A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis.

BACKGROUND: Shortly after the emergence of COVID-19, researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19-related publications. Identifying trends and areas of interest using traditional review methods (eg, scoping and systematic reviews) for such a large domain area is challenging. OBJECTIVE: We aimed to conduct an extensive bibliometric analysis to provide a comprehensive overview of the COVID-19 literature. METHODS: We used the COVID-19 Open Research Dataset (CORD-19) that consists of a large number of research articles related to all coronaviruses. We used a machine learning-based method to analyze the most relevant COVID-19-related articles and extracted the most prominent topics. Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. We have made our software accessible to the community via GitHub. RESULTS: Of the 196,630 publications retrieved from the database, we included 28,904 in our analysis. The mean number of weekly publications was 990 (SD 789.3). The country that published the highest number of COVID-19-related articles was China (2950/17,270, 17.08%). The highest number of articles were published in bioRxiv. Lei Liu affiliated with the Southern University of Science and Technology in China published the highest number of articles (n=46). Based on titles and abstracts alone, we were able to identify 1515 surveys, 733 systematic reviews, 512 cohort studies, 480 meta-analyses, and 362 randomized control trials. We identified 19 different topics covered among the publications reviewed. The most dominant topic was public health response, followed by clinical care practices during the COVID-19 pandemic, clinical characteristics and risk factors, and epidemic models for its spread. CONCLUSIONS: We provide an overview of the COVID-19 literature and have identified current hotspots and research directions. Our findings can be useful for the research community to help prioritize research needs and recognize leading COVID-19 researchers, institutes, countries, and publishers. Our study shows that an AI-based bibliometric analysis has the potential to rapidly explore a large corpus of academic publications during a public health crisis. We believe that this work can be used to analyze other eHealth-related literature to help clinicians, administrators, and policy makers to obtain a holistic view of the literature and be able to categorize different topics of the existing research for further analyses. It can be further scaled (for instance, in time) to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.

[Neurogenic paraosteopathy of the elbow: results of surgical arthrolysis (a retrospective study of 37 cases)]. / La para-ostéopathie neurogène du coude: résultat de l'arthrolyse chirurgicale (étude rétrospective de 37 cas).

Neurogenic paraosteoarthropathies are ectopic ossifications which develop near the joints. They are a process of neo-ectopic osteogenesis occurring after central or peripheral neurological lesions, in some types of comas (oxygen carbon intoxication, prolonged sedation) and following peripheral traumas including burns. They inolve almost exclusively the large proximal joints of the limbs. Elbow is the second area of involvment. The purpose of our study was to analyze the results of surgical arthrolysis in 37 patients with elbow stiffness due to neurogenic osteoarthropathy of the elbow. We conducted a retrospective study of 35 patients and 37 elbows over a 25-year period. Preoperative assessment included clinical and radiological examination. Since 2003 the patients had undergone systematic elbow arthroscopy. The gold standard surgical treatment was arthrolysis. All patients underwent functional rehabilitation protocol. Outcomes were analyzed after a mean 5-year follow-up period (6 months - 10 years). Neurogenic paraosteoarthropathy was caused by head injury with coma in 58.8% of cases. Preoperative assessment showed bending stiffness in the majority of cases (88%), severe or very severe in 64.7% of cases. Intraoperatively functional elbow range of motion from -30° to 130° was obtained in 61.7% of cases and in 41% of cases in the long term. Ulnar nerve liberation was satisfactory in 92% of cases. No postoperative instability of the elbow was reported. Two patients with definitive neurological lesions had osteoma recurrence. The results were equivalent regardless surgical delay. Surgical arthrolysis is an effective treatment for neurogenic osteomas of the elbow.