operative periods after total knee arthroplasty: a randomized controlled trial. Knee Surg Sports Traumatol Arthrosc.. 2017; 25:(9)2864-2872 https://doi.org/10.1007/s00167-016-3985-5

Coon TM. Integrating robotic technology into the operating room. Am J Orthop (Belle Mead NJ).. 2009; 38:(2)7-9

Fortin PR, Clarke AE, Joseph L Outcomes of total hip and knee replacement: preoperative functional status predicts outcomes at six months after surgery. Arthritis Rheum.. 1999; 42:(8)1722-1728 https://doi.org/10.1002/1529-0131(199908)42:8<1722::AID-ANR22>3.0.CO;2-R

Grau L, Lingamfelter M, Ponzio D Robotic arm assisted total knee arthroplasty workflow optimization, operative times and learning curve. Arthroplast Today.. 2019; 5:(4)465-470 https://doi.org/10.1016/j.artd.2019.04.007

Gwynne-Jones DP, Martin G, Crane C. Enhanced recovery after surgery for hip and knee replacements. Orthop Nurs.. 2017; 36:(3)203-210 https://doi.org/10.1097/NOR.0000000000000351

Haddad FS. What is the optimal level of expectation?. Bone Joint J. 2017; 99-B:(9)1121-1122 https://doi.org/10.1302/0301-620X.99B9.BJJ-2017-0938

Haddad FS, Horriat S. Robotic and other enhanced technologies. Bone Joint J.. 2019; 101-B:(12)1469-1471 https://doi.org/10.1302/0301-620X.100B12.BJJ-2019-0900

Jacofsky DJ, Allen M. Robotics in arthroplasty: a comprehensive review. J Arthroplasty.. 2016; 31:(10)2353-2363 https://doi.org/10.1016/j.arth.2016.05.026

Kayani B, Haddad FS. Robotic total knee arthroplasty: clinical outcomes and directions for future research. Bone Joint Res.. 2019; 8:(10)438-442 https://doi.org/10.1302/2046-3758.810.BJR-2019-0175

Kayani B, Konan S, Pietrzak JRT, Haddad FS. Iatrogenic bone and soft tissue trauma in robotic-arm assisted total knee arthroplasty compared with conventional jig-based total knee arthroplasty: a prospective cohort and validation of a new classification System. J Arthroplasty.. 2018a; 33:(8)2496-2501 https://doi.org/10.1016/j.arth.2018.03.042

Kayani B, Konan S, Tahmassebi J, Pietrzak JRT, Haddad FS. 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. Bone Joint J.. 2018b; 100-B:(7)930-937 https://doi.org/10.1302/0301-620X.100B7.BJJ-2017-1449.R1

Kayani B, Konan S, Ayuob A, Onochie E, Al-Jabri T, Haddad FS. Robotic technology in total knee arthroplasty: a systematic review. EFORT Open Rev.. 2019a; 4:(10)611-617 https://doi.org/10.1302/2058-5241.4.190022

Kayani B, Konan S, Tahmassebi J, Rowan FE, Haddad FS. An assessment of early functional rehabilitation and hospital discharge in conventional versus robotic-arm assisted unicompartmental knee arthroplasty. Bone Joint J.. 2019b; 101-B:(1)24-33 https://doi.org/10.1302/0301-620X.101B1.BJJ-2018-0564.R2

Kayani B, Konan S, Thakrar RR Assuring the long-term total joint arthroplasty: a triad of variables. Bone Joint J.. 2019; 101-B:(1)11-18 https://doi.org/10.1302/0301-620X.101B1.BJJ-2018-0377.R1

Kayani B, Konan S, Huq SS 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 Surg Sports Traumatol Arthrosc.. 2019d; 27:(4)1132-1141 https://doi.org/10.1007/s00167-018-5138-5

Kayani B, Konan S, Tahmassebi J, Rowan FE, Haddad FS. Infographic: robotics are guiding arthroplasties to less pain and faster recovery. Bone Joint J.. 2019e; 101-B:(1)22-23 https://doi.org/10.1302/0301-620X.101B1.BJJ-2018-1530

Kayani B, Konan S, Horriat S, Ibrahim MS, Haddad FS. Posterior cruciate ligament resection in total knee arthroplasty: the effect on flexion-extension gaps, mediolateral laxity, and fixed flexion deformity. Bone Joint J.. 2019f; 101-B:(10)1230-1237 https://doi.org/10.1302/0301-620X.101B10.BJJ-2018-1428.R2

Kayani B, Konan S, Tahmassebi J, Oussedik S, Moriarty PD, Haddad FS. A prospective double-blinded randomised control trial comparing robotic arm-assisted functionally aligned total knee arthroplasty versus robotic arm-assisted mechanically aligned total knee arthroplasty. Trials.. 2020a; 21:(1) https://doi.org/10.1186/s13063-020-4123-8

Kayani B, Konan S, Tahmassebi J, Ayuob A, Haddad FS. Computerised tomography-based planning with conventional total hip arthroplasty versus robotic-arm assisted total hip arthroplasty: study protocol for a prospective randomised controlled trial. Trials.. 2020b; 21:(1) https://doi.org/10.1186/s13063-020-04702-7

Kayani B, Konan S, Tahmassebi J, Ayuob A, Moriarty PD, Haddad FS. Robotic-arm assisted medial unicondylar knee arthroplasty versus jig-based unicompartmental knee arthroplasty with navigation control: study protocol for a prospective randomised controlled trial. Trials.. 2020c; 21:(1) https://doi.org/10.1186/s13063-020-04631-5

Kaye AD, Urman RD, Cornett EM Enhanced recovery pathways in orthopedic surgery. J Anaesthesiol Clin Pharmacol.. 2019; 35:S35-S39 https://doi.org/10.4103/joacp.JOACP_35_18

Khamiso R., Momin S, Panjwani N. Involvement of preoperative nurse: a strategy for optimization of risk factors before hospitalization for elective orthopedic surgeries at a tertiary care hospital in Karachi, Pakistan. i-manager's Journal on Nursing.. 2019; 9:(1) https://doi.org/10.26634/jnur.9.1.15392

Lang JE, Mannava S, Floyd AJ Robotic systems in orthopaedic surgery. J Bone Joint Surg Br.. 2011; 93:(10)1296-1299 https://doi.org/10.1302/0301-620X.93B10.27418

Liow MHL, Chin PL, Pang HN, Tay DKJ, Yeo SJ. THINK surgical TSolution-One ® (Robodoc) total knee arthroplasty. SICOT J.. 2017a; 3 https://doi.org/10.1051/sicotj/2017052

Liow MHL, Goh GSH, Wong MK, Chin PL, Tay DKJ, Yeo SJ. Robotic-assisted total knee arthroplasty may lead to improvement in quality-of-life measures: a 2-year follow-up of a prospective randomized trial. Knee Surg Sports Traumatol Arthrosc.. 2017b; 25:(9)2942-2951 https://doi.org/10.1007/s00167-016-4076-3

Lonner JH, Fillingham YA. Pros and cons: a balanced view of robotics in knee arthroplasty. J Arthroplasty.. 2018; 33:(7)2007-2013 https://doi.org/10.1016/j.arth.2018.03.056

McDonnell JM, Ahern DP, Ó Doinn T Surgeon proficiency in robot-assisted spine surgery. Bone Joint J.. 2020; 102-B:(5)568-572 https://doi.org/10.1302/0301-620X.102B5.BJJ-2019-1392.R2

Mont MA, Cool C, Gregory D, Coppolecchia A, Sodhi N, Jacofsky DJ. Health care utilization and payer cost analysis of robotic arm assisted total knee arthroplasty at 30, 60, and 90 days. J Knee Surg.. 2021; 34:(3)328-337 https://doi.org/10.1055/s-0039-1695741

Moschetti WE, Konopka JF, Rubash HE, Genuario JW. Can robot-assisted unicompartmental knee arthroplasty be cost-effective? A Markov Decision Analysis. J Arthroplasty.. 2016; 31:(4)759-765 https://doi.org/10.1016/j.arth.2015.10.018

Moyer R, Ikert K, Long K, Marsh J. The value of preoperative exercise and education for patients undergoing total hip and knee arthroplasty. JBJS Rev.. 2017; 5:(12) https://doi.org/10.2106/JBJS.RVW.17.00015

Oussedik S, Abdel MP, Cross MB, Haddad FS. Alignment and fixation in total knee arthroplasty. Bone Joint J.. 2015; 97-B:(10)16-19 https://doi.org/10.1302/0301-620X.97B10.36499

Oussedik S, Abdel MP, Victor J, Pagnano MW, Haddad FS. Alignment in total knee arthroplasty. Bone Joint J.. 2020; 102-B:(3)276-279 https://doi.org/10.1302/0301-620X.102B3.BJJ-2019-1729

Robinson PG, Clement ND, Hamilton D, Blyth MJG, Haddad FS, Patton JT. A systematic review of robotic-assisted unicompartmental knee arthroplasty. Bone Joint J.. 2019; 101-B:(7)838-847 https://doi.org/10.1302/0301-620X.101B7.BJJ-2018-1317.R1

Sau-Man Conny C, Wan-Yim I. The effectiveness of nurse-led preoperative assessment clinics for patients receiving elective orthopaedic surgery: A Systematic Review. J Perianesth Nurs.. 2016; 31:(6)465-474 https://doi.org/10.1016/j.jopan.2014.08.147

St Mart JP, de Steiger RN, Cuthbert A, Donnelly W. The three-year survivorship of robotically assisted versus non-robotically assisted unicompartmental knee arthroplasty. Bone Joint J.. 2020; 102-B:(3)319-328 https://doi.org/10.1302/0301-620X.102B3.BJJ-2019-0713.R1

Stambough JB, Nunley RM, Curry MC, Steger-May K, Clohisy JC. Rapid recovery protocols for primary total hip arthroplasty can safely reduce length of stay without increasing readmissions. J Arthroplasty.. 2015; 30:(4)521-526 https://doi.org/10.1016/j.arth.2015.01.023

Swank ML, Alkire M, Conditt M, Lonner JH. Technology and cost-effectiveness in knee arthroplasty: computer navigation and robotics. Am J Orthop (Belle Mead NJ). 2009; 38:32-36

University Hospital, Grenoble. Total knee arthroplasty robot assisted with MAKO™ robotic system compared to the conventional total knee arthroplasty by mechanical ancillary (TKA-MAKO). Identifier: NCT03566875. 2020. https://clinicaltrials.gov/ct2/show/NCT03566875 (accessed 14 May 2021)

Vermue H, Lambrechts J, Tampere T, Arnout N, Auvinet E, Victor J. How should we evaluate robotics in the operating theatre?. Bone Joint J.. 2020; 102-B:(4)407-413 https://doi.org/10.1302/0301-620X.102B4.BJJ-2019-1210.R1

Zambianchi F, Franceschi G, Rivi E, Banchelli F, Marcovigi A, Nardacchione R, Ensini A, Catani F. Does component placement affect short-term clinical outcome in robotic-arm assisted unicompartmental knee arthroplasty?. Bone Joint J.. 2019; 101-B:(4)435-442 https://doi.org/10.1302/0301-620X.101B4.BJJ-2018-0753.R1

Zhu S, Qian W, Jiang C, Ye C, Chen X. Enhanced recovery after surgery for hip and knee arthroplasty: a systematic review and meta-analysis. Postgrad Med J.. 2017; 93:(1106)736-742 https://doi.org/10.1136/postgradmedj-2017-134991

Nursing considerations for patients undergoing robotic-arm assisted joint replacements

27 May 2021
Volume 30 · Issue 10

Abstract

Robotic-arm assisted arthroplasty (RAA) has gained popularity over the past decade because of its ability to provide more accurate implant positioning with less surgical trauma than conventional manual arthroplasty. It has shown better early functional outcomes, less postoperative pain and shorter inpatient stays. A multidisciplinary approach is crucial in improving overall outcomes and ensuring this technology is implemented efficiently and safely, but there is limited published literature on the nursing considerations for managing patients undergoing RAA. This article aims to provide a pragmatic approach for nursing care in the pre-, intra-, and postoperative phases of RAA.

Major joint replacement surgery (arthroplasty) of the hip and knee joints is routinely carried out worldwide as an effective treatment for end-stage osteoarthritis (Haddad, 2017). Their purpose is to relieve pain and restore mobility. While arthroplasty has evolved through a number of different implants and surgical techniques, the basic principles remain the same: to replace diseased and arthritic bone surfaces with artificial implants.

Robotic technology has developed an ever-expanding range of roles within surgery as a whole, with its use in arthroplasty growing popular over the past 10 years (Coon, 2009; Kayani and Haddad, 2019; Kayani et al, 2019a; Banger et al, 2020; McDonnell et al, 2020; Vermue et al, 2020). The basic premise of this technology is that it minimises surgical trauma, improves the accuracy of implant positioning and reduces the overall systemic insult of surgery compared to conventional manual arthroplasty (Kayani et al, 2018a; 2019b; Begum et al, 2020).

A number of robotic systems have been developed for use in arthroplasty, with the Mako Robotic Arm Interactive Orthopaedics System (Stryker Ltd) being the most widely used and one that has the largest evidence base (Bautista et al, 2019).

The surgeon uses a preoperative CT scan to plan the optimal position of the implants and an intraoperative robotic arm to execute this, resulting in improved accuracy and fewer outliers. Robotic-arm assisted arthroplasty (RAA) has been shown to reduce postoperative pain, increase early postoperative functional rehabilitation and facilitate faster time to discharge compared to the conventional manual procedures (Kayani et al, 2018a; 2019b; Zambianchi et al, 2019; Begum et al, 2020; Burger et al, 2020). There is optimism that the more accurate implant positioning will translate to improved implant survival and reduce the burden of revision hip, total knee and unicompartmental knee arthroplasty (Kayani et al, 2019c; Haddad and Horriat, 2019).

Potential limitations of RAA include initial installation costs for the robotic device, additional training for the surgical team and longer operative times during the learning phase.

Successful implementation of any new technology into surgical practice relies heavily on the abilities of the dedicated multidisciplinary team. Despite the increasing popularity of RAA, there is limited published literature on nursing considerations for the treatment of patients undergoing RAA. This article provides a pragmatic approach for nursing care in the pre-, intra-, and postoperative phases of RAA.

Preoperative

The preoperative phase of RAA can be divided into three stages—education, assessment and planning—which is in line with the principles of enhanced recovery after surgery (ERAS) (Zhu et al, 2017; Kaye et al, 2019).

First, as with any elective orthopaedic procedure, patient education is crucial in managing expectations and ensuring patients are prepared for rehabilitation (Sau-Man Conny and Wan-Yim, 2016; Khamiso et al, 2019). Patients due to undergo arthroplasty attend a preoperative tutorial referred to as ‘Joint School’. This is a programme delivered by surgeons, specialist nurses, physiotherapists and occupational therapists, intended to optimise patients' preoperative health and knowledge about the operative procedure, and to improve postoperative compliance and rehabilitation (Fortin et al, 1999). The educational sessions have two parts: education and preoperative rehabilitation (prehabilitation).

Specialist nurses educate patients in how to prepare for their surgery and what to expect throughout the process from admission to discharge, as well as on specific issues including pain management, dressing/wound care and mobility precautions. Prehabilitation provides patients with a tailored exercise regimen that aims to improve the strength, range of movement and overall balance of relevant muscle groups, including the core and quadriceps. This is associated with better postoperative mobility and muscle strength, and a shorter stay in hospital (Fortin et al, 1999; Calatayud et al, 2017; Moyer et al, 2017). Robotic knee arthroplasty may involve additional incisions over the distal femur and proximal tibia for the insertion of the registration pins. Patients undergoing robotic total hip replacement will also require an additional incision over the pelvic crest. They should be advised about postoperative wound care for these additional incisions.

Second, patients will be required to undergo preassessment, as major arthroplasty is a large physiological undertaking. From a nursing perspective, a number of assessments are needed to assist this process. It is important to establish the patient's weight and BMI, and overweight or obese patients may be required to lose weight before surgery. Patients will require an ECG, and a full panel of blood tests including haemoglobin, urea and electrolytes, a clotting screen, and two group and save samples. A pertinent patient history including comorbidities and a social history to assess postoperative care arrangements must be taken; the history should also cover the use of anticoagulants such as aspirin, clopidogrel, warfarin or direct oral anticoagulants such as apixaban, as these will need to be stopped a number of days before surgery.

Patients must understand that robotic surgery has a greater risk of systemic perioperative complications than conventional surgery. However, robotic surgery does not use intramedullary referencing, where the surgeon inserts surgical instruments into the medullary canal to guide implant positioning during surgery. In theory, robotic surgery may have a lower risk of cardiorespiratory complications than conventional, jig-based surgery.

The operating surgeon will examine the patient to establish any clinical deformity, range of movement in the affected limb, as well as the other limb for reference, and any leg length discrepancies, which are important to note preoperatively as they should be accounted for during planning and eventual surgery. However, as the scope of extended nurse practitioners or surgical care practitioners expands in orthopaedics, such examinations may be carried out in clinics run by these practitioners. Robotic surgery requires careful correlation of preoperative clinical findings with intraoperative computer data, so careful documentation of any pre-existing coronal or sagittal plane deformities is essential.

Finally, patients require preoperative planning. To avoid operating blindly, the surgeon will carry out a process called ‘templating’, where the optimal choice of implant size and position are chosen. In the Mako system, this can be done digitally. Patients require a CT scan of the relevant joint to create a patient-specific, computer-aided design (CAD) model (Figure 1). Using this precise model, bone resections, implant sizes and implant positioning that are tailored to the patient can be planned. Adjustments can be made intraoperatively.

Figure 1. Patient specific CAD model of a knee joint with templated implants (green)

Other robotic systems may use intraoperative imaging instead of preoperative CT scans (Lang et al, 2011; Liow et al, 2017a; Bautista et al, 2019; Abdelfadeel et al, 2020). It is important for clinical and administrative staff to work together to ensure the CT scan and CAD model are performed in good time (usually 2 weeks before surgery) to enable the surgeon to perform the templating and ensure the required implants are available for surgery.

Intraoperative

Implementing any new technology into surgical practice requires time, effort and experience for seamless integration. In RAA, there are a number of extra considerations for the entire surgical team, including additional equipment, an initial increase in surgical times, more steps to the procedure and the overall learning curve associated with this technology.

Stages of robotic-arm assisted arthroplasty

The process of RAA can be divided into five stages:

  • Preoperative imaging with CT or radiographs to create a model of the patient's anatomy
  • Preoperative planning of patient-specific implant positioning and sizing
  • Intraoperative registration of the patient's skeletal anatomy
  • Intraoperative bone resections
  • Intraoperative assessment and adjustment of the bone resections and implant positioning.

The first two stages, discussed above in the preoperative section, are crucial in guiding the surgery. A number of steps can be performed before the patient arrives, which helps to maximise the efficiency of RAA (Grau et al, 2019). Before the procedure is started, while the patient is being anaesthetised, the robot should be calibrated by the product technician, then draped, and the scrub nurse can complete calibration of the robotic arm attachments before patient set-up (Figure 2). Equipment trays can be laid out before patient set-up. Patients are positioned as per surgeon preference: laterally or supine for hip replacements, and supine in knee replacements.

Figure 2. Scrub nurse calibrating the Mako robot: (a) Robotic-assisted arm with burr attachment. (b) Optical array for calibration. (c) Base of the robot with a clear, sterile drape

Once the patient, robot and instruments are set up, the hip or knee joint is surgically approached, and the process of bone registration can take place. A number of optical arrays are placed intraosseously to allow registration of the patient's anatomy, which maps their on-table anatomy to their preoperative CT scan. This is crucial in maximising the precision and accuracy of the procedure.

Bone resections can now begin, which adhere to the preoperative plan. The surgeon will use the robotic arm with saw, burr or reaming attachments configured to make these resections within the pre-planned boundaries, and with minimal soft tissue trauma (Figure 3). A large advantage of robotic technology is that the surgeon can make fine adjustments to the resections, which can be trialled on the computer to assess their effect before they are performed on the patient. The surgeon will use optical motion capture technology to reassess various parameters relating to the resections and perform adjustments accordingly to achieve optimal implant positioning and alignment (Oussedik et al, 2015; 2020).

Figure 3. Surgeon operating Mako robot on a knee joint: (a) Leg in sterile boot on rail. (b) Robotic assisted arm with burr attachment. (c) Optical arrays pinned into femur and tibia

Finally, the components are implanted manually, and these components may be cemented or cementless. Cemented fixation will add 10–15 minutes of time to the procedure; and are the more widely used implant type in knee arthroplasty.

Surgical team's learning curve

Although surgical teams routinely involved in arthroplasty should be familiar with RAA, there is a discernible learning curve associated with this novel technology.

Kayani et al (2019d) performed a prospective study of 60 robotic-assisted total knee replacements, analysing a number of factors, including anxiety levels of the entire surgical team and operating time. They found a distinct increase in anxiety levels in the surgical team during the learning phase, in particular the circulating nurse, which showed a statistically significant drop after seven cases (P=0.02). Importantly, however, despite the learning curve of seven cases for operative times with RAA, there was no learning curve effect regarding achieving the planned implant positioning or limb alignment. The risk of complications was also no greater during the learning phase. During this learning phase, the nursing team became progressively more efficient in setting up the robotic device and robotic instruments and calibrating the intraoperative machine.

Grau et al (2019) found a learning curve of six cases across their series of 132 robotic-assisted total knee replacements. They also highlighted the importance of using dedicated staff with all surgical team members having defined roles and responsibilities, which, when exercised in tandem with the surgeon, can greatly improve overall efficiency.

Theatre set-up

Each robotic system has a different set-up. In the Mako robotic system, there are three large devices to account for in terms of sterility and space within the theatre: the robotic arm itself, which needs to be placed in a sterile, clear drape (Figure 2); a computer stack with a separate technician to control the robot; and an optical camera to calibrate the robot (Figure 4). The camera, in conjunction with the pins inserted into the patient's limb, are used to calibrate the on-table anatomy against the computer model. Using this provides a representation of the patient in space to help guide the robotic arm. The space occupied by these devices may limit the number of theatre staff who can be present during RAA.

Figure 4. Theatre set-up showing practical considerations for space, robot not shown in picture. (a) Computer stack with dedicated technician. (b) Optical camera to calibrate robot. (c) General arthroplasty equipment and scrub trolley. (d) Optical array in patient to correspond with camera

Other instrumentation include: optical arrays which will be pinned into the pelvis or femur or tibia; and, in knee arthroplasty, a sterile boot and leg positioning rail. The robotic arm has a number of attachments, including multiple saw blades, a burr and an acetabular reamer. These are in addition to the standard equipment trays required in traditional hip or knee replacement.

Postoperative

In the postoperative phase, effective multidisciplinary working among nursing and therapy colleagues is key to ensuring patients who undergo RAA are appropriately cared for, rehabilitated and discharged both safely and early. This process forms part of the wider ERAS protocol (Gwynne-Jones et al, 2017), which, although routinely established in traditional arthroplasty, requires a number of extra considerations in RAA.

In the immediate 24 hours postoperatively, all surgical patients require regular monitoring. Nurses should observe for signs of hypovolaemia (hypotension and tachycardia), as there may have been some blood loss during the surgery. If patients are not in hypovolaemic shock, fluid resuscitation should be kept to a minimum, and patients should instead be encouraged to eat and drink as normal. Other key areas to monitor are urine output, postoperative haemoglobin and electrolytes, and pain levels. Arthroplasty surgery in general is very painful, and a variety of measures are implemented to minimise this, from local anaesthetic infiltration intraoperatively, to patient-controlled analgesia and regular opioids. Because of the high levels of surgical accuracy and reduced periarticular soft tissue injury, robotic surgery is associated with less postoperative pain and lower opiate analgesia consumption than conventional manual surgery in both total and unicompartmental knee arthroplasty (Kayani et al, 2018b; 2019b; 2019e).

Early mobilisation is a key part of the rehabilitation of any hip or knee arthroplasty and this is no different in robotics. As part of ERAS, patients are mobilised 2–6 hours after surgery, which has shown to both improve patient satisfaction and decrease length of stay (Kaye et al, 2019; Stambough et al, 2015). Physiotherapy protocols are based on patient needs and surgeon preferences, but aim to activate lower extremity muscles (hip and knee flexion and extension), initiate range of motion exercises, and mobilise patients fully weight-bearing from the day of surgery.

By 24 hours postoperatively, patients can restart gait education. Once patients are able to mobilise independently with crutches, and ascend and descend stairs safely, they can be discharged into the community with an ongoing physiotherapy plan (Kayani et al, 2019b). Robotic arthroplasty is associated with a reduced need for inpatient physiotherapy, better knee flexion, earlier mobilisation and a shorter time to hospital discharge than conventional jig-based surgery (Kayani, et al, 2019b).

It is hoped that these improved early functional outcomes with RAA will translate to more day case hip and knee arthroplasty. Nursing staff may see an expanding role in the management of hip and knee arthroplasty patients within the community over the coming years.

A distinct addition in robotic arthroplasty is the increased number of surgical incisions required. In addition to the main surgical incision, there needs to be placement of pin sites for the optical arrays. In a total hip replacement, these would be in a separate incision at the pelvic crest and, in a knee replacement, this would be either included in the main incision or through a separate incision in the tibial crest. Pin site incisions are an area for extra nursing care to manage the wounds.

In lower-limb arthroplasty, deep vein thrombosis is a major concern. While early mobilisation with good hydration is important, patients will require formal thromboprophylaxis in the form of compression stockings and anticoagulation. The choice of anticoagulation will be through patient factors and surgeon preference, but will vary between aspirin, low molecular weight heparin (eg enoxaparin or dalteparin) and direct oral anticoagulants (eg apixaban or rivaroxaban). Patients will need to be started on this 6 hours postoperatively, and must be discharged home on anticoagulation. It is important to monitor wound dressings (or the drain if placed) for any signs of bleeding, particularly after starting anticoagulation. It is hoped that the improved early functional rehabilitation and mobilisation with RAA will have a lower risk of venous thromboembolism than conventional manual arthroplasty.

The advantages gained through less soft tissue trauma and more accurate bone cuts include less postoperative pain and greater mobility. This, in turn, allows for faster time to hospital discharge in patients undergoing RAA (Kayani et al, 2019b). Patients may be discharged via a criteria-led discharge, whereby the nursing team will review the patients' pain to ensure that they are comfortable, and check that dressings are not soiled. They can then discharge patients once medication including anticoagulants have been prescribed, and patients have been discharged by the physiotherapy team following a mobility assessment. Patients will also require an X-ray to check the joint replaced before discharge to ensure there are no fractures and that the implant is in a satisfactory position.

Patients will be routinely followed up in 4–6 weeks in the surgeon's outpatient clinic but may require a 2-week follow-up with their GP or practice nurse for a wound check.

Evaluation of robotic-arm assisted arthroplasty

RAA is a rapidly evolving field, with proven benefits in the short term regarding patient satisfaction and early functional rehabilitation. However, because of the novelty of this technology, there are limited long-term data on whether these early perioperative benefits translate to long-term patient satisfaction, functional outcomes and implant survival (Robinson et al, 2019; Vermue et al, 2020). Several randomised controlled trials are in progress and will provide more robust evidence on this (Kayani et al, 2020a; 2020b; 2020c; University Hospital, Grenoble, 2020).

The main advantages of RAA are: its high-levels of accuracy, with preoperative templating of implant sizes and positions, leading to more precise bone resection and implant positioning; reduced periarticular soft tissue injury; the surgeon being able to intraoperatively assess knee biomechanics and fine tune implant positioning; and earlier postoperative functional rehabilitation than with conventional, jig-based surgery (Liow et al, 2017b; Lonner and Fillingham, 2018; Kayani et al, 2018a; 2019b; 2019f; St Mart et al, 2020).

The main limitations of RAA are the costs of installing the robotic device, extra time required for preoperative imaging and templating, and a learning curve of seven cases for the surgical team to become proficient with the procedure. Advocates of the technology cite the ability to recoup these initial costs through better patient outcomes that mean there is less revision surgery, fewer outpatient visits and greater economies of scale in high-volume centres (Swank et al, 2009; Jacofsky and Allen, 2016; Moschetti et al, 2016; Lonner and Fillingham, 2018).

Mont et al (2021) analysed healthcare utilisation costs in a comparison of 519 robot-assisted total knee replacements and 2595 conventional total knee replacements. They found consistently lower mean costs in the robotic cohort, with average costs of $18 565 (£13 215) compared to $20 960 (£14,920) (P<0.0001) at 90 days postoperatively in the robotic and conventional cohorts respectively. This was attributed to significantly reduced outpatient costs in the robotic cohort, with 47% fewer patients seeking skilled nursing care at 30 days (P<0.0001), fewer home visits (P<0.05), and fewer emergency department attendances and readmissions (P=0.0423).

Conclusion

Robotic-assisted arthroplasty has evolved rapidly over the past decade to become a powerful tool in arthroplasty surgery, and involves a number of additional considerations compared to traditional arthroplasty, from the pre- to the postoperative phase. These are important to understand for the entire multidisciplinary team.

The care provided to patients by the nursing team is critical at all stages. This includes preoperative patient education and assessment; pragmatic management of robotic equipment and intraoperative stages; postoperative monitoring, administration of analgesia and thromboprophylaxis; and facilitating a safe discharge.

Initial studies have shown that RAA is associated with less pain, lower opiate analgesia consumption, faster rehabilitation, less need for inpatient physiotherapy and earlier time to hospital discharge compared to conventional jig-based surgery.

The initial studies on RAA are encouraging, and higher quality studies comparing conventional arthroplasty versus robotic arthroplasty are in progress.

KEY POINTS

  • Robotic-arm assisted arthroplasty is a rapidly developing field and is associated with less surgical trauma, reduced postoperative pain, quicker rehabilitation, and a faster discharge time compared with conventional arthroplasty
  • Successful implementation relies on the efforts of the multidisciplinary team at each stage, although an initial learning curve can be expected
  • Preoperatively, patient education is important to ensure they understand the process ahead and are adequately prepared
  • Intraoperatively, the scrub team needs to be conscious of the extra equipment and steps required, with efficient preparation being important
  • Postoperatively, nursing teams need to be aware of mobilising patients early, ensuring adequate analgesia and thromboprophylaxis are administered

CPD reflective questions

  • Reflect on how you can affect a patient's journey in the preoperative, intraoperative, and postoperative phases
  • Consider the new technologies that you are using in practice. How are they are changing your practice?
  • When a new system, process or technology is introduced, how can you ensure that you become comfortable with using it?