Habboub, Ghaith

Study Design: Narrative review. Objectives: Artificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies with the potential to drastically affect clinical decision making in spine surgery. AI can enhance the delivery of spine care in several arenas: (1) preoperative patient workup, patient selection, and outcome prediction; (2) quality and reproducibility of spine research; (3) perioperative surgical assistance and data tracking optimization; and (4) intraoperative surgical performance. The purpose of this narrative review is to concisely assemble, analyze, and discuss current trends and applications of AI and ML in conventional and robotic-assisted spine surgery. Methods: We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2019 examining AI, ML, and robotics in spine surgery. Key findings were then compiled and summarized in this review. Results: The majority of the published AI literature in spine surgery has focused on predictive analytics and supervised image recognition for radiographic diagnosis. Several investigators have studied the use of AI/ML in the perioperative setting in small patient cohorts; pivotal trials are still pending. Conclusions: Artificial intelligence has tremendous potential in revolutionizing comprehensive spine care. Evidence-based, predictive analytics can help surgeons improve preoperative patient selection, surgical indications, and individualized postoperative care. Robotic-assisted surgery, while still in early stages of development, has the potential to reduce surgeon fatigue and improve technical precision.

OBJECTIVEGastrostomy tube placement can temporarily seed the peritoneal cavity with bacteria and thus theoretically increases the risk of shunt infection when the two procedures are performed contemporaneously. The authors hypothesized that gastrostomy tube placement would not increase the risk of ventriculoperitoneal shunt infection. The object of this study was to test this hypothesis by utilizing a large patient cohort combined from multiple institutions.METHODSA retrospective study of all adult patients admitted to five institutions with a diagnosis of aneurysmal subarachnoid hemorrhage between January 2005 and January 2015 was performed. The primary outcome of interest was ventriculoperitoneal shunt infection. Variables, including gastrostomy tube placement, were tested for their association with this outcome. Standard statistical methods were utilized.RESULTSThe overall cohort consisted of 432 patients, 47% of whom had undergone placement of a gastrostomy tube. The overall shunt infection rate was 9%. The only variable that predicted shunt infection was gastrostomy tube placement (p = 0.03, OR 2.09, 95% CI 1.07–4.08), which remained significant in the multivariate analysis (p = 0.04, OR 2.03, 95% CI 1.04–3.97). The greatest proportion of shunts that became infected had been placed more than 2 weeks (25%) and 1–2 weeks (18%) prior to gastrostomy tube placement, but the temporal relationship between shunt and gastrostomy was not a significant predictor of shunt infection.CONCLUSIONSGastrostomy tube placement significantly increases the risk of ventriculoperitoneal shunt infection.