Alzheimer’s disease (AD) presents a significant challenge to global health. It is characterized by progressive cognitive deterioration and increased rates of morbidity and mortality among older adults. Among the various pathophysiologies of AD, mitochondrial dysfunction, encompassing conditions such as increased reactive oxygen production, dysregulated calcium homeostasis, and impaired mitochondrial dynamics, plays a pivotal role. This review comprehensively investigates the mechanisms of mitochondrial dysfunction in AD, focusing on aspects such as glucose metabolism impairment, mitochondrial bioenergetics, calcium signaling, protein tau and amyloid-beta-associated synapse dysfunction, mitophagy, aging, inflammation, mitochondrial DNA, mitochondria-localized microRNAs, genetics, hormones, and the electron transport chain and Krebs cycle. While lecanemab is the only FDA-approved medication to treat AD, we explore various therapeutic modalities for mitigating mitochondrial dysfunction in AD, including antioxidant drugs, antidiabetic agents, acetylcholinesterase inhibitors (FDA-approved to manage symptoms), nutritional supplements, natural products, phenylpropanoids, vaccines, exercise, and other potential treatments.

Chronic subdural hematoma (cSDH) is a common neurosurgical condition that can cause severe morbidity and mortality. cSDH recurs after surgical evacuation in 5–30% of patients, but drains may help reduce this risk. We aimed to investigate the effect of drainage versus no drainage on the rates of recurrence and mortality, as well as the clinical outcomes of cSDH. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched four electronic databases (PubMed, Cochrane Library, Scopus, and Web of Science) to identify eligible studies reported up to June 2022. Using Review Manager software, we reported four primary outcomes as odds ratios (ORs) and confidence intervals (CIs). The meta-analysis included a total of 10 studies with 1961 patients. The use of drainage was found to be significantly more effective than non-drainage in reducing the “mortality rate” (OR = 0.65, 95% CI 0.43 to 0.97; P = 0.04), the “recurrence rate” (OR = 0.39, 95% CI 0.28 to 0.55; P < 0.00001), and occurrence of “gross focal neurological deficit” (OR = 0.58, 95% CI 0.37 to 0.89; P = 0.01). No significant difference was found in the occurrence of a Glasgow Coma Scale score of 15 (OR = 1.21, 95% CI 0.84 to 1.76; P = 0.30). The use of drains after burr-hole irrigation reduces the recurrence, mortality, and gross focal neurological deficit rates of chronic subdural hematomas.

Background: Chronic subdural hematoma (CSDH) is a prevalent type of intracranial hemorrhage. Surgical interventions, such as Twist Drill Craniostomy and Burr Hole Craniostomy, are employed for its treatment. However, limited information exists regarding the impact of postoperative head position (supine vs. elevated) on clinical outcomes. We aim to assess whether patients’ head position after surgery influences their prognosis. Method: We conducted a PRISMA-compliant systematic review and meta-analysis. Our search encompassed PubMed, Cochrane CENTRAL, Scopus, Web of Science, and Embase databases to identify relevant published studies. Data were meticulously extracted, pooled using a fixed model, and reported as risk ratios (RR) with 95% confidence intervals (CI). Statistical analysis was performed using R and Stata MP v.17. Results: Five studies involving 284 patients were included in our meta-analysis. We focused on three primary clinical outcomes, comparing the supine and elevated header positions. Notably, there was no statistically significant difference between the supine and elevated positions in terms of recurrence rate (RR 0.77, 95% CI [0.44, 1.37]), second intervention for recurrence (RR 1.07, 95% CI [0.42, 2.78]) and postoperative complications (RR 1.16, 95% CI [0.70, 1.92]). Conclusion: Current studies have proved no difference between supine and elevated bed header positions regarding recurrence rate, second intervention for recurrence, and postoperative complications. Future RCTs with long-term follow-ups are recommended.

The implementation of artificial intelligence (AI), particularly Viz.ai software in stroke care, has emerged as a promising tool to enhance the detection of large vessel occlusion (LVO) and to improve stroke workflow metrics and patient outcomes. The aim of this systematic review and meta-analysis is to evaluate the impact of Viz.ai on stroke workflow efficiency in hospitals and on patients’ outcomes. Following the PRISMA guidelines, we conducted a comprehensive search on electronic databases, including PubMed, Web of Science, and Scopus databases, to obtain relevant studies until 25 October 2024. Our primary outcomes were door-to-groin puncture (DTG) time, CT scan-to-start of endovascular treatment (EVT) time, CT scan-to-recanalization time, and door-in–door-out time. Secondary outcomes included symptomatic intracranial hemorrhage (ICH), any ICH, mortality, mRS score < 2 at 90 days, and length of hospital stay. A total of 12 studies involving 15,595 patients were included in our analysis. The pooled analysis demonstrated that the implementation of the Viz.ai algorithm was associated with lesser CT scan to EVT time (SMD −0.71, 95% CI [−0.98, −0.44], p < 0.001) and DTG time (SMD −0.50, 95% CI [−0.66, −0.35], p < 0.001) as well as CT to recanalization time (SMD −0.55, 95% CI [−0.76, −0.33], p < 0.001). Additionally, patients in the post-AI group had significantly lower door−in door-out time than the pre-AI group (SMD −0.49, 95% CI [−0.71, −0.28], p < 0.001). Despite the workflow metrics improvement, our analysis did not reveal statistically significant differences in patient clinical outcomes ( p > 0.05). Our results suggest that the integration of the Viz.ai platform in stroke care holds significant potential for reducing EVT delays in patients with LVO and optimizing stroke flow metrics in comprehensive stroke centers. Further studies are required to validate its efficacy in improving clinical outcomes in patients with LVO.

Background: Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) presents significant treatment challenges due to its chronic nature, varied clinical presentations, and rarity. Subcutaneous immunoglobulin (SCIG) has emerged as a maintenance therapy, offering potential advantages in administration and patient experience over the previously recognized intravenous immunoglobulin (IVIG). Methods: We included all clinical studies involving CIDP patients treated with SCIG from eleven databases up to March 2024. Results: 50 clinical studies were included in the systematic review, with 22 involved in the meta-analysis. These studies offer clinical data on around 1400 CIDP patients. Almost all studies considered SCIG a maintenance therapy, with the majority of results suggesting it as a viable substitute that may offer comparable or enhanced advantages. Studies covered aspects such as efficacy, safety, quality of life, practicality, economic evaluation, and patient preference. Meta-analysis showed SCIG significantly improved muscle strength and sensory function, had fewer and milder side effects, reduced relapse rates, and received a strong preference. Conclusions: Findings suggest that SCIG for CIDP maintenance not only provides a more feasible alternative, with economic evaluations showing considerable cost reductions over time, and patient preference for SCIG being pronounced, but may also deliver comparable or superior health outcomes. Ongoing research lines on formulations, techniques, and direct comparative studies are critical to further illuminate, enhance, and expand SCIG's role in treatment.

Background: Parkinson’s Disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta. PD is diagnosed by a combination of motor symptoms including bradykinesia, resting tremors, rigidity and postural instability. Prodromal PD is the stage preceding the onset of classic motor symptoms of PD. The diagnosis of prodromal PD remains challenging despite many available diagnostic modalities. Aim: This scoping review aims to investigate and explore the current diagnostic modalities used to detect prodromal PD, focusing particularly on multimodal imaging analysis and AI-based approaches. Methods: We adhered to the PRISMA-SR guidelines for scoping reviews. We conducted a comprehensive literature search at multiple databases such as PubMed, Scopus, Web of Science, and the Cochrane Library from inception to July 2024, using keywords related to prodromal PD and diagnostic modalities. We included studies based on predefined inclusion and exclusion criteria and performed data extraction using a standardized form. Results: The search included 9 studies involving 567 patients with prodromal PD and 35,643 control. Studies utilized various diagnostic approaches including neuroimaging techniques and AI-driven models. sensitivity ranging from 43 to 84% and specificity up to 96%. Neuroimaging and AI technologies showed promising results in identifying early pathological changes and predicting PD onset. The highest specificity was achieved by neuromelanin-sensitive imaging model, while highest sensitivity was achieved by standard 10-s electrocardiogram (ECG) + Machine learning model. Conclusion: Advanced diagnostic modalities such as AI-driven models and multimodal neuroimaging revealed promising results in early detection of prodromal PD. However, their clinical application as screening tool for prodromal PD is limited because of the lack of validation. Future research should be directed towards using Multimodal imaging in diagnosing and screening for prodromal PD. Clinical trial number: Not applicable.