ChatGPT in radiology: A systematic review of performance, pitfalls, and future perspectives.

PURPOSE: The purpose of this study was to systematically review the reported performances of ChatGPT, identify potential limitations, and explore future directions for its integration, optimization, and ethical considerations in radiology applications. MATERIALS AND METHODS: After a comprehensive review of PubMed, Web of Science, Embase, and Google Scholar databases, a cohort of published studies was identified up to January 1, 2024, utilizing ChatGPT for clinical radiology applications. RESULTS: Out of 861 studies derived, 44 studies evaluated the performance of ChatGPT; among these, 37 (37/44; 84.1%) demonstrated high performance, and seven (7/44; 15.9%) indicated it had a lower performance in providing information on diagnosis and clinical decision support (6/44; 13.6%) and patient communication and educational content (1/44; 2.3%). Twenty-four (24/44; 54.5%) studies reported the proportion of ChatGPT's performance. Among these, 19 (19/24; 79.2%) studies recorded a median accuracy of 70.5%, and in five (5/24; 20.8%) studies, there was a median agreement of 83.6% between ChatGPT outcomes and reference standards [radiologists' decision or guidelines], generally confirming ChatGPT's high accuracy in these studies. Eleven studies compared two recent ChatGPT versions, and in ten (10/11; 90.9%), ChatGPTv4 outperformed v3.5, showing notable enhancements in addressing higher-order thinking questions, better comprehension of radiology terms, and improved accuracy in describing images. Risks and concerns about using ChatGPT included biased responses, limited originality, and the potential for inaccurate information leading to misinformation, hallucinations, improper citations and fake references, cybersecurity vulnerabilities, and patient privacy risks. CONCLUSION: Although ChatGPT's effectiveness has been shown in 84.1% of radiology studies, there are still multiple pitfalls and limitations to address. It is too soon to confirm its complete proficiency and accuracy, and more extensive multicenter studies utilizing diverse datasets and pre-training techniques are required to verify ChatGPT's role in radiology.

Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study.

This study investigated the impact of ComBat harmonization on the reproducibility of radiomic features extracted from magnetic resonance images (MRI) acquired on different scanners, using various data acquisition parameters and multiple image pre-processing techniques using a dedicated MRI phantom. Four scanners were used to acquire an MRI of a nonanatomic phantom as part of the TCIA RIDER database. In fast spin-echo inversion recovery (IR) sequences, several inversion durations were employed, including 50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, and 3000 ms. In addition, a 3D fast spoiled gradient recalled echo (FSPGR) sequence was used to investigate several flip angles (FA): 2, 5, 10, 15, 20, 25, and 30 degrees. Nineteen phantom compartments were manually segmented. Different approaches were used to pre-process each image: Bin discretization, Wavelet filter, Laplacian of Gaussian, logarithm, square, square root, and gradient. Overall, 92 first-, second-, and higher-order statistical radiomic features were extracted. ComBat harmonization was also applied to the extracted radiomic features. Finally, the Intraclass Correlation Coefficient (ICC) and Kruskal-Wallis's (KW) tests were implemented to assess the robustness of radiomic features. The number of non-significant features in the KW test ranged between 0-5 and 29-74 for various scanners, 31-91 and 37-92 for three times tests, 0-33 to 34-90 for FAs, and 3-68 to 65-89 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The number of features with ICC over 90% ranged between 0-8 and 6-60 for various scanners, 11-75 and 17-80 for three times tests, 3-83 to 9-84 for FAs, and 3-49 to 3-63 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The use of various scanners, IRs, and FAs has a great impact on radiomic features. However, the majority of scanner-robust features is also robust to IR and FA. Among the effective parameters in MR images, several tests in one scanner have a negligible impact on radiomic features. Different scanners and acquisition parameters using various image pre-processing might affect radiomic features to a large extent. ComBat harmonization might significantly impact the reproducibility of MRI radiomic features.

Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.

BACKGROUND: Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication, clinical adoption of the developed methodology still needs to be improved. To overcome this limitation, we set out to predict the prognosis of a large multi-institutional cohort of patients with COVID-19 using a DL-based model. PURPOSE: This study aimed to evaluate the performance of deep privacy-preserving federated learning (DPFL) in predicting COVID-19 outcomes using chest CT images. METHODS: After applying inclusion and exclusion criteria, 3055 patients from 19 centers, including 1599 alive and 1456 deceased, were enrolled in this study. Data from all centers were split (randomly with stratification respective to each center and class) into a training/validation set (70%/10%) and a hold-out test set (20%). For the DL model, feature extraction was performed on 2D slices, and averaging was performed at the final layer to construct a 3D model for each scan. The DensNet model was used for feature extraction. The model was developed using centralized and FL approaches. For FL, we employed DPFL approaches. Membership inference attack was also evaluated in the FL strategy. For model evaluation, different metrics were reported in the hold-out test sets. In addition, models trained in two scenarios, centralized and FL, were compared using the DeLong test for statistical differences. RESULTS: The centralized model achieved an accuracy of 0.76, while the DPFL model had an accuracy of 0.75. Both the centralized and DPFL models achieved a specificity of 0.77. The centralized model achieved a sensitivity of 0.74, while the DPFL model had a sensitivity of 0.73. A mean AUC of 0.82 and 0.81 with 95% confidence intervals of (95% CI: 0.79-0.85) and (95% CI: 0.77-0.84) were achieved by the centralized model and the DPFL model, respectively. The DeLong test did not prove statistically significant differences between the two models (p-value = 0.98). The AUC values for the inference attacks fluctuate between 0.49 and 0.51, with an average of 0.50 ± 0.003 and 95% CI for the mean AUC of 0.500 to 0.501. CONCLUSION: The performance of the proposed model was comparable to centralized models while operating on large and heterogeneous multi-institutional datasets. In addition, the model was resistant to inference attacks, ensuring the privacy of shared data during the training process.

Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is a debilitating neurodegenerative disease. Early diagnosis of AD and its precursor, mild cognitive impairment (MCI), is crucial for timely intervention and management. Radiomics involves extracting quantitative features from medical images and analyzing them using advanced computational algorithms. These characteristics have the potential to serve as biomarkers for disease classification, treatment response prediction, and patient stratification. Of note, Magnetic resonance imaging (MRI) radiomics showed a promising result for diagnosing and classifying AD, and MCI from normal subjects. Thus, we aimed to systematically evaluate the diagnostic performance of the MRI radiomics for this task. METHODS AND MATERIALS: A comprehensive search of the current literature was conducted using relevant keywords in PubMed/MEDLINE, Embase, Scopus, and Web of Science databases from inception to August 5, 2023. Original studies discussing the diagnostic performance of MRI radiomics for the classification of AD, MCI, and normal subjects were included. Method quality was evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Radiomics Quality Score (RQS) tools. RESULTS: We identified 13 studies that met the inclusion criteria, involving a total of 5448 participants. The overall quality of the included studies was moderate to high. The pooled sensitivity and specificity of MRI radiomics for differentiating AD from normal subjects were 0.92 (95% CI [0.85; 0.96]) and 0.91 (95% CI [0.85; 0.95]), respectively. The pooled sensitivity and specificity of MRI radiomics for differentiating MCI from normal subjects were 0.74 (95% CI [0.60; 0.85]) and 0.79 (95% CI [0.70; 0.86]), respectively. Also, the pooled sensitivity and specificity of MRI radiomics for differentiating AD from MCI were 0.73 (95% CI [0.64; 0.80]) and 0.79 (95% CI [0.64; 0.90]), respectively. CONCLUSION: MRI radiomics has promising diagnostic performance in differentiating AD, MCI, and normal subjects. It can potentially serve as a non-invasive and reliable tool for early diagnosis and classification of AD and MCI.

Neurosarcoidosis in an adult man with a family history of MS: A case report.

Key clinical message: According to this report, a biopsy revealed a diagnosis of neurosarcoidosis in a patient with a history of MS. The development of the disease can be slowed down by early diagnosis and appropriate treatment. Abstract: Neurosarcoidosis is a rare type of sarcoidosis that affects the central nervous system (CNS). Herein, we present a case of neurosarcoidosis with a history of multiple sclerosis (MS). Based on the pathological findings of the biopsy, a diagnosis of neurosarcoidosis was established. The administration of appropriate treatment at an early stage can assist in decelerating its progression.

Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease and COVID-19: A Systematic Review.

Background: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is an uncommon neurological disease affecting the central nervous system (CNS). Numerous neurological disorders, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), acute transverse myelitis (ATM), and MOGAD, have been reported following the COVID-19 infection during the current COVID-19 pandemic. On the other hand, it has been suggested that patients with MOGAD may be at greater risk for infection (particularly in the current pandemic). Objective: In this systematic review, we gathered separately 1) MOGAD cases following COVID-19 infection as well as 2) clinical course of patients with MOGAD infected with COVID-19 based on case reports/series. Methods: 329 articles were collected from 4 databases. These articles were conducted from inception to March 1st, 2022. Results: Following the screening, exclusion criteria were followed and eventually, 22 studies were included. In 18 studies, a mean ± SD time interval of 18.6 ± 14.9 days was observed between infection with COVID-19 and the onset of MOGAD symptoms. Symptoms were partially or completely recovered in a mean of 67 days of follow-up.Among 4 studies on MOGAD patients, the hospitalization rate was 25%, and 15% of patients were hospitalized in the intensive care unit (ICU). Conclusion: Our systematic review demonstrated that following COVID-19 infection, there is a rare possibility of contracting MOGAD. Moreover, there is no clear consensus on the susceptibility of MOGAD patients to severe COVID-19. However, obtaining deterministic results requires studies with a larger sample size.

Worldwide prevalence of neuromyelitis optica spectrum disorder (NMOSD) and neuromyelitis optica (NMO): a systematic review and meta-analysis.

BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a progressive demyelinating disease of the central nervous system that has overlapping symptoms with multiple sclerosis (MS) but differs from it in a variety of ways. Previous studies have reported conflicting results trying to estimate the number of individuals affected by them which is why we designed this systematic review and meta-analysis to estimate the worldwide prevalence and incidence of NMOSD/NMO based on current evidence. METHODS: We searched PubMed, Scopus, EMBASE, Web of Science, and gray literature including references from the identified studies, review studies, and conference abstracts which were published up to February 1, 2022. We used all MeSH terms pertaining to "NMOSD," "NMO," and all the terms on "prevalence," "incidence," and "epidemiology" to identify the search components. Pooled effect sizes were measured using random-effect model by DerSimonian-Laird. RESULTS: The prevalence and incidence rates of NMOSD/NMO ranged from 0.07 to 10 and 0.029 to 0.880 per 100,000 population, respectively. The overall pooled prevalence of NMO per 100,000 population was 1.54 (I2: 98.4%, 95% CI: 1.13-1.96, P< 0.001) based on the 2006 criteria, 1.51 (I2: 99.4%, 95% CI: 1.21-1.81, P < 0.001) based on the 2015 criteria and 2.16 (I2: 89.4%, 95% CI: 1.46-2.86, P < 0.001) based on the 2006/2015 criteria. The overall annual incidence of NMO per 100,000 population was 0.155 (I2: 95%, 95% CI: 0.115-0.195, P < 0.001) based on the 2006 criteria and 0.278 (I2: 100%, 95% CI: 0.135-0.420, P < 0.001) based on the 2015 criteria. The prevalence rates were highest in French West Indies and South Korea, and lowest in Cuba and Australia, based on the 2006 and 2015 criteria, respectively. Also, the highest annual incidence rates were obtained for Sweden and Slovak republic and the lowest for Cuba and Australia based on the 2006 and 2015 criteria, respectively. All estimated rates were higher among females compared to males. CONCLUSION: Although rare, NMOSD/NMO impact affected individuals in devastating ways. Several large-scale prospective studies are required to reach a comprehension of the epidemiological aspects of these notorious demyelinating conditions.

Effectiveness of BBIBP-CorV vaccine in preventing SARS-CoV2 infection and severe outcomes in people living with multiple sclerosis: A population-based study.

BACKGROUND: The objective of the present study was to estimate the effectiveness of the BBIBP-CorV vaccine (VE) in preventing SARS-CoV-2 infection, related hospitalization, and death among people living with multiple sclerosis (PLWMS). METHODS: In this population-based retrospective observational study, data on all PLWMS, vaccination, SARS-CoV-2 tests, hospitalization, and deaths were collected in Isfahan, Iran between February 9, 2021, and November 4, 2021. We estimated the hazard ratio between vaccinated (partially and fully) and unvaccinated groups using the Andersen-Gill extension of the Cox proportional hazards model. We also performed Cox proportional hazards analysis to identify risk factors for breakthrough infection and COVID-19-related hospitalization in fully-immunized group. RESULTS: Of the 9869 PLWMS, 1368 were in partially-vaccinated group, 4107 were in the fully-vaccinated group, and 3794 were in the unvaccinated group. In the partially-vaccinated group, the estimated VE against COVID-19 infection was 39.3% (16%, 56.1%), hospitalization was 64.9% (1.3%, 87.5%), and mortality was 92.7% (88.8%, 100%). The respective results for the fully-vaccinated group were 63.9% (56%, 70.3%), 75.7% (57.5%, 86.1%), and 100%. Progressive MS was independently associated with a greater risk of breakthrough infection (HR=1.952, 95%CI: 1.174-3.246, p = 0.010). Older adults (≥50 years vs. 18-49 years, HR=3.115, 95%CI: 1.145-8.470, p = 0.026) and those on rituximab (HR=7.584; 95% CI: 1.864-30.854; p = 0.005) were at an increased risk of COVID-19-related hospitalization. CONCLUSION: This study showed that two doses of the BBIBP-CorV vaccine can effectively prevent COVID-19 infection and hospitalization among PLWMS. Old PLWMS and those who treating with rituximab are at increased risk of hospitalization after receiving two doses of the vaccine.

Prevalence of dysphagia in patients with multiple sclerosis: A systematic review and meta-analysis.

BACKGROUND: Dysphagia is a major disorder observed in patients with multiple sclerosis (MS), yet different prevalence rates are reported for it. Therefore, we designed this study to estimate the pooled prevalence of dysphagia in patients with MS. METHOD: We searched PubMed, Scopus, EMBASE, Web of Science, and gray literature including references from the identified studies, reviews studies, and conference abstracts which were published up to May 2022. Articles that were relevant to our topic and could provide information regarding the prevalence of dysphagia among MS patients were included; however, articles with self-report screening strategies were excluded. RESULTS: The literature search found 997 articles. After eliminating duplicates, 672 articles remained. Two conference abstracts were included for final analysis. A total of 11,266 MS cases and 5047 MS patients with dysphagia were included in the meta-analysis. The overall prevalence of dysphagia across all 54 studies was 44.8 % (95 % CI: [40.4 %-49.2 %]), with a high level of heterogeneity between countries (Q=; I2 = 94.96 %; p < 0.001). CONCLUSION: The results of this systematic review shows that the prevalence of dysphagia in MS patients is 45% which is greatly higher compared to the general population.

What Predict Self-rated Health: A Cross-sectional Study Among Men and Women with Non-cardiac Chest Pain.

The study aimed to determine different lifestyle and clinical factors that predict self-rated health (SRH) in non-cardiac chest pain (NCCP) patients. In this cross-sectional study, 360 NCCP patients filled out questionnaires about depression, somatization, body sensation, type D personality, and pain intensity. In addition, participants' lifestyle and socio-demographic data were obtained. Multiple regression analyses revealed that among men, pain intensity (OR 1.07; 95% CI 1.03, 1.12), depression (3.10; 1.38, 9.18), somatization (1.18; 1.08, 1.29) and sleep quality (6.23; 1.42, 27.27) were associated with self-rated health. In women NCCP patients, depression (2.44; 1.05, 6.82) pain intensity (1.05; 1.01, 1.10), and physical activity (2.21; 1.07, 5.55) were associated with SRH. The results on the predicting factors of SRH in NCCP patients provide potential insights for more advanced clinical management of NCCP. In addition, they can be applied to improve health policies and promote healthy behaviors among NCCP patients.

A Cardiovascular Risk Assessment Model According to Behavioral, Psychosocial and Traditional Factors in Patients With ST-Segment Elevation Myocardial Infarction (CRAS-MI): Review of Literature and Methodology of a Multi-Center Cohort Study.

This study aims to provide a comprehensive risk-assessment model including lifestyle, psychological parameters, and traditional risk factors to determine the risk of major adverse cardiovascular events (MACE) in patients with the first acute ST-segment elevation myocardial infarction episode. Patients were recruited from new hospital admissions of acute ST-segment elevation myocardial infarction and will be followed up to 3 years. Clinical and paraclinical characteristics, lifestyle, psychological, and MACE information are collected and will be used in the risk-assessment model. Totally, 1707 patients were recruited (male: 81.4%, mean age: 56.60 ± 10.34). Primary percutaneous coronary intervention was the most prevalent type of coronary revascularization (81.9%). In case of baseline psychological characteristics, mean depression score was 5.40 ± 4.88, and mean distress score was 7.64 ± 5.08. A comprehensive approach, focusing on medical, lifestyle, and psychological factors, will lead to better identification of cardiovascular disease patients at risk of developing MACE through comprehensive risk-assessment models.

The Efficacy of Fingolimod and Interferons in Controlling Disability and Relapse Rate in Patients with Multiple Sclerosis: A Systematic Review and Meta-Analysis.

Background: Fingolimod and interferons are used in the relapse form of multiple sclerosis (MS). The goal of this systematic review and meta-analysis was to evaluate the efficacy of fingolimod versus interferon in patients with MS. The systematic search was done in PubMed, Scopus, Embase, Web of Science, and Google Scholar. Methods: The references of included studies as well as conference abstracts were searched up to July 2021. The literature search revealed 8211 articles, and after deleting duplicates 5594 remained. For the meta-analysis, four studies were included. The standardized mean difference (SMD) of the Expanded Disability Status Scale (EDSS) after treatment (interferon vs fingolimod) was -0.06 (95% CI: -0.28, 0.17) (I2 = 80.2%, P = 0.002). Results: The SMD of the annual relapse rate (ARR) after treatment (interferon - fingolimod) was -0.08 (95% CI: -0.53, 0.36) (I2 = 95.5%, P < 0.001). The SMD of the ARR after treatment and before treatment in the interferon group was - 1.45, (95% CI: -1.55, -1.36) (I2 = 0, P = 0.3). The SMD of ARR after treatment and before treatment in the fingolimod group was - 1.3, (95% CI: -1.94, -0.65) (I2 = 97.4%, P < 0.001). Conclusions: The results of this systematic review show that efficacy of interferon and fingolimod in controlling relapse rate and disability is similar.

Social support and anxiety correlation with resilience in patients with multiple sclerosis during COVID-19 pandemic.

Background: Social support and anxiety are essential for patients with chronic diseases such as multiple sclerosis (MS). During coronavirus disease 2019 (COVID-19) pandemic, the psychological well-being of subjects with MS was an important issue, and we designed this study to assess anxiety, resilience, and social support in these patients during COVID-19 pandemic stage. Methods: We used convenience sampling for this study. Inclusion criteria were definite diagnosis of MS based on McDonald criteria and age more than 18 years. Two hundred patients with MS were enrolled. Subjects were asked to fill out valid and reliable Persian versions of Connor-Davidson Resilience Scale (CD-RISC), Beck Anxiety Inventory (BAI), and Perceived Social Support Scale. We also collected demographic data (age, sex, marital status, and occupation), disease duration, and disability level [Expanded Disability Status Scale (EDSS)]. Continuous variables were presented as mean ± standard deviation (SD) (except for EDSS, as its distribution was not normal), and categorical variables were presented as frequencies. Correlation coefficients were calculated. We did a subgroup analysis and compared patients with BAI less than 30 and more than 30 (severe anxiety). A P-value less than 0.05 was considered significant. Results: Mean age and mean duration of the disease were 36.5 ± 9.3 and 6.2 ± 5.4 years, respectively. Mean BAI, social support, and resilience scores were 33.8 ± 11.4, 65.7 ± 16.7, and 62.5 ± 19.4, respectively.There was a significant positive correlation between resilience and social support scales (r = 0.44, P < 0.001), and also a significant negative correlation between resilience and BAI (r = -0.31, P < 0.001). Patients with severe anxiety (BAI > 30) had lower social support scores and resilience (social support: 70.3 ± 13.1 vs. 61.5 ± 18.6, P < 0.001; resilience: 57.3 ± 17.0 vs. 68.2 ± 19.6, P < 0.001) compared to patients with BAI ≤ 30. By considering resilience score as the dependent variable and other variables as independent variables, we found that BAI and social support scores were independent predictors. Conclusion: Social support and anxiety are independent predictors of resilience during COVID-19 pandemic in patients with MS.

Olfactory dysfunction in patients with Parkinson's disease: A systematic review and meta-analysis.

Background: Parkinson's disease (PD) is a progressive neuro-degenerative disease and olfactory dysfunction is considered as an important issue in these patients. The prevalence of olfactory dysfunction in patients with PD was reported variously in previous studies. Therefore, we designed this systematic review and meta-analysis to estimate the pooled prevalence of olfactory dysfunction in patients with PD. Methods: Two expert researchers systematically searched PubMed, Scopus, EMBASE, Web of Science, Google Scholar, references of the papers, and conference abstracts. The titles and abstracts of the potential studies were evaluated after deleting the duplicates. We extracted data regarding the total number of participants, first author, publication year, the country of origin, mean age, mean disease duration, female/male, number with olfactory dysfunction, and name of the test. We evaluated the risk of potential bias by the Newcastle-Ottawa Quality Assessment Scale (adapted for cross-sectional studies). All statistical analyses were done using Stata software. To determine heterogeneity between the findings of included studies, inconsistency (I2) was calculated. We applied random effect model when I2 was more than 50%. P-value less than 0.05 was considered significant. Results: The literature search revealed 1546 studies; after deleting duplicates, 894 remained. Finally, twelve studies remained for meta-analysis. Studies were published between years of 2009 to 2021, the sample size of studies ranged between 30 and 2097, and the mean age ranged between 61 and 70 years. The pooled prevalence of olfactory dysfunction in patients with PD was estimated as 64% [95% confidence interval (CI): 44-84, I2 = 99.7%, P < 0.001]. The pooled prevalence of olfactory dysfunction using Sniffin's test was 67% (95% CI: 51-83) and using other tests was 60% (95% CI: 28-92). Conclusion: The results of this systematic review and meta-analysis showed that the pooled prevalence of olfactory dysfunction in patients with PD was 64% which should be considered by physicians.

Risk and severity of SARS-CoV-2 reinfection among patients with multiple sclerosis vs. the general population: a population-based study.

BACKGROUND: We conducted this study to compare the risk of reinfection between multiple sclerosis (MS) patients and a control group without MS. METHOD: In this retrospective study, data of all SARS-CoV-2 tests (n = 793,301) and almost all MS patients (n = 10,639) in Isfahan province were collected from January 01, 2020 to August 22, 2021. Of the 2196 MS patients and 793,301 persons from the general population who had been tested at least once, 3 control for each MS patient were identified, leaving 1560 MS patients and 4680 controls without MS. We compared the risk of reinfection after 90 days of a primary infection between those with and without a previous positive COVID-19 test. RESULTS: 736 (47.2%) MS patients and 2013 (43.0%) control individuals had at least one positive test. A total of 17 (2.3%) and 22 (1.1%) possible reinfections in MS and control groups were observed. The estimated protection against reinfection in all MS patients, MS patients on rituximab, MS patients on DMTs rather than rituximab, and controls were 68.2% (46.2, 81.2%), 57.4% (- 0.1, 83.1%), 71.5% (45.5, 85.2%), and 82.1% (72.1, 88.5%), respectively. We found no statistically significant difference in estimated protection (p = 0.123) and odd of reinfection (adjusted OR: 2.01 [0.98, 4.08]) between all MS patients and control group. Two patients were hospitalized at first infection but none required hospitalization at reinfection event. CONCLUSIONS: MS patients on rituximab may be at a greater risk of reinfection. Further studies are required to assess the risk of the second reinfection among the MS population.

Association of Disease-Modifying Therapies with COVID-19 Susceptibility and Severity in Patients with Multiple Sclerosis: A Systematic Review and Network Meta-Analysis.

Background: We conducted this study to assess the effect of disease-modifying therapies (DMTs) on coronavirus disease (COVID-19) susceptibility and severity in people with multiple sclerosis (MS). Methods: Available studies from PubMed, Scopus, EMBASE, Web of Science, and gray literature, including reference lists and conference abstracts, were searched from December 1, 2019, to July 26, 2021. We included cross-sectional, case-control, and cohort studies assessing the association of DMTs with risk of contracting COVID-19 or its outcomes in MS patients on univariate or multivariate regression analyses. We conducted a network meta-analysis (NMA) to compare the risk of COVID-19 and developing severe infection across DMTs. Results: Out of the initial 3893 records and 1883 conference abstracts, a total of 10 studies were included. Pairwise comparisons showed that none of the DMTs meaningfully affect the risk of acquiring infection. There was significant total heterogeneity and inconsistency across this NMA. In comparison with no DMT, dimethyl fumarate (0.62 (0.42, 0.93)), fingolimod (0.55 (0.32, 0.94)), natalizumab (0.50 (0.31, 0.81)), and interferon (0.42 (0.22, 0.79)) were associated with a decreased risk of severe COVID-19; but, rituximab was observed to increase the risk (1.94 (1.20, 3.12)). Compared to rituximab or ocrelizumab, all DMTs were associated with a decreased risk. Pairwise comparisons showed no differences across other DMTs. Interferon and rituximab were associated with the lowest and highest risks of severe COVID-19. Conclusion: Our study showed an increased risk of severe COVID-19 in patients on rituximab and ocrelizumab. No association with COVID-19 severity across other DMTs was observed.

Endothelium, Platelets, and Coagulation Factors as the Three Vital Components for Diagnosing Bleeding Disorders: A Simplified Perspective with Clinical Relevance.

Bleeding disorders are a major group of hematological disorders, which are highly prevalent in the world. Excessive bleeding can result in serious consequences including hypoperfusion and cardiac arrest. The body has its selfmechanism to control excessive bleeding which is termed hemostasis. Hemostasis is achieved in two major steps, the formation of the primary and secondary hemostatic plugs. Endothelium, platelets, and coagulation factors are three components involved in hemostasis. Endothelium and platelets have a major role in forming the primary hemostatic plug. Consequently, the first step in investigating a bleeding disorder is platelet count. Despite normal platelet count, abnormality in the primary hemostatic plug may arise due to functional defects of the platelets including adhesion, activation, and aggregation. Von Willebrand disease (VWD) is an endothelial defect and the most prevalent inherited defect in coagulation. Abnormalities in the secondary hemostatic plug are largely due to coagulation factor deficiencies, and, to a lesser extent, the presence of inhibitors. Techniques involving viscoelastics have been aiding in rapid diagnosis and are useful in point-of-care testing. This article discusses the investigation of bleeding disorders from the perspective of the endothelium, platelet, and coagulation factor physiology. These three components should be properly investigated to achieve the definitive diagnosis of bleeding disorders.

Is Myasthenia Gravis a Real Complication of the COVID-19 Vaccine? A Case Report-Based Systematic Review.

Background: Myasthenia gravis (MG) is a neuromuscular, autoimmune disease that causes weakness by impairing neuromuscular transmission. According to reports, vaccines can lead to autoimmunity in different ways, and COVID-19 vaccines are suggested to trigger MG. We conducted this systematic review to assess MG patients after the COVID-19 vaccination. Methods: We collected 231 studies from four databases from inception to 26 March 2022. Results: 4 case studies were selected from 231 research studies, and data were extracted based on inclusion criteria. In all cases, MG was reported following COVID-19 vaccination. Symptoms such as muscle weakness, numbness, and ptosis were common. The MG was confirmed through RNST, MRC, NCS, and AchR-binding antibody titer tests. Conclusion: Although all cases of MG were diagnosed following appropriate tests, the sample size was small; therefore, further investigation is required to demonstrate the possible association between MG and COVID-19 vaccination.

Serum and plasma levels of brain-derived neurotrophic factor in individuals with eating disorders (EDs): a systematic review and meta-analysis.

BACKGROUND: Brain-derived neurotrophic factor (BDNF) is essential for neuronal survival, differentiation, development, and plasticity. Evidence suggests that fluctuations in peripheral levels (i.e., plasma or serum) of BDNF are associated with eating behaviors. Nevertheless, the findings are inconsistent. The purpose of this study is to determine if serum or plasma levels of BDNF are altered in individuals with eating disorders (EDs) compared to controls. METHODS: We conducted a systematic search of the core electronic medical databases from inception to March 2022 and identified observational studies that compared individuals with EDs to controls without EDs on serum or plasma levels of BDNF. R version 4.0.4 was used for all visualizations and calculations. RESULTS: The current meta-analysis comprised 15 studies that fulfilled the inclusion criteria. Subjects with EDs (n = 795) showed lower BDNF levels compared to non-EDs controls (n = 552) (SMD: - 0.49, 95% CI [- 0.89; - 0.08], p-value = 0.01). Moreover, subgroup analysis was conducted based on the specimen (plasma and serum), which revealed no statistically significant difference in the levels of BDNF between the two subgroups (p-value = 0.92). Additionally, meta-regression results revealed that publication year, mean age of the individuals with EDs, NOS scores, and the number of individuals with EDs collectively accounted for 25.99% percent of the existing heterogeneity. CONCLUSION: Lower BDNF levels are associated with EDs.

Unraveling the Mystery of COVID-19 Postvaccination Myocarditis: A Systematic Review of Current Cases.

From the early stages of the pandemic, the development and mass production of a safe and effective vaccine seemed like the greatest tool, to win the fight against the virus. In the present study, we comprehensively conducted a systematic review of all current cases worldwide to better understand whether there is a link between COVID-19 vaccination and one of the most devastating complications, cardiac Inflammation. Our search retrieved over 250 results, of which 130 met the inclusion criteria, and their respective data were extracted. The results suggest that postvaccination myocarditis and pericarditis are more likely to be seen in male, younger, and mRNA-vaccinated individuals. Most affected patients experienced symptoms following the second shot, and complaint of chest pain was the most prevalent presentation. Currently, no direct link can be drawn between the vaccines and the risk of cardiac inflammation.