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Research Inefficiency in Degenerative Cervical Myelopathy: Findings of a Systematic Review on Research Activity Over the Past 20 Years.

ABSTRACT: Study Design:Scoping review. Objective:To describe activity, themes and trends in degenerative cervical myelopathy (DCM) research over the past 20 years with a view to considering DCM research inefficiency. Methods:A systematic review of MEDLINE and Embase for "Cervical" AND "Myelopathy" was conducted following PRISMA guidelines. Full-text papers in English, exclusively studying DCM, published between January 1, 1995 and December 31, 2015 were considered eligible. Country of origin, number of papers published, number of patients studied, research theme, and year of publication were assessed. Comparison was made between developed and developing countries. Results:A total of 1485 papers and 4?117?051 patients were included. Japan published more papers (450) than any other country while the United States studied the greatest number of patients (3?674?737). Over 99.4% of papers and 78.6% of patients were from developed countries. The number of papers (r = 0.96, P < .001) and patients (r = 0.83 P < .001) studied each year increased significantly overall and for both developed (r = 0.93, P < .001; r = 0.81, P < .001) and developing countries (r = 0.90, P < .001; r = 0.87, P < .001). Surgery was the most prevalent theme (58.3% papers; 55.7% patients) for developed and developing countries. Research from developing countries showed greater thematic variability. Conclusions:DCM research activity is increasing internationally, with surgery remaining the focus. Research output has predominantly been from developed countries; however, the rate of growth for developed and developing countries is comparable.

SUBMITTER: Mowforth OD

PROVIDER: S-EPMC7222686 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Research Inefficiency in Degenerative Cervical Myelopathy: Findings of a Systematic Review on Research Activity Over the Past 20 Years.

Mowforth Oliver D OD Davies Benjamin M BM Goh Samuel S O'Neill Cormac P CP Kotter Mark R N MRN

Global spine journal 20190612 4

<h4>Study design</h4>Scoping review.<h4>Objective</h4>To describe activity, themes and trends in degenerative cervical myelopathy (DCM) research over the past 20 years with a view to considering DCM research inefficiency.<h4>Methods</h4>A systematic review of MEDLINE and Embase for "Cervical" AND "Myelopathy" was conducted following PRISMA guidelines. Full-text papers in English, exclusively studying DCM, published between January 1, 1995 and December 31, 2015 were considered eligible. Country o ...[more]

PMID: 32435569

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Project description:BackgroundDegenerative cervical myelopathy (DCM) is widely accepted as the most common cause of adult myelopathy worldwide. Despite this, there is no specific term or diagnostic criteria in the International Classification of Diseases 11th Revision and no Medical Subject Headings (MeSH) or an equivalent in common literature databases. This makes searching the literature and thus conducting systematic reviews or meta-analyses imprecise and inefficient. Efficient research synthesis is integral to delivering evidence-based medicine and improving research efficiency.ObjectiveThis study aimed to illustrate the difficulties encountered when attempting to carry out a comprehensive and accurate evidence search in the field of DCM by identifying the key sources of imprecision and quantifying their impact.MethodsTo identify the key sources of imprecision and quantify their impact, an illustrative search strategy was developed using a validated DCM hedge combined with contemporary strategies used by authors in previous systematic reviews and meta-analyses. This strategy was applied to Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica dataBASE (EMBASE) databases looking for relevant DCM systematic reviews and meta-analyses published within the last 5 years.ResultsThe MEDLINE via PubMed search strategy returned 24,166 results, refined to 534 papers after the application of inclusion and exclusion criteria. Of these, 32.96% (176/534) results were about DCM, and 18.16% (97/534) of these were DCM systematic reviews or meta-analyses. Non-DCM results were organized into imprecision categories (spinal: 268/534, 50.2%; nonspinal: 84/534, 15.5%; and nonhuman: 8/534, 1.5%). The largest categories were spinal cord injury (75/534, 13.67%), spinal neoplasms (44/534, 8.24%), infectious diseases of the spine and central nervous system (18/534, 3.37%), and other spinal levels (ie, thoracic, lumbar, and sacral; 18/534, 3.37%). Counterintuitively, the use of human and adult PubMed filters was found to exclude a large number of relevant articles. Searching a second database (EMBASE) added an extra 12 DCM systematic reviews or meta-analyses.ConclusionsDCM search strategies face significant imprecision, principally because of overlapping and heterogenous search terms, and inaccurate article indexing. Notably, commonly employed MEDLINE filters, human and adult, reduced search sensitivity, whereas the related articles function and the use of a second database (EMBASE) improved it. Development of a MeSH labeling and a standardized DCM definition would allow comprehensive and specific indexing of DCM literature. This is required to support a more efficient research synthesis.

Project description:BACKGROUND:Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial. OBJECTIVE:The goal of the research was to perform a systematic review on the use of NLP in medical research with the aim of understanding the global progress on NLP research outcomes, content, methods, and study groups involved. METHODS:A systematic review was conducted using the PubMed database as a search platform. All published studies on the application of NLP in medicine (except biomedicine) during the 20 years between 1999 and 2018 were retrieved. The data obtained from these published studies were cleaned and structured. Excel (Microsoft Corp) and VOSviewer (Nees Jan van Eck and Ludo Waltman) were used to perform bibliometric analysis of publication trends, author orders, countries, institutions, collaboration relationships, research hot spots, diseases studied, and research methods. RESULTS:A total of 3498 articles were obtained during initial screening, and 2336 articles were found to meet the study criteria after manual screening. The number of publications increased every year, with a significant growth after 2012 (number of publications ranged from 148 to a maximum of 302 annually). The United States has occupied the leading position since the inception of the field, with the largest number of articles published. The United States contributed to 63.01% (1472/2336) of all publications, followed by France (5.44%, 127/2336) and the United Kingdom (3.51%, 82/2336). The author with the largest number of articles published was Hongfang Liu (70), while Stéphane Meystre (17) and Hua Xu (33) published the largest number of articles as the first and corresponding authors. Among the first author's affiliation institution, Columbia University published the largest number of articles, accounting for 4.54% (106/2336) of the total. Specifically, approximately one-fifth (17.68%, 413/2336) of the articles involved research on specific diseases, and the subject areas primarily focused on mental illness (16.46%, 68/413), breast cancer (5.81%, 24/413), and pneumonia (4.12%, 17/413). CONCLUSIONS:NLP is in a period of robust development in the medical field, with an average of approximately 100 publications annually. Electronic medical records were the most used research materials, but social media such as Twitter have become important research materials since 2015. Cancer (24.94%, 103/413) was the most common subject area in NLP-assisted medical research on diseases, with breast cancers (23.30%, 24/103) and lung cancers (14.56%, 15/103) accounting for the highest proportions of studies. Columbia University and the talents trained therein were the most active and prolific research forces on NLP in the medical field.

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Research Inefficiency in Degenerative Cervical Myelopathy: Findings of a Systematic Review on Research Activity Over the Past 20 Years.

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Research Inefficiency in Degenerative Cervical Myelopathy: Findings of a Systematic Review on Research Activity Over the Past 20 Years.

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