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Annals of Clinical Microbiology and... Sep 2023Urogenital Mycoplasma infections are considered an important public health problem, owing to the presence of antibiotic resistance or decreased susceptibility, the... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Urogenital Mycoplasma infections are considered an important public health problem, owing to the presence of antibiotic resistance or decreased susceptibility, the treatment options are limited.
OBJECTIVE
Therefore, this meta-analysis aimed to estimate resistance rates of genital Mycoplasmas to tetracyclines (tetracycline, doxycycline, and minocycline).
METHODS
We searched the relevant published studies in PubMed, Scopus, and Embase until 3, March 2022. All statistical analyses were carried out using the statistical package R.
RESULTS
The 26 studies included in the analysis were performed in 15 countries. In the metadata, the proportions of tetracycline, doxycycline, and minocycline resistance in Mycoplasma and Ureaplasma urogenital isolates were reported 14.2% (95% CI 8.2-23.2%), 5% (95% CI 3-8.1%), and 11.9% (95% CI 6.3-21.5%), respectively. According to the meta-regression, the tetracycline and minocycline resistance rate decreased over time. Although, the doxycycline resistance rate increased over time. There was a statistically significant difference in the tetracyclines resistance rates between different continents/countries (P < 0.05).
CONCLUSION
The prevalence rate and antibiotic susceptibility profiles vary geographically. Therefore, rigorous or improved antimicrobial stewardship, contact tracing, and enhanced intensive surveillance systems are necessitated for preventing the emergence and further spreading of tetracyclines resistance in genital Mycoplasmas.
Topics: Humans; Mycoplasma; Tetracycline; Doxycycline; Minocycline; Anti-Bacterial Agents
PubMed: 37697380
DOI: 10.1186/s12941-023-00628-5 -
Viruses Jan 2020A majority of emerging infectious diseases are of zoonotic origin. Metagenomic Next-Generation Sequencing (mNGS) has been employed to identify uncommon and novel...
A majority of emerging infectious diseases are of zoonotic origin. Metagenomic Next-Generation Sequencing (mNGS) has been employed to identify uncommon and novel infectious etiologies and characterize virus diversity in human, animal, and environmental samples. Here, we systematically reviewed studies that performed viral mNGS in common livestock (cattle, small ruminants, poultry, and pigs). We identified 2481 records and 120 records were ultimately included after a first and second screening. Pigs were the most frequently studied livestock and the virus diversity found in samples from poultry was the highest. Known animal viruses, zoonotic viruses, and novel viruses were reported in available literature, demonstrating the capacity of mNGS to identify both known and novel viruses. However, the coverage of metagenomic studies was patchy, with few data on the virome of small ruminants and respiratory virome of studied livestock. Essential metadata such as age of livestock and farm types were rarely mentioned in available literature, and only 10.8% of the datasets were publicly available. Developing a deeper understanding of livestock virome is crucial for detection of potential zoonotic and animal pathogens and One Health preparedness. Metagenomic studies can provide this background but only when combined with essential metadata and following the "FAIR" (Findable, Accessible, Interoperable, and Reusable) data principles.
Topics: Animals; Cattle; Communicable Diseases, Emerging; Disease Reservoirs; Farms; Genome, Viral; High-Throughput Nucleotide Sequencing; Livestock; Metagenome; Metagenomics; One Health; RNA, Viral; Virus Diseases; Viruses; Zoonoses
PubMed: 31963174
DOI: 10.3390/v12010107 -
JPMA. the Journal of the Pakistan... May 2023To review the seroprevalence of toxoplasmosis in Pakistan.
OBJECTIVE
To review the seroprevalence of toxoplasmosis in Pakistan.
METHODS
The systematic review comprised search on Science Direct, Google Scholar, PubMed and Scopus databases for studies related to the seroprevalence of toxoplasmosis in Pakistan published between 2006 and 2020 which used serological diagnostic tests to detect Toxoplasma gondii. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used throughout the review and statistical analysis was done using forest plot and random effect model.
RESULTS
Of the 7093 human studies initially found, 20(0.28%) were reviewed. Of the 16,432 animal studies, 16(0.09%) were selected for detailed review. The pooled seroprevalence of toxoplasmosis in humans, calculated in this review was found as (76%) (95% confidence interval: 69-83%). Seroprevalence of human toxoplasmosis was higher in Khyber Pakhtunkhwa (31.7%) than Punjab (20.4%). Pooled seroprevalence in animals calculated in this review was found as (69%) (95% confidence interval: 64-74%). Seroprevalence in animals was higher in Khyber Pakhtunkhwa (44.7%) than Punjab (29.4%).
CONCLUSIONS
The seroprevalence of toxoplasmosis in both humans and animals should be studied it other parts of Pakistan as well.
Topics: Animals; Humans; Pakistan; Seroepidemiologic Studies; Metadata; Antibodies, Protozoan; Toxoplasmosis; Risk Factors
PubMed: 37218234
DOI: 10.47391/JPMA.5699 -
PLOS Digital Health May 2022Federated learning (FL) allows multiple institutions to collaboratively develop a machine learning algorithm without sharing their data. Organizations instead share...
OBJECTIVES
Federated learning (FL) allows multiple institutions to collaboratively develop a machine learning algorithm without sharing their data. Organizations instead share model parameters only, allowing them to benefit from a model built with a larger dataset while maintaining the privacy of their own data. We conducted a systematic review to evaluate the current state of FL in healthcare and discuss the limitations and promise of this technology.
METHODS
We conducted a literature search using PRISMA guidelines. At least two reviewers assessed each study for eligibility and extracted a predetermined set of data. The quality of each study was determined using the TRIPOD guideline and PROBAST tool.
RESULTS
13 studies were included in the full systematic review. Most were in the field of oncology (6 of 13; 46.1%), followed by radiology (5 of 13; 38.5%). The majority evaluated imaging results, performed a binary classification prediction task via offline learning (n = 12; 92.3%), and used a centralized topology, aggregation server workflow (n = 10; 76.9%). Most studies were compliant with the major reporting requirements of the TRIPOD guidelines. In all, 6 of 13 (46.2%) of studies were judged at high risk of bias using the PROBAST tool and only 5 studies used publicly available data.
CONCLUSION
Federated learning is a growing field in machine learning with many promising uses in healthcare. Few studies have been published to date. Our evaluation found that investigators can do more to address the risk of bias and increase transparency by adding steps for data homogeneity or sharing required metadata and code.
PubMed: 36812504
DOI: 10.1371/journal.pdig.0000033 -
Reproduction (Cambridge, England) Jun 2023Adverse trends in reproductive function are a concern in humans, companion, livestock, and wildlife species. This study indicates that equine populations are at risk of...
IN BRIEF
Adverse trends in reproductive function are a concern in humans, companion, livestock, and wildlife species. This study indicates that equine populations are at risk of a comparable decline in sperm progressive motility.
ABSTRACT
There is increasing evidence reporting geographically sensitive adverse trends in human semen quality, with parallel trends observed in the dog sentinel. Despite significant economic and welfare complications associated with poor testicular function, trends in current equine populations are undetermined. Given the predictive value of sperm progressive motility (PMOT) in male factor infertility and fertilisation potential, research determining trends in this parameter is warranted. This research analysed trends in stallion sperm PMOT through systematic review and meta-regression. Using a comprehensive search strategy, Scopus, Embase (Ovid), Medline (Ovid), and VetMed (CAB direct) were scoped for eligible data. Using best practices, 230 meta-data points from 229 articles published from 1991 to 2021 were collated for meta-regression analysis. Sperm PMOT declined significantly between 1984 and 2019 (simple linear regression: b -0.340, P = 0.017; meta-regression: b -0.610, P ≤ 0.001). Overall and yearly PMOT declines were predicted at 33.51 and 0.96%, respectively (1984: 63.69 ± 5.07%; 2019: 42.35 ± 3.69%). Trends remained consistent irrespective of sensitivity analyses. Yearly and overall declines were stronger in western (yearly: 0.75%, overall: 26.29%) compared to non-western (yearly: 0.46%, overall: 10.65%) populations. Adverse trends contribute vital data to the debate surrounding declining semen quality, supporting the use of equines as novel comparative models for human reproduction. Results could have significant economic, health, and welfare consequences for equine breeding sectors. A comparable decline in human, dog, and horse sperm quality is indicative of a common environmental aetiology, indicating the need for a holistic One Health approach in determining causes and developing preventative strategies.
Topics: Male; Horses; Animals; Humans; Dogs; Semen Analysis; Semen; Sperm Motility; Spermatozoa; Infertility, Male; Sperm Count
PubMed: 37000597
DOI: 10.1530/REP-22-0490 -
PLOS Global Public Health 2023Enteric and parasitic infections such as soil-transmitted helminths cause considerable mortality and morbidity in low- and middle-income settings. Earthen household...
Enteric and parasitic infections such as soil-transmitted helminths cause considerable mortality and morbidity in low- and middle-income settings. Earthen household floors are common in many of these settings and could serve as a reservoir for enteric and parasitic pathogens, which can easily be transmitted to new hosts through direct or indirect contact. We conducted a systematic review and meta-analysis to establish whether and to what extent improved household floors decrease the odds of enteric and parasitic infections among occupants compared with occupants living in households with unimproved floors. Following the PRISMA guidelines, we comprehensively searched four electronic databases for studies in low- and middle-income settings measuring household flooring as an exposure and self-reported diarrhoea or any type of enteric or intestinal-parasitic infection as an outcome. Metadata from eligible studies were extracted and transposed on to a study database before being imported into the R software platform for analysis. Study quality was assessed using an adapted version of the Newcastle-Ottawa Quality Assessment Scale. In total 110 studies were eligible for inclusion in the systematic review, of which 65 were eligible for inclusion in the meta-analysis after applying study quality cut-offs. Random-effects meta-analysis suggested that households with improved floors had 0.75 times (95CI: 0.67-0.83) the odds of infection with any type of enteric or parasitic infection compared with household with unimproved floors. Improved floors gave a pooled protective OR of 0.68 (95CI: 0.58-0.8) for helminthic infections and 0.82 OR (95CI: 0.75-0.9) for bacterial or protozoan infections. Overall study quality was poor and there is an urgent need for high-quality experimental studies investigating this relationship. Nevertheless, this study indicates that household flooring may meaningfully contribute towards a substantial portion of the burden of disease for enteric and parasitic infections in low- and middle-income settings.
PubMed: 38039279
DOI: 10.1371/journal.pgph.0002631 -
BMJ Open Jan 2023Various studies have been published to better understand the underlying spatial and temporal dynamics of COVID-19. This review sought to identify different spatial and...
OBJECTIVE
Various studies have been published to better understand the underlying spatial and temporal dynamics of COVID-19. This review sought to identify different spatial and spatio-temporal modelling methods that have been applied to COVID-19 and examine influential covariates that have been reportedly associated with its risk in Africa.
DESIGN
Systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
DATA SOURCES
Thematically mined keywords were used to identify refereed studies conducted between January 2020 and February 2022 from the following databases: PubMed, Scopus, MEDLINE via Proquest, CINHAL via EBSCOhost and Coronavirus Research Database via ProQuest. A manual search through the reference list of studies was also conducted.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES
Peer-reviewed studies that demonstrated the application of spatial and temporal approaches to COVID-19 outcomes.
DATA EXTRACTION AND SYNTHESIS
A standardised extraction form based on critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist was used to extract the meta-data of the included studies. A validated scoring criterion was used to assess studies based on their methodological relevance and quality.
RESULTS
Among 2065 hits in five databases, title and abstract screening yielded 827 studies of which 22 were synthesised and qualitatively analysed. The most common socioeconomic variable was population density. HIV prevalence was the most common epidemiological indicator, while temperature was the most common environmental indicator. Thirteen studies (59%) implemented diverse formulations of spatial and spatio-temporal models incorporating unmeasured factors of COVID-19 and the subtle influence of time and space. Cluster analyses were used across seven studies (32%) to explore COVID-19 variation and determine whether observed patterns were random.
CONCLUSION
COVID-19 modelling in Africa is still in its infancy, and a range of spatial and spatio-temporal methods have been employed across diverse settings. Strengthening routine data systems remains critical for generating estimates and understanding factors that drive spatial variation in vulnerable populations and temporal variation in pandemic progression.
PROSPERO REGISTRATION NUMBER
CRD42021279767.
Topics: Humans; COVID-19; Africa; Cluster Analysis
PubMed: 36697047
DOI: 10.1136/bmjopen-2022-067134 -
PloS One 2023Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and...
Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available. Therefore, one may find it difficult to identify trends, successful paths, gaps, and opportunities for contribution. The present literature review aims to provide the state of research regarding deception detection with Machine Learning. We followed the PRISMA protocol and retrieved 648 articles from ACM Digital Library, IEEE Xplore, Scopus, and Web of Science. 540 of them were screened (108 were duplicates). A final corpus of 81 documents has been summarized as mind maps. Metadata was extracted and has been encoded as Python dictionaries to support a statistical analysis scripted in Python programming language, and available as a collection of Jupyter Lab Notebooks in a GitHub repository. All are available as Jupyter Lab Notebooks. Neural Networks, Support Vector Machines, Random Forest, Decision Tree and K-nearest Neighbor are the five most explored techniques. The studies report a detection performance ranging from 51% to 100%, with 19 works reaching accuracy rate above 0.9. Monomodal, Bimodal, and Multimodal approaches were exploited and achieved various accuracy levels for detection. Bimodal and Multimodal approaches have become a trend over Monomodal ones, although there are high-performance examples of the latter. Studies that exploit language and linguistic features, 75% are dedicated to English. The findings include observations of the following: language and culture, emotional features, psychological traits, cognitive load, facial cues, complexity, performance, and Machine Learning topics. We also present a dataset benchmark. Main conclusions are that labeled datasets from real-life data are scarce. Also, there is still room for new approaches for deception detection with Machine Learning, especially if focused on languages and cultures other than English-based. Further research would greatly contribute by providing new labeled and multimodal datasets for deception detection, both for English and other languages.
Topics: Neural Networks, Computer; Research Design; Publications; Machine Learning; Deception
PubMed: 36757928
DOI: 10.1371/journal.pone.0281323 -
Malaria Journal Jan 2021Malaria and HIV are two important public health issues. However, evidence on HIV-Plasmodium vivax co-infection (HIV/PvCo) is scarce, with most of the available...
BACKGROUND
Malaria and HIV are two important public health issues. However, evidence on HIV-Plasmodium vivax co-infection (HIV/PvCo) is scarce, with most of the available information related to Plasmodium falciparum on the African continent. It is unclear whether HIV can change the clinical course of vivax malaria and increase the risk of complications. In this study, a systematic review of HIV/PvCo studies was performed, and recent cases from the Brazilian Amazon were included.
METHODS
Medical records from a tertiary care centre in the Western Brazilian Amazon (2009-2018) were reviewed to identify HIV/PvCo hospitalized patients. Demographic, clinical and laboratory characteristics and outcomes are reported. Also, a systematic review of published studies on HIV/PvCo was conducted. Metadata, number of HIV/PvCo cases, demographic, clinical, and outcome data were extracted.
RESULTS
A total of 1,048 vivax malaria patients were hospitalized in the 10-year period; 21 (2.0%) were HIV/PvCo cases, of which 9 (42.9%) had AIDS-defining illnesses. This was the first malaria episode in 11 (52.4%) patients. Seven (33.3%) patients were unaware of their HIV status and were diagnosed on hospitalization. Severe malaria was diagnosed in 5 (23.8%) patients. One patient died. The systematic review search provided 17 articles (12 cross-sectional or longitudinal studies and 5 case report studies). A higher prevalence of studies involved cases in African and Asian countries (35.3 and 29.4%, respectively), and the prevalence of reported co-infections ranged from 0.1 to 60%.
CONCLUSION
Reports of HIV/PvCo are scarce in the literature, with only a few studies describing clinical and laboratory outcomes. Systematic screening for both co-infections is not routinely performed, and therefore the real prevalence of HIV/PvCo is unknown. This study showed a low prevalence of HIV/PvCo despite the high prevalence of malaria and HIV locally. Even though relatively small, this is the largest case series to describe HIV/PvCo.
Topics: Adolescent; Adult; Aged; Brazil; Child; Coinfection; Female; HIV Infections; HIV-1; Humans; Incidence; Malaria, Vivax; Male; Middle Aged; Plasmodium vivax; Prevalence; Young Adult
PubMed: 33407474
DOI: 10.1186/s12936-020-03518-9 -
MBio Dec 2021High-throughput 16S rRNA sequencing has allowed the characterization of helminth-uninfected (HU) and helminth-infected (HI) gut microbiomes, revealing distinct profiles.... (Meta-Analysis)
Meta-Analysis
High-throughput 16S rRNA sequencing has allowed the characterization of helminth-uninfected (HU) and helminth-infected (HI) gut microbiomes, revealing distinct profiles. However, there have been no qualitative or quantitative syntheses of these studies, which show marked variation in participant age, diet, pathogen of interest, and study location. A predefined minimally biased search strategy identified 23 studies in humans. For each of these studies, we qualitatively addressed the effects of helminth infection on within-individual (alpha) and between-individual (beta) fecal microbiome diversity, infection-associated microbial taxa, the effect of helminth clearance on microbiome composition, microbiome composition as a predictor of infection status or treatment outcome, and treatment-specific effects on the fecal microbiome. Concomitantly, we performed a meta-analysis on a subset of 7 of these studies containing raw, paired-end 16S reads and individual-level metadata, comprising 424 pretreatment or untreated HI individuals and 497 HU controls. After reducing the batch effect and adjusting for age, our data demonstrated that intestinal helminth parasites can alter the host gut microbiome by increasing alpha diversity and promoting taxonomic reassortment and gradient collapse. Most strongly influencing the microbiome composition were the helminths found in the large intestine, Enterobius vermicularis and Trichuris trichiura, suggesting that this influence appears to be specific to soil-transmitted helminths (STH) species and host anatomical niche. In summary, using a large and diverse sample set captured in the meta-analysis, we were able to evaluate the influence of individual helminth species as well as species-species interactions, each of which explained a significant portion of the variation in the microbiome. The gut microbiome has established importance in regulating many aspects of human health, including nutrition and immunity. While many internal and environmental factors are known to influence the microbiome, less is known about the effects of intestinal helminth parasites (worms), which together affect one-sixth of the world's population. Through a comprehensive qualitative systematic review and quantitative meta-analysis of existing literature, we provide strong evidence that helminth infection dynamically shifts the intestinal microbiome structure. Moreover, we demonstrated that such influence seems to be specific to helminth species and host anatomical niche. Our findings suggest that the gut microbiome may underlie some of the pathology associated with intestinal worm infection and support future work to understand the precise nature of the helminth-microbiome relationship.
Topics: Adolescent; Adult; Aged; Animals; Bacteria; Child; Child, Preschool; Dysbiosis; Feces; Female; Gastrointestinal Microbiome; Helminthiasis; Helminths; Humans; Infant; Male; Middle Aged; Phylogeny; Young Adult
PubMed: 34933444
DOI: 10.1128/mBio.02890-21