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ANZ Journal of Surgery Sep 2022Recurrent Testicular Torsion (RTT) is a rarely reported event after previous testicular torsion (TT) repair. Both conditions have similar signs and symptoms. Various... (Review)
Review
BACKGROUND
Recurrent Testicular Torsion (RTT) is a rarely reported event after previous testicular torsion (TT) repair. Both conditions have similar signs and symptoms. Various techniques have been attempted to reduce the incidence of retorsion. This review assesses the presentation, diagnosis, risk factors, management and outcomes associated with RTT.
METHODS
After PROSPERO Registration (CRD42021258997), a systematic search of PubMed, Google Scholar, Embase, Scopus, Web of Science, Cochrane Database of Systematic Reviews, Global Index Medicus and Cumulative Index to Nursing and Allied Health Literature (CIANHL) was performed using specific search terms. Study metadata including patient demographics, orchidopexy techniques, RTT rates and RTT timing were extracted.
RESULTS
Twenty-six articles, comprising 12 case series and 14 case reports, with a total of 46 patients were included. Overall, the median (IQR) age of the pooled cohort was 18 (15-26) years, the median (IQR) time to presentation was 6 (3-36) hours from the onset of testicular pain. The most common presenting features were testicular pain (100%), testicular swelling (60.9%) and a high riding testicle (34.8%). The left testicle was most commonly affected (63.0%), RTT was on the ipsilateral side in relation to the primary episode of TT in 52.2% of cases, the median (IQR) interval between torsion and retorsion events was 4 (1.3-10.0) years, non-absorbable sutures were the most common suture material used during orchidopexy after RTT (88.9%).
CONCLUSION
RTT is a rare presentation to the Emergency Department. Even with a prior history of TT, RTT should be considered in patients presenting with classic symptoms.
Topics: Adolescent; Adult; Humans; Male; Orchiopexy; Pain; Retrospective Studies; Spermatic Cord Torsion; Testicular Diseases; Young Adult
PubMed: 35257473
DOI: 10.1111/ans.17592 -
Epidemiology (Cambridge, Mass.) Nov 2018Seasonality in tuberculosis incidence has been widely observed across countries and populations; however, its drivers are poorly understood. We conducted a systematic...
BACKGROUND
Seasonality in tuberculosis incidence has been widely observed across countries and populations; however, its drivers are poorly understood. We conducted a systematic review of studies reporting seasonal patterns in tuberculosis to identify demographic and ecologic factors associated with timing and magnitude of seasonal variation.
METHODS
We identified studies reporting seasonal variation in tuberculosis incidence through PubMed and EMBASE and extracted incidence data and population metadata. We described key factors relating to seasonality and, when data permitted, quantified seasonal variation and its association with metadata. We developed a dynamic tuberculosis natural history and transmission model incorporating seasonal differences in disease progression and/or transmission rates to examine magnitude of variation required to produce observed seasonality in incidence.
RESULTS
Fifty-seven studies met inclusion criteria. In the majority of studies (n=49), tuberculosis incidence peaked in spring or summer and reached a trough in late fall or winter. A standardized seasonal amplitude was calculated for 34 of the studies, resulting in a mean of 17.1% (range: 2.7-85.5%) after weighting by sample size. Across multiple studies, stronger seasonality was associated with younger patients, extrapulmonary disease, and latitudes farther from the Equator. The mathematical model was generally able to reproduce observed levels of seasonal case variation; however, substantial variation in transmission or disease progression risk was required to replicate several extreme values.
CONCLUSIONS
We observed seasonal variation in tuberculosis, with consistent peaks occurring in spring, across countries with varying tuberculosis burden. Future research is needed to explore and quantify potential gains from strategically conducting mass screening interventions in the spring.
Topics: Humans; Incidence; Models, Theoretical; Seasons; Tuberculosis, Pulmonary
PubMed: 29870427
DOI: 10.1097/EDE.0000000000000877 -
Frontiers in Neurology 2022The implantation protocol for Carmustine Wafers (CWs) in high grade glioma (HGG) was developed to offer a bridge between surgical resection and adjuvant treatments, such...
BACKGROUND
The implantation protocol for Carmustine Wafers (CWs) in high grade glioma (HGG) was developed to offer a bridge between surgical resection and adjuvant treatments, such as radio- and chemotherapy. In the last years, however, a widespread use of CWs has been limited due to uncertainties regarding efficacy, in addition to increased risk of infection and elevated costs of treatment.
OBJECTIVE
The aims of our study were to investigate the epidemiology of patients that underwent surgery for HGG with CW implantation, in addition to the assessment of related complications, long-term overall survival (), and associated prognostic factors.
METHODS
Three different medical databases were screened for conducting a systematic review of the literature, according to the PRISMA statement guidelines, evaluating the role of BCNU wafer implantation in patients with newly diagnosed HGG. The search query was based on a combination of medical subject headings (MeSH): "high grade glioma" [MeSH] AND "Carmustine" [MeSH] and free text terms: "surgery" OR "BCNU wafer" OR "Gliadel" OR "systemic treatment options" OR "overall survival."
RESULTS
The analysis of the meta-data demonstrated that there was a significant advantage in using CWs in newly diagnosed GBM in terms of , and a very low heterogeneity among the included studies [mean difference 2.64 (95% 0.85, 4.44); = 0.004; I2149 = 0%]. Conversely, no significant difference between the two treatment groups in terms of PFS wad detected ( = 0.55). The analysis of complications showed a relatively higher rate in Carmustine implanted patients, although this difference was not significant ( = 0.53).
CONCLUSIONS
This meta-analysis seems to suggest that CWs implantation plays a significant role in improving the , when used in patients with newly diagnosed HGG. To minimize the risk of side effects, however, a carful patient selection based mainly on patient age and tumor volume should be desirable.
PubMed: 35812101
DOI: 10.3389/fneur.2022.884158 -
Frontiers in Artificial Intelligence 2024Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a...
BACKGROUND
Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a comprehensive approach is crucial.
PURPOSE
To meet this new workforce demand health policy and health economics programs are increasingly introducing data analysis and data visualization skills. Such skills facilitate data integration and discovery by linking multiple resources. Common linking strategies include individual or aggregate level linking (e.g., patient identifiers) in primary clinical data and conceptual linking (e.g., healthcare workforce, state funding, burnout rates) in secondary data. Often, the combination of primary and secondary datasets is sought, requiring additional skills, for example, understanding metadata and constructing interlinkages.
METHODS
To help improve those skills, we developed a 2-step process using a scoping method to discover data and network visualization to interlink metadata. Results: We show how these new skills enable the discovery of relationships among data sources pertinent to public policy research related to the opioid overdose crisis and facilitate inquiry across heterogeneous data resources. In addition, our interactive network visualization introduces (1) a conceptual approach, drawing from recent systematic review studies and linked by the publications, and (2) an aggregate approach, constructed using publicly available datasets and linked through crosswalks.
CONCLUSIONS
These novel metadata visualization techniques can be used as a teaching tool or a discovery method and can also be extended to other public policy domains.
PubMed: 38646414
DOI: 10.3389/frai.2024.1208874 -
Tuberculosis (Edinburgh, Scotland) Sep 2019The molecular epidemiology of Mycobacterium tuberculosis (M. tuberculosis, Mtb) is poorly documented in Ethiopia. The data that exists has not yet been collected in an... (Meta-Analysis)
Meta-Analysis
The molecular epidemiology of Mycobacterium tuberculosis (M. tuberculosis, Mtb) is poorly documented in Ethiopia. The data that exists has not yet been collected in an overview metadata form. Thus, this review summarizes available literature on the genomic diversity, geospatial distribution and transmission patterns of Mtb lineages (L) and sublineages in Ethiopia. Spoligotyping and Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats (MIRU-VNTR) based articles were identified from MEDLINE via PubMed and Scopus. The last date of article search was done on 12th February 2019. Articles were selected following the PRISMA flow diagram. The proportion of (sub)lineages was summarized at national level and further disaggregated by region. Clustering and recent transmission index (RTI) were determined using metan command and random effect meta-analysis model. The meta-analysis was computed using Stata 14 (Stata Corp. College Station, TX, USA). Among 4371 clinical isolates, 99.5% were Mtb and 0.5% were M. bovis. Proportionally, L4, L3, L1 and L7 made up 62.3%, 21.7%, 7.9% and 3.4% of the total isolates, respectively. Among sublineages, L4.2. ETH/SIT149, L4.10/SIT53, L3. ETH1/SIT25 and L4.6/SIT37 were the leading clustered isolates accounting for 14.4%, 9.7%, 7.2% and 5.5%, respectively. Based on MIRU-VNTR, the rate of clustering was 41% and the secondary case rate from a single source case was estimated at 29%. Clustering and recent transmission index was higher in eastern and southwestern Ethiopia compared with the northwestern part of the country. High level of genetic diversity with a high rate of clustering was noted which collectively mirrored the phenomena of micro-epidemics and super-spreading. The largest set of clustered strains deserves special attention and further characterization using whole genome sequencing (WGS) to better understand the evolution, genomic diversity and transmission dynamics of Mtb.
Topics: Bacterial Typing Techniques; Bias; Cluster Analysis; Ethiopia; Genetic Variation; Humans; Minisatellite Repeats; Mycobacterium tuberculosis; Phylogeny; Tuberculosis
PubMed: 31430694
DOI: 10.1016/j.tube.2019.101858 -
PLoS Neglected Tropical Diseases Oct 2017Preventive chemotherapy and transmission control (PCT) by mass drug administration is the cornerstone of the World Health Organization (WHO)'s policy to control... (Review)
Review
BACKGROUND
Preventive chemotherapy and transmission control (PCT) by mass drug administration is the cornerstone of the World Health Organization (WHO)'s policy to control soil-transmitted helminthiases (STHs) caused by Ascaris lumbricoides (roundworm), Trichuris trichiura (whipworm) and hookworm species (Necator americanus and Ancylostama duodenale) which affect over 1 billion people globally. Despite consensus that drug efficacies should be monitored for signs of decline that could jeopardise the effectiveness of PCT, systematic monitoring and evaluation is seldom implemented. Drug trials mostly report aggregate efficacies in groups of participants, but heterogeneities in design complicate classical meta-analyses of these data. Individual participant data (IPD) permit more detailed analysis of drug efficacies, offering increased sensitivity to identify atypical responses potentially caused by emerging drug resistance.
METHODOLOGY
We performed a systematic literature review to identify studies concluding after 2000 that collected IPD suitable for estimating drug efficacy against STH. We included studies that administered a variety of anthelmintics with follow ups less than 60 days after treatment. We estimated the number of IPD and extracted cohort- and study-level meta-data.
PRINCIPAL FINDINGS
We estimate that there exist individual data on approximately 35,000 participants from 129 studies conducted in 39 countries, including 34 out of 103 countries where PCT is recommended. We find significant heterogeneity in diagnostic methods, times of outcome assessment, and the reported measure of efficacy. We also quantify cohorts comprising pre-school age children, pregnant women, and co-infected participants, including with HIV.
CONCLUSIONS
We argue that establishing a global IPD repository would improve the capacity to monitor and evaluate the efficacy of anthelmintic drugs, respond to changes and safeguard the ongoing effectiveness of PCT. Establishing a fair, transparent data governance policy will be key for the engagement of the global STH community.
Topics: Anthelmintics; Clinical Trials as Topic; Helminthiasis; Humans; Meta-Analysis as Topic; Soil
PubMed: 29088274
DOI: 10.1371/journal.pntd.0006053 -
European Journal of Cancer (Oxford,... Oct 2021Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the...
BACKGROUND
Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinicopathological practice.
OBJECTIVE
The objective of the study was to systematically analyse the current state of research on reader studies involving melanoma and to assess their potential clinical relevance by evaluating three main aspects: test set characteristics (holdout/out-of-distribution data set, composition), test setting (experimental/clinical, inclusion of metadata) and representativeness of participating clinicians.
METHODS
PubMed, Medline and ScienceDirect were screened for peer-reviewed studies published between 2017 and 2021 and dealing with AI-based skin cancer classification involving melanoma. The search terms skin cancer classification, deep learning, convolutional neural network (CNN), melanoma (detection), digital biomarkers, histopathology and whole slide imaging were combined. Based on the search results, only studies that considered direct comparison of AI results with clinicians and had a diagnostic classification as their main objective were included.
RESULTS
A total of 19 reader studies fulfilled the inclusion criteria. Of these, 11 CNN-based approaches addressed the classification of dermoscopic images; 6 concentrated on the classification of clinical images, whereas 2 dermatopathological studies utilised digitised histopathological whole slide images.
CONCLUSIONS
All 19 included studies demonstrated superior or at least equivalent performance of CNN-based classifiers compared with clinicians. However, almost all studies were conducted in highly artificial settings based exclusively on single images of the suspicious lesions. Moreover, test sets mainly consisted of holdout images and did not represent the full range of patient populations and melanoma subtypes encountered in clinical practice.
Topics: Automation; Biopsy; Clinical Competence; Deep Learning; Dermatologists; Dermoscopy; Diagnosis, Computer-Assisted; Humans; Image Interpretation, Computer-Assisted; Melanoma; Microscopy; Neural Networks, Computer; Pathologists; Predictive Value of Tests; Reproducibility of Results; Skin Neoplasms
PubMed: 34509059
DOI: 10.1016/j.ejca.2021.06.049 -
Briefings in Bioinformatics Mar 2021This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer...
OBJECTIVE
This study aims at reviewing novel coronavirus disease (COVID-19) datasets extracted from PubMed Central articles, thus providing quantitative analysis to answer questions related to dataset contents, accessibility and citations.
METHODS
We downloaded COVID-19-related full-text articles published until 31 May 2020 from PubMed Central. Dataset URL links mentioned in full-text articles were extracted, and each dataset was manually reviewed to provide information on 10 variables: (1) type of the dataset, (2) geographic region where the data were collected, (3) whether the dataset was immediately downloadable, (4) format of the dataset files, (5) where the dataset was hosted, (6) whether the dataset was updated regularly, (7) the type of license used, (8) whether the metadata were explicitly provided, (9) whether there was a PubMed Central paper describing the dataset and (10) the number of times the dataset was cited by PubMed Central articles. Descriptive statistics about these seven variables were reported for all extracted datasets.
RESULTS
We found that 28.5% of 12 324 COVID-19 full-text articles in PubMed Central provided at least one dataset link. In total, 128 unique dataset links were mentioned in 12 324 COVID-19 full text articles in PubMed Central. Further analysis showed that epidemiological datasets accounted for the largest portion (53.9%) in the dataset collection, and most datasets (84.4%) were available for immediate download. GitHub was the most popular repository for hosting COVID-19 datasets. CSV, XLSX and JSON were the most popular data formats. Additionally, citation patterns of COVID-19 datasets varied depending on specific datasets.
CONCLUSION
PubMed Central articles are an important source of COVID-19 datasets, but there is significant heterogeneity in the way these datasets are mentioned, shared, updated and cited.
Topics: COVID-19; Datasets as Topic; Humans; Information Dissemination; PubMed; SARS-CoV-2
PubMed: 33757278
DOI: 10.1093/bib/bbaa331 -
Frontiers in Psychiatry 2024Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the... (Review)
Review
Recent developments in the fields of natural language processing (NLP) and machine learning (ML) have shown significant improvements in automatic text processing. At the same time, the expression of human language plays a central role in the detection of mental health problems. Whereas spoken language is implicitly assessed during interviews with patients, written language can also provide interesting insights to clinical professionals. Existing work in the field often investigates mental health problems such as depression or anxiety. However, there is also work investigating how the diagnostics of eating disorders can benefit from these novel technologies. In this paper, we present a systematic overview of the latest research in this field. Our investigation encompasses four key areas: (a) an analysis of the metadata from published papers, (b) an examination of the sizes and specific topics of the datasets employed, (c) a review of the application of machine learning techniques in detecting eating disorders from text, and finally (d) an evaluation of the models used, focusing on their performance, limitations, and the potential risks associated with current methodologies.
PubMed: 38596627
DOI: 10.3389/fpsyt.2024.1319522 -
Scandinavian Journal of Trauma,... Sep 2020Paediatric resuscitation is rare but potentially associated with maximal lifetime reduction. Notably, several nations experience high infant mortality rates even today....
BACKGROUND
Paediatric resuscitation is rare but potentially associated with maximal lifetime reduction. Notably, several nations experience high infant mortality rates even today. To improve clinical outcomes and promote research, detailed analyses on evolution and current state of research on paediatric resuscitation are necessary.
METHODS
Research on paediatric resuscitation published in-between 1900 and 2019 were searched using Web of Science. Metadata were extracted and analyzed based on the science performance evaluation (SciPE) protocol. Research performance was evaluated regarding quality and quantity over time, including comparisons to adult resuscitation. National research performance was related to population, financial capacities, infant mortality rate, collaborations, and authors' gender.
RESULTS
Similar to adult resuscitation, research performance on paediatric resuscitation grew exponentially with most original articles being published during the last decade (1106/1896). The absolute number, however, is only 14% compared to adults. The United States dominate global research by contributing the highest number of articles (777), Hirsch-Index (70), and citations (18,863). The most productive collaboration was between the United States and Canada (52). When considering nation's population and gross domestic product (GDP) rate, Norway is leading regarding population per article (62,467), per Hirsch-Index (223,841), per citation (2226), and per GDP (2.3E-04). Regarding publications per infant mortality rate, efforts of India and Brazil are remarkable. Out of the 100 most frequently publishing researchers, 25% were female.
CONCLUSION
Research efforts on paediatric resuscitation have increased but remain underrepresented. Specifically, nations with high infant mortality rates should be integrated by collaborations. Additional efforts are required to overcome gender disparities.
Topics: Bibliometrics; Biomedical Research; Humans; Pediatrics; Publishing; Resuscitation
PubMed: 32912262
DOI: 10.1186/s13049-020-00780-3