Literature DB >> 33162738

Gastrointestinal predictors of severe COVID-19: systematic review and meta-analysis.

Muhammad Aziz1, Hossein Haghbin1, Wade Lee-Smith2, Hemant Goyal3, Ali Nawras4, Douglas G Adler5.   

Abstract

BACKGROUND: COVID-19 pandemic has created a need to identify potential predictors of severe disease. We performed a systematic review and meta-analysis of gastrointestinal predictors of severe COVID-19.
METHODS: An extensive literature search was performed using PubMed, Embase, Web of Science and Cochrane. Odds ratio (OR) and mean difference (MD) were calculated for proportional and continuous outcomes using a random-effect model. For each outcome, a 95% confidence interval (CI) and P-value were generated.
RESULTS: A total of 83 studies (26912 patients, mean age 43.5±16.4 years, 48.2% female) were included. Gastrointestinal predictors of severe COVID-19 included the presence of diarrhea (OR 1.50, 95%CI 1.10-2.03; P=0.01), elevated serum aspartate aminotransferase (AST) (OR 4.00, 95%CI 3.02-5.28; P<0.001), and elevated serum alanine aminotransferase (ALT) (OR 2.54, 95%CI 1.91-3.37; P<0.001). Significantly higher levels of mean AST (MD 14.78 U/L, 95%CI 11.70-17.86 U/L; P<0.001), ALT (MD 11.87 U/L, 95%CI 9.23-14.52 U/L; P<0.001), and total bilirubin (MD 2.08 mmol/L, 95%CI 1.36-2.80 mmol/L; P<0.001) were observed in the severe COVID-19 group compared to non-severe COVID-19 group.
CONCLUSION: Gastrointestinal symptoms and biomarkers should be assessed early to recognize severe COVID-19. Copyright: © Hellenic Society of Gastroenterology.

Entities:  

Keywords:  COVID-19; SARS-CoV-2; diarrhea; predictors; severe COVID-19

Year:  2020        PMID: 33162738      PMCID: PMC7599357          DOI: 10.20524/aog.2020.0527

Source DB:  PubMed          Journal:  Ann Gastroenterol        ISSN: 1108-7471


Introduction

COVID-19, caused by SARS-CoV-2, has become a worldwide pandemic imposing a significant burden on healthcare systems around the globe. The virus causes a variety of manifestations, including pneumonia, acute respiratory distress syndrome, shock, sepsis, and death [1]. Currently, no specific therapy (preventive or therapeutic) is available for this disease [2]. Symptomatically, the virus leads to fever, fatigue, cough, shortness of breath, myalgias, arthralgias, nasal congestion, runny nose, sore throat, nausea/vomiting, and diarrhea [1]. The virus further causes laboratory abnormalities, including derangements of white cell count, platelet count, C-reactive protein, procalcitonin, lactate dehydrogenase, aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TB), creatinine, and D-dimer [1]. The pandemic nature of this disease necessitates emergent and early recognition of symptomatic patients to identify those at most severe risk and to provide supportive measures as needed, up to and including mechanical ventilation. Gastrointestinal parameters (symptoms and laboratory findings) have been reported in the literature among patients with COVID-19 [3], but there is little comprehensive information regarding gastrointestinal symptoms in these patients. We performed a systematic review and meta-analysis to evaluate whether gastrointestinal symptoms and abnormal laboratory findings predict disease severity.

Materials and methods

A comprehensive literature search was performed from January 1st, 2020, to May 31st, 2020, using the following databases: PubMed/Medline, Embase, Cochrane, Web of Science. The search strategy, using a predeveloped vocabulary for COVID-19 [4], was created by an experienced librarian (WLS) and crosschecked by another reviewer (MA). An example search strategy using EMBASE is highlighted in Supplementary Table 1. Article screening and data extraction was performed by 2 independent reviewers (MA and HH) and any discrepancies in screening/extraction were resolved through mutual discussion. Interobserver agreement was evaluated using % of agreement and Cohen’s Kappa (Κ) statistic. Articles were selected if they reported data on COVID-19 patients with respect to gastrointestinal symptoms (diarrhea, abdominal pain, and nausea/vomiting) or laboratory findings (serum AST, ALT, or TB). We excluded articles if the data of interest were not reported or the article had not undergone a peer-review process. We further excluded case reports and retrospective studies/case series reporting <10 cases. We used the bibliography of the finalized articles to further broaden our literature search. We did not restrict our search according to language. Severe COVID-19 was defined as respiratory distress (rate ≥30 /min, oxygen saturation ≤93% at rest and/or PaO2/FiO2 ≤300 mmHg) [1], intensive care unit (ICU) admission, and/or death. Laboratory data (mean serum AST, ALT and TB) were reported based on the local laboratory’s reference parameters for each study. Symptoms (diarrhea and nausea/vomiting) were reported based on initial presentation.

Statistical analysis

Data extraction was performed using Microsoft Excel (Microsoft, Redmond, Wash, USA). Continuous variables (using mean and standard deviation [SD]) and proportional variables (using event and total patients) were compared using the DerSimonian-Laird approach or a random-effects model. The fixed effect model was used as a sensitivity tool; however, given the presumed heterogeneity of study data from diverse sources and clinical settings, the random-effects model was considered more appropriate and results were reported using that approach [5,6]. The mean and SD were calculated from median and interquartile range where applicable. Results are displayed using forest plots for each summary estimate, i.e., mean difference (MD) and odds ratio (OR) for continuous and proportional variables, respectively. A 95% confidence interval (CI), P-value (<0.05 was considered statistically significant), and study heterogeneity using I2 statistic (>50% was considered as substantial heterogeneity) were calculated for each outcome [7]. Subgroup analysis was performed based on the definition of severe COVID-19 (respiratory distress, ICU admission, and death) if at least 3 studies reported the outcome. Sensitivity analysis using leave-one-out meta-analysis was performed and point estimates were generated. Meta-regression was attempted to assess the impact of moderator variables on study outcomes. The moderator variables assessed included female proportions in each study, region of study (Asia, Europe, North America, South America), and number of centers in each study (single center, dual center, multicenter). The statistical analysis was performed using Open Meta Analyst (CEBM, University of Oxford, Oxford, United Kingdom) and Comprehensive Meta-Analysis (BioStat, Englewood, NJ, USA). We utilized the Quality in Prognostic Studies (QUIPS) tool for assessing the risk of bias in the observational studies [8]. Publication bias was assessed qualitatively by visualizing the funnel plot and quantitatively using Egger’s regression analysis. We adhered to “preferred reporting items for systematic reviews and meta-analyses (PRISMA)” guidelines for the purposes of this manuscript.

Results

Literature search

Using the search strategy defined above, a total of 1525 records were generated. After the inclusion/exclusion criteria had been applied, a total of 83 published studies (all observational) remained that reported data on gastrointestinal symptoms and/or laboratory findings (Fig. 1) [1,3,9-89]. All studies included laboratory-confirmed COVID-19 patients. The percentage of agreement was >90% for both screening and data extraction and corresponding Κ values of 0.72 and 0.69 (substantial agreement), respectively, were noted. Of the 83 included studies, 42 reported data on disease severity with respect to symptoms and/or lab findings.
Figure 1

PRISMA diagram

PRISMA diagram

Characteristics of the included studies

Study details and demographics of included patients are highlighted in Table 1. Based on region, 70 studies originated from Asia, 8 from North America, 1 from South America, and 4 from Europe. The study duration was from December 11th through May 5th, 2020. Based on the number of centers reporting data, 17 studies were multicenter, 6 were dual-center, 57 were single-center, and 3 studies failed to mention the center from where the data originated. A total of 26,912 patients were included across these 83 studies. The patients’ mean age was 43.5±16.4 years and the female proportion was 48.2%.
Table 1

Study characteristics and baseline demographic data for included patients

Study characteristics and baseline demographic data for included patients

Prevalence of gastrointestinal parameters on admission

Symptoms

The overall prevalence of diarrhea on admission among the study population was 13.0% (95%CI 10.8-15.5%; I2=95.1%). Based on region, the following prevalences were noted: Europe 16.8% (95%CI 2.9-57.8%; I2=98.0%), North America 26.2% (95%CI 20.1-33.3%; I2=90.6%), and Asia 11.5% (95%CI 9.5-13.9%; I2=91.8%). The overall prevalence of nausea/vomiting on admission among the study population was 9.5% (95%CI 7.9-11.4%; I2=92.6%). Based on region, the following prevalences were noted: Europe 8.9% (95%CI 2.1-30.4%; I2=94.1%), North America 18.7% (95%CI 14.6-23.6%; I2=83.9%), and Asia 7.7% (95%CI 5.9-9.9%; I2=91.6%).

Laboratory abnormalities

The prevalence of abnormal AST findings on admission was 27.1% (95%CI 21.7-33.2%; I2=95.9%). Based on region, the following prevalences were noted: North America 46.3% (95%CI 27.7-66.0%; I2=96.6%), and Asia 26.3% (95%CI 22.1-31.0%; I2=89.3%). The prevalence of abnormal ALT findings on admission was 22.3% (95%CI 18.4-26.7%; I2=92.3%). Based on region, the following prevalences were noted: North America 21.4% (95%CI 16.5-27.4%; I2=69.1%), and Asia 22.1% (95%CI 17.4-27.6%; I2=92.7%). The prevalence of abnormal TB levels on admission was 10.6% (95%CI 5.0-21.0%; I2= 97.1%). All studies that reported abnormal TB were from Asia.

Gastrointestinal predictors of severe COVID-19

The odds of patients with diarrhea having severe disease were significantly greater compared to those without diarrhea (26 studies, OR 1.50, 95%CI 1.10-2.03; P=0.01; I2=54.1%) (Fig. 2A). Leave-one-out meta-analysis demonstrated consistent results, with a point estimate (OR) ranging between 1.46-1.74. A subgroup analysis of 17 studies that defined disease severity in terms of respiratory distress also showed consistent results (OR 1.62, 95%CI 1.11-2.37; P=0.01; I2=54.1%). Subgroup analysis based on ICU admission (5 studies) did not demonstrate increased odds of severe disease (OR 1.39, 95%CI 0.70-2.73; P=0.35; I2=27.1%). Meta-regression did not demonstrate any significant moderating impact of female proportion (P=0.39) or the number of centers involved in the study (P=0.89).
Figure 2

Forest plot demonstrating (A) severe disease in diarrhea vs. no diarrhea, and (B) severe disease in nausea/vomiting vs. no nausea/vomiting

Forest plot demonstrating (A) severe disease in diarrhea vs. no diarrhea, and (B) severe disease in nausea/vomiting vs. no nausea/vomiting Fourteen studies evaluated nausea/vomiting and disease severity and no significant association was found (OR 1.13, 95%CI 0.81-1.57; P=0.48; I2=22.6%) (Fig. 2B). Consistent results were obtained on leave-one-out meta-analysis (OR 1.07-1.24). The subgroup analysis also did not demonstrate a significant association when severity was classified on the basis of respiratory distress (8 studies, OR 1.27, 95%CI 0.84-1.90; P=0.26; I2=21.2%) or ICU admission (4 studies, OR 0.98, 95%CI 0.41-2.35; P=0.97; I2=42.1%). Meta-regression did not reveal any moderating impact of variables on outcomes, i.e., female proportion (P=0.20), region of study (P=0.19), or number of centers (P=0.33). Elevated serum AST levels in patients were evaluated in 16 studies and greater odds of disease severity were noted compared to patients without elevated AST (OR 4.00, 95%CI 3.02-5.28; P<0.001; I2=40.4%) (Fig. 3A). The results were consistent on leave-one-out meta-analysis (OR 3.64-4.14) as well as subgroup analysis for disease severity defined based on respiratory distress (11 studies, OR 3.80, 95%CI 2.77-5.22; P<0.001; I2=38.7%), and ICU admission (3 studies, OR 5.69, 95%CI 2.01-16.09; P=0.001; I2=45.8%). On meta-regression, the proportion of females in the study inversely correlated with the odds of having greater disease severity (P=0.04).
Figure 3

Forest plot demonstrating (A) severe disease in elevated AST vs, normal AST, (B) severe disease in elevated ALT vs. normal ALT, and (C) severe disease in elevated TB vs. normal TB

AST, aspartate aminotransferase; ALT, alanine aminotransferase; TB, total bilirubin

Forest plot demonstrating (A) severe disease in elevated AST vs, normal AST, (B) severe disease in elevated ALT vs. normal ALT, and (C) severe disease in elevated TB vs. normal TB AST, aspartate aminotransferase; ALT, alanine aminotransferase; TB, total bilirubin Elevated serum ALT levels on admission were evaluated in 14 studies and greater odds of disease severity were noted compared to patients with normal ALT (OR 2.54, 95%CI 1.91-3.37; P<0.001; I2=39.3%) (Fig. 3B). Similar results were obtained using leave-one-out meta-analysis (OR 2.28-2.73) and subgroup analysis for disease severity based on respiratory distress (9 studies, OR 2.93, 95%CI 1.92-4.48; P<0.001; I2=55.9%). No significant moderating impact of female proportion (P=0.35) or number of centers (P=0.24) was noted. Only 5 studies evaluated elevated serum TB levels in association with disease severity, and elevated TB was associated with severe disease (OR 2.09, 95%CI 1.36-3.21; P=0.001; I2=17.5%) (Fig. 3C). Leave-one-out meta-analysis demonstrated a consistent association (OR 1.89-2.51). A subgroup analysis and meta-regression were not possible because of the low number of studies.

Mean laboratory findings and severe COVID-19

The mean serum AST level was significantly higher in the severe group compared to the non-severe group (32 studies, MD 14.78 U/L, 95%CI 11.70-17.86 U/L; P<0.001; I2=97.5%) (Fig. 4A). The leave-one-out meta-analysis was consistent with a point estimate (MD) ranging from 13.70-15.32 U/L. Subgroup analysis was performed on the basis of severity and significantly higher mean AST levels were noted for the severe group, defined in terms of ICU admission (5 studies, MD 20.49 U/L, 95%CI 7.60-33.39 U/L; P=0.002; I2=98.03%), death (4 studies, MD 18.01 U/L; 95%CI 13.62-22.41 U/L; P<0.001; I2=93.7%), and respiratory distress (20 studies, MD 13.60 U/L, 95%CI 9.95-17.24 U/L; P<0.001; I2=96.9%). Meta-regression did not reveal any moderating impact of region of study (P=0.89) or number of centers (P=0.94).
Figure 4

Forest plot demonstrating (A) mean serum AST in severe vs. non-severe disease, (B) mean serum ALT in severe vs. non-severe disease, and (C) mean serum TB in severe vs. non-severe disease

AST, aspartate aminotransferase; ALT, alanine aminotransferase; TB, total bilirubin

Forest plot demonstrating (A) mean serum AST in severe vs. non-severe disease, (B) mean serum ALT in severe vs. non-severe disease, and (C) mean serum TB in severe vs. non-severe disease AST, aspartate aminotransferase; ALT, alanine aminotransferase; TB, total bilirubin The mean serum ALT level was also significantly higher for the severe group compared to the non-severe group (31 studies, MD 11.87 U/L, 95%CI 9.23-14.51 U/L; P<0.001; I2=95.5%) (Fig. 4B). The results were consistent on leave-one-out meta-analysis (MD 11.14-12.61 U/L) and subgroup analysis for severity based on respiratory distress (20 studies, MD 13.01 U/L, 95%CI 8.84-17.17 U/L; P<0.001; I2=96.7%), ICU admission (5 studies, MD 14.78 U/L, 95%CI 9.20-20.37 U/L; P<0.001; I2 = 83.7%), and death (3 studies, MD 6.56 U/L, 95%CI 3.00-10.13 U/L; P<0.001; I2=89.3%). On meta-regression, female proportions were inversely correlated with disease severity on the basis of mean ALT level (P=0.04). The mean serum TB level was evaluated in 26 studies and a significantly higher level was found in severe COVID-19 patients compared to the non-severe group (MD 2.08 mmol/L, 95%CI 1.36-2.80 mmol/L; P<0.001; I2=94.2%) (Fig. 4C). Consistent results were obtained using leave-one-out meta-analysis (MD 1.89-2.15 mmol/L) and subgroup analysis based on the severity criteria of ICU admission (5 studies, MD 2.91 mmol/L, 95%CI 1.24-4.58 mmol/L; P=0.001; I2=95.7%), death (3 studies, MD 2.92 mmol/L, 95%CI 1.20-4.64 mmol/L; P<0.001; I2=94.6%), and respiratory distress (14 studies, MD 1.62 mmol/L, 95%CI 0.92-2.33 mmol/L; P<0.001; I2=80.7%). On meta-regression, female proportions were inversely correlated with disease severity on the basis of mean TB level (P=0.03).

Risk of bias

Based on QUIPS tools, most of the studies (n=63) were at risk of bias for failing to account for confounders, while the remaining (n=20) accounted for some confounders. Twenty studies lacked details of the statistical design (Supplementary Table 2). Visible asymmetry was observed on a funnel plot based on the symptom of diarrhea; however, Egger’s regression did not reveal a significant publication bias (P=0.76) (Supplementary Fig. 1).

Discussion

Our meta-analysis demonstrated significant correlations between gastrointestinal parameters (diarrhea, elevated serum ALT, AST and TB) and severe disease outcomes, i.e., respiratory distress, ICU admission, and/or death. Although the most frequent manifestation of COVID-19 is pneumonia, gastrointestinal signs/symptoms are seen in a significant number of patients and can be the presenting manifestations of the disease [90]. A systematic review by Cheung et al reported diarrhea and nausea/vomiting in 13% and 10% of COVID-19 patients, respectively [91]. We demonstrated a similar prevalence of diarrhea (13%) and nausea/vomiting (9.5%). We believe that the reported prevalence of diarrhea and nausea/vomiting is somewhat lower than in reality, as some of these patients only present with these symptoms and may not undergo COVID-19 testing because they do not fulfill local hospital or laboratory criteria. The mechanism behind gastrointestinal symptoms is thought to be secondary to viral attachment and entry via angiotensin-converting enzyme 2 (ACE2), readily expressed in ileal and colonic epithelium [92]. This can explain symptoms such as diarrhea and nausea/vomiting. Furthermore, researchers have also identified viral RNA in the stool of patients infected with COVID-19, making diarrhea not only a marker for disease severity but a potential route of contagion [22]. Given the association of diarrhea with severe COVID-19 disease, based on our meta-analysis results, COVID-19 patients with diarrhea should be stratified into a high-risk group for developing severe disease as described above and managed accordingly. Admission symptoms and laboratory findings on admission Several mechanisms have been postulated to explain the hepatotoxicity seen in COVID-19 patients. One possible mechanism of hepatotoxicity of COVID-19 is immune system activation. It has been shown that many of the respiratory viruses, including COVID-19, lead to an activation of cytotoxic T cells and Kupffer cells in the liver that eventually damage hepatocytes [93]. Another mechanism is the triggering of a “cytokine storm,” leading to a massive surge in mediators such as interleukin-6, associated with sepsis, multiorgan dysfunction and death [8,94,95]. Direct viral entry through the intestines and invasion of the portal system and, subsequently, cholangiocytes, is another hypothesized mechanism [96]. Lastly, drug-induced hepatotoxicity should also be considered, as currently researchers are investigating all possible therapeutic options [97]. We demonstrated significantly increased elevation of ALT, AST and TB in patients with severe COVID-19 compared to non-severe patients, which can be attributed to some or all of the aforementioned mechanisms. Several limitations exist with our analysis. The most notable was the lack of high quality randomized controlled trials and cohort studies. We relied on data from observational studies that reported admission data. Observational studies have their own inherent biases that limit data interpretation, including selection, recall, and confounding bias. It is difficult to establish a temporal relation between cause and event using observational studies, as there is no follow up. However, as we reported admission data, we propose screening and risk-stratifying individuals, based on their admission laboratory findings and symptoms, into severe and non-severe categories. We were not able to account for factors such as comorbidities, timing of hospitalization and routine home medications. We were also not able to account for these related gastrointestinal symptoms due to lack of stratified data. Lastly, given that the major manifestations of COVID-19 are respiratory symptoms (cough, shortness of breath, sputum production) and fever, gastrointestinal symptoms may have been underreported. Despite the limitations, our analysis combines data from a large number of studies with a robust number of patients. We used admission data to avoid potential heterogeneity introduced by other factors, such as in-hospital medications, nosocomial infections, intubation, etc. The results of our study were consistent on both subgroup and sensitivity analysis. Furthermore, we provided subgroup prevalence based on region, i.e., Asia, Europe and North America where applicable. In conclusion, patients presenting with diarrhea or elevated ALT, AST and/or TB and diagnosed with COVID-19 should be stratified into a high-risk group for developing severe disease outcomes (i.e., respiratory distress, ICU admission, and/or death) and managed appropriately. What is already known: Gastrointestinal manifestations (diarrhea, nausea/vomiting, abnormal aspartate aminotransferase [AST], abnormal alanine aminotransferase[ALT], and abnormal total bilirubin [TB]) have been demonstrated in several studies in patients with COVID-19 A recent meta-analysis accounted for these manifestations in the form of pooled analysis What the new findings are: We performed a comprehensive systematic review and meta-analysis of the available literature through May 31st, 2020 to assess these manifestations with respect to disease severity Our results indicate that diarrhea, abnormal ALT, AST and TB were associated with severe disease (intensive care unit admission, respiratory distress, and/or mortality) Based on the current study results, patients with these manifestations should be stratified as high-risk and managed appropriately Click here for additional data file.
Table 2

Admission symptoms and laboratory findings on admission

  92 in total

1.  [Preliminary study of the relationship between novel coronavirus pneumonia and liver function damage: a multicenter study].

Authors:  C Liu; Z C Jiang; C X Shao; H G Zhang; H M Yue; Z H Chen; B Y Ma; W Y Liu; H H Huang; J Yang; Y Wang; H Y Liu; D Xu; J T Wang; J Y Yang; H Q Pan; S Q Zou; F J Li; J Q Lei; X Li; Q He; Y Gu; X L Qi
Journal:  Zhonghua Gan Zang Bing Za Zhi       Date:  2020-02-20

2.  [Clinical characteristics and outcomes of 112 cardiovascular disease patients infected by 2019-nCoV].

Authors:  Y D Peng; K Meng; H Q Guan; L Leng; R R Zhu; B Y Wang; M A He; L X Cheng; K Huang; Q T Zeng
Journal:  Zhonghua Xin Xue Guan Bing Za Zhi       Date:  2020-06-24

3.  Clinical and immunological features of severe and moderate coronavirus disease 2019.

Authors:  Guang Chen; Di Wu; Wei Guo; Yong Cao; Da Huang; Hongwu Wang; Tao Wang; Xiaoyun Zhang; Huilong Chen; Haijing Yu; Xiaoping Zhang; Minxia Zhang; Shiji Wu; Jianxin Song; Tao Chen; Meifang Han; Shusheng Li; Xiaoping Luo; Jianping Zhao; Qin Ning
Journal:  J Clin Invest       Date:  2020-05-01       Impact factor: 14.808

4.  The association of low serum albumin level with severe COVID-19: a systematic review and meta-analysis.

Authors:  Muhammad Aziz; Rawish Fatima; Wade Lee-Smith; Ragheb Assaly
Journal:  Crit Care       Date:  2020-05-26       Impact factor: 9.097

5.  Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study.

Authors:  Xin-Ying Zhao; Xuan-Xuan Xu; Hai-Sen Yin; Qin-Ming Hu; Tao Xiong; Yuan-Yan Tang; Ai-Ying Yang; Bao-Ping Yu; Zhi-Ping Huang
Journal:  BMC Infect Dis       Date:  2020-04-29       Impact factor: 3.090

6.  Taste Changes (Dysgeusia) in COVID-19: A Systematic Review and Meta-analysis.

Authors:  Muhammad Aziz; Abhilash Perisetti; Wade M Lee-Smith; Mahesh Gajendran; Pardeep Bansal; Hemant Goyal
Journal:  Gastroenterology       Date:  2020-05-05       Impact factor: 22.682

7.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

8.  Clinical characteristics and outcomes of patients with severe covid-19 with diabetes.

Authors:  Yongli Yan; Yan Yang; Fen Wang; Huihui Ren; Shujun Zhang; Xiaoli Shi; Xuefeng Yu; Kun Dong
Journal:  BMJ Open Diabetes Res Care       Date:  2020-04

9.  The clinical course and its correlated immune status in COVID-19 pneumonia.

Authors:  Ruyuan He; Zilong Lu; Lin Zhang; Tao Fan; Rui Xiong; Xiaokang Shen; Haojie Feng; Heng Meng; Weichen Lin; Wenyang Jiang; Qing Geng
Journal:  J Clin Virol       Date:  2020-04-12       Impact factor: 3.168

10.  Clinical Characteristics of Imported Cases of Coronavirus Disease 2019 (COVID-19) in Jiangsu Province: A Multicenter Descriptive Study.

Authors:  Jian Wu; Jun Liu; Xinguo Zhao; Chengyuan Liu; Wei Wang; Dawei Wang; Wei Xu; Chunyu Zhang; Jiong Yu; Bin Jiang; Hongcui Cao; Lanjuan Li
Journal:  Clin Infect Dis       Date:  2020-07-28       Impact factor: 9.079

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  13 in total

1.  Global research production pertaining to gastrointestinal involvement in COVID-19: A bibliometric and visualised study.

Authors:  Sa'ed H Zyoud; Samah W Al-Jabi; Moyad Jamal Shahwan; Ammar Abdulrahman Jairoun
Journal:  World J Gastrointest Surg       Date:  2022-05-27

Review 2.  Gastroenterological and hepatic manifestations of patients with COVID-19, prevalence, mortality by country, and intensive care admission rate: systematic review and meta-analysis.

Authors:  Mohammad Shehab; Fatema Alrashed; Sameera Shuaibi; Dhuha Alajmi; Alan Barkun
Journal:  BMJ Open Gastroenterol       Date:  2021-03

3.  Surveillance of COVID-19-Associated Multisystem Inflammatory Syndrome in Children, South Korea.

Authors:  Young June Choe; Eun Hwa Choi; Jong Woon Choi; Byung Wook Eun; Lucy Youngmin Eun; Yae-Jean Kim; Yeo Hyang Kim; Young A Kim; Yun-Kyung Kim; Ji Hee Kwak; Hyuk Min Lee; Hyunju Lee; Joon Kee Lee; June Dong Park; Eun-Jin Kim; Young Joon Park; Jin Gwack; Sang Won Lee
Journal:  Emerg Infect Dis       Date:  2021-02-04       Impact factor: 6.883

4.  Blood Hemoglobin Substantially Modulates the Impact of Gender, Morbid Obesity, and Hyperglycemia on COVID-19 Death Risk: A Multicenter Study in Italy and Spain.

Authors:  Jordi Mayneris-Perxachs; Maria Francesca Russo; Rafel Ramos; Ana de Hollanda; Arola Armengou Arxé; Matteo Rottoli; María Arnoriaga-Rodríguez; Marc Comas-Cufí; Michele Bartoletti; Ornella Verrastro; Carlota Gudiol; Ester Fages; Marga Giménez; Ariadna de Genover Gil; Paolo Bernante; Francisco Tinahones; Jordi Carratalà; Uberto Pagotto; Ildefonso Hernández-Aguado; Fernando Fernández-Aranda; Fernanda Meira; Antoni Castro Guardiola; Geltrude Mingrone; José Manuel Fernández-Real
Journal:  Front Endocrinol (Lausanne)       Date:  2021-11-02       Impact factor: 5.555

5.  Relationship Between Body Composition and Death in Patients with COVID-19 Differs Based on the Presence of Gastrointestinal Symptoms.

Authors:  Yael R Nobel; Steven H Su; Michaela R Anderson; Lyndon Luk; Jennifer L Small-Saunders; Gissette Reyes-Soffer; Dympna Gallagher; Daniel E Freedberg
Journal:  Dig Dis Sci       Date:  2021-11-24       Impact factor: 3.487

6.  Frequency and Impact of Preadmission Digestive Symptoms on Outcome in Severe COVID-19: A Prospective Observational Cohort Study.

Authors:  Sunaina Tejpal Karna; Pooja Singh; Gouroumourty Revadi; Alkesh Khurana; Aishwary Shivhare; Saurabh Saigal; Manoj Kumar Rathiswamy; Jai Prakash Sharma; Vaishali Waindeskar
Journal:  Indian J Crit Care Med       Date:  2021-11

7.  A machine learning approach for identification of gastrointestinal predictors for the risk of COVID-19 related hospitalization.

Authors:  Peter Lipták; Peter Banovcin; Róbert Rosoľanka; Michal Prokopič; Ivan Kocan; Ivana Žiačiková; Peter Uhrik; Marian Grendar; Rudolf Hyrdel
Journal:  PeerJ       Date:  2022-03-21       Impact factor: 2.984

Review 8.  Progression and Trends in Virus from Influenza A to COVID-19: An Overview of Recent Studies.

Authors:  Hakimeh Baghaei Daemi; Muhammad Fakhar-E-Alam Kulyar; Xinlin He; Chengfei Li; Morteza Karimpour; Xiaomei Sun; Zhong Zou; Meilin Jin
Journal:  Viruses       Date:  2021-06-15       Impact factor: 5.048

Review 9.  COVID-19 Pandemic and Periodontal Practice: The Immunological, Clinical, and Economic Points of View.

Authors:  Meshkat Naeimi Darestani; Amir Akbari; Siamak Yaghobee; Mina Taheri; Solmaz Akbari
Journal:  Biomed Res Int       Date:  2022-01-13       Impact factor: 3.411

Review 10.  [COVID-19 patients in Germany: exposure risks and associated factors for hospitalization and severe disease].

Authors:  Uwe Koppe; Hendrik Wilking; Thomas Harder; Walter Haas; Ute Rexroth; Osamah Hamouda
Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz       Date:  2021-07-29       Impact factor: 1.513

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