Abstract
The coronavirus disease 2019 (COVID-19) outbreak became the worst epidemic in decades. Since its inception, COVID-19 has had a dramatic impact on chronic obstructive pulmonary disease (COPD) patients. This study explores explore the current status, hot spots, and research frontiers of COVID-19 and COPD based on a bibliometric approach. The Web of Science Core Collection was used to search the literature related to COPD and COVID-19, and VOSviewer and CiteSpace software were applied to analyze the distribution characteristics, research hotspots, and research frontiers of literature in related fields and to map the scientific knowledge domains. A total of 816 valid publications were included, among which USA, China, and England are the core countries/regions publishing related literature, and the research institutions are concentrated in Huazhong University of Science and Technology (18 papers), University College London (17 papers), and Imperial College London (16 papers). Guan WJ is the most prolific author with the most articles. The journals with the most publications are PLOS ONE, JOURNAL OF CLINICAL MEDICINE, and FRONTIERS IN MEDICINE. The main research hotspots in this field are clinical features, disease management, and mechanism research. By constructing COPD and COVID-19 research network diagrams, we reveal the hot spots, frontiers, and development trends of relevant research fields, which provide a reference for subsequent researchers to quickly grasp the current status of related research fields.
Keywords: bibliometric analysis, chronic obstructive pulmonary disease, COVID-19
1. Introduction
The outbreak of the coronavirus disease 2019 (COVID-19) has developed into a public health event.[1] Due to the highly contagious nature of the virus, a large number of patients were infected in a short period of time, which seriously threatens people’s lives, health, and safety.[2,3] The virus causes flu-like symptoms, and in severe cases, even acute respiratory distress syndrome and death. In the early stages of the disease, it is difficult to make completely reasonable preventive and therapeutic measures due to an insufficient understanding of the disease's characteristics. As more patients are diagnosed and research on the disease deepens, the majority of medical professionals are becoming more comprehensive in understanding the clinical features and treatment of COVID-19.
The study found that the susceptible population to COVID-19 is concentrated in the middle-aged and elderly groups and that the majority of patients with life-threatening severe disease are elderly with underlying conditions, including chronic obstructive pulmonary disease (COPD).[4] In contrast, the majority of COVID-19 patients admitted to the intensive care unit (ICU) are often accompanied by other comorbidities, of which 50 to 52.3% were observed to have COPD, which contributes to the high mortality rate of these patients. This suggests that underlying disease may be a potential risk factor for COVID-19 patients.[5,6] These aspects are only the tip of the iceberg in studies related to COPD and COVID-19, and hundreds of literature exist describing the specific comorbidities of COVID-19. Therefore, research on this area is one of the current focuses and hotspots in the medical community, but there is a lack of summary literature on the latest developments and trends in this field, which prevents researchers from better understanding the latest frontiers and the full picture of academic research in this area. Therefore, there is an urgent need for suitable bibliometric tools to sort out the related institutions, authors, and their latest main lines and hotspots, so as to facilitate communication and cooperation among researchers and deeply grasp the research trends and trends in this field.
Bibliometrics is a cross-cutting science that uses mathematical and statistical methods for describing the accumulated knowledge and trends in a specific research field and for quantitatively analyzing knowledge carriers.[7] CiteSpace, developed by Chaomei Chen at Drexel University, USA, and VOSviewer, developed by Van Eck and Waltman at Leiden University, The Netherlands, play an important role in bibliometric research as visualization tools in bibliometric analysis.[7–9] To date, there has been no bibliometric analysis of global publications of studies on this aspect of COPD and COVID-19. To fill this gap, we performed a bibliometric analysis to quantitatively and qualitatively discuss the relevant studies published in recent years. Therefore, in this study, we searched the Web of Science Core Collection (WOSCC) and performed a bibliometric analysis of the literature on COPD and COVID-19 with the help of CiteSpace and VOSviewer software to visualize the current status, research hotspots, and frontiers in this field internationally, which helps to clarify the trajectory of academic development in this field, guide future research directions, and enhance communication and collaboration among researchers in this field.
2. Methods
2.1. Sources and search strategies
The data of this study was based on WOSCC, the world’s largest comprehensive database covering the largest number of disciplines, as the source database.[10] The search strategy was TS=(“COPD” OR “Chronic Obstructive Pulmonary Disease”) AND TS=(“novel coronavirus” OR “COVID-19” OR “SARS-CoV-2” OR “2019- nCoV”). The search time is unlimited, and the language of the literature is limited to English. All data were collected online, and no ethical certificate was required. To avoid bias in database updates, the search and data collection were completed on May 29, 2022, and 2 authors (Yaolin Li and Xiayahu Li) independently extracted all data from the included articles including title, keywords, authors, institutions, journals, publication date, countries/regions, citations, H-index, etc on the same day and at the same time. The specific search process is shown in Figure 1. The data were obtained from the public database, and hence, ethical approval does not apply to this research.
Figure 1.
Details of filtrating the data.
2.2. Bibliometric analysis and visualization
In this study, we used WOSCC and Microsoft Excel 2016 software to analyze the number of publications, year of publication, countries/regions, institutions, journals, authors, total number of citations, average number of citations, and H-index. We used VOSviewer to analyze authors, institutional and national collaborations, journal citations, journal co-citations, and keyword co-occurrences, and to map their scientific knowledge domains. In addition, CiteSpace row journal overlay mapping was used.
The H-index is a bibliometric method for assessing the research output of a particular scholar, institution, or country, which for a given author or country is the number of publications published by that author or country that have been cited at least H times, while all other publications have been cited less than H times.[10] Relative research interest (RRI) is the ratio of the number of publications in a research area to the number of publications in all research areas for the year, which is a good indicator of how active the research area is.[11,12] The impact factor is obtained from the latest version of the Journal Citation Reports.
3. Results
3.1. Overall publication performance
As shown in Figure 2, we statistically analyzed the included literature by publication time. As of May 29, 2022, a total of 816 studies related to COPD and COVID-19 were included in the WOSCC, including 635 articles and 181 reviews. The average annual number of publications was about 272, with the highest number of publications occurring in 2021 when 441 articles were published. These 816 publications were cited a total of 20,486 times (excluding self-citations, which were 19,303), with an average of 25.11 citations per publication. Among them, the literature published in 2021 was cited 12,458 times, and the H-index of all literature in the last 3 years was 57. The RRI for such research has shown a steady increase in the last 3 years, with a significant increase in 2021 compared to 2020 and a slower increase in 2022 compared to 2021, but it is foreseeable that the number of publications in this area will continue to grow in the future as research continues.
Figure 2.
The annual growth trend of countries district and RRI. RRI = relative research interest.
3.2. Countries/regions of publication and cooperation
In the field of COPD and COVID-19 research, the published research literature originated from 79 countries/regions, of which the USA had the highest number of publications (215, 26.35%), followed by China mainland (133, 16.30%), and the third-ranked country was England (101, 12.38%). The top 3 countries together published more than half of the total number of all literature (Fig. 3). As shown in Figure 4, China mainland published the most cited literature in total (8568 citations, 64 citations per article), and the second and third-ranked countries were the USA (4888 citations, 23 citations per article) and England (2587 citations, 30 citations per article), respectively. The countries with the highest H-index for all literature were the USA and China, both with 29, followed by England (22). From this, it can be understood that the US, China, and England have higher quality in both volume and quality of publications. In order to highlight the importance of core countries/regions in this area and to get a clearer understanding of country cooperation relations, VOSviewer 1.6.18 and Scimago Graphica 1.0.17 software were used for country cooperation geographic network mapping (Fig. 5).[13] The circles represent the number of articles issued, the color of the circles represents the total link strength, that is, the intensity of cooperation, and the lines between the circles represent the cooperation between countries. The wider the lines and the lower the transparency, the deeper the intensity of cooperation. It can be seen that there is close cooperation between the US, the UK, and China, especially between the US and China. Meanwhile, the US has the most extensive cooperation with other countries (total link strength = 139), followed by the UK (124) and China (92). In the country co-authorship overlay visualization map, the color of each circle indicates the average year of publication in that country. Based on the color gradient shown in the lower right corner, the earliest publications in China can be seen (Fig. 6).
Figure 3.
Number of articles published by country or region as a percentage.
Figure 4.
Top 10 most productive and influential countries regions.
Figure 5.
World collaborative relationships map.
Figure 6.
The country or region co-authorship overlay visualization map.
3.3. Institution and cooperation
As shown in Figure 7, among the 2110 institutions that published articles, 13 institutions published ≥10 articles, and the 3 institutions with the highest number of publications were Huazhong Univ Sci & Technol (18 papers), UCL (17 papers), and Imperial Coll London (16 papers). The 3 institutions with the highest total number of citations were Huazhong Univ Sci & Technol (3224), Wuhan Univ (2960), and Guangzhou Med Univ (2908). The 3 institutions with the highest average number of citations per article were Guangzhou Med Univ (291), Wuhan Univ (197), and Huazhong Univ Sci & Technol (179), which are all from China. A total of 72 institutions with >5 publications were used to generate institutional collaboration knowledge graphs by using VOSviewer. The circle represents centrality, the area of the circle is proportional to the number of publications, and the connecting line represents the collaboration relationship. As can be seen from Figure 8, there are 8 clusters of institutions with cooperative relationships, and there is relatively close cooperation between institutions within each cluster and more cooperation between institutions in different clusters. As total link strength shows from this point, Imperial Coll London (138), UCL (93), and Wuhan Univ (93) work most closely with other organizations. The important research results published in this field in the future are likely to originate from the aforementioned institutions, and it is suggested that relevant research scholars should collaborate and communicate more with scholars from these institutions.
Figure 7.
Top 10 most productive and influential institutions.
Figure 8.
The institution co-authorship overlay visualization map.
3.4. Publication journals and cooperation
We performed a statistical analysis of the journal sources of the literature to get an idea of the concentration of journals in which the literature is published. The literature obtained from the search was distributed in 419 journals, and in general, the distribution of journals in related fields is relatively scattered. Among them, the top 10 journals in terms of the number of articles contained 153 articles, accounting for 18.75% of the total literature. The distribution of the top 10 journals with relevant literature is shown in Table 1, among which PLOS ONE has relatively more publications (35) and a higher H-index (14). VOSviewer was used to generate journal citation network graphs and journal co-citation network graphs. Figure 9 shows the relationship network of different journal citations in VOSviewer. The relevance between journals is determined by the Link Strength between their literature, with the size of the circle representing the total link strength and the width of the link representing the Link Strength, that is, the strength of collaboration. Figure 10 shows the co-citation network of journals. The figure includes 61 journals that have been cited at least 90 times. Among them, the top 3 journals with the largest total link strength are as follows: AM J RESP CRIT CARE, EUR RESPIR J, and NEW ENGL J MED. The dual-map overlay of journals (Fig. 11) shows the citing journals on the left and the cited journals on the right, and the colored paths between them indicate citation relationships, showing the citation trajectory and knowledge flow of knowledge.[14] The 2 blue paths in the figure indicate that literature published in Molecular/Biology/Genetics and Health/Nursing Medicine journals are frequently cited in Medicine/Medical/Clinical journals.
Table 1.
The top 10 most productive journals.
| Rank | Journal | Document | Sum of citations | H-index | IF |
|---|---|---|---|---|---|
| 1 | PLOS ONE | 35 | 1211 | 14 | 3.752 |
| 2 | JOURNAL OF CLINICAL MEDICINE | 20 | 258 | 9 | 4.964 |
| 3 | FRONTIERS IN MEDICINE | 16 | 99 | 6 | 5.093 |
| 4 | RESPIRATORY MEDICINE | 16 | 192 | 4 | 3.415 |
| 5 | SCIENTIFIC REPORTS | 15 | 68 | 4 | 4.38 |
| 6 | INTERNATIONAL JOURNAL OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE | 13 | 71 | 5 | 2.893 |
| 7 | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | 12 | 83 | 4 | 4.614 |
| 8 | FRONTIERS IN IMMUNOLOGY | 11 | 46 | 4 | 8.786 |
| 9 | BMJ OPEN | 10 | 41 | 5 | 3.006 |
| 10 | EXPERT REVIEW OF RESPIRATORY MEDICINE | 10 | 72 | 3 | 4.3 |
IF = impact factor.
Figure 9.
The relationship network of different journal citations.
Figure 10.
Cluster visualization of the journal co-citation analysis.
Figure 11.
The dual-map overlay of journals.
3.5. Overview of articles of significance and authors
Citation analysis is an important part of bibliometric research. The citation rate of an article reflects, to some extent, its influence in the field. Table 2 lists the 10 most cited papers in COPD and COVID-19 studies with good correlation, including 7 original articles and 3 systematic reviews. The 10 literatures are focused on publications in 2020, with 5 from China and 2 from England. All 10 papers highlighted the adverse effects of comorbidities, including COPD, on COVID-19.
Table 2.
The top 10 highly cited articles.
| Rank | Title | Journal | Year | Author | Country | Citations |
|---|---|---|---|---|---|---|
| 1 | Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis | EUROPEAN RESPIRATORY JOURNAL | May 2020 | He, JX | China | 2517 |
| 2 | Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China | ALLERGY | July 2020 | Gao, YD | China | 1488 |
| 3 | Autopsy findings and venous thromboembolism in patients with COVID-19 | ANNALS OF INTERNAL MEDICINE | September 2020 | Wichmann, D | Germany | 1297 |
| 4 | Coronavirus disease 2019 in elderly patients: characteristics and prognostic factors based on 4-week follow-up | JOURNAL OF INFECTION | June 2020 | Jiang, H | China | 573 |
| 5 | Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis | AGING-US | May 2020 | Huang, Y | China | 568 |
| 6 | Risk factors associated with mortality among patients with COVID-19 in intensive care units in Lombardy, Italy | JAMA INTERNAL MEDICINE | October 2020 | Zanella, A | Italy | 553 |
| 7 | Prevalence, severity and mortality associated with COPD and smoking in patients with COVID-19: a rapid systematic review and meta-analysis | PLOS ONE | June 2020 | Alqahtani, JS | England | 355 |
| 8 | The impact of COPD and smoking history on the severity of COVID-19: a systemic review and meta-analysis | JOURNAL OF MEDICAL VIROLOGY | May 2020 | Lin, S | China | 324 |
| 9 | Distribution of ACE2, CD147, CD26, and other SARS-CoV-2 associated molecules in tissues and immune cells in health and in asthma, COPD, obesity, hypertension, and COVID-19 risk factors |
ALLERGY | September 2020 | Sokolowska, M | Switzerland | 226 |
| 10 | Preexisting comorbidities predicting COVID-19 and mortality in the UK Biobank community cohort |
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES | November 2020 | Melzer, D | England | 225 |
ACE2 = angiotensin-converting enzyme 2, COPD = chronic obstructive pulmonary disease, COVID-19 = coronavirus disease 2019.
A total of 5578 authors were included in the 816 articles, and Table 3 shows the 10 most prolific authors studying COPD and COVID-19. Four authors are from China, 3 from Australia, 1 from England, and 1 from the USA. The 4 authors from China have published articles with the top 4 total citations, indicating the great influence of their related research. Figure 12 is a visualization map of co-authorship, with the size of the circles representing the intensity of collaboration and the color difference representing the time spent studying this topic. We found that the collaborative groups are mainly represented by Hurst JR, Eapen MS, and Brent R. Stockwell, and some researchers are independently scattered with other active scholars and lack extensive collaboration. Therefore, countries and institutions should continue to strengthen communication and cooperation and commit to relevant research.
Table 3.
The top 10 most productive authors.
| Author | Document | Sum of citations | Average citations | H-index | Country | Institution |
|---|---|---|---|---|---|---|
| Guan WJ | 8 | 2589 | 324 | 5 | China | Guangzhou Med Univ, Affiliated Hosp 1, |
| Eapen MS | 7 | 83 | 12 | 5 | Australia | Univ Tasmania, Coll Hlth & Med, |
| Hurst JR | 7 | 411 | 59 | 5 | England | UCL, UCL Resp, |
| Sohal SS | 7 | 83 | 12 | 5 | Australia | Univ Tasmania, Coll Hlth & Med, |
| Li L | 6 | 2542 | 424 | 3 | China | Chinese Med Sci, Sichuan Inst Translat Chinese Med, |
| Liu J | 6 | 52 | 9 | 4 | USA | Univ Illinois, Coll Med, |
| Lu WY | 6 | 64 | 11 | 4 | Australia | Univ Tasmania, Coll Hlth & Med, |
| Wang T | 6 | 2870 | 478 | 4 | China | Wuhan Univ, Dept Resp & Crit Care Med, |
| Zhong NS | 6 | 2574 | 429 | 4 | China | Guangzhou Med Univ, Affiliated Hosp 1, |
Figure 12.
Visualization of the co-cited author analysis.
3.6. Fund supporting organizations
Table 4 lists the top 10 funding agencies contributing to this type of research, with the USA Department Of Health & Human Services funding the most (61), followed by the National Institutes Of Health (58), and the National Natural Science Foundation Of China (49). It can be seen that strong financial support is one of the essential conditions for research.
Table 4.
The top 10 funding agencies contributing to this type of research.
| Funding agency | Document | % of 816 | H-index |
|---|---|---|---|
| United States Department Of Health and Human Services, HHS | 61 | 7.475 | 15 |
| National Institutes Of Health, NIH | 58 | 7.108 | 15 |
| National Natural Science Foundation Of China, NSFC | 49 | 6.005 | 15 |
| National Institute For Health Research, NIHR | 19 | 2.328 | 12 |
| European Commission, EC | 17 | 2.083 | 8 |
| The Medical Research Council, MRC | 15 | 1.838 | 9 |
| Uk Research and Innovation, UKRI | 15 | 1.838 | 9 |
| National Heart, Lung and Blood Institute; NHLBI | 12 | 1.471 | 5 |
| German Research Foundation, DFG | 8 | 0.98 | 4 |
| AstraZeneca, AZN | 7 | 0.858 | 3 |
3.7. Hot and frontier
Keywords are a high summary of the core content of the literature research, and the visual analysis of keyword co-occurrence provides an understanding of the distribution and development of research hotspots in the field of COPD and COVID-19. Considering the huge number of keywords in the field of COPD and COVID-19, we set the minimum frequency of keywords to 10 occurrences, and out of 2844 keywords, a total of 82 keywords met this threshold requirement and were included in the analysis. These 82 keywords were analyzed and visualized for mapping using VOSviewer software. In the keyword analysis, the top 20 keywords in terms of the number of occurrences after the index words were removed are shown in Table 5. The contents reflected by these keywords are the hotspots of research in this field, among which mortality has the most occurrences (133), indicating that it is the most hotly researched.
Table 5.
The top 20 keywords in terms of number of occurrences after the index words were removed.
| Keywords | Occurrences | Total link strength |
|---|---|---|
| Mortality | 133 | 360 |
| Asthma | 79 | 229 |
| Pneumonia | 68 | 216 |
| Outcomes | 62 | 168 |
| Obstructive pulmonary disease | 61 | 167 |
| Risk | 51 | 155 |
| Disease | 47 | 116 |
| Infection | 43 | 128 |
| Inflammation | 41 | 115 |
| Ace2 | 38 | 119 |
| Epidemiology | 36 | 92 |
| Clinical characteristics | 33 | 134 |
| Risk factors | 33 | 80 |
| Severity | 33 | 136 |
| Wuhan | 33 | 101 |
| Expression | 32 | 102 |
| Impact | 31 | 121 |
| Comorbidities | 28 | 93 |
| Prevalence | 28 | 88 |
| Management | 27 | 79 |
ACE2 = angiotensin-converting enzyme 2.
The size in the keyword co-occurrence visualization mapping represents the frequency of keyword occurrence, and the line between 2 points represents 2 keywords appearing in 1 paper. The keyword clustering domain was obtained in VOSviewer by using the LinLog/modularity layout method (Fig. 13), and a total of 3 clustering modules were formed. The circles and labels form a module, and the modules of different colors form different clusters. As shown in Figure 13, we can see the red, green, and blue clusters, which represent 3 different research directions, respectively. After removing words such as index words, the main keywords in the red cluster are mortality, outcome, pneumonia, comorbidities, and risk factor, the main keywords in the green cluster are management, prevalence, and exacerbations, the main keywords in the blue cluster are inflammation, infection, angiotensin-converting enzyme 2 (ACE2), expression, and receptor. Figure 14 represents the keyword co-occurrence mapping with temporal attributes, which provides further insight into the average time of keyword occurrence.
Figure 13.
Co-occurrence analysis of keywords.
Figure 14.
The keyword co-occurrence mapping with temporal attributes.
4. Discussion
4.1. Current status and trends of research in the field of COPD and COVID-19
From late 2019 to date, COVID-19 has ravaged several countries around the world, with approximately 464 million confirmed cases worldwide as of March 2022, making it a global public health emergency.[15] COPD is one of the most common chronic diseases in the world, causing a considerable economic and social burden globally,[16] as well as being a priority for current COVID-19 epidemic preparedness.
In this study, the WOSCC search platform was selected for bibliometric analysis and visualization of authors, journals, and research hotspots related to COPD and COVID-19. The statistical results showed that a total of 79 countries, about 5578 authors, and 2110 research institutions were involved in COPD and COVID-19-related research worldwide, with the USA, China, England, and Italy having more total publications, and mainly the US, China, and England cooperating closely to publish the most research publications and making the largest contributions and sharing timely epidemic prevention and control with all countries in the world. The number of publications and RRI in related studies continues to grow, indicating that such research remains a hot topic.
4.2. Research hotspots in COPD and COVID-19
We can effectively clarify the current hotspots of research on COPD and COVID-19 and their frontier trends by comprehensively analyzing the co-occurrence and clustering of keywords. From the co-occurrence frequency of keywords, the high-frequency hot words include mortality, outcome, risk, infection, inflammation, ACE2, and epidemiology. From the keyword clustering analysis, it can be understood that the studies were divided into 3 main directions, Cluster 1 mainly focused on the clinical characteristics of COPD combined with COVID-19, such as outcome, prognosis, and risk factors. Cluster 2 mainly discussed the disease management of COPD combined with COVID-19. Cluster 3 focuses on the mechanism of COPD combined with COVID-19. The temporal distribution of keywords shows that the research hotspot has changed from exploring the clinical features of the disease to the management of the disease and the mechanisms of the disease.
4.3. Clinical features of COPD combined with COVID-19
Although whether COPD is a risk factor for COVID-19 is controversial, a growing body of research mostly suggests that COPD is associated with worse outcomes.[17–19] Statistically, during the COVID-19 pandemic, COPD was comorbid in approximately 18% of patients hospitalized with COVID-19.[20] A meta-analysis showed that the presence of comorbidities increased the risk of COVID-19, with COPD (OR: 5.97, P < .001) being a major risk factor for COVID-19.[21] In addition, an analysis of 1590 COVID-19 Chinese patients found that, even after adjusting for age and smoking factors, the odds ratio of COPD patients in ICU admission, mechanical ventilation, or death was 2.681 (95% confidence interval: 1.424–5.048; P = .002).[18] Factors associated with the risk of developing COVID-19 in COPD include poor patients’ treatment compliance, difficulties in self-management, reduced medical attention during the outbreak, missed diagnosis or misdiagnosis of AECOPD, and reduced pulmonary function reserve.[22] It is worth noting that the presence of COPD, in addition to increasing a patient’s chance of contracting COVID-19, also increases the risk of developing respiratory symptoms for >4 weeks after recovery from COVID-19 (OR = 3.13, 95% confidence interval: 1.89–5.00), resulting in repeated outpatient or emergency department visits and even hospitalization.[23]
4.4. Management of COPD combined with COVID-19
Disease management of COPD patients in the COVID-19 pandemic requires the active collaboration of patients and healthcare professionals. During the COVID-19 epidemic, new models of Internet hospitals and online platforms for remote access to medical consultations were developed, which can reduce the risk of infection associated with the movement of people.[24] Furthermore, the 2022 GOLD guidelines suggest that stable patients need to have adequate inhaler therapy and maintain a regular and standardized inhaler regimen during the epidemic(https://goldcopd.org/gold-reports/). However, it should be noted that the use of glucocorticoids is still controversial.[25,26] The COVID-19 vaccine is highly effective in patients requiring hospitalization, ICU, or emergency SARS-CoV-2 infection, including those with chronic respiratory disease.[27] And a study has shown that the COVID-19 vaccine induces a similar immune response in COPD patients as in healthy subjects. Patients with COPD should be vaccinated against COVID-19 in accordance with national recommendations. In addition, COPD patients wearing a high containment N95 mask may exacerbate preexisting dyspnea, especially in COPD patients with a modified Medical Research Council dyspnea scale score ≥ 3 or a FEV1 < 30% predicted especially need close attention.[28] However, this effect is negligible with the option of wearing a surgical mask.[29] Pulmonary rehabilitation is effective in reducing symptoms, improving health status, and increasing exercise tolerance in patients with COPD. However, due to social and physical distance limitations and concerns about SARS-CoV-2 transmission in the community, home-based telepulmonary rehabilitation may be considered.[30]
4.5. The mechanism of COPD combined with COVID-19
The outbreak of COVID-19 is a great test for healthcare workers. In the face of an unknown virus, there is a lack of many methods for diagnosis and treatment in the early stage. With the progression of the disease and the accumulation of diagnosis and treatment experience, basic researchers will also study the pathogenesis of the virus from various aspects. Studies have found increased expression of the ACE2 receptor in this disease, leading to severe symptoms in individuals with COVID-19, including structural lung damage, decreased immunity, and sputum production.[31] The spike protein (S protein) in the structure of SARS-CoV-2 binds to ACE2 during viral attachment to the host cell, and transmembrane serine protease 2 also facilitates viral entry.[32] In addition, it has been shown that differences in ACE2 and transmembrane serine protease 2 expressions may modulate individual susceptibility to and clinical course of SARS-CoV-2 infection.[33] And the ACE2 mRNA expression is increased in COPD bronchial and alveolar epithelial cells,[34] but is significantly downregulated in COPD patients with regular inhaled hormones.[35]
In conclusion, it is known that when COPD patients are combined with COVID-19, they are at increased risk of developing severe pneumonia and have a poor prognosis, which may be related to the potential lack of lung reserve or increased expression of ACE2 receptors in the small airways,[36] so the management of COPD patients during the epidemic is particularly important. How can uninfected individuals reduce the risk of SARS-CoV-2 infection while minimizing the impact on the continuity and stability of their own COPD therapy? Is COPD drug therapy continued in infected individuals? How to determine the treatment regimen for COPD patients with COVID-19? How to reduce the risk of progression to severe disease in patients with COPD combined with COVID-19? These may be the future research directions and priorities.
There are still some shortcomings in this study. First, bibliometric studies are cross-sectional analyses, and their findings vary over time, so the study needs to be updated in real-time in the future; second, the results of bibliometric studies do not fully represent the true situation because newly published literature, especially those published this year, have not yet been heavily cited, so there is a possibility that the key studies are missed in this research. We need to follow up on the progress in this area continuously.
5. Conclusion
In the context of the new coronary pneumonia epidemic, our research in the field of COPD disease also had to be combined with COVID-19, which is a hot topic and trend in COPD disease research, and the area that continues to stimulate a great deal of scholarly interest and research. The present study is the first bibliometric study to analyze publications on COPD and COVID-19 around the world, and it demonstrates the trends and characteristics of related studies, providing researchers with useful bibliometric analysis for further studies, which may help researchers to deepen their understanding of the disease under the epidemic and provides us with references to further optimize disease management measures, and then it may reduce the adverse effects of the epidemic on COPD patients.
Author contributions
Formal analysis: Huiqin Wang.
Software: Lixiang Jiang, Long Chen.
Visualization: Kai Zhao.
Writing – original draft: Yaolin Li, Xiayahu Li.
Writing – review & editing: Yaolin Li, Xiayahu Li.
Abbreviations:
- ACE2
- angiotensin-converting enzyme 2
- COPD
- chronic obstructive pulmonary disease
- COVID-19
- coronavirus disease 2019
- ICU
- intensive care unit
- RRI
- relative research interest
- WOSCC
- Web of Science Core Collection
This work was supported by the Medical Research Project of Chengdu Municipal Health Commission (NO.2021341).
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Li Y, Wang H, Jiang L, Chen L, Zhao K, Li X. A bibliometric analysis of chronic obstructive pulmonary disease and COVID-19. Medicine 2023;102:10(e33240).
Contributor Information
Yaolin Li, Email: lxyahu@qq.com.
Huiqin Wang, Email: 1257360518@qq.com.
Lixiang Jiang, Email: 642834028@qq.com.
Long Chen, Email: 331359623@qq.com.
Kai Zhao, Email: zhaokai1682022@163.com.
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