Pipeline Embolization Device (PED) and Flow Re-Direction Endoluminal Device (FRED) for Intracranial Aneurysms; A Comparative Systematic Review and Meta-Analysis Study.

BACKGROUND: When it comes to intracranial aneurysms, the quest for more effective treatments is ongoing. Flow diversion represents a growing advancement in this field. This review seeks to compare two variants of the endovascular flow diversion method: the Flow Re-Direction Endoluminal Device (FRED) and the Pipeline Embolization Device (PED). METHODS: A systematic review was conducted according to the PRISMA guideline using PubMed, Scopus, Web of Science, and Embase, using appropriate terms to compare PED and FRED in double-arm studies from conception until October 8th, 2023. RESULTS: The meta-analysis encompassed 1,769 patients, with a predominance of females (75.5%), among whom 973 patients underwent FRED procedures, while 651 received PED interventions. At six months, complete occlusion rates were 0.62 for FRED and 0.68 for PED (P = 0.68). At one year and the last follow-up, no significant differences were observed between FRED and PED, respectively. Adequate occlusion rates were similar between FRED and PED (0.82 vs 0.79, P = 0.68). FRED showed a statistically significant higher rate of good mRS scores at follow-up (1.00 vs. 0.97, P = 0.03). Hemorrhage and re-treatment rates were higher in PED (P < 0.01) without considering the rupture status of the aneurysms due to the lack of data. CONCLUSION: This meta-analysis suggests comparable efficacy but different safety profiles between FRED and PED in treating intracranial aneurysms. FRED demonstrated a higher rate of good mRS scores, while PED showed increased hemorrhage and re-treatment rates. Understanding these differences is crucial for informed decision-making in clinical practice.

Investigating the Safety and Efficacy of Therapeutic Hypothermia in Pediatric Severe Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

BACKGROUND: Prior guidelines recommended maintaining normothermia following traumatic brain injury (TBI), but recent studies suggest therapeutic hypothermia as a viable option in pediatric cases. However, some others demonstrated a higher mortality rate. Hence, the impact of hypothermia on neurological symptoms and overall survival remains contentious. METHODS: We conducted a systematic review and meta-analysis to evaluate the effects of hypothermia on neurological outcomes in pediatric TBI patients. The PubMed/Medline, Scopus, and Web of Science databases were searched until 1 January 2024 and data were analyzed using appropriate statistical methods. RESULTS: A total of eight studies, comprising nine reports, were included in this analysis. Our meta-analysis did not reveal significant differences in mortality (RR = 1.58; 95% CI = 0.89-2.82, p = 0.055), infection (RR = 0.95: 95% CI = 0.79-1.1, p = 0.6), arrhythmia (RR = 2.85: 95% CI = 0.88-9.2, p = 0.08), hypotension (RR = 1.54: 95% CI = 0.91-2.6, p = 0.10), intracranial pressure (SMD = 5.07: 95% CI = -4.6-14.8, p = 0.30), hospital length of stay (SMD = 0.10; 95% CI = -0.13-0.3, p = 0.39), pediatric intensive care unit length of stay (SMD = 0.04; 95% CI = -0.19-0.28, p = 0.71), hemorrhage (RR = 0.86; 95% CI = 0.34-2.13, p = 0.75), cerebral perfusion pressure (SMD = 0.158: 95% CI = 0.11-0.13, p = 0.172), prothrombin time (SMD = 0.425; 95% CI = -0.037-0.886, p = 0.07), and partial thromboplastin time (SMD = 0.386; 95% CI = -0.074-0.847, p = 0.10) between the hypothermic and non-hypothermic groups. However, the heart rate was significantly lower in the hypothermic group (-1.523 SMD = -1.523: 95% CI = -1.81--1.22 p < 0.001). CONCLUSIONS: Our findings challenge the effectiveness of therapeutic hypothermia in pediatric TBI cases. Despite expectations, it did not significantly improve key clinical outcomes. This prompts a critical re-evaluation of hypothermia's role as a standard intervention in pediatric TBI treatment.

The safety and efficacy of bevacizumab in treatment of recurrent low-grade glioma: a systematic review and meta-analysis.

BACKGROUND: Central nervous system (CNS) tumors are among the most common malignancies in various age ranges. Low-grade glioma (LGG) can account for nearly 30% of pediatric CNS malignancies. Progression or recurrence after the first-line treatments is common among these patients. Therefore, more treatments are required. Bevacizumab as an anti-VEGF antibody has come into the spotlight recently and is especially used in relapse or recurrence settings. This review aims to study the safety and efficacy of bevacizumab for patients with recurrent LGG. METHODS: This study was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PubMed, Scopus, Web of Science, and Embase were comprehensively searched using the relevant key terms until 24th August 2023 to retrieve the studies that investigated clinical outcomes of bevacizumab in patients with recurrent LGG. All statistical analysis was performed by STATA v.17. RESULTS: A total of 1306 papers were gathered, out of which 13 were incorporated in the meta-analysis. The pooled incidence rate of treatment according to the RANO scale was 70% (95% CI = 43-98%) for objective response rate, 26% (95% CI = 58-96%) for partial response, 21% (95% CI = 15-28%) for minor response, 14% (95% CI = 3-24%) for complete response, 48% (95% CI = 37-59%) for stable disease, and 8% (95% CI = 4-11%) for progressive disease. Furthermore, according to progressive survival after treatment, it was 4% (95% CI = -1 to 9%) for 6-month PFS, 41% (95% CI = 32-50%) for 2-year PFS, and 29% (95% CI = 22-35%) for 3-year PFS. CONCLUSION: According to the RANO scale and PFS, clinicians should be aware that Bevacizumab could be a favorable alternative therapy for recurrent LGG. Furthermore, bevacizumab exhibits minimal toxicity and high tolerability in recurrent LGG.

Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide local control, symptom relief, and improved survival rates, but it poses challenges in selecting optimal candidates, determining dose and fractionation, monitoring for toxicity, and integrating with other modalities. Practical tools to predict patient outcomes are also needed. Machine learning (ML) is currently used to predict treatment outcomes. We aim to investigate the accuracy of ML in predicting treatment response and local failure of brain metastasis treated with SRS. METHODS: PubMed, Scopus, Web of Science (WoS), and Embase were searched until April 16th, which was repeated on October 17th, 2023 to find possible relevant papers. The study preparation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The statistical analysis was performed by the MIDAS package of STATA v.17. RESULTS: A total of 17 articles were reviewed, of which seven and eleven were related to the clinical use of ML in predicting local failure and treatment response. The ML algorithms showed sensitivity and specificity of 0.89 (95% CI: 0.84-0.93) and 0.87 (95% CI: 0.81-0.92) for predicting treatment response. The positive likelihood ratio was 7.1 (95% CI: 4.5-11.1), the negative likelihood ratio was 0.13 (95% CI: 0.08-0.19), and the diagnostic odds ratio was 56 (95% CI: 25-125). Moreover, the pooled estimates for sensitivity and specificity of ML algorithms for predicting local failure were 0.93 (95% CI: 0.76-0.98) and 0.80 (95% CI: 0.53-0.94). The positive likelihood ratio was 4.7 (95% CI: 1.6-14.0), the negative likelihood ratio was 0.09 (95% CI: 0.02-0.39), and the diagnostic odds ratio was 53 (95% CI: 5-606). CONCLUSION: ML holds promise in predicting treatment response and local failure in brain metastasis patients receiving SRS. However, further studies and improvements in the treatment process can refine the models and effectively integrate them into clinical practice.

Woven endo bridge device for recurrent intracranial aneurysms: A systematic review and meta-analysis.

BACKGROUND: Recurrent intracranial aneurysms present a significant clinical challenge, demanding innovative and effective treatment approaches. The Woven EndoBridge (WEB) device has emerged as a promising endovascular solution for managing these intricate cases. This study aims to assess the safety and efficacy of the WEB device in treating recurrent intracranial aneurysms. METHODS: We conducted a comprehensive search across multiple databases, including PubMed, Scopus, Embase, and Web of Science, from inception to June 5, 2023. Eligible studies focused on evaluating WEB device performance and included a minimum of five patients with recurrent intracranial aneurysms. The complete and adequate occlusion rates, neck remnant rates, and periprocedural complication rates were pooled using SATA V.17. RESULTS: Our analysis included five studies collectively enrolling 73 participants. Participant ages ranged from 52.9 to 65 years, with 64.4% being female. Aneurysms were wide-necked and predominantly located in the middle cerebral artery, basilar artery, and anterior cerebral artery. Previous treatments encompassed coiling, clipping, and the use of WEB devices. Our study found an overall adequate occlusion rate of 0.80 (95% CI 0.71-0.89), a complete occlusion rate of 0.39 (95% CI 0.28-0.50), and a neck remnant rate of 0.38 (95% CI 0.27-0.48). Periprocedural complications were reported at a rate of 0%, although heterogeneity was observed in this data. Notably, evidence of publication bias was identified in the reporting of periprocedural complication rates. CONCLUSION: Our findings suggest that the WEB device is associated with favorable outcomes for treating recurrent wide-neck intracranial aneurysms.

Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants.

It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning (ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To better understand the importance and effectiveness of ML algorithms in practice, a systematic review and meta-analysis were conducted to predict cerebral aneurysm rupture risk. PubMed, Scopus, Web of Science, and Embase were searched without restrictions until March 20, 2023. Eligibility criteria included studies that used ML approaches in patients with cerebral aneurysms confirmed by DSA, CTA, or MRI. Out of 35 studies included, 33 were cohort, and 11 used digital subtraction angiography (DSA) as their reference imaging modality. Middle cerebral artery (MCA) and anterior cerebral artery (ACA) were the commonest locations of aneurysmal vascular involvement-51% and 40%, respectively. The aneurysm morphology was saccular in 48% of studies. Ten of 37 studies (27%) used deep learning techniques such as CNNs and ANNs. Meta-analysis was performed on 17 studies: sensitivity of 0.83 (95% confidence interval (CI), 0.77-0.88); specificity of 0.83 (95% CI, 0.75-0.88); positive DLR of 4.81 (95% CI, 3.29-7.02) and the negative DLR of 0.20 (95% CI, 0.14-0.29); a diagnostic score of 3.17 (95% CI, 2.55-3.78); odds ratio of 23.69 (95% CI, 12.75-44.01). ML algorithms can effectively predict the risk of rupture in cerebral aneurysms with good levels of accuracy, sensitivity, and specificity. However, further research is needed to enhance their diagnostic performance in predicting the rupture status of IA.