Open Access

Along with increasing average life expectancy, the number of elderly meningioma patients has grown proportionally. Our aim was to evaluate whether these specific patients benefit from surgery and to investigate a previously published score for decision-making in meningioma patients (SKALE). Of 421 patients who underwent primary intracranial meningioma resection between 2009 and 2015, 71 patients were ≥70 years of age. We compared clinical data including World Health Organization (WHO) grade, MIB-1 proliferation index, Karnofsky Performance Status Scale (KPS), progression free survival (PFS) and mortality rate between elderly and all other meningioma patients. Preoperative SKALE scores (Sex, KPS, ASA score, location and edema) were determined for elderly patients. SKALE ≥8 was set for dichotomization to determine any association with outcome parameters. In 71 elderly patients (male/female 37/34) all data were available. Postoperative KPS was significantly lower in elderly patients (p < 0.0001). Pulmonary complications including pneumonia (10% vs. 3.2%; p = 0.0202) and pulmonary embolism (12.7% vs. 6%; p = 0.0209) occurred more frequently in our elderly cohort. Analyses of the Kaplan Meier curves revealed differences in three-month (5.6% vs. 0.3%; p = 0.0033), six-month (7% vs. 0.3%; p = 0.0006) and one-year mortality (8.5% vs. 0.3%; p < 0.0001) for elderly patients. Statistical analysis showed significant survival benefit in terms of one-year mortality for elderly patients with SKALE scores ≥8 (5.1 vs. 25%; p = 0.0479). According to our data, elderly meningioma patients face higher postoperative morbidity and mortality than younger patients. However, resection is reasonable for selected patients, particularly when reaching a SKALE score ≥ 8.

Objective: In light of the ongoing COVID-19 pandemic and the associated hospitalization of an overwhelming number of ventilator-dependent patients, medical and/or ethical patient triage paradigms have become essential. While guidelines on the allocation of scarce resources do exist, such work within the subdisciplines of intensive care (e.g., neurocritical care) remains limited. Methods: A 16-item questionnaire was developed that sought to explore/quantify the expert opinions of German neurointensivists with regard to triage decisions. The anonymous survey was conducted via a web-based platform and in total, 96 members of the Initiative of German Neurointensive Trial Engagement (IGNITE)-study group were contacted via e-mail. The IGNITE consortium consists of an interdisciplinary panel of specialists with expertise in neuro-critical care (i.e., anesthetists, neurologists and neurosurgeons). Results: Fifty members of the IGNITE consortium responded to the questionnaire; in total the respondents were in charge of more than 500 Neuro ICU beds throughout Germany. Common determinants reported which affected triage decisions included known patient wishes (98%), the state of health before admission (96%), SOFA-score (85%) and patient age (69%). Interestingly, other principles of allocation, such as a treatment of “youngest first” (61%) and members of the healthcare sector (50%) were also noted. While these were the most accepted parameters affecting the triage of patients, a “first-come, first-served” principle appeared to be more accepted than a lottery for the allocation of ICU beds which contradicts much of what has been reported within the literature. The respondents also felt that at least one neurointensivist should serve on any interdisciplinary triage team. Conclusions: The data gathered in the context of this survey reveal the estimation/perception of triage algorithms among neurointensive care specialists facing COVID-19. Further, it is apparent that German neurointensivists strongly feel that they should be involved in any triage decisions at an institutional level given the unique resources needed to treat patients within the Neuro ICU.

Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy. Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma. Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis. Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches.

Higher grade meningiomas tend to recur. We aimed to evaluate protein levels of vascular endothelial growth factor (VEGF)-A with the VEGF-receptors 1-3 and the co-receptors Neuropilin (NRP)-1 and -2 in WHO grade II and III meningiomas to elucidate the rationale for targeted treatments. We investigated 232 specimens of 147 patients suffering from cranial meningioma, including recurrent tumors. Immunohistochemistry for VEGF-A, VEGFR-1-3, and NRP-1/-2 was performed on tissue micro arrays. We applied a semiquantitative score (staining intensity x frequency). VEGF-A, VEGFR-1-3, and NRP-1 were heterogeneously expressed. NRP-2 was mainly absent. We demonstrated a significant increase of VEGF-A levels on tumor cells in WHO grade III meningiomas (p = 0.0098). We found a positive correlation between expression levels of VEGF-A and VEGFR-1 on tumor cells and vessels (p < 0.0001). In addition, there was a positive correlation of VEGF-A and VEGFR-3 expression on tumor vessels (p = 0.0034). VEGFR-2 expression was positively associated with progression-free survival (p = 0.0340). VEGF-A on tumor cells was negatively correlated with overall survival (p = 0.0084). The VEGF-A-driven system of tumor angiogenesis might still present a suitable target for adjuvant therapy in malignant meningioma disease. However, its role in malignant tumor progression may not be as crucial as expected. The value of comprehensive testing of the ligand and all receptors prior to administration of anti-angiogenic therapy needs to be evaluated in clinical trials.

Glioblastoma (GBM) is a cancer type with high thrombogenic potential and GBM patients are therefore at a particularly high risk for thrombotic events. To date, only limited data on anticoagulation management after pulmonary embolism (PE) in GBM is available and the sporadic use of DOACs remains off-label. A retrospective cohort analysis of patients with GBM and postoperative, thoracic CT scan confirmed PE was performed. Clinical course, follow-up at 6 and 12 months and the overall survival (OS) were evaluated using medical charts and neuroradiological data. Out of 584 GBM patients, 8% suffered from postoperative PE. Out of these, 30% received direct oral anticoagulants (DOACs) and 70% low-molecular-weight heparin (LMWH) for therapeutic anticoagulation. There was no significant difference in major intracranial hemorrhage (ICH), re-thrombosis, or re-embolism between the two cohorts. Although statistically non-significant, a tendency to reduced mRS at 6 and 12 months was observed in the LMWH cohort. Furthermore, patients receiving DOACs had a statistical benefit in OS. In our analysis, DOACs showed a satisfactory safety profile in terms of major ICH, re-thrombosis, and re-embolism compared to LMWH in GBM patients with postoperative PE. Prospective, randomized trials are urgent to evaluate DOACs for therapeutic anticoagulation in GBM patients with PE.