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BMC Neurology Dec 2023Neuromuscular diseases (NMD) emerged as one of the main side effects of the COVID-19 vaccination. We pooled and summarized the evidence on the clinical features and...
BACKGROUND
Neuromuscular diseases (NMD) emerged as one of the main side effects of the COVID-19 vaccination. We pooled and summarized the evidence on the clinical features and outcomes of NMD associated with COVID-19 vaccination.
METHODS
We comprehensively searched three databases, Medline, Embase, and Scopus, using the key terms covering "Neuromuscular disease" AND "COVID-19 vaccine", and pooled the individual patient data extracted from the included studies.
RESULTS
A total of 258 NMD cases following COVID-19 have been reported globally, of which 171 cases were Guillain-Barré syndrome (GBS), 40 Parsonage-Turner syndrome (PTS), 22 Myasthenia Gravis (MG), 19 facial nerve palsy (FNP), 5 single fiber neuropathy, and 1 Tolosa-Hunt syndrome. All (100%) SFN patients and 58% of FNP patients were female; in the remaining NMDs, patients were predominantly male, including MG (82%), GBS (63%), and PTS (62.5%). The median time from vaccine to symptom was less than 2 weeks in all groups. Symptoms mainly appeared following the first dose of vector vaccine, but there was no specific pattern for mRNA-based.
CONCLUSION
COVID-19 vaccines might induce some NMDs, mainly in adults. The age distribution and gender characteristics of affected patients may differ based on the NMD type. About two-thirds of the cases probably occur less than 2 weeks after vaccination.
Topics: Adult; Humans; Female; Male; COVID-19 Vaccines; COVID-19; Neuromuscular Diseases; Myasthenia Gravis; Guillain-Barre Syndrome; Bell Palsy; Facial Paralysis
PubMed: 38082244
DOI: 10.1186/s12883-023-03486-y -
Cureus Nov 2023The use of artificial intelligence in the field of medicine - including spine surgery - is now widespread and prominent. Kyphosis is a prevalent disease in spine surgery... (Review)
Review
The use of artificial intelligence in the field of medicine - including spine surgery - is now widespread and prominent. Kyphosis is a prevalent disease in spine surgery with abundant morbidity. Predicting the development of kyphosis disease has been somewhat difficult, and the use of AI to aid in the prediction of kyphosis disease may yield new opportunities for spine surgeons. The aim of this review is to recognize the contributions of AI in predicting the development of kyphosis. Five databases/registers were searched to identify suitable records for this review. Nine studies were included in this review. The studies demonstrated that AI could be utilized to predict the development of kyphosis disease after corrective surgery for a variety of spinal pathologies, including thoracolumbar burst fracture, cervical deformity, previous kyphosis disease, and adult degenerative scoliosis. The studies utilized a variety of AI modalities, including support vector machines, decision trees, random forests, and artificial neural networks. Two of the included studies also compared the use of different AI modalities in predicting the development of kyphosis disease. The literature has demonstrated that AI can be utilized effectively to predict the development of kyphosis disease. However, the current research is limited and only sparsely covers this broad field. Therefore, we suggest that further research is needed to explore the uncharted opportunities in predicting the development of kyphosis disease. Also, further research would confirm and consolidate the benefits demonstrated by the literature included in this review.
PubMed: 38060748
DOI: 10.7759/cureus.48341 -
Frontiers in Public Health 2023As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche...
INTRODUCTION
As emerging infectious diseases (EIDs) increase, examining the underlying social and environmental conditions that drive EIDs is urgently needed. Ecological niche modeling (ENM) is increasingly employed to predict disease emergence based on the spatial distribution of biotic conditions and interactions, abiotic conditions, and the mobility or dispersal of vector-host species, as well as social factors that modify the host species' spatial distribution. Still, ENM applied to EIDs is relatively new with varying algorithms and data types. We conducted a systematic review (PROSPERO: CRD42021251968) with the research question: via
METHODS
We searched five research databases and eight widely recognized One Health journals between 1995 and 2020. We screened 383 articles at the abstract level (included if study involved vector-borne or zoonotic disease and applied ENM) and 237 articles at the full-text level (included if study described ENM features and modeling processes). Our objectives were to: (1) describe the growth and distribution of studies across the types of infectious diseases, scientific fields, and geographic regions; (2) evaluate the likely effectiveness of the studies to represent ecological niches based on the biotic, abiotic, and mobility framework; (3) explain some potential pitfalls of ENM algorithms and techniques; and (4) provide specific recommendation for future studies on the analysis of ecological niches to predict EIDs.
RESULTS
We show that 99% of studies included mobility factors, 90% modeled abiotic factors with more than half in tropical climate zones, 54% modeled biotic conditions and interactions. Of the 121 studies, 7% include only biotic and mobility factors, 45% include only abiotic and mobility factors, and 45% fully integrated the biotic, abiotic, and mobility data. Only 13% of studies included modifying social factors such as land use. A majority of studies (77%) used well-recognized ENM algorithms (MaxEnt and GARP) and model selection procedures. Most studies (90%) reported model validation procedures, but only 7% reported uncertainty analysis.
DISCUSSION
Our findings bolster ENM to predict EIDs that can help inform the prevention of outbreaks and future epidemics.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier (CRD42021251968).
Topics: Animals; Communicable Diseases, Emerging; Ecosystem; Zoonoses; Disease Outbreaks; Epidemics
PubMed: 38026359
DOI: 10.3389/fpubh.2023.1244084 -
Frontiers in Public Health 2023The emergence of COVID-19 in Wuhan, China, rapidly escalated into a worldwide public health crisis. Despite numerous clinical treatment endeavors, initial defenses...
The emergence of COVID-19 in Wuhan, China, rapidly escalated into a worldwide public health crisis. Despite numerous clinical treatment endeavors, initial defenses against the virus primarily relied on hygiene practices like mask-wearing, meticulous hand hygiene (using soap or antiseptic solutions), and maintaining social distancing. Even with the subsequent advent of vaccines and the commencement of mass vaccination campaigns, these hygiene measures persistently remain in effect, aiming to curb virus transmission until the achievement of herd immunity. In this scoping review, we delve into the effectiveness of these measures and the diverse transmission pathways, focusing on the intricate interplay within the food network. Furthermore, we explore the virus's pathophysiology, considering its survival on droplets of varying sizes, each endowed with distinct aerodynamic attributes that influence disease dispersion dynamics. While respiratory transmission remains the predominant route, the potential for oral-fecal transmission should not be disregarded, given the protracted presence of viral RNA in patients' feces after the infection period. Addressing concerns about food as a potential viral vector, uncertainties shroud the virus's survivability and potential to contaminate consumers indirectly. Hence, a meticulous and comprehensive hygienic strategy remains paramount in our collective efforts to combat this pandemic.
Topics: Humans; COVID-19; SARS-CoV-2; Hygiene; Hand Hygiene; Pandemics
PubMed: 38026326
DOI: 10.3389/fpubh.2023.1202216 -
Bioengineering (Basel, Switzerland) Oct 2023Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML)... (Review)
Review
Pulmonary auscultation is essential for detecting abnormal lung sounds during physical assessments, but its reliability depends on the operator. Machine learning (ML) models offer an alternative by automatically classifying lung sounds. ML models require substantial data, and public databases aim to address this limitation. This systematic review compares characteristics, diagnostic accuracy, concerns, and data sources of existing models in the literature. Papers published from five major databases between 1990 and 2022 were assessed. Quality assessment was accomplished with a modified QUADAS-2 tool. The review encompassed 62 studies utilizing ML models and public-access databases for lung sound classification. Artificial neural networks (ANN) and support vector machines (SVM) were frequently employed in the ML classifiers. The accuracy ranged from 49.43% to 100% for discriminating abnormal sound types and 69.40% to 99.62% for disease class classification. Seventeen public databases were identified, with the ICBHI 2017 database being the most used (66%). The majority of studies exhibited a high risk of bias and concerns related to patient selection and reference standards. Summarizing, ML models can effectively classify abnormal lung sounds using publicly available data sources. Nevertheless, inconsistent reporting and methodologies pose limitations to advancing the field, and therefore, public databases should adhere to standardized recording and labeling procedures.
PubMed: 37892885
DOI: 10.3390/bioengineering10101155 -
Infectious Disease Reports Oct 2023'Query' (Q) fever is a neglected but emerging or re-emerging zoonotic disease caused by the bacterium (C.) . Several host species are considered or speculated to be the... (Review)
Review
'Query' (Q) fever is a neglected but emerging or re-emerging zoonotic disease caused by the bacterium (C.) . Several host species are considered or speculated to be the primary reservoir hosts for human infection. In the past, several research groups in Nigeria have evaluated the prevalence of in various vertebrate and invertebrate hosts. Currently, there is a paucity of knowledge regarding the epidemiology of the pathogen in Nigeria with limited or no attention to control and prevention programs. Therefore, this review was undertaken to comprehend the current situation of infection in human, domestic and peri-domestic animals, and some tick species in Nigeria since 1960 with the aim to help identify future research priorities for the country. A comprehensive literature search was performed using the PRISMA guidelines on five scientific databases including Google Scholar, PubMed, AJOL, Science Direct, and Scopus for articles published from Nigeria dealing with the screening of blood, milk, or tick DNA for evidence of using any standard diagnostic approach. Of the 33 published articles subjected to full-text evaluation, more than 48% of the articles met the inclusion criteria and were thus included in this review. We observed different ranges of prevalence for antibodies from four vertebrate hosts including cattle (2.5-23.5%), sheep (3.8-12.0%), goats (3.1-10.9%), and humans (12.0-61.3%). Additionally, the use of molecular diagnostics revealed that the DNA of has been amplified in eight tick species including () , , , , , , , and Two rodent's species ( and ) in Nigeria were documented to show evidence of the bacterium with the detection of the DNA of in these two mammals. In conclusion, this review has provided more insight on the prevalence of and its associated host/vector in Nigeria. Domestic animals, peri-domestic animals, and ticks species harbor and could be a source of human infections. Due to the paucity of studies from southern Nigeria, we recommend that research groups with interest on vector-borne diseases need to consider more epidemiological studies in the future on prevalence in diverse hosts to help unravel their distribution and vector potentials in Nigeria as a whole.
PubMed: 37888137
DOI: 10.3390/idr15050056 -
F1000Research 2022: Climatic change is an inescapable fact that implies alterations in seasons where weather occurrences have their schedules shift from the regular and magnitudes...
: Climatic change is an inescapable fact that implies alterations in seasons where weather occurrences have their schedules shift from the regular and magnitudes intensify to more extreme variations over a multi-year period. Southeast Asia is one of the many regions experiencing changes in climate and concurrently still has endemicities of malaria. Given that previous studies have suggested the influence of climate on malaria's vector the mosquitoes and parasite the Plasmodium group, this study was conducted to review the evidence of associations made between malaria cases and climatic variables in Southeast Asia throughout a multi-year period. : Our systematic literature review was informed by the PRISMA guidelines and registered in PROSPERO: CRD42022301826 on 5 February 2022. We searched for original articles in English and Indonesian that focused on the associations between climatic variables and malaria cases. : The initial identification stage resulted in 535 records of possible relevance and after abstract screening and eligibility assessment we included 19 research articles for the systematic review. Based on the reviewed articles, changing temperatures, precipitation, humidity and windspeed were considered for statistical association across a multi-year period and are correlated with malaria cases in various regions throughout Southeast Asia. : According to the review of evidence, climatic variables that exhibited a statistically significant correlation with malaria cases include temperatures, precipitation, and humidity. The strength of each climatic variable varies across studies. Our systematic review of the limited evidence indicates that further research for the Southeast Asia region remains to be explored.
Topics: Animals; Climate Change; Mosquito Vectors; Malaria; Anopheles; Asia, Southeastern; Asia, Eastern
PubMed: 37867624
DOI: 10.12688/f1000research.125294.2 -
Veterinary Microbiology Nov 2023Ticks are the main vectors for the transmission of bacterial, protist and viral pathogens in Europe affecting wildlife and domestic animals. However, some of them are... (Review)
Review
Exploring the diversity of tick-borne pathogens: The case of bacteria (Anaplasma, Rickettsia, Coxiella and Borrelia) protozoa (Babesia and Theileria) and viruses (Orthonairovirus, tick-borne encephalitis virus and louping ill virus) in the European continent.
Ticks are the main vectors for the transmission of bacterial, protist and viral pathogens in Europe affecting wildlife and domestic animals. However, some of them are zoonotic and can cause serious, sometimes fatal, problems in human health. A systematic review in PubMed/MEDLINE database was conducted to determine the spatial distribution and host and tick species ranges of a selection of tick-borne bacteria (Anaplasma spp., Borrelia spp., Coxiella spp., and Rickettsia spp.), protists (Babesia spp. and Theileria spp.), and viruses (Orthonairovirus, and flaviviruses tick-borne encephalitis virus and louping ill virus) on the European continent in a five-year period (November 2017 - November 2022). Only studies using PCR methods were selected, retrieving a total of 429 articles. Overall, up to 85 species of the selected tick-borne pathogens were reported from 36 European countries, and Anaplasma spp. was described in 37% (159/429) of the articles, followed by Babesia spp. (34%, 148/429), Borrelia spp. (34%, 147/429), Rickettsia spp. (33%, 142/429), Theileria spp. (11%, 47/429), tick-borne flaviviruses (9%, 37/429), Orthonairovirus (7%, 28/429) and Coxiella spp. (5%, 20/429). Host and tick ranges included 97 and 50 species, respectively. The highest tick-borne pathogen diversity was detected in domestic animals, and 12 species were shared between humans, wildlife, and domestic hosts, highlighting the following zoonotic species: Anaplasma phagocytophilum, Babesia divergens, Babesia microti, Borrelia afzelii, Borrelia burgdorferi s.s., Borrelia garinii, Borrelia miyamotoi, Crimean-Congo hemorrhagic fever virus, Coxiella burnetii, Rickettsia monacensis and tick-borne encephalitis virus. These results contribute to the implementation of effective interventions for the surveillance and control of tick-borne diseases.
Topics: Animals; Humans; Babesia; Encephalitis Viruses, Tick-Borne; Anaplasma; Theileria; Coxiella; Ixodes; Borrelia; Rickettsia; Animals, Domestic; Tick-Borne Diseases; Animals, Wild
PubMed: 37866329
DOI: 10.1016/j.vetmic.2023.109892 -
BMC Infectious Diseases Oct 2023Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical...
BACKGROUND
Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.
METHODS
We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).
RESULTS
We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.
CONCLUSIONS
Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.
Topics: Animals; Humans; Arboviruses; Aedes; Arbovirus Infections; Yellow Fever; Zika Virus Infection; Chikungunya Fever; Zika Virus; Mosquito Vectors; Dengue
PubMed: 37864153
DOI: 10.1186/s12879-023-08717-8 -
Infectious Diseases of Poverty Oct 2023Clonorchis sinensis, one of the most important food-borne zoonotic trematodes, remains prevalent in China. Understanding its infection status in animals is crucial for... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Clonorchis sinensis, one of the most important food-borne zoonotic trematodes, remains prevalent in China. Understanding its infection status in animals is crucial for controlling human clonorchiasis. Here we conducted a systematic review and meta-analysis to focus on the spatio-temporal disparities of C. sinensis infection in animals in China.
METHODS
Data on C. sinensis prevalence in snails, the second intermediate hosts, or animal reservoirs in China were extracted from electronic databases including PubMed, Embase, Web of Science, Chinese Wanfang database, CNKI, VIP, and China Biomedical Literature database. A random-effects meta-analysis model was utilized to estimate the pooled prevalence in each of the above animal hosts. Subgroup analysis and multivariable meta-regression were performed to explore potential sources of heterogeneity across studies and compare the temporal disparity of infection rates between high and low epidemic areas. Scatter plots were used to depict the biogeographical characteristics of regions reporting C. sinensis infection in animals.
RESULTS
The overall pooled prevalence of C. sinensis was 0.9% (95% CI: 0.6-1.2%) in snails, 14.2% (12.7-15.7%) in the second intermediate host, and 14.3% (11.4-17.6%) in animal reservoirs. Prevalence in low epidemic areas (with human prevalence < 1%) decreased from 0.6% (0.2-1.2%) before 1990 to 0.0% (0.0-3.6%) after 2010 in snails (P = 0.0499), from 20.3% (15.6-25.3%) to 8.8% (5.6-12.6%) in the second intermediate hosts (P = 0.0002), and from 18.3% (12.7-24.7%) to 4.7% (1.0-10.4%) in animal reservoirs. However, no similar decrease in prevalence was observed in high epidemic areas (with human prevalence ≥ 1.0%). C. sinensis infections were predominantly reported in areas with altitudes below 2346 m and annual cumulative precipitation above 345 mm and were mostly concentrated in eastern China.
CONCLUSIONS
There are spatio-temporal disparities in the animal infections of C. sinensis in different areas of China. Animal infections are primarily concentrated in regions with low altitude and high precipitation. The results suggest that implementing One Health-based comprehensive measures targeting both humans and animals, especially in high epidemic areas, is essential for successful eradication of C. sinensis in China.
Topics: Animals; Humans; Clonorchiasis; Clonorchis sinensis; China; Prevalence; Snails
PubMed: 37845775
DOI: 10.1186/s40249-023-01146-4