BACKGROUND: An understanding of global, regional, and national macroeconomic losses caused by stroke is important for allocation of clinical and research resources. The authors investigated the macroeconomic consequences of stroke disease burden in the year 2019 in 173 countries. METHODS: Disability-adjusted life year data for overall stroke and its subtypes (ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage) were collected from the GBD study (Global Burden of Disease) 2019 database. Gross domestic product (GDP, adjusted for purchasing power parity [PPP]) data were collected from the World Bank; GDP and disability-adjusted life year data were combined to estimate macroeconomic losses using a value of lost welfare (VLW) approach. All results are presented in 2017 international US dollars adjusted for PPP. RESULTS: Globally, in 2019, VLW due to stroke was $2059.67 billion or 1.66% of the global GDP. Global VLW/GDP for stroke subtypes was 0.78% (VLW=$964.51 billion) for ischemic stroke, 0.71% (VLW=$882.81 billion) for intracerebral hemorrhage, and 0.17% (VLW=$212.36 billion) for subarachnoid hemorrhage. The Central European, Eastern European, and Central Asian GBD super-region reported the highest VLW/GDP for stroke overall (3.01%), ischemic stroke (1.86%), and for subarachnoid hemorrhage (0.26%). The Southeast Asian, East Asian, and Oceanian GBD super-region reported the highest VLW/GDP for intracerebral hemorrhage (1.48%). CONCLUSIONS: The global macroeconomic consequences related to stroke are vast even when considering stroke subtypes. The present quantification may be leveraged to help justify increased spending of finite resources on stroke in an effort to improve outcomes for patients with stroke globally.

Background: Surgical intervention is a critical tool to address adult spinal deformity (ASD). Given the evolution of spinal surgical techniques, we sought to characterize developments in ASD correction and barriers impacting clinical outcomes. Methods: We conducted a literature review utilizing PubMed, Embase, Web of Science, and Google Scholar to examine advances in ASD surgical correction and ongoing challenges from patient and clinician perspectives. ASD procedures were examined across pre-, intra-, and post-operative phases. Results: Several factors influence the effectiveness of ASD correction. Standardized radiographic parameters and three-dimensional modeling have been used to guide operative planning. Complex minimally invasive procedures, targeted corrections, and staged procedures can tailor surgical approaches while minimizing operative time. Further, improvements in osteotomy technique, intraoperative navigation, and enhanced hardware have increased patient safety. However, challenges remain. Variability in patient selection and deformity undercorrection have resulted in heterogenous clinical responses. Surgical complications, including blood loss, infection, hardware failure, proximal junction kyphosis/failure, and pseudarthroses, pose barriers. Although minimally invasive approaches are being utilized more often, clinical validation is needed. Conclusions: The growing prevalence of ASD requires surgical solutions that can lead to sustained symptom resolution. Leveraging computational and imaging advances will be necessary as we seek to provide comprehensive treatment plans for patients.

Background: Posterior fossa tumors (PFTs) are a morbid group of central nervous system tumors that most often present in childhood. While early diagnosis is critical to drive appropriate treatment, definitive diagnosis is currently only achievable through invasive tissue collection and histopathological analyses. Machine learning has been investigated as an alternative means of diagnosis. In this systematic review and meta-analysis, we evaluated the primary literature to identify all machine learning algorithms developed to classify and diagnose pediatric PFTs using imaging or molecular data. Methods: Of the 433 primary papers identified in PubMed, EMBASE, and Web of Science, 25 ultimately met the inclusion criteria. The included papers were extracted for algorithm architecture, study parameters, performance, strengths, and limitations. Results: The algorithms exhibited variable performance based on sample size, classifier(s) used, and individual tumor types being investigated. Ependymoma, medulloblastoma, and pilocytic astrocytoma were the most studied tumors with algorithm accuracies ranging from 37.5% to 94.5%. A minority of studies compared the developed algorithm to a trained neuroradiologist, with three imaging-based algorithms yielding superior performance. Common algorithm and study limitations included small sample sizes, uneven representation of individual tumor types, inconsistent performance reporting, and a lack of application in the clinical environment. Conclusions: Artificial intelligence has the potential to improve the speed and accuracy of diagnosis in this field if the right algorithm is applied to the right scenario. Work is needed to standardize outcome reporting and facilitate additional trials to allow for clinical uptake.

Background Expandable interbody cages, while popular in minimally invasive fusions due to their slim profile and increased ease of insertion, have not been widely explored in open surgery. The benefits of expandable cages may also extend to open fusions through their potential to achieve a greater restoration of lumbar lordosis while minimizing intraoperative complications. To highlight these benefits, we present a case series of adult spinal deformity (ASD) patients treated with an open transforaminal lumbar interbody fusion (TLIF) using expandable cages and compare outcomes to those of patients treated with static cages from the literature. Methods A retrospective cohort study of patients who underwent a deformity correction procedure and TLIF with expandable interbody cages at Brigham and Women's Hospital between 2018 and 2022 was conducted. Patient demographics, complications, and pre- and postoperative radiographic parameters of spinopelvic alignment were collected. A literature search was completed to identify studies employing static cages. T-tests were performed to compare postoperative changes in radiographic parameters by cage type. Results Forty-five patients (mean age of 62.6 years) with an average of 2.1 cages placed met the inclusion criteria. Patients experienced five intraoperative complications and 23 neurologic deficits (from minor to major), while nine patients required a revision operation. Lumbar lordosis increased by 9.8° ± 14.5° (p < 0.0001), the sagittal vertical axis (SVA) decreased by 25.5 mm ± 56.7 mm (p = 0.0048), and pelvic incidence-lumbar lordosis mismatch decreased by 13.3° ± 17.5° (p < 0.0001) with the use of expandable cages. Expandable cages yielded similar changes in lumbar lordosis to 15° and 8° cages but improved the lumbar lordosis generated from rectangular and 4° cages. When compared to static cages, expandable cages mildly reduced intraoperative complications. Conclusions Expandable interbody cages are an effective means of restoring spinopelvic alignment in ASD that have the potential to improve patient outcomes in open fusions compared to standard static cages. Especially when compared to rectangular and 4° static cages, expandable cages provide a clear benefit in the correction of lumbar lordosis. The impact of open spinal fusions with expandable cages on outcomes should continue to be explored in other cohorts.