To report the development of the technique for minimally invasive lumbar decompression using robotic-assisted navigation. Robotic planning software was used to map out bone removal for a laminar decompression after registration of CT scan images of one cadaveric specimen. A specialized acorn-shaped bone removal robotic drill was used to complete a robotic lumbar laminectomy. Post-procedure advanced imaging was obtained to compare actual bony decompression to the surgical plan. After confirming accuracy of the technique, a minimally invasive robotic-assisted laminectomy was performed on one 72-year-old female patient with lumbar spinal stenosis. Postoperative advanced imaging was obtained to confirm the decompression.Aims
Methods
Psychoeducative prehabilitation to optimize surgical outcomes is relatively novel in spinal fusion surgery and, like most rehabilitation treatments, they are rarely well specified. Spinal fusion patients experience anxieties perioperatively about pain and immobility, which might prolong hospital length of stay (LOS). The aim of this prospective cohort study was to determine if a Preoperative Spinal Education (POSE) programme, specified using the Rehabilitation Treatment Specification System (RTSS) and designed to normalize expectations and reduce anxieties, was safe and reduced LOS. POSE was offered to 150 prospective patients over ten months (December 2018 to November 2019) Some chose to attend (Attend-POSE) and some did not attend (DNA-POSE). A third independent retrospective group of 150 patients (mean age 57.9 years (SD 14.8), 50.6% female) received surgery prior to POSE (pre-POSE). POSE consisted of an in-person 60-minute education with accompanying literature, specified using the RTSS as psychoeducative treatment components designed to optimize cognitive/affective representations of thoughts/feelings, and normalize anxieties about surgery and its aftermath. Across-group age, sex, median LOS, perioperative complications, and readmission rates were assessed using appropriate statistical tests.Aims
Methods
