A guide to selecting upper thoracic versus lower thoracic uppermost instrumented vertebra in adult spinal deformity correction.

PURPOSE: Operative treatment of adult spinal deformity (ASD) has been shown to improve patient health-related quality of life (HRQOL). Selection of the uppermost instrumented vertebra (UIV) in either the upper thoracic (UT) or lower thoracic (LT) spine is a pivotal decision with effects on operative and postoperative outcomes. This review overviews the multifaceted decision-making process for UIV selection in ASD correction. METHODS: PubMed was queried for articles using the keywords "uppermost instrumented vertebra", "upper thoracic", "lower thoracic", and "adult spinal deformity". RESULTS: Optimization of UIV selection may lead to superior deformity correction, better patient-reported outcomes, and lower risk of proximal junctional kyphosis (PJK) and failure (PJF). Patient alignment characteristics, including preoperative thoracic kyphosis, coronal deformity, and the magnitude of sagittal correction influence surgical decision-making when selecting a UIV, while comorbidities such as poor body mass index, osteoporosis, and neuromuscular pathology should also be taken in to account. Additionally, surgeon experience and resources available to the hospital may also play a role in this decision. Currently, it is incompletely understood whether postoperative HRQOLs, functional and radiographic outcomes, and complications after surgery differ between selection of the UIV in either the UT or LT spine. CONCLUSION: The correct selection of the UIV in surgical planning is a challenging task, which requires attention to preoperative alignment, patient comorbidities, clinical characteristics, available resources, and surgeon-specific factors such as experience.

Advances in Anterolateral Approaches to the Lumbar Spine: A Focus on Technological Developments.

A historical overview of the evolution of anterolateral approaches to the lumber spine and associated patient outcomes is presented. In addition, the modern incorporation of new technologies is discussed, including interbody cages, intraoperative image guidance, robotics, augmented reality, and machine learning, which have significantly improved the spine surgery safety and efficacy profile. Current challenges and future directions are also covered, emphasizing the need for further research and development, particularly in robotic assistance and machine learning algorithms.

Art and Neurosurgery: The Importance of Medical Illustration.

Art in neurosurgery has been a critical part of the discipline for centuries. Numerous cultures, such as ancient India, China, and Egypt, and more contemporary scientists, such as Leonardo da Vinci, Max Brödel, and Norman Dott, have significantly contributed to medical illustration. Today, advancements in three-dimensional technology have allowed for the creation of detailed neuroanatomy models for surgical planning and education. Medical illustrations are also used for research and outcome documentation as they help visualize anatomy and surgical procedures. Its use in education, surgical planning, and navigation remains integral to the advancement of neurosurgery. This review demonstrates the invaluable contribution of art in neurosurgery and how it has enabled continuous progress in the field.

Excelencia en Neurocirugía: María Cristina García-Sancho, the First Latina Neurosurgeon in the World.

BACKGROUND: Neurosurgery is a specialty that has been dominated by males. Although there has been an increase in the number of women in the field, it is not yet close to being equal. Some noteworthy women who have carved the path for other women to follow in their footsteps include Drs. Sofía Ionescu and Diana Beck, the first and second female neurosurgeons worldwide, respectively. However, there are limited publications on Dr. María Cristina García-Sancho, the first Latina neurosurgeon. METHODS: The purpose of this review was to illuminate the neurosurgical community on the life of Dr. García-Sancho. A thorough literature was performed on medical and non-medical publications that were either authored by Dr. García-Sancho or mentioned her directly. RESULTS: Dr. García-Sancho earned her medical degree at the School of Medicine of the National Autonomous University of Mexico under the guidance of Dr. Clemente Robles, who founded Mexico's first neurosurgical department. Her training took her worldwide. CONCLUSIONS: Her expertise allowed her to pioneer a revolutionary advancement known as the one-step bilateral cordotomy. Her perseverance led her to becoming the head of the Department of Neurosurgery at the National Cancer Institute of Mexico and co-found the Mexican Society of Neurological Surgery, where she served on the board of directors. This review aims to advocate for an equitable environment in the field of neurosurgery with Dr. García-Sancho's story.

Impact of environmental pollutants on pediatric brain tumor incidence in New Jersey.

OBJECTIVE: The relationship between environmental contaminants and brain tumor incidence in adults has been thoroughly explored but research into how these contaminants affect pediatric brain tumor (PBT) incidence has not been explored. Children, typically having more limited geographical movement and thus more consistent environmental contaminant exposure, might offer more reliable insights into which environmental contaminants affect the incidence of brain tumors. The present study is the first to focus on exploring whether a possible association exists between the incidence of PBTs and exposure to environmental pollutants in New Jersey (NJ). METHODS: Linear regressions were run between PBT incidence and the concentration of air quality pollutants such as Ozone (O3), Particulate Matter 2.5 (PM2.5), Particulate Matter 10 (PM10), and Carbon Monoxide (CO). Similarly, linear regressions were run between PBT incidence and Elevated Blood Lead Levels (BLL). RESULTS: The study observed a significant positive relationship between O3 and PBT incidence (ß = 0.34, p = 0.028). However, the relationship between PBT incidence, and environmental pollutants such as CO (ß = 0.0047, p = 0.098), PM2.5 (ß = -0.2624, p = 0.74), and PM10 (ß = -0.7353, p = 0.073) were found to be nonsignificant. For elevated BLL, nonsignificant relationships with PBT incidence were observed at 10-14 µg/dL (ß = -39.38, p = 0.30), 15-19 µg/dL (ß = -67.00, p = 0.21), and 20-44 µg/dL (ß = -201.98, p = 0.12). CONCLUSIONS: The results indicate a possible impact of O3 on the incidence of PBTs in NJ. In contrast to the significant links found in prior studies of adult brain tumors, the associations between PBT occurrence and particulate matter were not significant. These findings highlight the importance of further investigating how environmental factors, especially O3, relate to PBTs.

Can Publicly Available Artificial Intelligence Successfully Identify Current Procedural Terminology Codes for Common Procedures in Neurosurgery?

OBJECTIVE: Coding for neurosurgical procedures is a complex process that is dynamically changing year to year, through the annual introduction and removal of codes and modifiers. The authors hoped to elucidate if publicly available artificial intelligence (AI) could offer solutions for neurosurgeons with regard to coding. METHODS: Multiple publicly available AI platforms were asked to provide Current Procedural Terminology (CPT) codes and Revenue Value Units (RVU) values for common neurosurgical procedures of the brain and spine with a given indication for the procedure. The responses of platforms were recorded and compared to the currently valid CPT codes used for the procedure and the amount of RVUs that would be gained. RESULTS: Six platforms and Google were asked for the appropriate CPT codes for 10 endovascular, spinal, and cranial procedures each. The highest performing platforms were as follows: Perplexity.AI identified 70% of endovascular, BingAI identified 55% of spinal, and ChatGPT 4.0 with Bing identified 75% of cranial CPT codes. With regard to RVUs, the top performer gained 78% of endovascular, 42% of spinal, and 70% of cranial possible RVUs. With regard to accuracy, AI platforms on average outperformed Google (45% vs. 25%, P = 0.04236). CONCLUSIONS: The ability of publicly available AIs to successfully code for neurosurgical procedures holds great promise in the future. Future development of AI should focus on improving accuracy with regard to CPT codes and providing supporting documentation for its decisions. Improvement on the existing capabilities of AI platforms can allow for increased operational efficiency and cost savings for practices.

Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, this study seeks to elucidate their role in assisting neurosurgeons with the differential diagnosis process, especially during preliminary consultations. METHODS: This study employed 3 chat-based LLMs, ChatGPT (versions 3.5 and 4.0), Perplexity AI, and Bard AI, to evaluate their diagnostic accuracy. Each LLM was prompted using clinical vignettes, and their responses were recorded to generate differential diagnoses for 20 common and uncommon neurosurgical disorders. Disease-specific prompts were crafted using Dynamed, a clinical reference tool. The accuracy of the LLMs was determined based on their ability to identify the target disease within their top differential diagnoses correctly. RESULTS: For the initial differential, ChatGPT 3.5 achieved an accuracy of 52.63%, while ChatGPT 4.0 performed slightly better at 53.68%. Perplexity AI and Bard AI demonstrated 40.00% and 29.47% accuracy, respectively. As the number of considered differentials increased from 2 to 5, ChatGPT 3.5 reached its peak accuracy of 77.89% for the top 5 differentials. Bard AI and Perplexity AI had varied performances, with Bard AI improving in the top 5 differentials at 62.11%. On a disease-specific note, the LLMs excelled in diagnosing conditions like epilepsy and cervical spine stenosis but faced challenges with more complex diseases such as Moyamoya disease and amyotrophic lateral sclerosis. CONCLUSIONS: LLMs showcase the potential to enhance diagnostic accuracy and decrease the incidence of missed diagnoses in neurosurgery.

Usefulness and Accuracy of Artificial Intelligence Chatbot Responses to Patient Questions for Neurosurgical Procedures.

BACKGROUND AND OBJECTIVES: The Internet has become a primary source of health information, leading patients to seek answers online before consulting health care providers. This study aims to evaluate the implementation of Chat Generative Pre-Trained Transformer (ChatGPT) in neurosurgery by assessing the accuracy and helpfulness of artificial intelligence (AI)-generated responses to common postsurgical questions. METHODS: A list of 60 commonly asked questions regarding neurosurgical procedures was developed. ChatGPT-3.0, ChatGPT-3.5, and ChatGPT-4.0 responses to these questions were recorded and graded by numerous practitioners for accuracy and helpfulness. The understandability and actionability of the answers were assessed using the Patient Education Materials Assessment Tool. Readability analysis was conducted using established scales. RESULTS: A total of 1080 responses were evaluated, equally divided among ChatGPT-3.0, 3.5, and 4.0, each contributing 360 responses. The mean helpfulness score across the 3 subsections was 3.511 ± 0.647 while the accuracy score was 4.165 ± 0.567. The Patient Education Materials Assessment Tool analysis revealed that the AI-generated responses had higher actionability scores than understandability. This indicates that the answers provided practical guidance and recommendations that patients could apply effectively. On the other hand, the mean Flesch Reading Ease score was 33.5, suggesting that the readability level of the responses was relatively complex. The Raygor Readability Estimate scores ranged within the graduate level, with an average score of the 15th grade. CONCLUSION: The artificial intelligence chatbot's responses, although factually accurate, were not rated highly beneficial, with only marginal differences in perceived helpfulness and accuracy between ChatGPT-3.0 and ChatGPT-3.5 versions. Despite this, the responses from ChatGPT-4.0 showed a notable improvement in understandability, indicating enhanced readability over earlier versions.

Patient perception of spinal cord injury through social media: An analysis of 703 Instagram and 117 Twitter posts.

Introduction: Social media has developed exponentially over the last decade as a means for individuals and patients to connect to others and has provided a unique opportunity for physicians to provide broader information to the general public to attempt to positively modify health behavior. The purpose of this study was to assess the patient's perception of spinal cord injury (SCI) on social media. Methods: Instagram and Twitter social media platforms were analyzed to determine posts written by patients with SCI. The initial search for Instagram posts tagged with "#spinalcordinjury" yielded over 270,000 posts in April 2021. Posts pertaining to the patient's experience were retrospectively collected from January 2020 to April 2021. Twitter posts that included "#spinalcordinjury," "@spinalcordinjury," and "spinal cord injury" were retrospectively collected in April 2021. One hundred seventeen tweets were found that were directly from a patient with SCI. Themes associated with patients' experiences living with SCI were coded. Results: The most common theme on Instagram was spreading positivity and on Twitter was the appearance of the wheelchair (75.8% and 37.3%, respectively). Other common themes on Instagram were the appearance of a wheelchair (71.8%), recovery or rehabilitation (29.9%), and life satisfaction (29.0%). Prevalent themes on Twitter included spreading positivity (23.2%) and recovery or rehabilitation (21.3%). Conclusion: The prevalence of themes of positivity and awareness may indicate the utilization of social media as a support mechanism for patients living with SCI. Identification of prevalent themes is important for the holistic treatment of SCI survivors.