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Medical Mycology Jul 2023The (1→3)-β-D-glucan (BDG) is a component of the fungal cell wall that can be detected in serum and used as an adjunctive tool for the diagnosis of invasive mold... (Meta-Analysis)
Meta-Analysis
The (1→3)-β-D-glucan (BDG) is a component of the fungal cell wall that can be detected in serum and used as an adjunctive tool for the diagnosis of invasive mold infections (IMI) in patients with hematologic cancer or other immunosuppressive conditions. However, its use is limited by modest sensitivity/specificity, inability to differentiate between fungal pathogens, and lack of detection of mucormycosis. Data about BDG performance for other relevant IMI, such as invasive fusariosis (IF) and invasive scedosporiosis/lomentosporiosis (IS) are scarce. The objective of this study was to assess the sensitivity of BDG for the diagnosis of IF and IS through systematic literature review and meta-analysis. Immunosuppressed patients diagnosed with proven or probable IF and IS, with interpretable BDG data were eligible. A total of 73 IF and 27 IS cases were included. The sensitivity of BDG for IF and IS diagnosis was 76.7% and 81.5%, respectively. In comparison, the sensitivity of serum galactomannan for IF was 27%. Importantly, BDG positivity preceded the diagnosis by conventional methods (culture or histopathology) in 73% and 94% of IF and IS cases, respectively. Specificity was not assessed because of lacking data. In conclusion, BDG testing may be useful in patients with suspected IF or IS. Combining BDG and galactomannan testing may also help differentiating between the different types of IMI.
Topics: Animals; Fusariosis; beta-Glucans; Invasive Fungal Infections; Sensitivity and Specificity
PubMed: 37381179
DOI: 10.1093/mmy/myad061 -
CNS Neuroscience & Therapeutics Nov 2023The aim of this systematic review and meta-analysis was to evaluate the efficacy of noninvasive brain stimulation (NIBS) on cognition using functional magnetic resonance... (Meta-Analysis)
Meta-Analysis Review
The effects of noninvasive brain stimulation on cognitive function in patients with mild cognitive impairment and Alzheimer's disease using resting-state functional magnetic resonance imaging: A systematic review and meta-analysis.
OBJECTIVE
The aim of this systematic review and meta-analysis was to evaluate the efficacy of noninvasive brain stimulation (NIBS) on cognition using functional magnetic resonance imaging (fMRI) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), thus providing the neuroimaging mechanism of cognitive intervention.
METHODS
English articles published up to April 30, 2023 were searched in the PubMed, Web of Science, Embase, and Cochrane Library databases. We included randomized controlled trials where resting-state fMRI was used to observe the effect of NIBS in patients with MCI or AD. RevMan software was used to analyze the continuous variables, and SDM-PSI software was used to perform an fMRI data analysis.
RESULTS
A total of 17 studies comprising 258 patients in the treatment group and 256 in the control group were included. After NIBS, MCI patients in the treatment group showed hyperactivation in the right precuneus and decreased activity in the left cuneus and right supplementary motor area. In contrast, patients in the control group showed decreased activity in the right middle frontal gyrus and no hyperactivation. The clinical cognitive scores in MCI patients were significantly improved by NIBS, while not in AD. Some evidence regarding the modulation of NIBS in resting-state brain activity and functional brain networks in patients with AD was found.
CONCLUSIONS
NIBS could improve cognitive function in patients with MCI and AD. fMRI evaluations could be added to evaluate the contribution of specific NIBS treatment therapeutic effectiveness.
Topics: Humans; Alzheimer Disease; Cognitive Dysfunction; Cognition; Magnetic Resonance Imaging; Brain; Magnetic Resonance Spectroscopy
PubMed: 37349974
DOI: 10.1111/cns.14314 -
Cureus Jun 2022The ongoing coronavirus disease 2019 (COVID-19) pandemic has turned into one of the most serious public health crises of the last few decades. Although the disease can... (Review)
Review
The ongoing coronavirus disease 2019 (COVID-19) pandemic has turned into one of the most serious public health crises of the last few decades. Although the disease can result in diverse and multiorgan pathologies, very few studies have addressed the postmortem pathological findings of COVID-19 cases. Active autopsy findings amid this pandemic could be an essential tool for diagnosis, surveillance, and research. We aimed to provide a comprehensive picture of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) histopathological features of different body organs through a systematic review of the published literature. A systematic search of electronic databases (PubMed, ScienceDirect, Google Scholar, medRxiv, and bioRxiv) for journal articles of different study designs reporting postmortem pathological findings in COVID-19 cases was performed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used for conducting the review. A total of 50 articles reporting 430 cases were included in our analysis. Postmortem pathological findings were reported for different body organs: pulmonary system (42 articles), cardiovascular system (23 articles), hepatobiliary system (22 articles), kidney (16 articles), spleen and lymph nodes (12 articles), and central nervous system (seven articles). In lung samples, diffuse alveolar damage (DAD) was the most commonly reported finding in 239 cases (84.4%). Myocardial hypertrophy (87 cases, 51.2%), arteriosclerosis (121 cases, 62%), and steatosis (118 cases, 59.3%) were the most commonly reported pathological findings in the heart, kidney, and the hepatobiliary system respectively. Autopsy examination as an investigation tool could lead to a better understanding of SARS-CoV-2 pathophysiology, diagnosis, and management, subsequently improving patient care.
PubMed: 35784976
DOI: 10.7759/cureus.25573 -
Scientific Reports Aug 2022High-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However,... (Meta-Analysis)
Meta-Analysis
High-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However, differentiating true tumour progression (TTP) from treatment-related effects or pseudoprogression (PsP), may critically influence subsequent management options. Structural MRI is routinely employed to evaluate treatment responses, but misdiagnosis of TTP or PsP may lead to continuation of ineffective or premature cessation of effective treatments, respectively. A systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses method. Embase, MEDLINE, Web of Science and Google Scholar were searched for methods applied to differentiate PsP and TTP, and studies were selected using pre-specified eligibility criteria. The sensitivity and specificity of included studies were summarised. Three of the identified methods were compared in a separate subgroup meta-analysis. Thirty studies assessing seven distinct neuroimaging methods in 1372 patients were included in the systematic review. The highest performing methods in the subgroup analysis were DWI (AUC = 0.93 [0.91-0.95]) and DSC-MRI (AUC = 0.93 [0.90-0.95]), compared to DCE-MRI (AUC = 0.90 [0.87-0.93]). 18F-fluoroethyltyrosine PET (18F-FET PET) and amide proton transfer-weighted MRI (APTw-MRI) also showed high diagnostic accuracy, but results were based on few low-powered studies. Both DWI and DSC-MRI performed with high sensitivity and specificity for differentiating PsP from TTP. Considering the technical parameters and feasibility of each identified method, the authors suggested that, at present, DSC-MRI technique holds the most clinical potential.
Topics: Brain Neoplasms; Glioma; Humans; Magnetic Resonance Imaging; Sensitivity and Specificity; Treatment Outcome
PubMed: 35918373
DOI: 10.1038/s41598-022-16726-x -
European Journal of Investigation in... Dec 2022The use of virtual worlds in health-related education is increasingly popular, but an overview of their use in physiotherapy education is still needed. The aim of this... (Review)
Review
The use of virtual worlds in health-related education is increasingly popular, but an overview of their use in physiotherapy education is still needed. The aim of this review was to analyse the use of virtual and augmented reality (VR/AR) compared to traditional methods for teaching physiotherapy. A systematic review was performed up to October 2022 in PubMed, Web of Science, Scopus, CINAHL, and PsycInfo. The quality appraisal and risk of bias were assessed by the Joana Briggs Institute checklist and the Cochrane Collaboration's RoB Tool 2.0, respectively. A total of seven randomised and non-randomised controlled studies were included, involving 737 students. VR/AR-based teaching approaches included simulation and virtual worlds, and were conducted through immersive head-mounted displays, AR-based applications, and 3D visualisations. Three studies were focused on teaching anatomy content, two on clinical decision making skills, and the rest were focused on pathology, physiotherapy tasks or exercise performance, and movement analysis of lower limbs. Inconclusive results were found in terms of learning satisfaction and academic performance, showing VR/AR-based teaching models to be equally effective as traditional methods for teaching physiotherapy. We encourage researchers and teachers to include games in their VR/AR-based teaching approaches to enhance interaction and active learning in physiotherapy education.
PubMed: 36547026
DOI: 10.3390/ejihpe12120125 -
Modern Pathology : An Official Journal... Sep 2021The severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) pandemic has had devastating effects on global health and worldwide economy. Despite an initial...
The severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) pandemic has had devastating effects on global health and worldwide economy. Despite an initial reluctance to perform autopsies due to concerns for aerosolization of viral particles, a large number of autopsy studies published since May 2020 have shed light on the pathophysiology of Coronavirus disease 2019 (COVID-19). This review summarizes the histopathologic findings and clinicopathologic correlations from autopsies and biopsies performed in patients with COVID-19. PubMed and Medline (EBSCO and Ovid) were queried from June 4, 2020 to September 30, 2020 and histopathologic data from autopsy and biopsy studies were collected based on 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 58 studies reporting 662 patients were included. Demographic data, comorbidities at presentation, histopathologic findings, and virus detection strategies by organ system were collected. Diffuse alveolar damage, thromboembolism, and nonspecific shock injury in multiple organs were the main findings in this review. The pathologic findings emerging from autopsy and biopsy studies reviewed herein suggest that in addition to a direct viral effect in some organs, a unifying pathogenic mechanism for COVID-19 is ARDS with its known and characteristic inflammatory response, cytokine release, fever, inflammation, and generalized endothelial disturbance. This study supports the notion that autopsy studies are of utmost importance to our understanding of disease features and treatment effect to increase our knowledge of COVID-19 pathophysiology and contribute to more effective treatment strategies.
Topics: COVID-19; Humans; Respiratory Distress Syndrome; SARS-CoV-2
PubMed: 34031537
DOI: 10.1038/s41379-021-00814-w -
Breast (Edinburgh, Scotland) Oct 2023Assumptions on the natural history of ductal carcinoma in situ (DCIS) are necessary to accurately model it and estimate overdiagnosis. To improve current estimates of... (Review)
Review
OBJECTIVE
Assumptions on the natural history of ductal carcinoma in situ (DCIS) are necessary to accurately model it and estimate overdiagnosis. To improve current estimates of overdiagnosis (0-91%), the purpose of this review was to identify and analyse assumptions made in modelling studies on the natural history of DCIS in women.
METHODS
A systematic review of English full-text articles using PubMed, Embase, and Web of Science was conducted up to February 6, 2023. Eligibility and all assessments were done independently by two reviewers. Risk of bias and quality assessments were performed. Discrepancies were resolved by consensus. Reader agreement was quantified with Cohen's kappa. Data extraction was performed with three forms on study characteristics, model assessment, and tumour progression.
RESULTS
Thirty models were distinguished. The most important assumptions regarding the natural history of DCIS were addition of non-progressive DCIS of 20-100%, classification of DCIS into three grades, where high grade DCIS had an increased chance of progression to invasive breast cancer (IBC), and regression possibilities of 1-4%, depending on age and grade. Other identified risk factors of progression of DCIS to IBC were younger age, birth cohort, larger tumour size, and individual risk.
CONCLUSION
To accurately model the natural history of DCIS, aspects to consider are DCIS grades, non-progressive DCIS (9-80%), regression from DCIS to no cancer (below 10%), and use of well-established risk factors for progression probabilities (age). Improved knowledge on key factors to consider when studying DCIS can improve estimates of overdiagnosis and optimization of screening.
Topics: Female; Humans; Carcinoma, Intraductal, Noninfiltrating; Breast Neoplasms; Disease Progression; Computer Simulation; Early Detection of Cancer; Carcinoma, Ductal, Breast
PubMed: 37541171
DOI: 10.1016/j.breast.2023.07.012 -
European Journal of Surgical Oncology :... Mar 2022Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models were qualitative and did not assess performance at external validation. We assessed the performance of prognostic models for HCC and set a benchmark for biomarker studies.
METHODS
All externally validated models predicting survival for patients with resected HCC were systematically reviewed. After selection, we extracted descriptive statistics and aggregated c-indices using meta-analysis.
RESULTS
Thirty-eight validated prognostic models were included. Models used on average 7 (IQR:4-9) prognostic factors. Tumor size, tumor number, and vascular invasion were almost always included. Alpha-fetoprotein (AFP) was commonly incorporated since 2007. Recently, the more subjective items ascites and encephalopathy have been dropped. Eight established models performed poor to moderate at external validation, with a pooled C-index below 0.7; including the Barcelona Clinic Liver Cancer (BCLC) system, the American Joint Committee on Cancer (AJCC) 7th edition, the Cancer of the Liver Italian (CLIP) Program, and the Japan Integrated Staging (JIS) score. Out of 24 prognostic models predicting OS, only 6 (25%) had good performance at external validation with pooled C-indices above 0.7; the Li-post (0.77), Li-OS (0.74), Yang-pre (0.74), Yang-post (0.76), Shanghai-score (0.70), and Wang-nomogram (0.71). Models improved over time, but overall performance and study quality remained low.
CONCLUSIONS
Six validated prognostic models demonstrated good performance for predicting survival after resection of HCC. These models can guide patients and doctors and are a benchmark for future models incorporating novel biomarkers.
Topics: Biomarkers; Carcinoma, Hepatocellular; China; Humans; Liver Neoplasms; Neoplasm Staging; Prognosis
PubMed: 34602315
DOI: 10.1016/j.ejso.2021.09.012 -
Alzheimer's & Dementia (New York, N. Y.) 2022Given the ineffectiveness of the available drug treatment against Alzheimer disease (AD), light-based therapeutic modalities have been increasingly receiving attention... (Review)
Review
INTRODUCTION
Given the ineffectiveness of the available drug treatment against Alzheimer disease (AD), light-based therapeutic modalities have been increasingly receiving attention with photobiomodulation (PBM) and, more recently, visual stimulation (VS) being among the most promising approaches. However, the PBM and VS light parameters tested so far, as well as their outcomes, vary a lot with conflicting results being reported.
METHODS
Based on Scopus, PubMed, and Web of Science databases search, this systematic review summarizes, compares, and discusses 43 cell, animal, and human studies of PBM and VS related to cognitive decline and AD pathology.
RESULTS
Preclinical work suggests that PBM with 640±30-nm light and VS at 40 Hz attenuates Aβ and Tau pathology and improves neuronal and synaptic plasticity with most studies pointing towards enhancement of degradation/clearance mechanisms in the brain of AD animal models. Despite the gap of the translational evidence for both modalities, the few human studies performed so far support the use of PBM at 810-870 nm light pulsing at 40 Hz for improving brain network connectivity and memory in older subjects and AD patients, while 40 Hz VS in humans seems to improve cognition; further clinical investigation is urgently required to clarify the beneficial impact of PBM and VS in AD patients.
DISCUSSION
This review highlights PBM and VS as promising light-based therapeutic approaches against AD brain neuropathology and related cognitive decline, clarifying the most effective light parameters for further preclinical and clinical testing and use.
HIGHLIGHTS
Light-based brain stimulation produces neural entrainment and reverts neuronal damageBrain PBM and VS attenuate AD neuropathologyPMB and VS are suggested to improve cognitive performance in AD patients and animal modelsLight stimulation represents a promising therapeutic strategy against neurodegeneration.
PubMed: 36447479
DOI: 10.1002/trc2.12249 -
Journal of Cachexia, Sarcopenia and... Oct 2023Automated computed tomography (CT) scan segmentation (labelling of pixels according to tissue type) is now possible. This technique is being adapted to achieve... (Review)
Review
Automated computed tomography (CT) scan segmentation (labelling of pixels according to tissue type) is now possible. This technique is being adapted to achieve three-dimensional (3D) segmentation of CT scans, opposed to single L3-slice alone. This systematic review evaluates feasibility and accuracy of automated segmentation of 3D CT scans for volumetric body composition (BC) analysis, as well as current limitations and pitfalls clinicians and researchers should be aware of. OVID Medline, Embase and grey literature databases up to October 2021 were searched. Original studies investigating automated skeletal muscle, visceral and subcutaneous AT segmentation from CT were included. Seven of the 92 studies met inclusion criteria. Variation existed in expertise and numbers of humans performing ground-truth segmentations used to train algorithms. There was heterogeneity in patient characteristics, pathology and CT phases that segmentation algorithms were developed upon. Reporting of anatomical CT coverage varied, with confusing terminology. Six studies covered volumetric regional slabs rather than the whole body. One study stated the use of whole-body CT, but it was not clear whether this truly meant head-to-fingertip-to-toe. Two studies used conventional computer algorithms. The latter five used deep learning (DL), an artificial intelligence technique where algorithms are similarly organized to brain neuronal pathways. Six of seven reported excellent segmentation performance (Dice similarity coefficients > 0.9 per tissue). Internal testing on unseen scans was performed for only four of seven algorithms, whilst only three were tested externally. Trained DL algorithms achieved full CT segmentation in 12 to 75 s versus 25 min for non-DL techniques. DL enables opportunistic, rapid and automated volumetric BC analysis of CT performed for clinical indications. However, most CT scans do not cover head-to-fingertip-to-toe; further research must validate using common CT regions to estimate true whole-body BC, with direct comparison to single lumbar slice. Due to successes of DL, we expect progressive numbers of algorithms to materialize in addition to the seven discussed in this paper. Researchers and clinicians in the field of BC must therefore be aware of pitfalls. High Dice similarity coefficients do not inform the degree to which BC tissues may be under- or overestimated and nor does it inform on algorithm precision. Consensus is needed to define accuracy and precision standards for ground-truth labelling. Creation of a large international, multicentre common CT dataset with BC ground-truth labels from multiple experts could be a robust solution.
PubMed: 37562946
DOI: 10.1002/jcsm.13310