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Systematic Reviews Jun 2015Automation of the parts of systematic review process, specifically the data extraction step, may be an important strategy to reduce the time necessary to complete a... (Review)
Review
BACKGROUND
Automation of the parts of systematic review process, specifically the data extraction step, may be an important strategy to reduce the time necessary to complete a systematic review. However, the state of the science of automatically extracting data elements from full texts has not been well described. This paper performs a systematic review of published and unpublished methods to automate data extraction for systematic reviews.
METHODS
We systematically searched PubMed, IEEEXplore, and ACM Digital Library to identify potentially relevant articles. We included reports that met the following criteria: 1) methods or results section described what entities were or need to be extracted, and 2) at least one entity was automatically extracted with evaluation results that were presented for that entity. We also reviewed the citations from included reports.
RESULTS
Out of a total of 1190 unique citations that met our search criteria, we found 26 published reports describing automatic extraction of at least one of more than 52 potential data elements used in systematic reviews. For 25 (48 %) of the data elements used in systematic reviews, there were attempts from various researchers to extract information automatically from the publication text. Out of these, 14 (27 %) data elements were completely extracted, but the highest number of data elements extracted automatically by a single study was 7. Most of the data elements were extracted with F-scores (a mean of sensitivity and positive predictive value) of over 70 %.
CONCLUSIONS
We found no unified information extraction framework tailored to the systematic review process, and published reports focused on a limited (1-7) number of data elements. Biomedical natural language processing techniques have not been fully utilized to fully or even partially automate the data extraction step of systematic reviews.
Topics: Data Mining; Humans; Information Storage and Retrieval; Publishing; Research Report; Review Literature as Topic
PubMed: 26073888
DOI: 10.1186/s13643-015-0066-7 -
Photodiagnosis and Photodynamic Therapy Dec 2022Photodynamic therapy (PDT) is an adjunctive treatment that aims to inactivate microorganisms through an oxidative reaction produced by irradiating a photosensitizing... (Review)
Review
BACKGROUND
Photodynamic therapy (PDT) is an adjunctive treatment that aims to inactivate microorganisms through an oxidative reaction produced by irradiating a photosensitizing agent. The quest for improved root canal disinfection has sought supplementary methods when performing chemomechanical procedures. From this perspective, PDT protocols were proposed as an auxiliary approach in endodontics. Thus, the aim of this study was to investigate publication metrics and research trends related to this scope.
METHODS
This review is reported in accordance with the PRISMA 2020 recommendations. Two blinded and independent reviewers systematically searched five electronic databases until December 2021. The acquired bibliometric parameters were analyzed through descriptive statistics and graphical mappings with VOSViewer software.
RESULTS
The search retrieved 342 studies from 84 journals originating from 33 countries. About 85% of the included studies were published over the last decade. Most of the available evidence is laboratory-based (74.5%), and the main clinical outcomes evaluated were microbiological load reduction and postoperative pain. Mayram Pourhajibagher is the researcher with the most publications as the first author (n = 16). Tehran University of Medical Sciences carried out the highest number of studies (n = 29), and Photodiagnosis and Photodynamic Therapy is the journal that most published on the theme (n = 111).
CONCLUSIONS
This bibliometric analysis mapped and discussed the scientific progress and publication metrics in PDT in endodontic research. Additionally, future perspectives were highlighted and should focus on discovering new photosensitizer agents, standardizing optimal photoactivation protocols, and conducting more clinical-oriented research.
Topics: Photochemotherapy; Iran; Endodontics; Photosensitizing Agents; Bibliometrics
PubMed: 35907620
DOI: 10.1016/j.pdpdt.2022.103039 -
Journal of Clinical Epidemiology Dec 2017The aim of this study was to identify and quantify the characteristics of studies associated with the likelihood of publication. (Meta-Analysis)
Meta-Analysis Review
OBJECTIVES
The aim of this study was to identify and quantify the characteristics of studies associated with the likelihood of publication.
STUDY DESIGN AND SETTING
We searched for manuscripts that tracked cohorts of clinical studies ("cohorts") that from launch to publication. We explored the association of study characteristics with the probability of publication via traditional meta-analyses and meta-regression using random effects models.
RESULTS
The literature review identified 85 cohorts of studies that met our inclusion criteria. The probability of publication was significantly higher for studies whose characteristics were favorable (odds ratio [OR] = 2.04; 95% confidence interval [CI]: 1.62, 2.57) or statistically significant (OR = 2.07; 95% CI: 1.52, 2.81), had a multicenter design (OR = 1.32; 95% CI: 1.16, 1.45), and were of later regulatory phase (3/4 vs. 1/2, OR = 1.34; 95% CI: 1.14, 1.49). Industry funding was modestly associated with lower (OR = 0.81; 95% CI: 0.67, 0.99) probability of publication. An exploratory analysis of effect modification revealed that the effect of the study characteristic "favorable results" on likelihood for publication was stronger for industry-funded studies.
CONCLUSION
The study characteristics of favorable and significant results were associated with greater probability of publication.
Topics: Confidence Intervals; Financial Management; Odds Ratio; Probability; Publication Bias; Publications; United States
PubMed: 28842289
DOI: 10.1016/j.jclinepi.2017.08.004 -
World Neurosurgery Jul 2017Despite the increasing awareness of scientific fraud, no attempt has been made to assess its prevalence in neurosurgery. The aim of our review was to assess the... (Review)
Review
OBJECTIVES
Despite the increasing awareness of scientific fraud, no attempt has been made to assess its prevalence in neurosurgery. The aim of our review was to assess the chronologic trend, reasons, research type/design, and country of origin of retracted neurosurgical publications.
METHODS
Three independent reviewers searched the EMBASE and MEDLINE databases using neurosurgical keywords for retracted articles from 1995 to 2016. Archives of retracted articles (retractionwatch.com) and the independent Web sites of neurosurgical journals were also searched. Data including the journal, impact factor, reason for retraction, country of origin, and citations were extracted.
RESULTS
A total of 97 studies were included for data extraction. Journal impact factor ranged from 0.57 to 35.03. Most studies (61) were retracted within the last 5 years. The most common reason for retraction was because of a duplicated publication found elsewhere (26), followed closely by plagiarism (22), or presenting fraudulent data (14). Other reasons included scientific errors/mistakes, author misattribution, and compromised peer review. Articles originated from several countries and some were widely cited.
CONCLUSIONS
Retractions of neurosurgical publications are increasing significantly, mostly because of issues of academic integrity, including duplicate publishing and plagiarism. Implementation of more transparent data-sharing repositories and thorough screening of data before manuscript submission, as well as additional educational programs for new researchers, may help mitigate these issues in the future.
Topics: Duplicate Publications as Topic; Humans; Journal Impact Factor; Neurosurgery; Peer Review, Research; Periodicals as Topic; Plagiarism; Retraction of Publication as Topic; Scientific Misconduct
PubMed: 28412480
DOI: 10.1016/j.wneu.2017.04.014 -
Annals of Vascular Surgery Sep 2022Artificial intelligence (AI) and machine learning (ML) have seen increasingly intimate integration with medicine and healthcare in the last 2 decades. The objective of... (Review)
Review
BACKGROUND
Artificial intelligence (AI) and machine learning (ML) have seen increasingly intimate integration with medicine and healthcare in the last 2 decades. The objective of this study was to summarize all current applications of AI and ML in the vascular surgery literature and to conduct a bibliometric analysis of published studies.
METHODS
A comprehensive literature search was conducted through Embase, MEDLINE, and Ovid HealthStar from inception until February 19, 2021. Reporting of this study was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Title and abstract screening, full-text screening, and data extraction were conducted in duplicate. Data extracted included study metadata, the clinical area of study within vascular surgery, type of AI/ML method used, dataset, and the application of AI/ML. Publishing journals were classified as having either a clinical scope or technical scope. The author academic background was classified as clinical, nonclinical (e.g., engineering), or both, depending on author affiliation.
RESULTS
The initial search identified 7,434 studies, of which 249 were included for a final analysis. The rate of publications is exponentially increasing, with 158 (63%) studies being published in the last 5 years alone. Studies were most commonly related to carotid artery disease (118, 47%), abdominal aortic aneurysms (51, 20%), and peripheral arterial disease (26, 10%). Study authors employed an average of 1.50 (range: 1-6) distinct AI methods in their studies. The application of AI/ML methods broadly related to predictive models (54, 22%), image segmentation (49, 19.4%), diagnostic methods (46, 18%), or multiple combined applications (91, 37%). The most commonly used AI/ML methods were artificial neural networks (155/378 use cases, 41%), support vector machines (64, 17%), k-nearest neighbors algorithm (26, 7%), and random forests (23, 6%). Datasets to which these AI/ML methods were applied frequently involved ultrasound images (87, 35%), computed tomography (CT) images (42, 17%), clinical data (34, 14%), or multiple datasets (36, 14%). Overall, 22 (9%) studies were published in journals specific to vascular surgery, with the majority (147/249, 59%) being published in journals with a scope related to computer science or engineering. Among 1,576 publishing authors, 46% had exclusively a clinical background, 48% a nonclinical background, and 5% had both a clinical and nonclinical background.
CONCLUSIONS
There is an exponentially growing body of literature describing the use of AI and ML in vascular surgery. There is a focus on carotid artery disease and abdominal aortic disease, with many other areas of vascular surgery under-represented. Neural networks and support vector machines composed most AI methods in the literature. As AI/ML continue to see expanded applications in the field, it is important that vascular surgeons appreciate its potential and limitations. In addition, as it sees increasing use, there is a need for clinicians with expertise in AI/ML methods who can optimize its transition into daily practice.
Topics: Artificial Intelligence; Bibliometrics; Carotid Artery Diseases; Humans; Machine Learning; Treatment Outcome; Vascular Surgical Procedures
PubMed: 35339595
DOI: 10.1016/j.avsg.2022.03.019 -
Systematic Reviews Aug 2017Producing high-quality, relevant systematic reviews and keeping them up to date is challenging. Cochrane is a leading provider of systematic reviews in health. For... (Review)
Review
BACKGROUND
Producing high-quality, relevant systematic reviews and keeping them up to date is challenging. Cochrane is a leading provider of systematic reviews in health. For Cochrane to continue to contribute to improvements in heath, Cochrane Reviews must be rigorous, reliable and up to date. We aimed to explore existing models of Cochrane Review production and emerging opportunities to improve the efficiency and sustainability of these processes.
METHODS
To inform discussions about how to best achieve this, we conducted 26 interviews and an online survey with 106 respondents.
RESULTS
Respondents highlighted the importance and challenge of creating reliable, timely systematic reviews. They described the challenges and opportunities presented by current production models, and they shared what they are doing to improve review production. They particularly highlighted significant challenges with increasing complexity of review methods; difficulty keeping authors on board and on track; and the length of time required to complete the process. Strong themes emerged about the roles of authors and Review Groups, the central actors in the review production process. The results suggest that improvements to Cochrane's systematic review production models could come from improving clarity of roles and expectations, ensuring continuity and consistency of input, enabling active management of the review process, centralising some review production steps; breaking reviews into smaller "chunks", and improving approaches to building capacity of and sharing information between authors and Review Groups. Respondents noted the important role new technologies have to play in enabling these improvements.
CONCLUSIONS
The findings of this study will inform the development of new Cochrane Review production models and may provide valuable data for other systematic review producers as they consider how best to produce rigorous, reliable, up-to-date reviews.
Topics: Databases, Bibliographic; Editorial Policies; Humans; Information Storage and Retrieval; Quality Control; Review Literature as Topic
PubMed: 28760162
DOI: 10.1186/s13643-017-0542-3 -
Clinical and Experimental Dental... Aug 2020The present systematic review aimed to perform an in-depth analysis of the different features of retracted publications in the dental field. (Review)
Review
OBJECTIVES
The present systematic review aimed to perform an in-depth analysis of the different features of retracted publications in the dental field.
MATERIAL AND METHODS
This review has been recorded in the PROSPERO database (CRD42017075634). Two independent reviewers performed an electronic search (Pubmed, Retraction Watch) for retracted articles in dental literature up to December 31, 2018.
RESULTS
180 retracted papers were identified, the first published in 2001. Retractions increased by 47% in the last four-year period (2014-2018), when compared with 2009-2013 (94 and 64 retracted publications, respectively). Author misconduct was the most common reason for retraction (65.0%), followed by honest scientific errors (12.2%) and publisher-related issues (10.6%). The majority of retracted research was conducted in Asia (55.6%), with 49 papers written in India (27.2%). 552 researchers (89%) are listed as authors in only one retracted article, while 10 researchers (1.6%) are present in five or more retracted publications. Retracted articles were cited 530 times after retraction: the great majority of these citations (89.6%) did not consider the existence of the retraction notice and treated data from retracted articles as reliable.
CONCLUSIONS
Retractions in dental literature have constantly increased in recent years, with the majority of them due to misconduct and fraud. The publication of unreliable research has many negative consequences. Studies derived from such material are designed on potentially incorrect bases, waste funds and resources, and most importantly, increase risk of incorrect treatment for patients. Citation of retracted papers represents a major issue for the scientific community.
Topics: Biomedical Research; Databases, Factual; Dentistry; Fraud; Humans; Periodicals as Topic; Retraction of Publication as Topic; Scientific Experimental Error; Scientific Misconduct
PubMed: 32233020
DOI: 10.1002/cre2.292 -
American Journal of Obstetrics &... Sep 2022
Meta-Analysis
Topics: Bibliometrics; Obstetrics; Publication Bias
PubMed: 35413471
DOI: 10.1016/j.ajogmf.2022.100644 -
The Journal of Urology Nov 2015Systematic reviews synthesize the current best evidence to address a clinical question. Given the growing emphasis on evidence-based clinical practice, systematic... (Review)
Review
PURPOSE
Systematic reviews synthesize the current best evidence to address a clinical question. Given the growing emphasis on evidence-based clinical practice, systematic reviews are being increasingly sought after and published. We previously reported limitations in the methodological quality of 57 individual systematic reviews published from 1998 to 2008. We provide an update to our previous study, adding systematic reviews published from 2009 to 2012.
MATERIALS AND METHODS
We systematically searched PubMed® and hand searched the table of contents of 4 major urological journals to identify systematic reviews related to questions of prevention and therapy. Two independent reviewers with prior formal evidence-based medicine training assessed the methodological quality using the validated 11-point AMSTAR (A Measurement Tool to Assess Systematic Reviews) instrument. We performed predefined statistical hypothesis testing for differences by publication period (1998 to 2008 vs 2009 to 2012) and journal of publication. We performed statistical testing using SPSS®, version 23.0 with a 2-sided α of 0.05 using the Student t-test, ANOVA and the chi-square test.
RESULTS
A total of 113 systematic reviews published from 2009 to 2012 met study inclusion criteria. The most common topics were oncology (44 reviews or 38.9%), voiding dysfunction (26 or 23.0%) and stones/endourology (13 or 11.5%). The largest contributor was European Urology (46 reviews or 40.7%), followed by BJU International (31 or 27.4%) and The Journal of Urology® (22 or 19.5%). The mean ± SD AMSTAR score for the 2009 to 2012 period was 5.3 ± 2.3 compared to 4.8 ± 2.0 for 1998 to 2008 with a mean difference of 0.5 (95% CI 0.2 to 1.2, p = 0.133).
CONCLUSIONS
While the number of systematic reviews published in the urological literature has increased substantially, the methodological quality of these studies remains suboptimal. Systematic review authors and editors should make every effort to adhere to well established methodological standards to enhance the impact of their research efforts.
Topics: Evidence-Based Medicine; Humans; Periodicals as Topic; Quality Improvement; Urology
PubMed: 26025501
DOI: 10.1016/j.juro.2015.05.085 -
Nursing Open May 2022This review aimed to elucidate research trends in global nursing in international literature. (Review)
Review
AIM
This review aimed to elucidate research trends in global nursing in international literature.
DESIGN
A scoping literature review of the PRISMA was used to guide the review.
METHODS
PubMed was used to search for English articles published in academic journals between 2016-2018. The search keywords were "global/international/world nursing." We used thematic synthesis to analyse and interpret the data and generated topics for global nursing literature.
RESULTS
In total, 133 articles were analysed. Six topics emerged: (a) conceptualization of global nursing, (b) environmental health, (c) infectious diseases, (d) security efforts, (e) global shortage of nursing personnel and (f) diversification of study abroad programmes. The results of this review reflect today's serious international health, labour and global environmental issues. Based on these latest global nursing topics, it is necessary to develop new strategies, nursing models and environment-related theories to create and maintain a healthy environment.
Topics: Environmental Health; Global Health; Publications
PubMed: 34021729
DOI: 10.1002/nop2.938