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Zoonoses and Public Health Aug 2024Lyme disease (LD), caused by the spirochete Borrelia burgdorferi, is the most common vector-borne disease in the United States. Although most surveillance-reported cases... (Review)
Review
INTRODUCTION
Lyme disease (LD), caused by the spirochete Borrelia burgdorferi, is the most common vector-borne disease in the United States. Although most surveillance-reported cases are in people who are White, data suggest worse outcomes among people from racial and ethnic minority groups.
METHODS
We conducted a systematic literature review to describe racial disparities in LD. We described the epidemiology of LD by race and ethnicity, including clinical presentation at diagnosis, and summarised the literature on knowledge, attitudes and practices related to LD and ticks by race and ethnicity.
RESULTS
Overall, the incidence and prevalence of LD were 1.2-3.5 times higher in White persons than in persons who identified as Asian or Pacific Islander and 4.5-6.3 times higher in White persons than in persons who identified as Black. Across multiple studies, people from racial and ethnic minority groups were more likely than White people to have disseminated manifestations of LD, including neurological manifestations and arthritis, and less likely to have erythema migrans. People from racial and ethnic minority groups were also more likely to report disease onset in the fall and less likely to report disease onset in the summer. Possible reasons for these disparities include lack of recognition of the disease in people with darker skin tones, lack of knowledge of disease risk for some groups and differences in exposure risk.
CONCLUSIONS
Taken together, these results reinforce that all people residing in high-incidence areas are at risk of LD, regardless of race or ethnicity. Future prevention measures should be broadly targeted to reach all at-risk populations.
Topics: Lyme Disease; Humans; United States; Ethnicity; Incidence; Health Status Disparities; Animals
PubMed: 38659178
DOI: 10.1111/zph.13137 -
Parasites & Vectors Jul 2023Eucoleus aerophilus (syn. Capillaria aerophila) is a nematode with a worldwide geographical distribution. It causes a disease called lung capillariosis by affecting the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Eucoleus aerophilus (syn. Capillaria aerophila) is a nematode with a worldwide geographical distribution. It causes a disease called lung capillariosis by affecting the respiratory tract of wild and domestic animals, and has also occasionally been described in humans. Despite steady increases in knowledge of the morphology of this neglected parasite, many aspects are still poorly understood. Epidemiological data regarding, for example, geographic distribution, range of hosts, clinical relevance and the actual zoonotic potential of this nematode are scarce and incomplete.
METHODS
This article is a systematic review based on the screening of three databases (PubMed, Web of Science and Science Direct) to identify eligible studies published from 1973 to the end of 2022.
RESULTS
From a total of 606 studies describing the occurrence of E. aerophilus, 141 articles from 38 countries worldwide were included in this meta-analysis, all of which presented results obtained mainly with flotation and necropsy. Due to the occurrence of E. aerophilus in many different species and different matrices (lungs and faeces), we decided to conduct the meta-analysis separately for each species with a given matrix. This systematic review confirmed the status of the Red fox as the main reservoir and main transmitter of E. aerophilus (average prevalence of 43% in faeces and 49% in lungs) and provided evidence of a higher prevalence of E. aerophilus in wild animals in comparison to domestic animals, such as dogs (3% in faeces) and cats (2% in faeces and 8% in lungs). Previous studies have investigated many host-related factors (age, sex, environmental/living conditions) in relation to the prevalence of E. aerophilus, but they show wide variations and no simple relationship has been demonstrates. Furthermore, mixed infections with other pulmonary nematodes, such as Crenosoma vulpis and/or Angiostrongylus vasorum, are reported very frequently, which greatly complicates the diagnosis.
CONCLUSIONS
This systematic review focused on identifying data gaps and promoting future research directions in this area. To the best of our knowledge, this is the first systematic review that evaluates and summarizes existing knowledge on the occurrence and prevalence of E. aerophilus in wild and domestic animals originating from different geographical locations worldwide.
Topics: Animals; Dogs; Cats; Humans; Nematode Infections; Animals, Domestic; Animals, Wild; Lung; Metastrongyloidea; Foxes
PubMed: 37475031
DOI: 10.1186/s13071-023-05830-0 -
Frontiers in Neurology 2024Guillain-Barré syndrome (GBS) is a rare disease that affects almost 0.8-1.9 cases per 100,000 people worldwide every year. This is the most prevalent cause of subacute... (Review)
Review
INTRODUCTION
Guillain-Barré syndrome (GBS) is a rare disease that affects almost 0.8-1.9 cases per 100,000 people worldwide every year. This is the most prevalent cause of subacute flaccid paralyzing illness today. It is a subacute inflammatory demyelinating polyradiculoneuropathy; the typical scenario involves ascending symmetrical flaccid paralysis, but in some circumstances, sensory, autonomic, and cranial neuropathy may also be involved. Several vaccines have been found to have complications since the previous century. Numerous case reports of GBS in the literature have been reported following COVID-19 vaccines in recent times.
OBJECTIVE
This study aimed to conduct a comprehensive examination of GBS cases that have been reported after COVID-19 vaccines; to analyze the descriptive statistical analysis of data gathered regarding clinical, laboratory, electrophysiological, and radiological characteristics; to discuss, based on the available evidence, whether the disease has a preference for a particular vaccine type; and to speculate on the potential pathogenesis.
METHODOLOGY
This review has been carried out by recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
RESULT
Reviewing 60 case reports illustrated that most of them are from the USA (18.1%) and the majority of affected individuals were males (60%). The results favored the association between vector-based SARS-CoV-2 vaccine, particularly AstraZeneca vaccine, and the GBS. The mean of symptoms onset is 11.4 days. The results of diagnostic tests such as LP are consistent mostly with albumin-cytological dissociation (81.81%), where brain and spine MRI was unremarkable in 59.52%. Regarding electrodiagnostic tests, AIDP is the most common variant (61.81%). The management was not consistent among the case reports. However, IVIG is the most frequent way of treating these patients (68.33%). The functional outcome was documented in 47 patients; 65% improved with medical management.
CONCLUSION
This study aimed to conduct a systematic review of reported cases of GBS following COVID-19 vaccines and descriptive statistical analysis of collected data on clinical, laboratory, electrophysiological, and radiological features, to discuss, based on available results, whether the disease has a predilection to a specific vaccine type and to speculate the potential pathogenesis.
PubMed: 38352138
DOI: 10.3389/fneur.2024.1332364 -
Vector Borne and Zoonotic Diseases... May 2024The burden of zoonotic diseases in developing countries is significantly underestimated, influenced by various factors such as misdiagnosis, underreporting, natural... (Review)
Review
The burden of zoonotic diseases in developing countries is significantly underestimated, influenced by various factors such as misdiagnosis, underreporting, natural disasters, climate change, resource limitations, rapid unplanned urbanization, poverty, animal migration, travel, ecotourism, and the tropical environmental conditions prevalent in the region. Despite Sri Lanka's provision of a publicly funded free health care system, zoonoses still contribute significantly to the burden of communicable diseases in the country. This study serves as a timely and exhaustive systematic review of zoonoses reported over the past 22 years in Sri Lanka. This systematic review adhered to the guidelines provided by the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA) statement. A systematic literature search was conducted between July and September 2022, utilizing the following databases and sources: Google Scholar, PubMed, Cochrane Library, Weekly Epidemiological Reports, and Rabies Statistical Bulletins published by the Ministry of Health, Sri Lanka. From the initial database search, 1,710 articles were identified. After excluding nonzoonotic diseases, duplicated reports, inaccessible articles, and those not meeting the inclusion criteria, 570 reports were evaluated for eligibility. Of these, 91 reports were selected for data extraction, comprising 58 original research articles, 10 case reports, 16 weekly epidemiological reports, and 7 rabies statistical bulletins. Over the study period (2000-2022), 14 parasitic, 7 bacterial, and 7 viral zoonoses have been reported in Sri Lanka. Notably, leptospirosis emerged as the most reported zoonotic disease in the country. In response to these findings, we strongly recommend the implementation of a tailored, country-specific prevention and control program. To achieve this goal effectively, we emphasize the importance of adopting a country-specific "One Health" approach as a comprehensive framework for managing and controlling zoonotic diseases in Sri Lanka.
PubMed: 38775108
DOI: 10.1089/vbz.2023.0141 -
Frontiers in Aging Neuroscience 2023In recent years, radiomics has been increasingly utilized for the differential diagnosis of Parkinson's disease (PD). However, the application of radiomics in PD...
BACKGROUND
In recent years, radiomics has been increasingly utilized for the differential diagnosis of Parkinson's disease (PD). However, the application of radiomics in PD diagnosis still lacks sufficient evidence-based support. To address this gap, we carried out a systematic review and meta-analysis to evaluate the diagnostic value of radiomics-based machine learning (ML) for PD.
METHODS
We systematically searched Embase, Cochrane, PubMed, and Web of Science databases as of November 14, 2022. The radiomics quality assessment scale (RQS) was used to evaluate the quality of the included studies. The outcome measures were the c-index, which reflects the overall accuracy of the model, as well as sensitivity and specificity. During this meta-analysis, we discussed the differential diagnostic value of radiomics-based ML for Parkinson's disease and various atypical parkinsonism syndromes (APS).
RESULTS
Twenty-eight articles with a total of 6,057 participants were included. The mean RQS score for all included articles was 10.64, with a relative score of 29.56%. The pooled c-index, sensitivity, and specificity of radiomics for predicting PD were 0.862 (95% CI: 0.833-0.891), 0.91 (95% CI: 0.86-0.94), and 0.93 (95% CI: 0.87-0.96) in the training set, and 0.871 (95% CI: 0.853-0.890), 0.86 (95% CI: 0.81-0.89), and 0.87 (95% CI: 0.83-0.91) in the validation set, respectively. Additionally, the pooled c-index, sensitivity, and specificity of radiomics for differentiating PD from APS were 0.866 (95% CI: 0.843-0.889), 0.86 (95% CI: 0.84-0.88), and 0.80 (95% CI: 0.75-0.84) in the training set, and 0.879 (95% CI: 0.854-0.903), 0.87 (95% CI: 0.85-0.89), and 0.82 (95% CI: 0.77-0.86) in the validation set, respectively.
CONCLUSION
Radiomics-based ML can serve as a potential tool for PD diagnosis. Moreover, it has an excellent performance in distinguishing Parkinson's disease from APS. The support vector machine (SVM) model exhibits excellent robustness when the number of samples is relatively abundant. However, due to the diverse implementation process of radiomics, it is expected that more large-scale, multi-class image data can be included to develop radiomics intelligent tools with broader applicability, promoting the application and development of radiomics in the diagnosis and prediction of Parkinson's disease and related fields.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=383197, identifier ID: CRD42022383197.
PubMed: 37484694
DOI: 10.3389/fnagi.2023.1199826 -
Clinical Infectious Diseases : An... Jan 2024Tularemia is caused by the gram-negative bacterium Francisella tularensis. Although rare, tularemia during pregnancy has been associated with pregnancy complications;...
BACKGROUND
Tularemia is caused by the gram-negative bacterium Francisella tularensis. Although rare, tularemia during pregnancy has been associated with pregnancy complications; data on efficacy of recommended antimicrobials for treatment are limited. We performed a systematic literature review to characterize clinical manifestations of tularemia during pregnancy and examine maternal, fetal, and neonatal outcomes with and without antimicrobial treatment.
METHODS
We searched 9 databases, including Medline, Embase, Global Health, and PubMed Central, using terms related to tularemia and pregnancy. Articles reporting cases of tularemia with ≥1 maternal or fetal outcome were included.
RESULTS
Of 5891 articles identified, 30 articles describing 52 cases of tularemia in pregnant patients met inclusion criteria. Cases were reported from 9 countries, and oropharyngeal and ulceroglandular tularemia were the most common presenting forms. A plurality (46%) of infections occurred in the second trimester. Six complications were observed: lymph node aspiration, lymph node excision, maternal bleeding, spontaneous abortion, intrauterine fetal demise, and preterm birth. No deaths among mothers were reported. Of 28 patients who received antimicrobial treatment, 1 pregnancy loss and 1 fetal death were reported. Among 24 untreated patients, 1 pregnancy loss and 3 fetal deaths were reported, including one where F. tularensis was detected in placental and fetal tissues.
CONCLUSIONS
Pregnancy loss and other complications have been reported among cases of tularemia during pregnancy. However, risk of adverse outcomes may be lower when antimicrobials known to be effective are used. Without treatment, transplacental transmission appears possible. These data underscore the importance of prompt recognition and treatment of tularemia during pregnancy.
Topics: Humans; Female; Infant, Newborn; Pregnancy; Tularemia; Premature Birth; Placenta; Francisella tularensis; Abortion, Spontaneous; Anti-Infective Agents
PubMed: 38294114
DOI: 10.1093/cid/ciad686 -
Journal of Trace Elements in Medicine... May 2024Cutaneous leishmaniasis (LC) is an infectious vector-borne disease caused by parasites belonging to the genus Leishmania. Metallic nanoparticles (MNPs) have been... (Review)
Review
BACKGROUND
Cutaneous leishmaniasis (LC) is an infectious vector-borne disease caused by parasites belonging to the genus Leishmania. Metallic nanoparticles (MNPs) have been investigated as alternatives for the treatment of LC owing to their small size and high surface area. Here, we aimed to evaluate the effect of MNPs in the treatment of LC through experimental, in vitro and in vivo investigations.
METHODS
The databases used were MEDLINE/ PubMed, Scopus, Web of Science, Embase, and Science Direct. Manual searches of the reference lists of the included studies and grey literature were also performed. English language and experimental in vitro and in vivo studies using different Leishmania species, both related to MNP treatment, were included. This study was registered in PROSPERO (CRD42021248245).
RESULTS
A total of 93 articles were included. Silver nanoparticles are the most studied MNPs, and L. tropica is the most studied species. Among the mechanisms of action of MNPs in vitro, we highlight the production of reactive oxygen species, direct contact of MNPs with the biomolecules of the parasite, and release of metal ions.
CONCLUSION
MNPs may be considered a promising alternative for the treatment of LC, but further studies are needed to define their efficacy and safety.
Topics: Humans; Leishmania tropica; Metal Nanoparticles; Silver; Leishmaniasis, Cutaneous
PubMed: 38364464
DOI: 10.1016/j.jtemb.2024.127404 -
Parasites & Vectors Aug 2023Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they...
Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.
Topics: Humans; Animals; Mosquito Vectors; Africa; Asia; Culicidae; Disease Outbreaks
PubMed: 37641089
DOI: 10.1186/s13071-023-05912-z -
Microorganisms Jul 2023Control and treatment programs (CDTI) have been set up nationally in all endemic countries to overcome the impact of onchocerciasis on the affected populations. However,... (Review)
Review
Control and treatment programs (CDTI) have been set up nationally in all endemic countries to overcome the impact of onchocerciasis on the affected populations. However, Gabon must still succeed in setting up real onchocerciasis control programs. Here, various database articles have been used to provide the scientific community with a summary document showing the mapping of this disease in Gabon. The articles dealing with onchocerciasis, animal reservoirs, surveillance, and elimination were analyzed. Results showed that little research has been performed. Most studies are concentrated in one region (The area of Lastourville). In addition, we observed that the distribution of the disease varies significantly across the country. Indeed, specific environments present a hyper-endemicity of the disease, while others are meso and hypo-endemic. So, we found some departments with a prevalence ranging from 0% to over 20%; within them, villages had infection levels comprising 10% to 60%, indicating potential hotspots. Vectors activities were studied in some areas. This paper showed the challenges encountered in the country to eliminate this disease. One solution is a deeper understanding of the disease's bioecology to establish effective health policies to eliminate onchocerciasis in Gabon effectively.
PubMed: 37630506
DOI: 10.3390/microorganisms11081946 -
Journal of Medical Internet Research Jul 2023Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic,... (Review)
Review
BACKGROUND
Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological improvements and emerging machine learning (ML) technologies have enabled possibilities of extracting digital vocal features from the voice for automated diagnosis and monitoring systems.
OBJECTIVE
This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring through voice samples where systematic conditions, nonlaryngeal aerodigestive disorders, and neurological disorders are specifically of interest.
METHODS
This systematic literature review (SLR) investigated the state of the art of voice-based diagnostic and monitoring systems with ML technologies, targeting voice-affecting disorders without direct relation to the voice box from the point of view of applied health technology. Through a comprehensive search string, studies published from 2012 to 2022 from the databases Scopus, PubMed, and Web of Science were scanned and collected for assessment. To minimize bias, retrieval of the relevant references in other studies in the field was ensured, and 2 authors assessed the collected studies. Low-quality studies were removed through a quality assessment and relevant data were extracted through summary tables for analysis. The articles were checked for similarities between author groups to prevent cumulative redundancy bias during the screening process, where only 1 article was included from the same author group.
RESULTS
In the analysis of the 145 included studies, support vector machines were the most utilized ML technique (51/145, 35.2%), with the most studied disease being Parkinson disease (PD; reported in 87/145, 60%, studies). After 2017, 16 additional voice-affecting disorders were examined, in contrast to the 3 investigated previously. Furthermore, an upsurge in the use of artificial neural network-based architectures was observed after 2017. Almost half of the included studies were published in last 2 years (2021 and 2022). A broad interest from many countries was observed. Notably, nearly one-half (n=75) of the studies relied on 10 distinct data sets, and 11/145 (7.6%) used demographic data as an input for ML models.
CONCLUSIONS
This SLR revealed considerable interest across multiple countries in using ML techniques for diagnosing and monitoring voice-affecting disorders, with PD being the most studied disorder. However, the review identified several gaps, including limited and unbalanced data set usage in studies, and a focus on diagnostic test rather than disorder-specific monitoring. Despite the limitations of being constrained by only peer-reviewed publications written in English, the SLR provides valuable insights into the current state of research on ML-based voice-affecting disorder diagnosis and monitoring and highlighting areas to address in future research.
Topics: Humans; Monitoring, Physiologic; Machine Learning
PubMed: 37467031
DOI: 10.2196/46105