A tale of two robots: Operating times and learning curves in robot-assisted lumbar fusion

Learning curve analyses in spine surgery: a systematic simulation-based critique of methodologies

BACKGROUND CONTEXT

Various statistical approaches exist to delineate learning curves in spine surgery. Techniques range from dividing cases into intervals for metric comparison, to employing regression and cumulative summation (CUSUM) analyses. However, their inherent inconsistencies and methodological flaws limit their comparability and reliability.

PURPOSE

To critically evaluate the methodologies used in existing literature for studying learning curves in spine surgery and to provide recommendations for future research.

STUDY DESIGN

Systematic literature review.

METHODS

A comprehensive literature search was conducted using PubMed, Embase, and Scopus databases, covering articles from January 2010 to September 2023. For inclusion, articles had to evaluate the change in a metric of performance during human spine surgery across time/a case series. Results had to be reported in sufficient detail to allow for evaluation of individual performance rather than group/institutional performance. Articles were excluded if they included cadaveric/nonhuman subjects, aggregated performance data or no way to infer change across a number of cases. Risk of bias was assessed using the Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I) tool. Surgical data were simulated using Python 3 and then examined via multiple commonly used analytic approaches including division into consecutive intervals, regression and CUSUM techniques. Results were qualitatively assessed to determine the effectiveness and limitations of each approach in depicting a learning curve.

RESULTS

About 113 studies met inclusion criteria. The majority of the studies were retrospective and evaluated a single-surgeon's experience. Methods varied considerably, with 66 studies using a single proficiency metric and 47 using more than 1. Operating time was the most commonly used metric. Interval division was the simplest and most commonly used method yet inherent limitations prevent collective synthesis. Regression may accurately describe the learning curve but in practice is hampered by sample size and model choice. CUSUM analyses are of widely varying quality with some being fundamentally flawed and widely misinterpreted however, others provide a reliable view of the learning process.

CONCLUSION

There is considerable variation in the quality of existing studies on learning curves in spine surgery. CUSUM analyses, when correctly applied, offer the most reliable estimates. To improve the validity and comparability of future studies, adherence to methodological guidelines is crucial. Multiple or composite performance metrics are necessary for a holistic understanding of the learning process.

Effectiveness and safety of robot-assisted minimally invasive transforaminal lumbar interbody fusion for degenerative lumbar spinal diseases: a systematic review and meta-analysis

Robot-assisted (RA) technology has been widely used in spine surgery. This analysis aimed to compare the effectiveness and safety of RA minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) and fluoroscopy-assisted (FA) MIS-TLIF for degenerative lumbar spinal diseases (DLSD). PubMed, Web of Science, Cochrane Library, and China National Knowledge Infrastructure were systematically searched, and the outcomes included surgical parameters [operation time, blood loss, number of fluoroscopic, accuracy of pedicle screw position, superior facet joint violation (FJV)], and clinical indexes (Visual Analog Scale (VAS), Oswestry Disability Index (ODI), Japanese Orthopaedic Association (JOA) score, clinical efficacy, hospital stays, complications). Eleven articles involving 1066 patients were included. RA group produced better results than the FA group in operation time (WMD = - 6.59; 95% CI - 12.79 to - 0.40; P = 0.04), blood loss (WMD = - 34.81; 95% CI - 50.55 to - 19.08; P < 0.0001), number of fluoroscopic (WMD = - 18.24; 95% CI - 30.63 to - 5.85; P = 0.004), accuracy of pedicle screw position: Grade A (OR = 3.16; 95% CI 2.36-4.23; P < 0.00001), Grade B (OR = 0.39; 95% CI 0.28-0.54; P < 0.00001), Grade C (OR = 0.27; 95% CI 0.13-0.54; P = 0.0002), and Grade D (OR = 0.17; 95% CI 0.03-0.98; P = 0.05), FJV: Grade 0 (OR = 3.27; 95% CI 1.34-8.02; P = 0.010), Grade 1 (OR = 0.24; 95% CI 0.16-0.38; P < 0.00001), Grade 2 (OR = 0.24; 95% CI 0.12-0.51; P = 0.0002), and Grade 3 (OR = 0.26; 95% CI 0.07-0.93; P = 0.04). But no significant differences in VAS score, ODI, JOA score, clinical efficacy, hospital stays, and complications. These results demonstrate a significant improvement in the intraoperative course of the RA technique. However, RA-MIS-TLIF has not yet demonstrated significant advantages in terms of postoperative symptom relief and functional improvement. Future research and clinical practice should further explore the efficacy of this technique to optimize outcomes and quality of life for patients with DLSD. The study was registered in the PROSPERO (CRD42023454405).

Spine Surgical Robotics: Current Status and Recent Clinical Applications

With the development of artificial intelligence and the further deepening of medical-engineering integration, spine surgical robot-assisted (RA) technique has made significant progress and its applicability in clinical practice is constantly expanding in recent years. In this review, we have systematically summarized the majority of literature related to spine surgical robots in the past decade, and not only classified robots accordingly, but also summarized the latest research progress in RA technique for screw placement such as cervical, thoracic, and lumbar pedicle screws, cortical bone trajectory screws, cervical lateral mass screws, and S2 sacroiliac screws; guiding targeted puncture and placement of endoscope via the intervertebral foramen; complete resection of spinal tumor tissue; and decompressive laminectomy. In addition, this report also provides a detailed evaluation of RA technique's advantages and disadvantages, and clarifies the accuracy, safety, and practicality of RA technique. We consider that this review can help clinical physicians further understand and familiarize the current clinical application status of spine surgical robots, thereby promoting the continuous improvement and popularization of RA technique, and ultimately benefiting numerous patients.

Robotics in spine surgery: systematic review of literature

PURPOSE

Over 4.83 million spine surgery procedures are performed annually around the world. With the considerable caseload and the precision needed to achieve optimal spinal instrumentation, technical progress has helped to improve the technique's safety and accuracy with the development of peri-operative assistance tools. Contrary to other surgical applications already part of the standard of care, the development of robotics in spine surgery is still a novelty and is not widely available nor used. Robotics, especially when coupled with other guidance modalities such as navigation, seems to be a promising tool in our quest for accuracy, improving patient outcomes and reducing surgical complications. Robotics in spine surgery may also be for the surgeon a way to progress in terms of ergonomics, but also to respond to a growing concern among surgical teams to reduce radiation exposure.

METHOD

We present in this recent systematic review of the literature realized according to the PRISMA guidelines the place of robotics in spine surgery, reviewing the comparison to standard techniques, the current and future indications, the learning curve, the impact on radiation exposure, and the cost-effectiveness.

RESULTS

Seventy-six relevant original studies were identified and analyzed for the review.

CONCLUSION

Robotics has proved to be a safe help for spine surgery, both for the patient with a decrease of operating time and increase in pedicular screw accuracy, and for the surgical team with a decrease of radiation exposure. Medico-economic studies demonstrated that despite a high buying cost, the purchase of a robot dedicated for spine surgery is cost-effective resulting in lesser revision, lower infection, reduced length of stay, and shorter surgical procedure.