key: cord-0768612-tskdmidu authors: Alkhathami, M. G.; Advani, S.; Al Shehri, M. K.; Abalkhail, A.; Alkhathami, F.; Al Salamah, J. A.; Albeashy, E. title: Prevalence and mortality of Lung Comorbidities Among Patients with COVID-19: A systematic review and meta-analysis date: 2020-06-03 journal: nan DOI: 10.1101/2020.06.01.20119271 sha: 03315669601c97e39bcaded337cc11c7aa0871d7 doc_id: 768612 cord_uid: tskdmidu Abstract Background The World Health Organization declared COVID-19 associated infections as a global health public emergency that has led to more than 3,50,000 deaths worldwide. COVID-19 infections are seen across all age groups but they have shown to have a predisposition for the elderly and those with underlying comorbidities. Specifically, these include cardiovascular diseases, diabetes and underlying lung conditions. Further, patients with severe COVID-19 infections and comorbidities are more prone to respiratory distress syndrome (ARDS), mechanical ventilator use and ultimately succumb to these complications. Little evidence exists of the prevalence of underlying lung comorbidities among COVID-19 patients and associated mortality. Methods We performed a systematic review of the literature including PubMed (Medline), Embase (Ovid), Google Scholar and Cochrane Library. The last date for our search was 29th April 2020. We included all original research articles on COVID-19 and calculated prevalence of chronic lung disease patients among COVID-19 patients using random effects model. Further we assessed for mortality rates among COVID-19 patients associated with these lung comorbidities. We calculated pooled prevalence of these conditions among COVID-19 patients using random effects model. Results The authors identified 29 articles that reported the prevalence of chronic lung conditions among COVID-19 patients. Among those, 26 were from China and 3 from the United States. The pooled prevalence of lung comorbidities including Asthma, COPD, and lung cancer was 3% (95% CI=0-14%), 2.2% (95% CI=0.02-0.03%) and 2.1% (95% CI=0.00-0.21%) respectively. Mortality rates associated with these comorbidities was 30% (41/137) for COPD and 19% (7/37) for lung cancer respectively. No mortality rates were reported for patients with asthma. Conclusion This study provides preliminary evidence of the prevalence of chronic lung conditions among patients with COVID-19. Future studies are needed to assess other lung comorbidities and associated mortality among patients diagnosed with COVID-19. The novel coronavirus (2019-nCoV/SARS-Cov-2) also termed as COVID-19 discovered in late 2019 in Wuhan, China has been established to be the main cause of a cluster of pneumonia cases which have disrupted the world order today [1] . As of May 26th, 2019, the spread of COVID-19 has been rapid across the globe with more than 5,307,298 confirmed cases of COVID-19, including 342,070 deaths, have been reported by the World Health Organization. Given the rapid spread of COVID-19 and driven by international concern, the WHO declared coronavirus as a global pandemic [2] . Caused by a new strain of the virus, COVID-19 belongs to the family of the class of coronavirus that included viruses associated with the outbreak of Middle East Respiratory (MERS) in 2012 and severe acute respiratory syndrome (SARS) in 2002 [3] . Today, most COVID-19 patients show symptoms of viral pneumonia such as fever, fatigue, dry cough, and lymphopenia [4] . Reports from around the world highlight that COVID-19 infection is more common among the elderly, those who live in elderly homes or nursing homes, and those with preexisting conditions like diabetes, heart diseases, and cancer [5] . Rapidly evolving evidence highlight the burden and rates of infection among people with and without comorbidities and see a significant higher burden among those with comorbidities [6] . Especially, in this early systematic review and meta-analysis, authors identified that most prevalent comorbidities among patients with COVID-19 included hypertension (21.1%, 95% CI: 13.0-27.2%), diabetes (9.7%, 95% CI: 7.2-12.2%), cardiovascular disease (8.4%, 95% CI: 3.8-13.8%) and respiratory system disease (1.5%, 95% CI: 0.9-2.1%) [6] . In addition to symptoms associated with pneumonia, COVID-19 has been shown to cause damage to other organs including heart, liver, and kidneys as well as blood and immune system [4] . In severe COVID-19 infection, All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint patients develop or succumb to multiple organ failure, shock, acute respiratory distress syndrome, heart failure, arrhythmias, and renal failure [7] . Finally, smoking and associated comorbidities have shown to increase the risk of infection with COVID-19 due to underlying mechanisms surrounding angiotensin-converting enzyme receptors and high affinity of COVID-19 to ACE receptors [8] . According to recent findings, COVID-19 related lung injury leading to acute respiratory distress syndrome remains the leading cause of mortality worldwide [9] . This includes the development of secondary haemophagocytic lymphohistiocytosis (sHLH), a hyperinflammatory syndrome triggered by a viral infection and characterized by a fulminant and fatal hypercytokinaemia with multiorgan failure and ARDS is the hallmark of COVID-19 infection-associated mortality [9] . Due to the underlying predisposition of COVID-19 to lung tissue, it remains imperative to assess the burden of lung-specific comorbidities including COPD, asthma, lung cancer, and cystic fibrosis among COVID-19 patients. This remains crucial to improving outcomes among those with underlying comorbidities as they might share common underlying mechanisms. Up to date, there is no comprehensive evidence to evaluate the prevalence of chronic lung diseases in COVID-19 patients. Therefore, the primary objective of this systemic review and meta-analysis is to determine the prevalence and mortality of chronic lung diseases which include COPD, lung cancer, asthma, and cystic fibrosis in confirmed COVID-19 cases. We registered this systematic review with PROSPERO (ID: CRD42020178039). Also, it was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [10] . Authors performed a literature search of scientific databases including PubMed (Medline), Embase (Ovid), and the Cochrane Library. Furthermore, we did an additional search Moreover, two independent authors were assessed all the included papers using the modified version of the Newcastle-Ottawa Scale (NOS) and the results are provided in Table 1 [11] . This detailed table includes seven domains, each one of these domains was scored from 0 (high risk of bias) to 1 (low risk of bias) and we took a total of the domains to result in a score between 0 to 7, where a higher score indicates a low risk of bias. During this collective investigation, we calculated pooled estimates of chronic lung conditions among COVID-19 patients. We used random effects model to estimate these prevalence's among COVID-19 patients. Further we assessed for heterogeneity and publication bias. In addition, 95% confidence interval used to estimate the Inverse variance method, and heterogeneity was evaluated by using I^2. Further, the restricted maximum-likelihood estimator was used to estimate the between-study variance biases. Data were displayed using forest plots and all statistical analyses were performed using metaprop command in R metaprop command. Further publication bias was assessed using Funnel Plots and Egger's regression test [12, 13] . The trim-and-fill procedure includes the following five steps: a. Estimating the number of studies in the outlying (right) part of the funnel plot. b. Removing (trimming) these effect sizes and pooling the results with the remaining effect sizes. c. This pooled effect is then taken as the center of all effect sizes. d. For each trimmed/removed study, an additional study is imputed, mirroring the effect of the study on the left side of the funnel plot. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint e. Pooling the results with the imputed studies and the trimmed studies included. A summary of the included studies is presented in Table 1 , which included a total of 6261 confirmed COVID-19 patients across 29 included studies. Majority of our participants were males (54%). Due to the novel nature and outbreak of COVID-19, our articles found that only three lung comorbidities were included in these articles. These included asthma, COPD, and lung cancer respectively. Surprisingly, no studies estimated prevalence of cystic fibrosis that increases risk of individuals to opportunistic infections. This might be due to it being a rare disease and having low population prevalence. The sample size of the included studies ranged from 2 to 1590 patients. Most of the studies were retrospective in nature and based mainly in China (n=26) followed by the United States (n=3). Further mortality rates were only reported for COPD and lung cancer. The crude mortality rate was 30% (41/137) and 19% (7/37), respectively. Figure 1 provides an overview of our selection process using the PRISMA flow chart. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. Studies included in quantitative synthesis (meta-analysis) (n = 29) All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint Fig2: Prevalence of asthma among patients hospitalized with COVID-19. We identified 8 studies that measured prevalence of asthma among patients diagnosed with COVID-19. In pooled analysis we found that prevalence of asthma among patients hospitalized with COVID-19 was 3% (range 0-14%). Figure 2 shows the forest plot for asthma prevalence among COVID-19 patients. Our analysis identified significant presence of heterogeneity in our estimate (I 2 =79%, p<0.01). There was significant publication bias in studies was present because there was asymmetry of the funnel plot presented in figure 3 based on Egger's test was (t=2.71, p=0.04). Therefore, we performed a trim and fill method in figure 3 . This estimate showed little change, which indicated influence of the publication bias was small (t = 0.15, p = 0.89). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint The pooled prevalence of COPD identified in 22 studies among patients hospitalized with COVID-19. It was estimated to be 2.2% (95% CI=0.02-0.03%). Figure 4 shows the forest plot for COPD prevalence among COVID-19 patients. Our analysis identified significant presence of heterogeneity in our estimate (I 2 =70%, p<0.01). The estimate of the heterogeneity variance using the statistic I 2 was 70 %, value of t is 6.052 and the p-value was 0.00001, which means that a high significant publication bias was present. This is represented in of the funnel plot in Figure 3 . As a result, we carry out a trim and fill method in figure 3 . Here, the asymmetry outlying part of the funnel plot was trimmed off and number of studies was estimated. This estimate showed little change, which indicated influence of the publication bias was small. Egger's test was (t = 0.66, p-value = 0.51). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . We identified 6 studies that measured prevalence of lung cancer among patients diagnosed with COVID-19. In pooled analysis we found that prevalence of lung cancer among patients hospitalized with COVID-19 was 2.1% (95% CI=0.00-0.21%). Figure 5 shows the forest plot for lung cancer prevalence among COVID-19 patients. Our analysis identified significant presence of heterogeneity in our estimate (I 2 =93%, p<0.01). A significant publication bias was found in studies (t = 5.18, p = 0.01) in funnel plot see Figure 3 . Consequently, we implement a trim and fill method in figure 3 . These studies were used to estimate the true center of the funnel. This estimate showed little change, which indicated influence of the publication bias was small. Egger's regression test was (t = 0.46, p = 0.66). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. High levels of quality of the included studies in a meta-analysis are preferable. In our study, there was variable quality of the included studies. Another limitation is that the funnel plot indicated there was publication bias because there was asymmetry. Using the trim and fill method we showed that there was no change in the center of the proportion and therefore the All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint influence of publication bias was small. To search for all available evidence, we included all comparative studies, strengthen the outcomes. Other strengths of our study are the large number of patients and revisions and no restrictions in the search on publication. We used the modified Newcastle-Ottawa scale for quality assessment. We performed quality assessment on the included studies. This scale assesses quality of included studies on 7 main domains which are representativeness of population, representativeness of the cases, missing data, ascertainment of exposure, statistical analysis, assessment of outcome and follow-up of outcome. Each one of these domains was scored from 0 (high risk of bias) to 1 (low risk of bias) and we took a total of the domains to result in a score between 0 to 7, where a higher score indicates a low risk of bias. It shows that risk of bias ranged from 4 to 7; all the included studies scored ≥ 4, which indicates low risk of bias. This study helps provide and strengthen the growing evidence that comorbidities play a major role in risk profiling for at risk patients for COVID-19. Though every individual faces the risk of contracting COVID-19, many remain asymptomatic. However, the elderly and those with underlying comorbidities have shown to not only be affected by COVID-19 infection but have a more severe infection, they are more likely to face adverse outcomes, including lifethreatening illnesses, use of life-saving support equipment's including ventilators and succumb to COVID-19 related illnesses of the heart and the lung [14, 15] . Hence, individuals with underlying comorbid conditions are particularly vulnerable and should provide a high level of care including prevention and treatment to maximize benefits and minimize harms. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint We found that the pooled prevalence of COPD among COVID-19 patients ranged from 2-3%. COPD remains an important sequalae of smoking associated behaviors. COPD is an obstructive pulmonary disorder that encompasses emphysema, chronic bronchitis, and refractory asthma, characterized by increasing breathlessness, bronchial inflammation, and a decline in lung function tests. Globally, COPD incidence continues to increase with smoking prevalence and age; it is now considered to be an important comorbid condition that impacts both smoking associated outcomes including lung cancer and overall quality of life [8] . Further COPD has been shown to be associated with a nearly fourfold increase in the risk of COVID-19 infection [14] . A potential mechanism underlying higher risk of COVID-19 infection among patients with smoking-related illnesses directs towards the evidence of smoking associated upregulation of ACE-2 receptors in lower airways (type 2 pneumocytes) leading to higher rates of infection with COVID-19 among patients with underlying smoking associated comorbidities [8] . The microbial structure of coronavirus is characterized by transmembrane (spike or S) glycoproteins namely S1 and S2 [16] . The S1 contains sites for bindings of an angiotensinconverting enzyme that provides the virus the pathway to enter into the host cells while the S2 domain is responsible for cellular infiltration [17] . Recent studies have shown that ACE2receptors provide a binding site for SARS-COV-2 i.e. COVID-19 with an affinity 10-20 times as compared to other coronaviruses [18] . Further, patients with COPD also show high levels of ACE2 leading to a potentially higher risk of infection with COVID-19, mediate other potential enzymatic mechanisms, leading to lung injury, respiratory failure, and ultimately death [19, 20] . report from New York City, the prevalence of asthma was 12.5% among patients diagnosed with COVID-19 [22] . Patients diagnosed with asthma are highly prone to infections including COVID-19 that can trigger their asthma exacerbations, thereby leading to these patients presenting to primary and emergency departments with common symptoms associated with COVID-19 including fever, dry cough and shortness of breath [23] . Further, due to differential expression of underlying genes including ACE2 and TMPRSS2 among asthma patients based on clinical and demographic characteristics, it further warrants the need to identify the subgroup of asthma patients who might be at heightened risk of COVID-19 and develop appropriate isolation, treatment, and management strategies [24] . Finally, patients with asthma have shown to have a weakened immune system including a deficiency and delay in lung cell interferon (IFN)-α, IFN-β and IFN-λ(7) leading to asthma exacerbations and risk of viral infections, quantifying these cytokines might be helpful to further elucidate underlying mechanisms for progression of disease and COVID-19 and develop potential therapeutic targets [25] . In a case report of patient who died of COVID-19 and had underlying asthma, post-mortem analysis showed mixed features of mucus plugging (hallmark of asthma) and diffuse alveolar damage (hallmark of COVID-19 pneumonia) [26] . Hence it remains imperative to manage patients with asthma with utmost care to prevent exacerbations and associated morbidity and mortality In pooled analysis we found that prevalence of lung cancer among patients hospitalized with COVID-19 was 2.1% (95% CI=0.00-0.21%). Cancer predisposes an individual to a heightened risk of viral and bacterial infections due to weakened immune system. In a retrospective analysis of patients with COVID-19 and cancer in Wuhan, China, authors identified that lung cancer was the most common cancer (25%) among COVID-19 patients with cancer [27] . Further the study found that patients with cancer were more likely to have more adverse events, including admission to ICU, use of mechanical ventilation and death [27] . All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint Due to the complexity of multiple factors surrounding cancer patients including patients' clinical and demographic characteristics like age, gender, site, and stage as well as treatment and comorbidity history, certain groups recommend that baseline SARS-CoV-2 testing for all patients affected by lung cancer should be recommended and practiced [28] . Finally, in a pathology study of 2 patients who died of lung cancer, autopsy findings identified features associated with early COVID-19 infection including edema, proteinaceous exudate, focal reactive hyperplasia of pneumocytes with patchy inflammatory cellular infiltration, and multinucleated giant cells [29] . COVID-19 pandemic has led to an urgent need to focus on high risk patients including the elderly with underlying comorbidities. Evidence suggests that 14%-24% of patients developed pneumonitis and required hospitalization and oxygen support [28] . Further, about 5% of patients with COVID-19 infection develop acute respiratory distress syndrome (ARDS) or sepsis-related acute organ dysfunction, requiring admission to intensive care units [28] . Given the highly contagious nature of the virus and its affinity for lung tissue, special focus and emphasis on developing guidelines for the management of patients with underlying lung conditions remain critical to preventing disability and death. Our study has limitations and strengths. COVID-19 is rapidly evolving globally. Hence as new literature continues to be reported, estimates of individuals with COVID-19 and chronic comorbidities might change. Further, the majority of our studies were from China, the epicenter of the COVID-19 outbreak. Hence our results might not be an adequate representation of COVID-19 cases from the global perspective. Furthermore, certain studies reported low to medium risk of bias which might be due to heterogeneity due to sample size differences, data collection procedures, differences in assessment of comorbidities or evaluation of COVID-19, and assessment of other characteristics. Our strengths include the use of all available literature on lung-specific comorbidities and calculating pooled estimates. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 3, 2020. . https://doi.org/10.1101/2020.06.01.20119271 doi: medRxiv preprint To conclude, our results identify key areas for future work. First, designing and implementing smoking cessation interventions on a nationwide scale to help reduce risk to high-risk smokers. Second, identifying high risk individuals in community settings with underlying lung comorbidities including those with uncontrolled COPD and asthma. Third, promoting and identifying new treatment strategies for these conditions that reduce the risk of immunosuppression, thereby reducing the risk of COVID-19 infection. Finally, Isolating, Tracking and Tracing COVID-19 patients with lung comorbidities to prevent adverse outcomes. In summary, our review aimed to study the prevalence and mortality associated with lung comorbidity among patients with COVID-19. It shows that the most prevalent lung comorbidity associated with COVID-19 was asthma followed by COPD and lung cancer, while the higher mortality rate was found in COPD followed by lung cancer. Future studies are needed to assess prevalence and mortality of other lung comorbidities among patients diagnosed with COVID-19. All rights reserved. No reuse allowed without permission. 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(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted