The February 2023 Spine Roundup. 360. looks at: S2AI screws: At what cost?; Just how good is spinal deformity surgery?; Is 80 years of age too late in the day for spine surgery?; Factors affecting the accuracy of pedicle screw placement in
Continuous technical improvement in spinal surgical procedures, with the aim of enhancing patient outcomes, can be assisted by the deployment of advanced technologies including navigation, intraoperative CT imaging, and surgical robots. The latest generation of robotic surgical systems allows the simultaneous application of a range of digital features that provide the surgeon with an improved view of the surgical field, often through a narrow portal. There is emerging evidence that procedure-related complications and intraoperative blood loss can be reduced if the new technologies are used by appropriately trained surgeons. Acceptance of the role of surgical robots has increased in recent years among a number of surgical specialities including general surgery, neurosurgery, and orthopaedic surgeons performing major joint arthroplasty. However, ethical challenges have emerged with the rollout of these innovations, such as ensuring surgeon competence in the use of surgical robotics and avoiding financial conflicts of interest. Therefore, it is essential that trainees aspiring to become spinal surgeons as well as established spinal specialists should develop the necessary skills to use robotic technology safely and effectively and understand the ethical framework within which the technology is introduced. Traditional and more recently developed platforms exist to aid skill acquisition and surgical training which are described. The aim of this narrative review is to describe the role of surgical robotics in spinal surgery, describe measures of proficiency, and present the range of training platforms that institutions can use to ensure they employ confident spine surgeons adequately prepared for the era of robotic spinal surgery. Cite this article:
The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs). A questionnaire was administered to 340 patients (422 knees) who underwent primary TKA for osteoarthritis (OA) between September 2013 and June 2019. A total of 231 patients (284 knees) responded. The Knee Society Score 2011 (KSS 2011), Knee injury and Osteoarthritis Outcome Score-12 (KOOS-12), and Forgotten Joint Score-12 (FJS-12) were used to assess clinical outcomes. Using preoperative and postoperative anteroposterior full-leg radiographs, the arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) were calculated and classified based on the CPAK classification. To investigate the impact on PROMs, multivariable regression analyses using stepwise selection were conducted, considering factors such as age at surgery, time since surgery, BMI, sex, implant use, postoperative aHKA classification, JLO classification, and changes in aHKA and JLO classifications from preoperative to postoperative.Aims
Methods
Robots have been used in surgery since the late
1980s. Orthopaedic surgery began to incorporate robotic technology
in 1992, with the introduction of ROBODOC, for the planning and
performance of total hip replacement. The use of robotic systems
has subsequently increased, with promising short-term radiological
outcomes when compared with traditional orthopaedic procedures.
Robotic systems can be classified into two categories: autonomous
and haptic (or surgeon-guided). Passive surgery systems, which represent
a third type of technology, have also been adopted recently by orthopaedic
surgeons. While autonomous systems have fallen out of favour, tactile systems
with technological improvements have become widely used. Specifically,
the use of tactile and passive robotic systems in unicompartmental
knee replacement (UKR) has addressed some of the historical mechanisms
of failure of non-robotic UKR. These systems assist with increasing
the accuracy of the alignment of the components and produce more
consistent ligament balance. Short-term improvements in clinical
and radiological outcomes have increased the popularity of robot-assisted
UKR.
The aim of this study was to determine the risk of tibial eminence avulsion intraoperatively for bi-unicondylar knee arthroplasty (Bi-UKA), with consideration of the effect of implant positioning, overstuffing, and sex, compared to the risk for isolated medial unicondylar knee arthroplasty (UKA-M) and bicruciate-retaining total knee arthroplasty (BCR-TKA). Two experimentally validated finite element models of tibia were implanted with UKA-M, Bi-UKA, and BCR-TKA. Intraoperative loads were applied through the condyles, anterior cruciate ligament (ACL), medial collateral ligament (MCL), and lateral collateral ligament (LCL), and the risk of fracture (ROF) was evaluated in the spine as the ratio of the 95th percentile maximum principal elastic strains over the tensile yield strain of proximal tibial bone.Aims
Methods
The aim of this study was to assess the accuracy of pedicle screw placement, as well as intraoperative factors, radiation exposure, and complication rates in adult patients with degenerative disorders of the thoracic and lumbar spines who have undergone robotic-navigated spinal surgery using a contemporary system. The authors reviewed the prospectively collected data on 196 adult patients who had pedicle screws implanted with robot-navigated assistance (RNA) using the Mazor X Stealth system between June 2019 and March 2022. Pedicle screws were implanted by one experienced spinal surgeon after completion of a learning period. The accuracy of pedicle screw placement was determined using intraoperative 3D fluoroscopy.Aims
Methods
The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs? The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS).Aims
Methods
The application of robotics in the operating theatre for knee arthroplasty remains controversial. As with all new technology, the introduction of new systems might be associated with a learning curve. However, guidelines on how to assess the introduction of robotics in the operating theatre are lacking. This systematic review aims to evaluate the current evidence on the learning curve of robot-assisted knee arthroplasty. An extensive literature search of PubMed, Medline, Embase, Web of Science, and Cochrane Library was conducted. Randomized controlled trials, comparative studies, and cohort studies were included. Outcomes assessed included: time required for surgery, stress levels of the surgical team, complications in regard to surgical experience level or time needed for surgery, size prediction of preoperative templating, and alignment according to the number of knee arthroplasties performed. A total of 11 studies met the inclusion criteria. Most were of medium to low quality. The operating time of robot-assisted total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) is associated with a learning curve of between six to 20 cases and six to 36 cases respectively. Surgical team stress levels show a learning curve of seven cases in TKA and six cases for UKA. Experience with the robotic systems did not influence implant positioning, preoperative planning, and postoperative complications. Robot-assisted TKA and UKA is associated with a learning curve regarding operating time and surgical team stress levels. Future evaluation of robotics in the operating theatre should include detailed measurement of the various aspects of the total operating time, including total robotic time and time needed for preoperative planning. The prior experience of the surgical team should also be evaluated and reported. Cite this article:
The primary aim of the study was to perform an analysis to identify the cost per quality-adjusted life-year (QALY) of robot-assisted unicompartmental knee arthroplasty (rUKA) relative to manual total knee arthroplasty (TKA) and unicompartmental knee arthroplasty (UKA) for patients with isolated medial compartment osteoarthritis (OA) of the knee. Secondary aims were to assess how case volume and length of hospital stay influenced the relative cost per QALY. A Markov decision analysis was performed, using known parameters for costs, outcomes, implant survival, and mortality, to assess the cost-effectiveness of rUKA relative to manual TKA and UKA for patients with isolated medial compartment OA of the knee with a mean age of 65 years. The influence of case volume and shorter hospital stay were assessed.Aims
Patients and Methods
To assess the accuracy of patient-specific instruments (PSIs) CT scans were obtained from five female cadaveric pelvises. Five osteotomies were designed using Mimics software: sacroiliac, biplanar supra-acetabular, two parallel iliopubic and ischial. For cases of the left hemipelvis, PSIs were designed to guide standard oscillating saw osteotomies and later manufactured using 3D printing. Osteotomies were performed using the standard manual technique in cases of the right hemipelvis. Post-resection CT scans were quantitatively analysed. Student’s Objectives
Methods
The use of robots in orthopaedic surgery is an
emerging field that is gaining momentum. It has the potential for significant
improvements in surgical planning, accuracy of component implantation
and patient safety. Advocates of robot-assisted systems describe
better patient outcomes through improved pre-operative planning
and enhanced execution of surgery. However, costs, limited availability,
a lack of evidence regarding the efficiency and safety of such systems
and an absence of long-term high-impact studies have restricted
the widespread implementation of these systems. We have reviewed
the literature on the efficacy, safety and current understanding of
the use of robotics in orthopaedics. Cite this article:
The April 2015 Spine Roundup360 looks at: Hyperostotic spine in injury; App based back pain control; Interspinous process devices should be avoided in claudication; Robot assisted pedicle screws: fad or advance?; Vancomycin antibiotic power in spinal surgery; What to do with that burst fracture?; Increasing complexity of spinal fractures in major trauma pathways; Vitamin D and spinal fractures
