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Meningiomas are the most common intracranial lesions and constitute one-third of diagnoses. Surgical resection is the gold-standard treatment option. In case of treatment failure, therapeutic options are limited. Bevacizumab is a vascular endothelial growth factor ligand-binding monoclonal antibody that prevents angiogenesis. This study aims to investigate the efficacy and feasibility of bevacizumab in meningiomas On December 30, 2023, a systematic search was conducted according to PRISMA guidelines using the PubMed, Scopus, Web of Science, and Embase databases. This study is conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart. Our study included 12 studies, comprising 243 individuals and 310 tumors. Most of the studies were retrospective (80%). Most of the patients were male (47.9%). The bevacizumab was mostly administered intravenously at 10 mg/kg every two weeks (77.8%). The mean progression-free survival (PFS) and overall survival (OS) were 19.1 ± 4.7 and 23.9 ± 8.4 months, respectively. The response rate was 0.33 (95%CI: 0.14–0.60). The PFS-6, PFS-12, and PFS-24 were 0.80 (95% CI: 0.64–0.89), 0.66 (95%CI: 0.46–0.82), and 25% (95%CI: 0.16–0.37), respectively. The OS-6, OS-12, and OS-24 were 0.89 (95% CI: 0.80–0.96), 0.86 (95%CI: 0.65–0.95), and 0.48 (95%CI: 0.16–0.82), respectively. The meta-regression identified the total number of individuals, number of tumors, gender, WHO II/III, and prior resection as a possible source of heterogeneity for outcomes. This study highlights the effectiveness of bevacizumab in meningiomas, especially in refractory, high-grade, or neurofibromatosis patients. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Myelomeningocele (MMC) is a prevalent form of neural tube defect. Despite advancements in treatment, MMC still poses significant health risks, including complications leading to chronic disability and mortality. Identifying prognostic risk factors for early outcomes is crucial for tailored intervention strategies. Methods: This prospective study involved newborns and infants diagnosed with MMC who underwent surgery between 2020 and 2023 at Urmia University of Medical Sciences. Demographic data and surgical outcomes were collected, and participants were followed up for six months. Statistical analyses were conducted using descriptive statistics, Chi-Square, and independent t-test. Results: The study included 29 MMC cases, with an incidence rate of 1.4 per 10,000 live births. Lesions were predominantly located in the lumbar spine. Although mortality rates appeared to increase with ascending lesion sites, this trend was not statistically significant. Short-term outcomes revealed high morbidity and mortality rates, with neurological deficits being the most prevalent complication. Multivariable analysis identified head circumference as a significant predictor of adverse outcomes (IRR = 1.37, 95% CI = 1.02 to 1.86, p = 0.04). Furthermore, an increase in birth weight was associated with a reduction in the incidence of requiring a ventriculoperitoneal shunt (IRR = 0.99, 95% CI = 0.998 to 0.999, p = 0.02). Conclusion: This prospective study highlights prognostic risk factors for early outcomes in MMC patients, emphasizing the need for personalized intervention strategies. By addressing modifiable risk factors and implementing targeted interventions, healthcare providers can strive to improve outcomes and enhance the quality of life for MMC patients. [ABSTRACT FROM AUTHOR]

Regeneration of the sciatic nerve is a sophisticated process that involves the interplay of several signaling pathways that orchestrate the cellular responses critical to regeneration. Among the key pathways are the mitogen-activated protein kinase (MAPK), phosphatidylinositol 3-kinase (PI3K)/AKT, cyclic adenosine monophosphate (cAMP), and Janus kinase/signal transducers and transcription activators (JAK/STAT) pathways. In particular, the cAMP pathway modulates neuronal survival and axonal regrowth. It influences various cellular behaviors and gene expression that are essential for nerve regeneration. MAPK is indispensable for Schwann cell differentiation and myelination, whereas PI3K/AKT is integral to the transcription, translation, and cell survival processes that are vital for nerve regeneration. Furthermore, GTP-binding proteins, including those of the Ras homolog gene family (Rho), regulate neural cell adhesion, migration, and survival. Notch signaling also appears to be effective in the early stages of nerve regeneration and in preventing skeletal muscle fibrosis after injury. Understanding the intricate mechanisms and interactions of these pathways is vital for the development of effective therapeutic strategies for sciatic nerve injuries. This review underscores the need for further research to fill existing knowledge gaps and improve therapeutic outcomes.Highlights: Sciatic nerve regeneration relies on complex signaling networks, including neurotrophic factors, cytokines, extracellular matrix components, and intracellular signaling cascades. This review highlights the critical role of signaling pathways in coordinating sciatic nerve regeneration. There is a need for further research to better understand these pathways and develop targeted therapies. The potential to improve sciatic nerve injury treatments involves a focus on specific signaling pathways. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is one of the deadliest cancers worldwide with low survival rates and poor outcomes. The treatment landscape for PC is fraught with obstacles, including drug resistance, lack of effective targeted therapies and the immunosuppressive tumor microenvironment (TME). The resistance of PC to existing immunotherapies highlights the need for innovative approaches, with the TME emerging as a promising therapeutic target. The recent advancements in understanding the role of macrophages, this context highlight their significant impact on tumor development and progression. There are two important types of macrophages: M1 and M2, which play critical roles in the TME. Therapeutics strategies including, depletion of tumor-associated macrophages (TAMs), reprogramming TAMs to promote anti-tumor activity, and targeting macrophage recruitment can lead to promising outcomes. Targeting macrophage-related pathways may offer novel strategies for modulating immune responses, inhibiting angiogenesis, and overcoming resistance to chemotherapy in PC treatment. [ABSTRACT FROM AUTHOR]

Bevacizumab, temozolomide (TMZ), and radiotherapy are three therapeutic methods, but the combination of them as a new approach for the treatment of newly diagnosed high-grade gliomas (HGGs) is still under investigation. Therefore, this study aims to evaluate the safety, efficacy, and clinical utility of this treatment approach for patients with glioblastoma (GBM). PubMed/Medline, Scopus, Embase, and Web of Science were systematically reviewed from inception to 24 August 2023. Relevant studies evaluating the therapeutic effect of adding Bevacizumab to TMZ-based chemotherapy and radiation therapy were enrolled. All statistical analysis was performed using the "meta" package of R. A total of 21 studies were included in this study. Our meta-analysis found that adding bevacizumab to standard therapy improved progression-free survival (PFS) in patients with newly diagnosed GBM. The pooled 6-month PFS rate was significantly higher with bevacizumab (79% vs. 56%, odds ratio 3.17). Overall survival (OS) showed modest improvements, with 2-year OS rates of 39% vs. 20% favoring bevacizumab. Radiological response rates varied, with a pooled overall response rate of 44% for bevacizumab-treated patients. The complete response rate was 16%, partial response 32%, and progressive disease 25%. Adverse events occurred in 62% of bevacizumab-treated patients. Common complications included fatigue, thrombocytopenia, and thromboembolic events. When added to standard therapy, bevacizumab demonstrates modest improvements in PFS and OS for newly diagnosedGBM. While it shows promise in short-term outcomes and radiological responses, long-term survival benefits remain limited. The risk of adverse events, particularly CNS hemorrhage, necessitates careful patient selection. These findings suggest that bevacizumab may have a role in treating high-grade gliomas, but its use should be individualized based on patient characteristics and risk-benefit assessment. [ABSTRACT FROM AUTHOR]

Melanoma brain metastases present a major challenge in cancer treatment and reduce overall survival despite advances in managing primary melanoma. Immune checkpoint inhibitors (ICIs) that target PD-1/PD-L1 pathways have shown promise in treating advanced melanoma, but their efficacy for melanoma brain metastases is debated. This systematic review and meta-analysis summarize evidence on anti-PD-1/PD-L1 inhibitors for melanoma brain metastases. This systematic review and meta-analysis followed PRISMA guidelines. PICO criteria targeted melanoma brain metastasis patients treated with PD-1/PD-L1 inhibitors, assessing overall survival, progression-free survival, and complications. Inclusion criteria were English studies on humans using PD-1/PD-L1 inhibitors for melanoma brain metastases with > 10 patients. A total of 22 trials involving 1523 melanoma brain metastase patients treated with anti-PD-1/PD-L1 inhibitors were thoroughly analyzed. Our findings show the 6-month OS rate of 0.75 [95%CI:0.67–0.84], the 6-months PFS rate of 0.42 [95%CI:0.31–0.52], the 1-year OS rate of 0.63 [95%CI:0.52–0.74], the 1-year PFS rate was 0.45 [95%CI:0.32–0.58], the 18-months OS rate of 0.52 [95%CI:0.37–0.67], the 2-year OS rate of 50% [95% CI: (34%-65%)], the 2 year PFS rate of 0.36 (95%CI:0.23–0.50), the 3-year OS rate of 0.42 (95%CI:0.17–0.67), the 4-year PFS rate of 0.35 [95%CI:0.08–0.61], the 4-year OS rate of 0.29 [95%CI:0.01–0.56], the 5-year OS rate of 0.29 (95%CI:0.09–0.50), and the 5-year PFS rate of 0.11 (95%CI:0.03–0.19). The combined disease stability rate was 0.13 [95%CI:0.05–0.20], the progressive disease rate was 0.49 [95%CI:0.37–0.62], the partial response rate was 0.14 [95%CI:0.07–0.20], the object response rate was 0.35 [95%CI:0.24–0.46], and the complete response rate was 0.22 [95%CI:0.12–0.32]. In conclusion, our meta-analysis provides compelling evidence supporting the efficacy of PD-1/PD-L1 inhibitors in patients with melanoma brain tumors, as evidenced by favorable survival outcomes and disease control rates. [ABSTRACT FROM AUTHOR]

Recurrent glioblastoma (rGBM) is a brain tumor that is resistant to standard treatments. Although stereotactic radiosurgery (SRS) is a non-invasive radiation technique, it cannot fully prevent tumor recurrence and progression. Bevacizumab blocks tumor blood supply and has been approved for rGBM. However, the best way to combine SRS and bevacizumab is still unclear. We did a systematic review and meta-analysis of studies comparing SRS alone and SRS plus bevacizumab for rGBM. We searched three databases for articles published until June 2023. All statistical analysis was performed by STATA v.17. Our meta-analysis included 20 studies with 926 patients. We found that the combination therapy had a significantly lower rate of overall survival (OS) than SRS alone at 6-month 0.77[95%CI:0.74–0.85] for SRS alone and (100%) for SRS plus bevacizumab. At 1-year OS, 0.39 [95%CI: 0.32–0.47] for SRS alone and 0.61 [95%CI:0.44–0.77] for SRS plus bevacizumab (P-value:0.02). However, this advantage was not seen in the long term (18 months and two years). Additionally, the combination therapy had lower chances of progression-free survival (PFS) than SRS alone at the 6-month and 1-year time points, but the differences were insignificant. Our study indicates that incorporating bevacizumab with SRS may lead to a short-term increase in OS for rGBM patients but not long-term. Additionally, the PFS rate did not show significant improvement in the group receiving combination therapy. Further clinical trials are necessary to validate the enhanced overall survival with combination therapy for rGBM. [ABSTRACT FROM AUTHOR]

Background: Stereotactic radiosurgery is the preferred option for treating brain arteriovenous malformation (AVM) when the risks associated with surgery outweigh the potential benefits. However, some patients require repeat radiosurgery due to residual AVM after the first procedure. This systematic review and meta-analysis aimed to investigate the safety and efficacy of repeated procedure of radiosurgery for AVM. Method: A systematic review was conducted according to the PRISMA guideline. The search was conducted on PubMed, Scopus, Embase, and Web of Science, using a pre-designed search string. Studies investigating the efficacy of repeat radiosurgery for residual AVM following initial single session radiosurgery were included. The risk of bias was assessed using the JBI tool. Meta-analysis and met-regression were performed to pool and inspect data. Results: Our meta-analysis, with a mean follow-up of 45.57 months, reveals repeat radiosurgery as a viable option for arteriovenous malformations (AVMs), achieving a 60.82% obliteration rate with a mean time to obliteration of 33.18 months. Meta-regression identifies AVM volume and Spetzler-Martin (SM) grade as factors influencing obliteration, with smaller volume and lower SM grades associated with higher rates. Complications include 10.33% radiation-induced changes, 5.26% post-radiosurgery hemorrhage, 2.56% neurologic deficits, and 0.67% cyst formation. Heterogeneity in complications is primarily attributed to male proportion and SM grade, while factors influencing post-radiosurgery hemorrhage remain unclear. The type of radiosurgery, whether Gamma Knife Radiosurgery (GKRS) or LINAC, does not significantly impact outcomes. Conclusion: Repeat radiosurgery is a feasible, effective, and safe treatment for AVMs following failure of initial radiosurgery. When utilized in appropriate patient subgroups, it provides an acceptable risk-to-benefit profile. Feature studies are required to clarify its clear indications. [ABSTRACT FROM AUTHOR]

Background: Dabrafenib and trametinib represent targeted therapy options under investigation for treatment of gliomas harboring BRAF V600 mutations. We systematically reviewed the literature and conducted meta-analyses to assess the efficacy and safety of these agents. Methods: PubMed, Embase, and Scopus were searched from inception to September 2023 for studies examining dabrafenib and/or trametinib for gliomas. Outcomes included response rates (ORR, CR, PR), progression rates (PD), 6- and 12-month PFS, adverse events, and dosing modifications. Meta-analyses were conducted using random effect models. Results: Nine studies met the inclusion criteria. Meta-analysis demonstrated overall response rates (ORR) of 50% (95% confidence interval (CI): 35–65%) for low-grade gliomas (LGG) and 40% (95% CI: 29–51%) for high-grade gliomas (HGG). Pooled ORR was 45% (95% CI: 36–54%) for both glioma grades. The complete response rate was 13% (95% CI: 05–27%) for HGG and 5% (95% CI: 1–10%) for both LGG and HGG. Six-month progression-free survival (PFS) rates reached 87% in LGG and 67% in HGG and a pooled 6-month PFS 78% (95% CI: 58–98%), declining at 12 months to 67% and 44%, respectively, with a pooled 12-month PFS 56% (95% CI: 34–79%). Grade 1–4 adverse events occurred in 100% of LGG and 63% of HGG patients. Conclusions: Dabrafenib and trametinib demonstrate promising anti-tumor efficacy in gliomas, particularly low-grade tumors, achieving durable disease stabilization in many patients. However, toxicity significantly limited tolerability. Additional research should further examine efficacy and refine safe administration protocols across glioma subtypes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

There are two controversial surgery methods which are traditionally used: craniotomy and decompressive craniectomy. The aim of this study was to evaluate the efficacy and complications of DC versus craniotomy for surgical management in patients with acute subdural hemorrhage (SDH) following traumatic brain injury (TBI). We conducted a comprehensive search on PubMed, Scopus, Web of Science, and Embase up to July 30, 2023, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Relevant articles were reviewed, with a focus on studies comparing decompressive craniectomy to craniotomy techniques in patients with SDH following TBI. Ten studies in 2401 patients were reviewed. A total of 1170 patients had a craniotomy, and 1231 had decompressive craniectomy. The mortality rate was not significantly different between the two groups (OR: 0.46 [95% CI: 0.42–0.5] P-value: 0.07). The rate of revision surgery was insignificantly different between the two groups (OR: 0.59 [95% CI: 0.49–0.69] P-value: 0.08). No significant difference was found between craniotomy and decompressive craniectomy regarding unilateral mydriasis (OR: 0.46 [95% CI: 0.35–0.57] P-value < 0.001). However, the craniotomy group had significantly lower rates of non-pupil reactivity (OR: 0.27 [95% CI: 0.17–0.41] P-value < 0.001) and bilateral mydriasis (OR: 0.59 [95% CI: 0.5–0.66] P-value: 0.04). There was also no significant difference in extracranial injury between the two groups, although the odds ratio of significant extracranial injury was lower in the craniotomy group (OR: 0.58 [95% CI: 0.45–0.7] P-value: 0.22). Our findings showed that non-pupil and bilateral-pupil reactivity were significantly more present in decompressive craniectomy. However, there was no significant difference between the two groups regarding mortality rate, extracranial injury, revision surgery, and one-pupil reactivity. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Rheumatoid arthritis (RA) is a chronic, progressive, and systemic disease that broadly affects connective tissues, especially synovial joints. The aim of this study was to investigate the prevalence of cervical spine instability in patients diagnosed with RA. Material and methods: Fifty patients with rheumatoid arthritis referred to Imam Khomeini Hospital in Urmia were selected by the census. After taking a history, the neck X-ray was taken from the lateral view in static, flexion, and extension. Results: Among 50 patients, 11 were male (22%) and 39 were female (78%). The average disease duration period was 5.63 ± 5.21 years. 43 patients (86%) had normal AADI, 5 patients (10%) had abnormal dynamic AADI, and 2 patients (4%) had abnormal AADI static. Basilar invagination instability was not found in the studied patients. There was no significant difference in terms of gender between normal and abnormal cases of AADI. Among normal AADI cases, 40 cases (93%) were taking drugs and among abnormal AADI cases, 4 cases (57.1%) were taking drugs and 3 patients (42.9%) were not receiving drug treatment. There is a significant difference between normal and abnormal cases of AADI in terms of drug use. Conclusions: In our study, 7 cases of abnormal AADI were found among 50 patients, of which 2 had abnormal static AADI, which indicates the worsening of cervical spine instability. The study also found that those not treated with DMARDS were more likely to have cervical spine instability. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) has been associated with nervous system involvement, with more than one-third of COVID-19 patients experiencing neurological manifestations. Utilizing a systematic review, this study aims to summarize brain MRI findings in COVID-19 patients presenting with neurological symptoms. Methods: Systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist. The electronic databases of PubMed/MEDLINE, Embase, Scopus, and Web of Science were systematically searched for literature addressing brain MRI findings in COVID-19 patients with neurological symptoms. Results: 25 publications containing a total number of 3118 COVID-19 patients with neurological symptoms who underwent MRI were included. The most common MRI findings and the respective pooled incidences in decreasing order were acute/subacute infarct (22%), olfactory bulb abnormalities (22%), white matter abnormalities (20%), cerebral microbleeds (17%), grey matter abnormalities (12%), leptomeningeal enhancement (10%), ADEM (Acute Disseminated Encephalomyelitis) or ADEM-like lesions (10%), non-traumatic ICH (10%), cranial neuropathy (8%), cortical gray matter signal changes compatible with encephalitis (8%), basal ganglia abnormalities (5%), PRES (Posterior Reversible Encephalopathy Syndrome) (3%), hypoxic-ischemic lesions (4%), venous thrombosis (2%), and cytotoxic lesions of the corpus callosum (2%). Conclusion: The present study revealed that a considerable proportion of patients with COVID-19 might harbor neurological abnormalities detectable by MRI. Among various findings, the most common MRI alterations are acute/subacute infarction, olfactory bulb abnormalities, white matter abnormalities, and cerebral microbleeds. [ABSTRACT FROM AUTHOR]

Introduction: COVID-19 can result in an extensive range of extrapulmonary, and neurological signs and symptoms such as olfactory and/or taste dysfunction, and otologic symptoms. The aim of this study was to investigate the hearing loss manifestation from COVID-19. Methods: The goal of this umbrella review was to examine hearing loss associated with COVID-19 disease. English literature published until October 15, 2022 in online databases including PubMed, Scopus, Web of Science, and Embase was considered for this purpose. Eligibility of the articles for subsequent data extraction was evaluated in a two-step selection process with consideration to an inclusion/exclusion criterion. This review followed the PRISMA protocol and the Amstar-2 checklist for quality assessment. Results: A total of four treatment strategies were used by different studies which included oral corticosteroids, intratympanic corticosteroids, combined oral and intratympanic corticosteroids, and hyperbaric oxygen therapy. Five studies investigated corticosteroid use in the forms of oral or intratympanic injection; four studies reported (complete or partial) hearing improvements after steroid treatment, while one study stated no significant improvement in hearing function. One study reported that oral corticosteroid monotherapy alone was not effective, while vestibular symptoms were ameliorated by a combination of oral prednisone, intratympanic dexamethasone injection, and hydroxychloroquine. Conclusion: The findings suggest that despite being one of the rare complications of COVID-19, hearing loss can impact a patient's quality of life. The most common type reported was sensorineural hearing loss, which can be diagnosed with variable techniques. [ABSTRACT FROM AUTHOR]

Introduction: The Omicron variant of COVID-19 is highly transmissible, triggering unprecedented infection rates. The present study aimed to investigate the course of multiple sclerosis (MS) in the Omicron era among Iranian patients with MS. Methods: This observational study was designed on MS patients of the national MS registry of Iran through a self-designed online questionnaire. A questionnaire was prepared as a Google Form for MS patients during the Omicron outbreak from 1 March to 30 April 2022. Results: One hundred seventy-four patients with a mean age of 37.3 ± 9.04 were enrolled. Of the patients, 95.97% used DMT, the most common of which were rituximab and fingolimod. Of the patients, 77.58% were fully vaccinated for COVID-19. Regardless of the COVID-19 vaccination status, 76 patients developed COVID-19, which was mild to moderate. Except for recent corticosteroid therapy and secondary progressive MS (SPMS), other demographic and MS characteristics were not significantly associated with the severity of COVID-19. There was also a marginal association between the Expanded Disability Status Scale (EDSS) and the severity of COVID-19. In addition, 17.10% of patients reported MS relapse following COVID-19 leading to escalation therapy in eight patients. Conclusion: Our study demonstrated that in the Omicron era, most patients developed mild COVID-19. Although the predominant COVID-19 variant in this period was Omicron, we could not separate the pathogenic variants. The risk factors for COVID-19 during the Omicron era were not different from other pandemic waves. Our preliminary results revealed that the MS relapse following COVID-19 was higher than in previous waves. [ABSTRACT FROM AUTHOR]

Background: Medulloblastoma (MB) is the pediatric population's most frequent malignant intracranial lesions. Prognostication plays a crucial role in optimizing treatment strategy in the MB setting. Several studies have developed ML-based models to predict survival outcomes in individuals with MB. In this systematic review and meta-analysis study, we aimed to evaluate the role of ML-based models in predicting survival in MB patients.Literature records were retrieved on May 14th, 2024, using the relevant key terms without filters in PubMed, Embase, Scopus, and Web of Science. Records were screened according to the eligibility criteria, and the data from the included studies were extracted. The quality assessment was performed using the QUADAS-2 tool. The meta-analysis and sensitivity analysis were conducted using R software.Six studies were included, with 2771 patients ranging from 46 to 1759 individuals. A total of 23 ML and DL models were developed, 20 of which were ML and three DL. Random forest (RF) was the most frequent classifier, as it was utilized in nine models, followed by support vector machine (SVM). Eight models were included in the meta-analysis. Our meta-analysis revealed a pooled AUC of 0.77 (95% CI: 0.75–0.80). In addition, the radionics-based and genomics-based models had a pooled AUC of 0.77 (95% CI: 0.76–079) and 0.76 (0.63–0.88), respectively (P = 0.77).Our results suggested that ML-based models, especially ML algorithms, could play a vital and efficient role in the prediction of survival of patients based on radiomics and genomics.Method: Medulloblastoma (MB) is the pediatric population's most frequent malignant intracranial lesions. Prognostication plays a crucial role in optimizing treatment strategy in the MB setting. Several studies have developed ML-based models to predict survival outcomes in individuals with MB. In this systematic review and meta-analysis study, we aimed to evaluate the role of ML-based models in predicting survival in MB patients.Literature records were retrieved on May 14th, 2024, using the relevant key terms without filters in PubMed, Embase, Scopus, and Web of Science. Records were screened according to the eligibility criteria, and the data from the included studies were extracted. The quality assessment was performed using the QUADAS-2 tool. The meta-analysis and sensitivity analysis were conducted using R software.Six studies were included, with 2771 patients ranging from 46 to 1759 individuals. A total of 23 ML and DL models were developed, 20 of which were ML and three DL. Random forest (RF) was the most frequent classifier, as it was utilized in nine models, followed by support vector machine (SVM). Eight models were included in the meta-analysis. Our meta-analysis revealed a pooled AUC of 0.77 (95% CI: 0.75–0.80). In addition, the radionics-based and genomics-based models had a pooled AUC of 0.77 (95% CI: 0.76–079) and 0.76 (0.63–0.88), respectively (P = 0.77).Our results suggested that ML-based models, especially ML algorithms, could play a vital and efficient role in the prediction of survival of patients based on radiomics and genomics.Results: Medulloblastoma (MB) is the pediatric population's most frequent malignant intracranial lesions. Prognostication plays a crucial role in optimizing treatment strategy in the MB setting. Several studies have developed ML-based models to predict survival outcomes in individuals with MB. In this systematic review and meta-analysis study, we aimed to evaluate the role of ML-based models in predicting survival in MB patients.Literature records were retrieved on May 14th, 2024, using the relevant key terms without filters in PubMed, Embase, Scopus, and Web of Science. Records were screened according to the eligibility criteria, and the data from the included studies were extracted. The quality assessment was performed using the QUADAS-2 tool. The meta-analysis and sensitivity analysis were conducted using R software.Six studies were included, with 2771 patients ranging from 46 to 1759 individuals. A total of 23 ML and DL models were developed, 20 of which were ML and three DL. Random forest (RF) was the most frequent classifier, as it was utilized in nine models, followed by support vector machine (SVM). Eight models were included in the meta-analysis. Our meta-analysis revealed a pooled AUC of 0.77 (95% CI: 0.75–0.80). In addition, the radionics-based and genomics-based models had a pooled AUC of 0.77 (95% CI: 0.76–079) and 0.76 (0.63–0.88), respectively (P = 0.77).Our results suggested that ML-based models, especially ML algorithms, could play a vital and efficient role in the prediction of survival of patients based on radiomics and genomics.Conclusion: Medulloblastoma (MB) is the pediatric population's most frequent malignant intracranial lesions. Prognostication plays a crucial role in optimizing treatment strategy in the MB setting. Several studies have developed ML-based models to predict survival outcomes in individuals with MB. In this systematic review and meta-analysis study, we aimed to evaluate the role of ML-based models in predicting survival in MB patients.Literature records were retrieved on May 14th, 2024, using the relevant key terms without filters in PubMed, Embase, Scopus, and Web of Science. Records were screened according to the eligibility criteria, and the data from the included studies were extracted. The quality assessment was performed using the QUADAS-2 tool. The meta-analysis and sensitivity analysis were conducted using R software.Six studies were included, with 2771 patients ranging from 46 to 1759 individuals. A total of 23 ML and DL models were developed, 20 of which were ML and three DL. Random forest (RF) was the most frequent classifier, as it was utilized in nine models, followed by support vector machine (SVM). Eight models were included in the meta-analysis. Our meta-analysis revealed a pooled AUC of 0.77 (95% CI: 0.75–0.80). In addition, the radionics-based and genomics-based models had a pooled AUC of 0.77 (95% CI: 0.76–079) and 0.76 (0.63–0.88), respectively (P = 0.77).Our results suggested that ML-based models, especially ML algorithms, could play a vital and efficient role in the prediction of survival of patients based on radiomics and genomics. 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