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INTRODUCTION: Hydrocephalus treatment can be very challenging. While some hydrocephalic patients can be treated endoscopically, many will require ventricular shunting. Frequent shunt issues over a lifetime is not uncommon. Although most shunt malfunctions are of the ventricular catheter or valve, distal failures occur as well. A subset of patients will accumulate non-functioning distal drainage sites. CASE DESCRIPTION: We present a 27-year-old male with developmental delay who was shunted perinatally for hydrocephalus from intraventricular hemorrhage of prematurity. After failure of the peritoneum, pleura, superior vena cava (SVC), gallbladder, and endoscopy, an inferior vena cava (IVC) shunt was placed minimally-invasively via the common femoral vein. We believe this is only the eighth reported ventriculo-inferior-venacaval shunt. IVC occlusion years later was successfully treated with endovascular angioplasty and stenting followed by anticoagulation. To our knowledge, a ventriculo-inferior-venacaval shunt salvaged by endovascular surgery has not been previously described in the literature. CONCLUSION: After failure of the peritoneum, pleura, SVC, gallbladder, and endoscopy, IVC shunt placement is an option. Subsequent IVC occlusion can be rescued by endovascular angioplasty and stenting. Anticoagulation after stenting (and potentially after initial IVC placement) is advised.
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Glioblastoma multiforme (GBM) is an aggressive cancer that has been difficult to treat and often requires multimodal therapy consisting of surgery, radiotherapy, and chemotherapy. Chimeric antigen receptor-expressing (CAR-T) cells have been efficacious in treating hematological malignancies, resulting in several FDA-approved therapies. CAR-T cells have been more recently studied for the treatment of GBM, with some promising preclinical and clinical results. The purpose of this literature review is to highlight the commonly targeted antigens, results of clinical trials, novel modifications, and potential solutions for challenges that exist for CAR-T cells to become more widely implemented and effective in eradicating GBM.
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BACKGROUND: Glioblastoma is the most common malignant brain tumor, and thus it is important to be able to identify patients with this diagnosis for population studies. However, this can be challenging as diagnostic codes are nonspecific. The aim of this study was to create a computable phenotype (CP) for glioblastoma multiforme (GBM) from structured and unstructured data to identify patients with this condition in a large electronic health record (EHR). METHODS: We used the University of Florida (UF) Health Integrated Data Repository, a centralized clinical data warehouse that stores clinical and research data from various sources within the UF Health system, including the EHR system. We performed multiple iterations to refine the GBM-relevant diagnosis codes, procedure codes, medication codes, and keywords through manual chart review of patient data. We then evaluated the performances of various possible proposed CPs constructed from the relevant codes and keywords. RESULTS: We underwent six rounds of manual chart reviews to refine the CP elements. The final CP algorithm for identifying GBM patients was selected based on the best F1-score. Overall, the CP rule "if the patient had at least 1 relevant diagnosis code and at least 1 relevant keyword" demonstrated the highest F1-score using both structured and unstructured data. Thus, it was selected as the best-performing CP rule. CONCLUSIONS: We developed and validated a CP algorithm for identifying patients with GBM using both structured and unstructured EHR data from a large tertiary care center. The final algorithm achieved an F1-score of 0.817, indicating a high performance, which minimizes possible biases from misclassification errors.