PurposeThis review summarizes the current use of extended reality (XR) including virtual reality (VR), mixed reality, and augmented reality (AR) in the medical field, ranging from medical imaging to training to preoperative planning. It covers the integration of these technologies into clinical practice and within medical training while discussing the challenges and future opportunities in this sphere. This will hopefully encourage more physicians to collaborate on integrating medicine and technology.ApproachThe review was written by experts in the field based on their knowledge and on recent publications exploring the topic of extended realities in medicine.ResultsBased on our findings, XR including VR, mixed reality, and AR are increasingly utilized within surgery both for preoperative planning and intraoperative procedures. These technologies are also promising means for improved education at every level of physician training. However, there are still barriers to the widespread adoption of VR, mixed reality, and AR, including human factors, technological challenges, and regulatory issues.ConclusionsBased on the current use of VR, mixed reality, and AR, it is likely that the use of these technologies will continue to grow over the next decade. To support the development and integration of XR into medicine, it is important for academic groups to collaborate with industrial groups and regulatory agencies in these endeavors. These joint projects will help address the current limitations and mutually benefit both fields.

Spinal surgeries are a common procedure, but there is significant risk of adverse events following these operations. While the rate of adverse events ranges from 8% to 18%, surgical site infections (SSIs) alone occur in between 1% and 4% of spinal surgeries. We completed a systematic review addressing factors that contribute to surgical site infection after spinal surgery. From the included studies, we separated the articles into groups based on whether they propose a clinical predictive tool or model. We then compared the prediction variables, model development, model validation, and model performance. About 47 articles were included in this study: 10 proposed a model and 5 validated a model. The models were developed from 7,720 participants in total and 210 participants with SSI. Only one of the proposed models was externally validated by an independent group. The other 4 validation papers examined the performance of the ACS NSQIP surgical risk calculator. While some preoperative risk models have been validated, and even successfully implemented clinically, the significance of postoperative SSIs and the unique susceptibility of spine surgery patients merits the development of a spine-specific preoperative risk model. Additionally, comprehensive and stratified risk modeling for SSI would be of invaluable clinical utility and greatly improve the field of spine surgery.

With an aging population, the incidence of both ischemic heart disease and strokes have become the most prevalent diseases globally. These diseases have similar risk factors, such as hypertension, diabetes, and smoking. However, there is also evidence of a relationship between the heart and the brain, referred to as the heart–brain axis. In this relationship, dysfunction of either organs can lead to injury to the other. There are several proposed physiologies to explain this relationship. These theories usually involve vascular, neuromodulatory, and inflammatory processes; however, few articles have explored and compared these different mechanisms of interaction between the heart and brain. A better understanding of the heart–brain axis can inform physicians of current and future treatment and preventive care options in heart and brain pathologies. The relationship between the brain and heart depends on inflammation, vascular anatomy and function, and neuromodulation. The pathways connecting these organs often become injured or dysfunctional when a major pathology, such as a myocardial infarction or stroke, occurs. This leads to long-term impacts on the patient’s overall health and risk for future disease. This study summarizes the current research involved in the heart–brain axis, relates these interactions to different diseases, and proposes future research in the field of neurocardiology. Conditions of the brain and heart are some of the most prevalent diseases. Through understanding the connection between these two organs, we can help inform patients and physicians of novel therapeutics for these pathologies.

Objective To review the decision aids currently available or being developed to predict a patient's odds that their external cephalic version (ECV) will be successful. Study Design We searched PubMed/MEDLINE, Cochrane Central, and ClinicalTrials.gov from 2015 to 2022. Articles from a pre-2015 systematic review were also included. We selected English-language articles describing or evaluating models (prediction rules) designed to predict an outcome of ECV for an individual patient. Acceptable model outcomes included cephalic presentation after the ECV attempt and whether the ECV ultimately resulted in a vaginal delivery. Two authors independently performed article selection following PRISMA 2020 guidelines. Since 2015, 380 unique records underwent title and abstract screening, and 49 reports underwent full-text review. Ultimately, 17 new articles and 8 from the prior review were included. Of the 25 articles, 22 proposed one to two models each for a total of 25 models, while the remaining 3 articles validated prior models without proposing new ones. Results Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the United States. The models found had diverse presentations including score charts, decision trees (flowcharts), and equations. The majority (13/25) had no form of validation and only 5/25 reached external validation. Only the Newman–Peacock model (United States, 1993) was repeatedly externally validated (Pakistan, 2012 and Portugal, 2018). Most models (14/25) were published in the last 5 years. In general, newer models were designed more robustly, used larger sample sizes, and were more mathematically rigorous. Thus, although they await further validation, there is great potential for these models to be more predictive than the Newman–Peacock model. Conclusion Only the Newman–Peacock model is ready for regular clinical use. Many newer models are promising but require further validation. Key Points

Strokes are a leading cause of death worldwide, with a majority being ischemic. Treatments include intravenous thrombolytics and mechanical thrombectomy (MT) for large vessel occlusions. With both being time-sensitive, there has been a focus on emergency transport decisions; however, there is a deficit of large, multi-institutional studies to support the use of a bypass transport system where patients suspected of large vessel occlusion are transported directly to a comprehensive stroke center (CSC) even if they bypass other centers. A query was completed of PubMed, Scopus, and Web of Science for articles related to clinical outcomes with the bypass transport method. Patients directly transported to a CSC were compared to patients transferred from a peripheral stroke center. A mixed-effect meta-regression model was used to investigate the effect of patient and treatment variables on 90-day mortality and functional outcome rates. Two hundred sixty articles were included in the final analysis. The time to tissue plasminogen activator treatment was insignificantly but slightly delayed in the direct group (132.1 vs. 130.6 minutes; P value: 0.8823), while the time to MT was significantly faster in the direct group (225.6 vs. 275.4 minutes; P value: 0.0114). Mortality and good neurological outcome rates were not significantly different in these groups (odds ratio=0.7060; 95% confidence interval 0.4802-1.0379 and odds ratio=1.1305; 95% confidence interval 0.8830-1.4473). This meta-analysis compares the 90-day mortality and functional outcomes between patients, and we found a statistically significant improvement in time to MT for those directly transported to a CSC; however, there was not a significant difference in clinical outcomes.

Placement of an external ventricular drain (EVD) involves navigating a catheter into a lateral ventricle of the brain, allowing drainage of cerebrospinal fluid. This can be a life-saving procedure in emergency situations. Ventricular cannulation is classically performed freehand, using landmarks on the skull to align the trajectory. However, this technique is vulnerable to misplacement and can lead to complications. New technologies have emerged to improve EVD placement accuracy and claim to reduce adverse effects. The objective of this report is to examine recent technology developed to improve EVD accuracy. A qualitative review of the literature was completed on publications collected from 6 databases: Pub Med, Medline, Web of Knowledge, Scopus, ClinicalTrials.Gov, and Google Scholar. The google scholar patent search was also used to query all patented devices. Relevant studies presented technology and innovations for EVD placement. The article and patent search returned 15 devices for EVD placement within 4 categories: ultrasound guidance, electromagnetic guidance, computed tomography-based guidance, and mechanical assist devices. The potential benefits of these devices range from real-time feedback for adjustments during insertion to reducing the number of passes and improving placement accuracy. Downsides include the cost of these devices and procedural changes that may increase the overall time of placement. A survey of neurosurgeons and residents found that 51.7% preferred image guidance, 41.6% preferred freehand technique, and 6.7% preferred the Ghajar guide in patients with slit ventricles. Although the freehand technique has been the traditional method for EVD insertion, a number of guidance technologies have been developed to improve placement accuracy. Image-guided procedures have become the preferred method in patients with complicated anatomy. However, changes in procedure time, device availability, and cost have limited the use of these technologies.