Saphenous Vein Graft Pseudoaneurysm Treated With Covered Stenting.

Saphenous vein graft (SVG) pseudoaneurysms are an infrequent, but life-threatening complication of coronary artery bypass grafting (CABG) surgery if left untreated. Here, we discuss the case of a 77-year-old patient, with a prior history of CABG and transcatheter aortic valve implantation (TAVI), who was incidentally found on computed tomography angiography (CTA) to have a pseudoaneurysm of his SVG with an initial chief complaint of dizziness. Despite increasing reports of SVG pseudoaneurysm, there is no consensus on definitive treatment. Due to the high mortality risk of this patient with surgical intervention, a minimally invasive percutaneous coronary intervention was performed. The patient was effectively treated with two overlapping Viabahn-covered stents, which completely excluded the pseudoaneurysm. Follow-up imaging at two months showed two well-positioned overlapping self-expanding stents with total occlusion of the pseudoaneurysm.

Anterior and posterior surgical approach for vertebral lumbar Mycobacterium abscessus osteomyelitis.

Mycobacterium abscessus (M. abscessus) infections primarily affect immunocompromised patients who commonly present with non-orthopedic infections. We present a case of a 63-year-old female presented with persistent back pain and radicular pain. Computed tomography and magnetic resonance imaging showed a large multiloculated anterior epidural abscess. We show here the unique occurrence of lumbar M. abscessus vertebral osteomyelitis, which was treated with L2 and L3 corpectomies, anterior lumbar interbody fusion, and posterior instrumentation via an anterolateral thoracoabdominal (TA) incision. Vascular surgery provided L1-L4 spine exposure via a left anterolateral TA incision, whereas orthopedic surgery performed L2 and L3 corpectomies with lumbar cage placement and posterior instrumentation in two separate procedures. The patient was discharged to a skilled nursing facility, retaining all neurological function, and is progressing well on follow-up.

Ventriculoperitoneal Shunt Failure and Cerebrospinal Fluid Protein: A Meta-Analysis and Systematic Review.

Ventriculoperitoneal shunts (VPS) are used to manage hydrocephalus but suffer from high failure rates. Our objectives were to (1) conduct a meta-analysis to objectively weigh this conflicting evidence, and (2) conduct a systematic review compiling and synthesizing what is known about the association between CSF proteins and shunt failure. A literature search was performed in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Embase, PubMed, and CENTRAL databases were searched from inception to June 2023. The articles were screened based on the inclusion criteria. A meta-analysis was conducted using R statistical software (R Foundation for Statistical Computing, Vienna, Austria); heterogeneity, subgroup, sensitivity, risk of bias, and publication bias analyses were performed. Thirty-one studies were selected for the systematic review, of which eight were selected for the meta-analysis. Perioperative CSF protein level was compared between 351 shunt failures and 1,094 shunt survivals; the mean difference of 24.37 mg/dL favoring shunt failure was significant (95% confidence interval=2.44-46.29 mg/dL). Our systematic review yielded a hypothesized pathogenesis: proteins attached to imperfections in the shunt surface lead to secondary attachment of cells, particularly astrocytes, and tertiary attachment of ependymal cells and the choroid plexus. Owing to the limitations of this meta-analysis, including lack of robustness due to missing data, heterogeneity, and certainty of the evidence, future research is needed to better understand the relationship between perioperative CSF protein levels and shunt failure.

Expression of E-cadherin and N-cadherin in Epithelial-to-Mesenchymal Transition of Osteosarcoma: A Systematic Review.

Osteosarcoma (OS) is a debilitating cancer of the bone that commonly afflicts the young and old. This may be de novo or associated with tumorigenic syndromes. However, many molecular mechanisms are still being uncovered and may offer greater avenues for screening and therapy. Cadherins, including E-cadherin and N-cadherin/vimentin, are involved in epithelial-to-mesenchymal transmission (EMT), which is key for tumor invasion. A study reviewing the relationship between OS and cadherins might elucidate a potential target for therapy and screening. A robust literature review was conducted by searching PubMed with the keywords "osteosarcoma", "cadherin", "e-cadherin" and "n-cadherin". Of a preliminary 266 papers, 25 were included in the final review. Review articles and those without primary data were excluded. Loss of E-cadherin is noted in metastatic cell lines of osteosarcoma. Overexpression of E-cadherin or knockout of N-cadherin/vimentin results in loss of metastatic potential. There are several methods of gene knockout, including CRISPR-Cas9 gene editing, viral vector insertion with micro RNA complementary to long noncoding RNA within gene segments, or proteomic editing. Screening for EMT and genetic treatment of EMT is a possible avenue for the treatment of refractory osteosarcoma. Several studies were conducted ex vivo. Further testing involving in vitro therapy is necessary to validate these methods. Limitations of this study involve a lack of in vivo trials to validate methods.

Utilizing Deep Learning for X-ray Imaging: Detecting and Classifying Degenerative Spinal Conditions.

Background Degenerative spinal conditions (DSCs) involve a diverse set of pathologies that significantly impact health and quality of life, affecting many individuals at least once during their lifetime. Treatment approaches are varied and complex, reflecting the intricacy of spinal anatomy and kinetics. Diagnosis and management pose challenges, with the accurate detection of lesions further complicated by age-related degeneration and surgical implants. Technological advancements, particularly in artificial intelligence (AI) and deep learning, have demonstrated the potential to enhance detection of spinal lesions. Despite challenges in dataset creation and integration into clinical settings, further research holds promise for improved patient outcomes. Methods This study aimed to develop a DSC detection and classification model using a Kaggle dataset of 967 spinal X-ray images at the Department of Neurosurgery of Arrowhead Regional Medical Center, Colton, California, USA. Our entire workflow, including data preprocessing, training, validation, and testing, was performed by utilizing an online-cloud based AI platform. The model's performance was evaluated based on its ability to accurately classify certain DSCs (osteophytes, spinal implants, and foraminal stenosis) and distinguish these from normal X-rays. Evaluation metrics, including accuracy, precision, recall, and confusion matrix, were calculated.  Results The model achieved an average precision of 0.88, with precision and recall values of 87% and 83.3%, respectively, indicating its high accuracy in classifying DSCs and distinguishing these from normal cases. Sensitivity and specificity values were calculated as 94.12% and 96.68%, respectively. The overall accuracy of the model was calculated to be 89%.  Conclusion These findings indicate the utility of deep learning algorithms in enhancing early DSC detection and screening. Our platform is a cost-effective tool that demonstrates robust performance given a heterogeneous dataset. However, additional validation studies are required to evaluate the model's generalizability across different populations and optimize its seamless integration into various types of clinical practice.

Deep Learning Classification of Drusen, Choroidal Neovascularization, and Diabetic Macular Edema in Optical Coherence Tomography (OCT) Images.

Background Age-related macular degeneration (AMD), diabetic retinopathy (DR), drusen, choroidal neovascularization (CNV), and diabetic macular edema (DME) are significant causes of visual impairment globally. Optical coherence tomography (OCT) imaging has emerged as a valuable diagnostic tool for these ocular conditions. However, subjective interpretation and inter-observer variability highlight the need for standardized diagnostic approaches. Methods This study aimed to develop a robust deep learning model using artificial intelligence (AI) techniques for the automated detection of drusen, CNV, and DME in OCT images. A diverse dataset of 1,528 OCT images from Kaggle.com was used for model training. The performance metrics, including precision, recall, sensitivity, specificity, F1 score, and overall accuracy, were assessed to evaluate the model's effectiveness. Results The developed model achieved high precision (0.99), recall (0.962), sensitivity (0.985), specificity (0.987), F1 score (0.971), and overall accuracy (0.987) in classifying diseased and healthy OCT images. These results demonstrate the efficacy and efficiency of the model in distinguishing between retinal pathologies. Conclusion The study concludes that the developed deep learning model using AI techniques is highly effective in the automated detection of drusen, CNV, and DME in OCT images. Further validation studies and research efforts are necessary to evaluate the generalizability and integration of the model into clinical practice. Collaboration between clinicians, policymakers, and researchers is essential for advancing diagnostic tools and management strategies for AMD and DR. Integrating this technology into clinical workflows can positively impact patient care, particularly in settings with limited access to ophthalmologists. Future research should focus on collecting independent datasets, addressing potential biases, and assessing real-world effectiveness. Overall, the use of machine learning algorithms in conjunction with OCT imaging holds great potential for improving the detection and management of drusen, CNV, and DME, leading to enhanced patient outcomes and vision preservation.

Exploring the Surgical Outcomes of Pancreatic Cancer Resections Performed in Low- Versus High-Volume Centers.

Introduction Pancreatic cancer resections comprise a class of complex surgical operations with a high postoperative morbidity rate. Due to the complicated nature of pancreatic resection, individuals who undergo this procedure are advised to visit a high-volume medical center that performs such pancreatic surgeries frequently. However, this specialized treatment option may not be available for uninsured patients or patients with other socioeconomic limitations that may restrict their access to these facilities. To gain a better understanding of the impact of healthcare disparities on surgical outcomes, we aimed to explore if there were significant differences in mortality rate post-pancreatic resection between high- and low-volume hospitals within San Bernardino, Riverside, Los Angeles, and Orange Counties. Methods We utilized the California Health and Human Services Agency (CHHS) California Hospital Inpatient Mortality Rates and Quality Ratings public dataset to compare risk-adjusted mortality rates (RA-MR) of pancreatic cancer resections procedures. We focused on procedures performed in hospitals within San Bernardino, Riverside, Los Angeles, and Orange County from 2012 to 2015. To assess post-resection outcomes in relation to hospital volume, we utilized an independent T-test (significance level was set equal to 0.05) to determine if there is a statistically significant difference in RA-MR after pancreatic resection between high- and low-volume hospitals. Results During the 2012-2015 study period, 57 hospitals across San Bernardino, Riverside, Orange, and Los Angeles Counties were identified to perform a total of 6,204 pancreatic resection procedures. The low-volume hospital group (N=2,539) was associated with a higher RA-MR of M=4.45 (SD=11.86). By comparison, the high-volume hospital group (N=3,665) was associated with a lower RA-MR of M=1.72 (SD=2.61). Conclusion Pancreatic resection surgeries performed at low-volume hospitals resulted in a significantly higher RA-MR compared to procedures done at high-volume hospitals in California.

AAV Engineering for Improving Tropism to the Central Nervous System.

Adeno-associated virus (AAV) is a non-pathogenic virus that mainly infects primates with the help of adenoviruses. AAV is being widely used as a delivery vector for in vivo gene therapy, as evidenced by five currently approved drugs and more than 255 clinical trials across the world. Due to its relatively low immunogenicity and toxicity, sustained efficacy, and broad tropism, AAV holds great promise for treating many indications, including central nervous system (CNS), ocular, muscular, and liver diseases. However, low delivery efficiency, especially for the CNS due to the blood-brain barrier (BBB), remains a significant challenge for more clinical application of AAV gene therapy. Thus, there is an urgent need for utilizing AAV engineering to discover next-generation capsids with improved properties, e.g., enhanced BBB penetrance, lower immunogenicity, and higher packaging efficiency. AAV engineering methods, including directed evolution, rational design, and in silico design, have been developed, resulting in the discovery of novel capsids (e.g., PhP.B, B10, PAL1A/B/C). In this review, we discuss key studies that identified engineered CNS capsids and/or established methodological improvements. Further, we also discussed important issues that need to be addressed, including cross-species translatability, cell specificity, and modular engineering to improve multiple properties simultaneously.

Evaluating the Utilization of Ethylenediaminetetraacetic Acid as a Treatment Supplement for Gliomas.

Gliomas are the most common primary tumors of the nervous system, accounting for approximately 81% of brain tumors. The primary treatment for these primary brain tumors, especially those of high grade, is surgical resection with subsequent therapy such as targeted radiotherapy, chemotherapy, or supportive care. In an effort to devise nuanced ways to treat gliomas, studies have examined various chemical agents to expand therapeutic avenues for gliomas. In this study, we investigate the applications of ethylenediaminetetraacetic acid (EDTA) in the investigation and treatment of gliomas. Searches were conducted on PubMed to find studies about the use of EDTA in the treatment of glioma. We identified 36 studies that had the information needed for analysis. We collected information on the dosage of EDTA, the agent that EDTA was complexed with, the route of administration, the outcome of the EDTA usage, and the type of glioma cells that were involved. In addition, a one-way analysis of variance was performed to identify any relationships between the effect of cell type, study purpose, and year published on dosage. We identified 36 articles that met our inclusion criteria. In-vitro studies utilized EDTA in various complexes to evaluate cellular viability, including proliferation and toxicity, intracellular enzyme kinetics, and intercellular interactions such as chelation and cellular aggregation. In-vivo studies predominantly utilized the versatile nature of EDTA as a tracer for imaging studies involved in diagnostics and identifying recurrent tumor growth and localization in human patients. Our statistical analysis failed to identify any significant relationships between cell type, study purpose, and publication year on EDTA dosage. We identified a variety of uses for EDTA in the investigation hopefully providing physicians with information regarding the context and applications of EDTA to assist in exploring new treatment options for glioma patients.

A Review of the Usage and Post-surgical Outcomes of Anesthesia for Laser In Situ Keratomileusis (LASIK) Procedure.

When laser in situ keratomileusis (LASIK) surgery is employed for myopia, hyperopia, and astigmatism, the process requires the usage of anesthetics to ensure that there is minimal patient harm and negative consequences once the procedure is complete. Statistical analysis was conducted as part of this review to evaluate the application of and distinctions between the different analgesics used for LASIK surgery by compiling and filtering information from multiple research studies. Topically administered oxybuprocaine and proparacaine were found to be the most commonly used anesthetics for LASIK, according to the data included in the review. It was also determined that there were no significant differences in terms of patient outcomes and drug concentrations when proparacaine was substituted for oxybuprocaine. This is particularly intriguing given their different chemical compositions. Temporary dry eyes were the most commonly reported adverse effect of LASIK when the anesthetic was employed. Perhaps cocaine derivatives produce similar anesthetic and post-surgical effects, but further investigations are needed to verify this hypothesis.

Evaluating the Reliability of Neurological Pupillary Index as a Prognostic Measurement of Neurological Function in Critical Care Patients.

Background Neurological pupil index (NPi) is a novel method of assessing pupillary size and reactivity using pupillometry to reduce human subjectivity. This paper aims to evaluate the use of NPi as a potential prognostic tool in a broad population of neurocritical care patients by observing the correlation between NPi, modified Rankin Scale (mRS), and Glasgow Coma Scale (GCS). Methods Our data was collected from 194 patients in the neurosurgical intensive care unit (ICU) at Arrowhead Regional Medical Center (ARMC), as determined by the power calculation. We utilized the Kolmogorov-Smirnova and Shapiro-Wilk normality tests with Lilliefors significance correction. Pearson product-moment correlation was performed between average final NPi and final GCS. Multi-variate linear regression and analysis of variance (ANOVA) were used to evaluate the association and predictive capabilities of NPi on GCS and discharge mRS. Finally, we evaluated whether age, ethnicity, sex, length of stay (LOS), or discharge location were significantly associated with NPi.  Results We observed a significant correlation between final GCS and NPi (r=0.609, p<0.001). Our regression analysis revealed that NPi significantly predicted GCS and mRS scores; however, no associations were found between age, ethnicity, sex, LOS, or discharge location. Limitations of our study include a single institutional study with a lack of disease subtyping and the inability to quantify the predictive ability of NPi. Conclusion The analysis revealed a strong correlation between final GCS and average final NPi. NPi was also able to significantly predict GCS and mRS scores. The correlation between NPi and established methods to determine neurological function, such as mRS and GCS, suggests that NPi can be a good prognostication tool for neurological diseases.

Deep Brain Stimulation Surgery Using a Mobile Intraoperative CT Scanner.

Introduction Deep brain stimulation (DBS) is widely used for the treatment of movement disorders. Precise placement of electrodes is critical for treatment success. The aim of this study was to analyze the accuracy of the intraoperative computer tomography (CT) images compared to that of a traditional fixed CT for patients undergoing DBS procedures. Methods We retrospectively analyzed the charts from 30 patients who underwent DBS. In group 1, 10 patients underwent electrode implantation surgery using a fixed CT scanner for pre- and post-operative (OP) images. In group 2, 20 patients underwent surgery using an intraoperative CT scanner for pre- and post-operative images, as well as a fixed CT scanner for post-operative images. We compared the average pre-operative localizer box registration error acquired in these two groups. We also analyzed, in group 2, the final electrode position given on each post-operative CT images. We compared the average Euclidean distances between each set of cartesian coordinates to assess target accuracy between both scanning methodologies. Results Thirty patients had ages ranging from 40 to 88 years, with a median of 69 years old. In the 20 patients who utilized an intraoperative CT scanner pre-operatively in group 2, the mean error, given by the Medtronic software (Medtronic Minimally Invasive Therapies, Minneapolis, MN) with the Leksell frame on, was 0.37. For the 10 pre-operative scans with the stealth fixed CT scanner in group 1, the mean error was 0.44 (p = 0.13). In group 2, the average of the 20 Euclidean distances for each target, in those 20 patients who had post-operative images with both scanners, was 0.36. Conclusion We concluded that the accuracy of the intraoperative CT scanner is comparable to the gold standard fixed CT scanner for DBS electrode planning and placement, as well as for positioning confirmation after the electrodes are in place.

An Examination of Clopidogrel in the Treatment of Coronary Microvascular Disease.

The ability of clopidogrel (Plavix) to work in tandem with aspirin in a dual therapy strategy to boost the anti-platelet therapeutic impact and diminish platelet aggregation induced by platelet receptor inhibition is one of its many key advantages. The researchers discovered that the average reduction in risk of adverse cardiovascular events related to Plavix much outweighed any potential systemic effects. The analysis also revealed that, even though treatment results for diabetic patients with coronary microvascular disease (CMD) are poorer, the dosage and administration of clopidogrel for dual therapy are not modified to address this issue. Although it has been established that the current standard of care for microvascular disease decreases damage, more study is necessary to ensure that this standard is enhanced. It may become more usual in the future to include patient groups in trials who do not have diabetes as a criterion. Patients with diabetes often have higher low-density lipoprotein (LDL) cholesterol levels than the general population, therefore, it is possible that the research findings are flawed. To confirm or reject this assumption, further research is necessary.