Martin Del Campo, Isabel

OBJECTIVE The implementation of robotics and spinal anesthesia (SA) in spine surgery is rapidly expanding, offering significant benefits for an increasingly complex and aging patient population with degenerative spinal disease. Here, the authors present the largest cohort to date evaluating the combined use of these two techniques in minimally invasive (MIS) transforaminal lumbar interbody fusion (TLIF). METHODS The authors retrospectively analyzed surgical outcomes of a series of patients who underwent robot-assisted (RA)–MIS TLIF under SA and general anesthesia (GA) at their institution from 2018 to 2024. Primary outcomes included operative times and postoperative pain intensity. Secondary outcomes included estimated blood loss, intraoperative complications, postoperative functional status, length of stay (LOS), and discharge status. To address potential confounders, a 1:1 propensity score–matching and regression analysis was implemented. Statistical analyses were conducted using Python. RESULTS A total of 209 patients underwent RA-MIS TLIF, with 31 (14.83%) receiving SA and 178 (85.17%) GA. After propensity score matching, the SA cohort demonstrated significantly shorter median total operating room (OR) time, total procedure time, time from entering the OR to skin incision, and time from closure to leaving the OR (all p < 0.01). Additionally, postoperative pain scores were significantly lower (p < 0.01), and LOS was significantly shorter (p < 0.01) in the SA cohort. Regression analysis, adjusting for potential confounders, further supported these findings. CONCLUSIONS RA-MIS TLIF fusion under SA is a safe and effective approach that significantly reduces operative time, postoperative pain, and hospital LOS in patients undergoing surgery for degenerative lumbar spine disease.

OBJECTIVE Traditionally, resection of nondominant hemisphere brain tumors was performed under general anesthesia. An improved understanding of right-lateralized neural networks has led to a paradigm shift in recent decades, where the right or nondominant hemisphere is no longer perceived as "functionally silent." There is an increasing interest in awake brain mapping for nondominant hemisphere resections. The objective of this study was to perform a comprehensive review of the existing brain mapping paradigms for patients with nondominant hemisphere gliomas undergoing awake craniotomies. METHODS In accordance with PRISMA guidelines, systematic searches of the Medline, Embase, and American Psychological Association PsycInfo databases were undertaken from database inception to July 1, 2023. Studies providing a description of the intraoperative mapping paradigm used to assess cognition during an awake craniotomy for resection of a nondominant hemisphere glioma were included. RESULTS The search yielded 1084 potentially eligible articles. Thirty-nine unique studies reporting on 788 patients were included in the systematic review. The most frequently tested cognitive domains in patients with nondominant hemisphere tumors were spatial attention/neglect (17/39 studies, 43.6%), speech-motor/language (17/39 studies, 43.6%), and social cognition (9/39 studies, 23.1%). Within the frontal lobe, the highest number of positive mapping sites was identified for speech-motor/language, spatial attention/neglect, dual tasking assessing motor and language function, working memory, and social cognition. Within the parietal lobe, eloquence was most frequently found upon testing spatial attention/neglect, speech-motor/language, and calculation. Within the temporal lobe, the assessment of spatial attention/neglect yielded the highest number of positive mapping sites. CONCLUSIONS Cognitive testing in the nondominant hemisphere is predominantly focused on evaluating two domains: spatial attention/neglect and the motor aspects of speech/language. Multidisciplinary teams involved in awake brain mapping should consider testing an extended range of functions to minimize the risk of postoperative deficits and provide valuable information about anatomo-functional organization of cognitive networks.