A Practical and Empirical Comparison of Three Topic Modeling Methods Using a COVID-19 Corpus: LSA, LDA, and Top2Vec

This study was prepared as a practical guide for researchers interested in using topic modeling methodologies. This study is specially designed for those with difficulty determining which methodology to use. Many topic modeling methods have been developed since the 1980s namely, latent semantic indexing or analysis (LSI/LSA), probabilistic LSI/LSA (pLSI/pLSA), naïve Bayes, the Author-Recipient-Topic (ART), Latent Dirichlet Allocation (LDA), Topic Over Time (TOT), Dynamic Topic Models (DTM), Word2Vec, Top2Vec, and \variation and combination of these techniques. Researchers from disciplines other than computer science may find it challenging to select a topic modeling methodology. We compared a recently developed topic modeling algorithm Top2Vec with two of the most conventional and frequently-used methodologiesLSA and LDA. As a study sample, we used a corpus of 65,292 COVID-19-focused abstracts. Among the 11 topics we identified in each methodology, we found high levels of correlation between LDA and Top2Vec results, followed by LSA and LDA and Top2Vec and LSA. We also provided information on computational resources we used to perform the analyses and provided practical guidelines and recommendations for researchers

A critical analysis of COVID-19 research literature: Text mining approach

Objective: Among the stakeholders of COVID-19 research, clinicians particularly experience difficulty keeping up with the deluge of SARS-CoV-2 literature while performing their much needed clinical duties. By revealing major topics, this study proposes a text-mining approach as an alternative to navigating large volumes of COVID-19 literature. Materials and methods: We obtained 85,268 references from the NIH COVID-19 Portfolio as of November 21. After the exclusion based on inadequate abstracts, 65,262 articles remained in the final corpus. We utilized natural language processing to curate and generate the term list. We applied topic modeling analyses and multiple correspondence analyses to reveal the major topics and the associations among topics, journal countries, and publication sources. Results: In our text mining analyses of NIH’s COVID-19 Portfolio, we discovered two sets of eleven major research topics by analyzing abstracts and titles of the articles separately. The eleven major areas of COVID-19 research based on abstracts included the following topics: 1) Public Health, 2) Patient Care & Outcomes, 3) Epidemiologic Modeling, 4) Diagnosis and Complications, 5) Mechanism of Disease, 6) Health System Response, 7) Pandemic Control, 8) Protection/Prevention, 9) Mental/Behavioral Health, 10) Detection/Testing, 11) Treatment Options. Further analyses revealed that five (2,3,4,5, and 9) of the eleven abstract-based topics showed a significant correlation (ranked from moderate to weak) with title-based topics. Conclusion: By offering up the more dynamic, scalable, and responsive categorization of published literature, our study provides valuable insights to the stakeholders of COVID-19 research, particularly clinicians.3417985

Increased P-Wave and QT Dispersions Necessitate Long-Term Follow-up Evaluation of Down Syndrome Patients With Congenitally Normal Hearts

Reports state that Down syndrome (DS) patients with congenitally normal hearts might experience the development of cardiac abnormalities such as cardiac autonomic dysfunction, valvular lesions, bradycardia, and atrioventricular block. However, the presence of any difference in terms of P-wave dispersion (PWd) and QT dispersion (QTd) was not evaluated previously. This study prospectively investigated 100 DS patients with structurally normal hearts and 100 age- and sex-matched healthy control subjects. Standard 12-lead electrocardiograms were used to assess and compare P-wave and QT durations together with PWd and QTd. The median age of the DS patients and control subjects was 48 months. Heart rates and P-wave and QT dispersions were significantly greater in the DS group than in the control group (113 +/- A 22.9 vs 98.8 +/- A 16.6 bpm, p < 0.001; 31.3 +/- A 9.5 vs 24 +/- A 8.6 ms, p < 0.001; and 46.6 +/- A 15.9 vs 26 +/- A 9.1 ms, p < 0.001, respectively). A positive correlation was found between PWd and age in the DS patients (p < 0.05; r = 0.2). All children with DS should be followed up carefully with electrocardiography in terms of increased P-wave and QT dispersions even in the absence of concomitant congenital heart disease for management of susceptibility to arryhthmias

Anemia and Its Effect on Cardiovascular Findings in Obese Adolescents

Objective: We assessed the effect of anemia on cardiovascular findings in obese adolescents. Materials and Methods: We studied 29 anemic and 33 nonanemic obese adolescents, and 33 nonobese healthy adolescents. These three groups were investigated for clinical and laboratory features of anemia and obesity. Echocardiography was used to examine cardiac functions. Results: The anemia was mild (mean hemoglobin: 11.67 +/- 0.79 g/dL), ferritin level was significantly low, and C-reactive protein and fibrinogen levels were significantly high in anemic obese patients. Increased cardiac pulse and echocardiographic findings, which may be indicative of early left ventricular diastolic dysfunction, were present in these patients. Conclusion: Anemia may develop due to iron deficiency and chronic inflammation in obese adolescents. Even mild anemia may cause increased heart rate and affect left ventricular diastolic functions. Diet programs for obese children should be carefully planned to avoid iron deficiency anemia, which may worsen the cardiac events in longterm follow-up