Estimating the global and regional burden of meningitis in children caused by Haemophilus influenzae type b:A systematic review and meta-analysis

BACKGROUND: Haemophilus influenzae Type B (Hib) meningitis caused significant public health concern for children. Recent assessment in 2015 suggests vaccination has virtually eliminated invasive Hib diseases. However, many countries launched their programs after 2010, and few are yet to establish routine Hib immunisations. We therefore aimed to update the most recent global burden of Hib meningitis before the impact of COVID-19 pandemic, from 2010 to 2020, in order to aid future public health policies on disease management and prevention. METHODS: Epidemiological data regarding Hib meningitis in children <5 years old were systematically searched and evaluated from PubMed and Scopus in August, 2020. We included studies published between 2010 and 2019 that reported incidence, prevalence, mortality, or case-fatality-ratio (CFR), and confirmation of meningitis by cerebrospinal fluid culture, with a minimum one year study period and ten cases. Each data was stratified by one study-year. Median study-year was used if information was not available. Quality of all studies were assessed using our adapted assessment criteria from Grading of Recommendations Assessment, Development and Evaluation (GRADE) and Study Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies from National Heart, Lung and Blood Institute (NHLBI). We constructed and visually inspected a funnel plot of standard error by the incidence rate and performed an Egger’s regression test to statistically assess publication bias. To ascertain incidence and CFR, we performed generalised linear mixed models on crude individual study estimates. Heterogeneity was assessed using I-squared statistics whilst further exploring heterogeneity by performing subgroup analysis. RESULTS: 33 studies were identified. Pooled incidence of global Hib meningitis in children was 1.13 per 100 000-child-years (95% confidence interval (CI) = 0.80-1.59). Southeast Asian Region (SEAR) of World Health Organisation (WHO) region reported the highest incidence, and European Region (EUR) the lowest. Considering regions with three or more data, Western Pacific Region (WPR) had the highest incidence rate of 5.22 (95% CI = 3.12-8.72). Post-vaccination incidence (0.67 cases per 100 000-child-years, 95% CI = 0.48-0.94) was dramatically lower than Pre-vaccination incidence (4.84 cases per 100 000-child-years, 95% CI = 2.95-7.96). Pooled CFR in our meta-analysis was 11.21% (95% CI = 7.01-17.45). Eastern Mediterranean Region (EMR) had the highest CFR (26.92, 95% CI = 13.41-46.71) while EUR had the lowest (4.13, 95% CI = 1.73-9.54). However, considering regions with three or more data, African Region (AFR) had the highest CFR at 21.79% (95% CI = 13.65-32.92). Before the coronavirus disease 2019 (COVID-19) impact, the estimation for global Hib meningitis cases in 2020 is 7645 and 857 deaths. CONCLUSIONS: Global burden of Hib meningitis has markedly decreased, and most regions have implemented vaccination programs. Extrapolating population-at-risk from studies has possibly led to an underestimation. Continuous surveillance is necessary to monitor vaccination impact, resurgence, vaccine failures, strain variance, COVID-19 impact, and to track improvement of regional and global Hib meningitis mortality

The role of artificial intelligence in surgical simulation

Artificial Intelligence (AI) plays an integral role in enhancing the quality of surgical simulation, which is increasingly becoming a popular tool for enriching the training experience of a surgeon. This spans the spectrum from facilitating preoperative planning, to intraoperative visualisation and guidance, ultimately with the aim of improving patient safety. Although arguably still in its early stages of widespread clinical application, AI technology enables personal evaluation and provides personalised feedback in surgical training simulations. Several forms of surgical visualisation technologies currently in use for anatomical education and presurgical assessment rely on different AI algorithms. However, while it is promising to see clinical examples and technological reports attesting to the efficacy of AI-supported surgical simulators, barriers to wide-spread commercialisation of such devices and software remain complex and multifactorial. High implementation and production costs, scarcity of reports evidencing the superiority of such technology, and intrinsic technological limitations remain at the forefront. As AI technology is key to driving the future of surgical simulation, this paper will review the literature delineating its current state, challenges, and prospects. In addition, a consolidated list of FDA/CE approved AI-powered medical devices for surgical simulation is presented, in order to shed light on the existing gap between academic achievements and the universal commercialisation of AI-enabled simulators. We call for further clinical assessment of AI-supported surgical simulators to support novel regulatory body approved devices and usher surgery into a new era of surgical education

The use of advanced neuroimaging modalities in the evaluation of low-grade glioma in adults: a literature review

Low-grade gliomas encompass a subgroup of cancerous glial cell growths within the central nervous system and are distinguished by their slow growth and relatively low malignant potential. Despite their less aggressive nature, these tumors can still cause significant neurological symptoms through the compression of surrounding neural and vascular structures and, in some instances, undergo malignant transformation. For these reasons, timely and appropriate evaluation and management of low-grade gliomas is critical. Medical imaging stands as a cornerstone for evaluating patients with low-grade gliomas because of its noninvasive nature and ability to provide a vast amount of information about the underlying lesion. With the growing number of neuroimaging techniques and their capabilities, there is a lack of clear guidance on which techniques to utilize for the assessment of low-grade gliomas and what their respective core use cases should be. In this literature review, the authors discuss in significant depth the available evidence pertaining to the use of advanced neuroimaging techniques in the evaluation and management of low-grade gliomas. Specifically, they review the specificity, sensitivity, accuracy, and use cases of magnetic resonance spectroscopy (MRS), perfusion MR imaging (perfusion MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), single-photon emission computed tomography (SPECT), as well as other emerging imaging techniques. They conclude that most of the advanced neuroimaging techniques are reliable in differentiating low- from high-grade gliomas, whereas MRS and DTI may further support molecular subclassification of the tumor. PET has been best employed for the purpose of tumor biopsy, whereas fMRI and DTI can be particularly valuable in preoperative surgical planning, as they delineate the functionally eloquent brain regions that need to be preserved during tumor resection. MRS, PET, SPECT, and perfusion MRI are best suited to monitor tumor progression, as their respective metrics closely correlate with the underlying metabolic activity of the tumor. Together, these techniques offer a vast amount of information and serve as tools for neurologists and neurosurgeons managing patients with low-grade gliomas

The Utility of Transcranial Electrical Stimulation Motor Evoked Potential Monitoring in Predicting Post-operative Supplementary Motor Area Syndrome and Motor Function Recovery

Postoperative hemiparesis following frontal lobe lesion resection is alarming, and predicting motor function recovery is challenging. Supplementary motor area (SMA) syndrome following resection of frontal lobe lesions is often indistinguishable from post-operative motor deficit due to surgical injury of motor tracts. We aim to describe the use of intra-operative TES (transcranial-electrical stimulation) with MEP (motor evoked potential) monitoring data as a diagnostic tool in distinguishing between SMA syndrome and permanent motor deficit (PMD). A retrospective analysis of 235 patients undergoing craniotomy and resection with TES-MEP monitoring for a frontal lobe lesion was performed. Patients that developed immediate post-operative motor deficit were included in analysis. Motor deficit and TES-MEP findings were categorized by muscle group as left upper extremity (LUE), left lower extremity (LLE), right upper extremity (RUE), or right lower extremity (RLE). Statistical analysis was performed to determine the predictive value of stable TES-MEP for SMA syndrome versus PMD. Twenty patients comprising 29 cases of immediate post-operative motor deficit by muscle group were included. Of these, 27 cases resolved and were diagnosed as SMA syndrome while two cases progressed to PMD. TES-MEP stability was significantly associated with diagnosis of SMA syndrome (p=.015). TES-MEP showed excellent diagnostic utility with a sensitivity and positive-predictive value of 100% and 92.6% respectively. Negative predictive value was 100%. Temporary SMA syndrome versus PMD is difficult to distinguish immediately postoperatively. TES-MEP may be a useful intra-operative adjunct that may aid in distinguishing SMA syndrome from PMD secondary to surgical injury