Background: A meta-analysis was performed to evaluate the association of chronic kidney disease (CKD) and acute kidney injury (AKI) with the clinical prognosis of patients with coronavirus disease 2019 (COVID-19). Methods: The PubMed, EMBASE, Cochrane Library, medRxiv, Social Science Research Network, and Research Square databases (from December 1, 2019 to May 15, 2020) were searched to identify studies that reported the associations of CKD/AKI and disease severity/mortality. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated and meta-regression was performed. Results: In total, 42 studies enrolling 8,932 participants were included in this meta-analysis. The quality of most included studies was moderate to high. Compared with patients without previously diagnosed CKD, those with CKD had a significantly increased risk of progressing to a severe condition (OR 2.31, 95% CI 1.64–3.24) or death (OR 5.11, 95% CI 3.36–7.77). Similarly, compared with patients without AKI, those with AKI had a significantly increased risk of progressing to a severe condition (OR 11.88, 95% CI 9.29–15.19) or death (OR 30.46, 95% CI 18.33–50.59). Compared with patients with previously diagnosed CKD, those with AKI were more likely to progress to a severe condition (pgroup < 0.001, I2 = 98.3%) and even to death (pgroup < 0.001, I2 = 96.5%). Age had a significant impact on the association between CKD and disease severity (p = 0.001) but had no impact on the associations between AKI and disease severity (p = 0.80), between CKD and mortality (p = 0.51), or between AKI and mortality (p = 0.86). Four important complications (cardiac injury, shock, acute respiratory distress syndrome, and liver injury) did not significantly affect the associations between CKD/AKI and disease severity/mortality, indicating that CKD/AKI may be independent clinical prognostic indicators for patients with COVID-19. Conclusions: In COVID-19 patients, CKD/AKI was associated with worse outcomes compared with those without CKD/AKI. AKI was associated with higher risks of severity and mortality than CKD.

Since December 2019, a severe pneumonia outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly around the world [1]. On February 11, 2020 the World Health Organization declared the name of the pandemic condition to be coronavirus disease 2019 (COVID-19).

In patients with severe COVID-19, the infection may rapidly progress to hypoxemia, septic shock, acute respiratory distress syndrome (ARDS), need for intensive care unit (ICU) care, and even death. Recently, several reports have revealed that comorbidities or other conditions can affect the clinical progression of patients with COVID-19 [2, 3]. Several meta-analyses have demonstrated the impact of diabetes [4], cardiac injury [5, 6], and chronic obstructive pulmonary disease and smoking [7] on the clinical progression of patients with COVID-19.

A meta-analysis reported that the incidence of acute kidney injury (AKI) was estimated to be 3% in hospitalized patients with COVID-19, while this incidence was increased to 19% in patients admitted to an ICU [8]. Serum creatinine levels ≥133 μmol/L were reported to be associated with disease severity in a meta-analysis (three studies enrolling 979 patients) [9]. Another meta-analysis (three studies enrolling 944 patients) reported that AKI was associated with a higher risk of mortality [10]. However, the number of studies included in these published meta-analyses was relatively small. During the past half year, numerous new studies evaluating the association of chronic kidney disease (CKD)/AKI and disease severity/mortality have been published. Therefore, a systematic review of the accumulated evidence with the aim of providing an up-to-date assessment of the association between kidney impairment (CKD/AKI) and clinical prognosis (disease severity/mortality) in patients with COVID-19 is important.

Literature Search

This meta-analysis was performed in accordance with the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) method [11]. The MOOSE checklist is provided in online supplementary Table S1 (for all online suppl. material, see www.karger.com/doi/10.1159/000512211). The databases (MEDLINE, Embase, and Cochrane Library) were systematically searched for eligible published studies, with the medRxiv, Social Science Research Network, and Research Square websites searched for eligible unpublished studies from December 1, 2019 to May 15, 2020. The key words “COVID-19,” “2019 novel coronavirus infection,” “coronavirus disease 2019,” “coronavirus,” “SARS-CoV-2,” “2019-nCoV,” “mortality,” “severe,” “survival,” “outcomes,” “prognosis,” “chronic kidney disease,” “acute renal failure,” “acute kidney injury,” and “renal replacement therapy” were used in various combinations.

Study Eligibility Criteria

After candidate articles had been collected, further selection was conducted according to the following inclusion criteria: (1) Adult patients. (2) The numbers of patients who were diagnosed with CKD or AKI were reported or could be calculated. In the absence of explicit definitions of CKD or AKI in the included studies, patients with high serum creatinine before or on admission were considered to be diagnosed with CKD (meeting the diagnostic criteria of the Kidney Disease: Improving Global Outcomes [KDIGO] guidelines) [12], while patients who had an increase in serum creatinine (meeting the diagnostic criteria of the KDIGO guidelines [12]) after SARS-CoV-2 infection were considered to have AKI. The definition of AKI was the same as that in the KDIGO guidelines. Patients with both preexisting CKD before infection and an increase in serum creatinine after infection were still considered to be diagnosed with CKD, but not AKI, during data extraction and synthesis. (3) The primary outcomes were disease severity and mortality. Diagnosis of the severe cases was defined by the authors in each individual study. Most of the included studies defined severe cases as ICU admission, mechanical ventilation, or both. In the absence of an explicit definition of severe cases, the guidelines for the diagnosis and treatment of SARS-CoV-2 issued by the National Health Commission of China (sixth edition) were used [13]. In detail, severe cases were defined as patients with dyspnea, respiratory rate ≥30/min, blood oxygen saturation ≤93%, partial pressure of arterial oxygen to fraction of inspired oxygen ratio <300, lung infiltrates >50% within 24–48 h, or needing ICU care. (4) The patients were to be consecutively confirmed and enrolled. The studies were in the following cases: (1) reviews, editorials, conference abstracts, systematic reviews, and meta-analyses; (2) children <18 years old; (3) insufficient data provided to explore the associations between kidney impairment and the clinical outcomes; (4) repeated or updated reports containing or overlapping with the same group of participants.

Data Extraction and Quality Assessment

The extracted data included publication status, study type, regions/countries, enrollment hospitals and departments, enrollment periods, numbers of patients, age, sex, complications (cardiac injury, ARDS, shock, and liver injury), and treatment strategies. Quality assessment of the studies was conducted using the Newcastle-Ottawa Scale (NOS) for all included studies [14]. Eight different domains, including selection bias (adequate case definition, representativeness of the cases, selection of controls, and definition of controls), comparability (comparability of cases and controls on the basis of the design or analysis), and exposure (ascertainment of exposure, same method of ascertainment for cases and controls, and reports of nonresponse rate) were assessed. The total scores for each included study ranged from 0 to 10 points. These scores were chosen a priori to simplify description for the present review.

Data Synthesis and Statistical Analysis

Dichotomous variables were expressed as odds ratio (OR) and 95% confidence interval (CI). Heterogeneity was assessed using the Q test and quantified using the I2 statistic [15]. The threshold p value of heterogeneity was 0.10. I2 statistics <25%, 25–49%, 50–75%, and >75% were interpreted to indicate low, medium, high, and very high levels of heterogeneity, respectively. If the I2 value was <50%, the fixed-effect model was used. Otherwise, the random-effects model was used. For subgroup difference analysis, the I2 value indicated the percentage of the variability in effect estimates from the different subgroups that is due to genuine subgroup differences rather than sampling error. Publication bias was explored using a funnel plot if more than 10 studies were included. Subgroup analyses were performed to evaluate whether the results differed according to the location of the studies (Wuhan city or non-Wuhan regions) and the publication status (published or unpublished). Meta-regression was performed to investigate the effects of age and complications such as cardiac injury, ARDS, shock, and liver injury on the relationship between kidney impairment and clinical prognosis. The Review Manager (version 5.3, The Cochrane Collaboration) software was used for data synthesis and publication bias. The STATA 14.0 (StataCorp, College Station, TX, USA) software was used for meta-regression. The searching and selection of the studies, data extraction and quality assessment, data synthesis, and statistical analysis were performed independently by two of the researchers (B. Wang and Q. Luo), and any discrepancies were resolved by consulting a third investigator (Y. Chen).

Literature Search Results

A total of 1,724 papers were screened, and finally 42 studies with 8,932 participants were included in this meta-analysis. Eighteen of the 42 studies were published [16-33], and the remaining 24 studies were rapidly posted on the medRxiv, Social Science Research Network, and Research Square websites without peer review [34-57]. A flow diagram outlining the literature search process is provided in Figure 1. The characteristics of the included studies are presented in Table 1. The median number of participants was 147 (range 16–1,000). Twelve studies used mortality as the primary outcome, 29 studies used disease severity as the primary outcome, and 1 study used both disease severity and mortality as the primary outcomes. Five studies were performed outside China (2 in the United States [16, 38], 1 in Italy [20], 1 in Switzerland [56], and 1 in Saudi Arabia [40]). The remaining 37 studies were conducted in China (22 in Wuhan City and 15 in non-Wuhan regions). In the studies conducted in China and Saudi Arabia, severe disease was defined by the National Health Commission of China criteria [13]. In the Italian study, severe disease was defined as a requirement for high-flow oxygen support. In the study conducted in Switzerland, severe disease was defined as the requirement for mechanical ventilation. For the studies conducted in the United States, severe disease was defined as the need for mechanical ventilation or ICU admission. Twenty-two of the included studies were performed in Wuhan city. Among them, 2 studies were conducted in two different departments with different enrollment periods (surgery department until December 31 [21] and respiratory department from December 26 to January 31 [52]) in the same hospital (Wuhan Jinyintan Hospital). Two studies were conducted in two different departments with overlapping enrollment periods (respiratory department from January 1 to February 15 [53] and infectious disease department from January 16 to February 3 [30]) in the same hospital (Seventh Hospital of Wuhan City). Three studies were conducted in three different departments with similar enrollment periods (infectious disease department from January 13 to February 12 [19], neurology department from January 10 to February 12 [22], and endocrinology department from January 10 to February 24 [28]) in the same hospital (Wuhan Tongji Hospital). Four studies were conducted in three different departments with similar enrollment periods (ICU department from January 1 to January 28 [26], ICU department until February 10 [27], cardiology department from January 3 to February 1 [17], and respiratory department from January 2 to February 10 [29]) in the same hospital (Wuhan University Zhongnan Hospital). The remaining 11 studies were conducted in different hospitals.

Table 1.

Characteristics of the studies included in this meta-analysis

Characteristics of the studies included in this meta-analysis
Characteristics of the studies included in this meta-analysis
Fig. 1.

Flow diagram of search strategy and study selection. SSRN, Social Science Research Network.

Fig. 1.

Flow diagram of search strategy and study selection. SSRN, Social Science Research Network.

Close modal

Quality Assessment Results

Twenty-eight studies had NOS points ranging from 6 to 7 (13 studies scored 6 points and 15 studies scored 7 points), 14 studies had NOS points >7 (8 studies scored 8 points and 6 studies scored 9 points), and no included study had <6 points (online suppl. Table S2).

The Association of Previously Diagnosed CKD or AKI with Disease Severity

A total of 27 studies with 5,155 patients reported an association between previously diagnosed CKD and disease severity (Fig. 2A). The overall prevalence of CKD was 3.03% (155/5,115) in all included studies. Compared with COVID-19 patients without previously diagnosed CKD, those with previously diagnosed CKD had a significantly increased risk of progressing to a severe condition (OR = 2.31, 95% CI 1.64–3.24, p < 0.001, I2 = 13%, pheterogeneity = 0.27). Eighteen studies with 3,850 patients reported an association between AKI and disease severity (Fig. 2A). The overall incidence of AKI was 14.68% (565/3,850) in all included studies. Compared with COVID-19 patients without AKI, those with AKI had a significantly increased risk of progressing to a severe condition (OR = 11.88, 95% CI 9.29–15.19, p < 0.001, I2 = 0%, pheterogeneity = 0.55). Subgroup analysis indicated that patients with AKI were more likely to progress to a severe condition compared with patients with previously diagnosed CKD, which was demonstrated by the significant difference between the AKI and CKD groups (AKI vs. CKD: OR = 11.88, 95% CI 9.29–15.19 vs. OR = 2.31, 95% CI 1.64–3.24; pgroup < 0.001, I2 = 98.3%) (Fig. 2A). The funnel plots indicated no publication bias for the associations of CKD/AKI with disease severity (Fig. 2B, C).

Fig. 2.

Association between CKD/AKI and disease severity in patients with COVID-19. A Forest plot analyzing the association of CKD/AKI with disease severity in patients with COVID-19. B Funnel plot analyzing the publication bias in the association of CKD with disease severity. C Funnel plot analyzing the publication bias in the association of AKI with disease severity. AKI, acute kidney injury; CKD, chronic kidney disease; COVID-19, coronavirus disease 2019.

Fig. 2.

Association between CKD/AKI and disease severity in patients with COVID-19. A Forest plot analyzing the association of CKD/AKI with disease severity in patients with COVID-19. B Funnel plot analyzing the publication bias in the association of CKD with disease severity. C Funnel plot analyzing the publication bias in the association of AKI with disease severity. AKI, acute kidney injury; CKD, chronic kidney disease; COVID-19, coronavirus disease 2019.

Close modal

Subgroup analyses indicated that the publication status did not significantly affect the associations between CKD/AKI and disease severity (CKD: published vs. unpublished studies: OR = 2.41, 95% CI 1.36–4.30 vs. OR = 2.25, 95% CI 1.47–3.43, psubgroup = 0.84, I2 = 0%; AKI: published vs. unpublished studies: OR = 6.53, 95% CI 3.02–14.11 vs. OR = 12.74, 95% CI 9.82–16.52, psubgroup = 0.11, I2 = 61.5%) (online suppl. Fig. S1A, S1B). Similarly, subgroup analyses revealed that the geographic region did not significantly affect the associations of CKD/AKI with disease severity (CKD: Wuhan City vs. non-Wuhan regions: OR = 2.40, 95% CI 1.43–4.01 vs. OR = 2.23, 95% CI 1.41–3.51, psubgroup = 0.83, I2 = 0%; AKI: OR = 11.67, 95% CI 6.90–19.73 vs. OR = 11.95, 95% CI 9.06–15.77, psubgroup = 0.94, I2 = 0%) (online suppl. Fig. S2A, S2B). Neither the publication status nor the geographic region had an influence on the associations of CKD/AKI with disease severity.

The Association of Previously Diagnosed CKD or AKI with Disease Mortality

Eleven studies with 2,140 participants reported an association between previously diagnosed CKD and disease mortality (Fig. 3A). The overall prevalence of CKD was 6.73% (144/2,140) in all included studies. Compared with COVID-19 patients without previously diagnosed CKD, those with previously diagnosed CKD had a significantly increased risk of death (OR = 5.11, 95% CI 3.36–7.77, p < 0.001, I2 = 0%, pheterogeneity = 0.68). Six studies with 1,220 patients reported an association between AKI and disease mortality. The incidence of AKI was 13.28% (162/1,220) in all included studies. Compared with COVID-19 patients without AKI, those with AKI had a significantly increased risk of death, with medium heterogeneity (OR = 30.46, 95% CI 18.33–50.59, p < 0.001, I2 = 42%, pheterogeneity = 0.12) (Fig. 3A). Subgroup analysis indicated that patients with AKI were more likely to die than patients with previously diagnosed CKD, which was demonstrated by the significant difference between the AKI and CKD groups (AKI vs. CKD: OR = 30.46, 95% CI 18.33–50.59 vs. OR = 5.11, 95% CI 3.36–7.77, pgroup < 0.001, I2 = 96.5%) (Fig. 3A). The funnel plot indicated no publication bias for the associations of CKD with disease mortality (Fig. 3B). Publication bias was not explored for the association of AKI and mortality because the number of included studies was <10.

Fig. 3.

Association between CKD/AKI and disease mortality in patients with COVID-19. A Forest plot analyzing the association of CKD/AKI with disease mortality in patients with COVID-19. B Funnel plot analyzing the publication bias in the association of CKD and disease mortality. AKI, acute kidney injury; CKD, chronic kidney disease; COVID-19, coronavirus disease 2019.

Fig. 3.

Association between CKD/AKI and disease mortality in patients with COVID-19. A Forest plot analyzing the association of CKD/AKI with disease mortality in patients with COVID-19. B Funnel plot analyzing the publication bias in the association of CKD and disease mortality. AKI, acute kidney injury; CKD, chronic kidney disease; COVID-19, coronavirus disease 2019.

Close modal

Subgroup analysis indicated that the publication status did not significantly affect the association between CKD and disease mortality (published vs. unpublished studies: OR = 4.77, 95% CI 1.93–11.77 vs. OR = 5.21, 95% CI 3.25–8.36, psubgroup = 0.87, I2 = 0%) (online suppl. Fig. S3A). However, subgroup analysis revealed that the publication status had a significant impact on the association of AKI with disease mortality (published vs. unpublished studies: OR = 86.13, 95% CI 25.26–293.68 vs. OR = 18.61, 95% CI 10.49–33.02, psubgroup = 0.03, I2 = 79.7%) (online suppl. Fig. S3B). The subgroup analyses to explore the impact of geographic region on the association of CKD/AKI with disease mortality were not performed because all the included studies were conducted in Wuhan City.

The Impact of Age and Complications on the Association between Kidney Impairment and Clinical Prognosis

Meta-regression analysis indicated that age had a significant impact on the association between CKD and disease severity (p = 0.001) (Fig. 4A). However, meta-regression analyses indicated that age did not significantly affect the associations between AKI and disease severity (p = 0.80) (Fig. 4B), between CKD and mortality (p = 0.51) (Fig. 4C), or between AKI and mortality (p = 0.86) (Fig. 4D). Meta-regression analyses indicated that four important complications (cardiac injury, shock, ARDS, and liver injury) did not significantly affect the associations between CKD/AKI and disease severity/mortality (Table 2).

Table 2.

Meta-regression analyzing the impact of complications on the association between kidney injury and clinical prognosis

Meta-regression analyzing the impact of complications on the association between kidney injury and clinical prognosis
Meta-regression analyzing the impact of complications on the association between kidney injury and clinical prognosis
Fig. 4.

Meta-regression investigating the impact of age on the association between CKD/AKI and clinical prognosis. A Impact of age on the association between CKD and disease severity. B Impact of age on the association between AKI and disease severity. C Impact of age on the association between CKD and mortality. D Impact of age on the association between AKI and mortality. AKI, acute kidney injury; CKD, chronic kidney disease.

Fig. 4.

Meta-regression investigating the impact of age on the association between CKD/AKI and clinical prognosis. A Impact of age on the association between CKD and disease severity. B Impact of age on the association between AKI and disease severity. C Impact of age on the association between CKD and mortality. D Impact of age on the association between AKI and mortality. AKI, acute kidney injury; CKD, chronic kidney disease.

Close modal

We provide an up-to-date analysis of the evidence regarding the associations of CKD/AKI with clinical prognosis in patients with COVID-19 (42 studies with 8,932 patients). We demonstrated that COVID-19 patients with previously diagnosed CKD or AKI had significantly increased risks of progression to a severe condition and even death. Compared with patients with previously diagnosed CKD before SARS-CoV-2 infection, patients with AKI after SARS-CoV-2 infection were more likely to progress to a severe condition or death.

Since the outbreak of the COVID-19 epidemic, several meta-analyses concerning kidney impairment and clinical prognosis have been published. Ng et al. [8] reported that the overall risk of AKI in hospitalized patients was 3% and that this risk increased to 19% when patients were admitted to an ICU. Zheng et al. [9] found that serum creatinine could impact the risk of progression of COVID-19. Ali et al. [10] revealed that severe AKI was associated with a higher risk of mortality (relative risk = 3.08, 95% CI 1.54–6.19). Potere et al. [58] reported that the incidence of AKI was 6% in hospitalized patients. Lim et al. [59] demonstrated that AKI was associated with increased mortality, severe condition, and the need for ICU care. In our study, we demonstrated that not only previously diagnosed CKD but also AKI significantly affected the disease severity and mortality of COVID-19. We also found that AKI was associated with a more severe condition and a higher risk of mortality than CKD. Four major complications (cardiac injury, ARDS, shock, and liver injury) did not participate substantially in the associations between CKD/AKI and clinical prognoses, indicating that kidney impairment may be an independent clinical prognostic indicator for these patients.

The reason why COVID-19 patients with CKD comorbidity exhibited an increased risk of progression to a severe condition or death has not been fully elucidated to date. Plausible explanations are as follows: (1) Patients with CKD have a proinflammatory milieu and functional defects in innate and adaptive immune cell populations [60]. In a community-based cohort of nearly 10,000 adult individuals, reduced glomerular filtration rate and elevated albumin-creatinine ratios were associated with a higher risk of hospitalization, with infection and subsequent mortality [61]. (2) Patients with CKD have a high risk of upper respiratory tract infection and pneumonia [62, 63], which may become important concurrent infections with SARS-CoV-2. (3) CKD frequently coexists with comorbidities, especially diabetes and cardiovascular disease, which are also known to be associated with worse outcomes in patients with COVID-19 [9]. (4) CKD prevalence rises with age, and the burden of COVID-19 morbidity and mortality is heavily concentrated in older age groups. An important limitation of the present study is that we were unable to determine the extent to which age and comorbidities independently contribute to poor outcomes in patients with CKD.

AKI is a syndrome of abrupt loss of kidney function that is strongly associated with increased mortality and morbidity in several conditions [64]. There is a high incidence of AKI in patients with COVID-19, especially in the cohort with severe disease [46, 49, 65]. The following reasons have been postulated to explain why an increased incidence of AKI occurs after SARS-CoV-2 infection: (1) The severity of the disease may be associated with an increase in the initial renal viral load or severe systemic inflammation, or both. SARS-CoV-2 can penetrate cells via two receptors – angiotensin-converting enzyme 2 (ACE2) and transmembrane protease, serine 2 (TMPRSS2) [66] –, and ACE2 is highly expressed in proximal tubular epithelial cells and in podocytes. Nine of 26 autopsied Chinese patients with AKI after SARS-CoV-2 infection had diffuse proximal tubular injury, with some frank necrosis and no glomerular injury [67]. (2) The fever, vomiting, diarrhea, and shock often observed with SARS-CoV-2 infection can cause kidney hypoperfusion. These reasons may cooperatively contribute to an increased risk of AKI. Additionally, COVID-19 patients with severe conditions also have complications involving various organ dysfunctions, which may in turn lead to AKI.

This meta-analysis has several limitations: (1) Twenty-two of the included studies were from Wuhan, China, and although it is unlikely that the same patients were included in multiple studies, the low heterogeneity in the outcome of our study may be attributable to the fact that these patients from the same region with similar genetic background were infected by the same strain of SARS-CoV-2 virus in similar periods. This may limit generalizability, although subgroup analysis showed that the as-sociation with CKD/AKI and disease severity was con-sistent between studies from China and outside China. (2) Half of the included studies were posted on academic websites and were not peer-reviewed, and subgroup analysis demonstrated that the impact of AKI on the mortality in published studies was significantly higher than that in unpublished studies. This significant subgroup difference indicated the existence of publication bias. (3) The comparability of the baseline characteristics between the two groups (severe/nonsevere, survivors/deaths) was not well matched in a majority of studies, indicating that residual confounding is likely.

In conclusion, not only previously diagnosed CKD before SARS-CoV-2 infection, but also AKI after SARS-CoV-2 infection were associated with disease severity and mortality. AKI had a higher risk of disease progression and death compared with CKD.

We would like to acknowledge Victoria Muir, PhD, from Liwen Bianji, Edanz Group China (www.liwenbianji.cn/ac) for editing the English text of the manuscript.

Our study adhered to the MOOSE guidelines [11]. Institutional approval and patient consent were not necessary.

The authors have no conflicts of interest to declare.

This study was funded by the Specialized Scientific Program of the Hainan Province Academician Innovation Platform (YSPTZX202026).

B. Wang, Q. Luo, Y. Chen, and Xiangmei Chen designed the study, with input into the study protocol from all authors. B. Wang, Q. Luo, and Y. Chen searched the literature and extracted the data. W. Zhang and S. Yu performed the statistical analyses. Xiaowei Cheng and L. Wang contributed to the discussion section. B. Wang and Q. Luo drafted the manuscript. Y. Chen and Xiangmei Chen supervised the study and provided critical revision to the intellectual content. All authors contributed to the interpretation of the data and approved the final version.

1.
Calisher
C
,
Carroll
D
,
Colwell
R
,
Corley
RB
,
Daszak
P
,
Drosten
C
, et al
Statement in support of the scientists, public health professionals, and medical professionals of China combatting COVID-19
.
Lancet
.
2020
Mar
;
395
(
10226
):
e42
3
.
[PubMed]
0140-6736
2.
Renu
K
,
Prasanna
PL
,
Valsala Gopalakrishnan
A
.
Coronaviruses pathogenesis, comorbidities and multi-organ damage - A review
.
Life Sci
.
2020
Aug
;
255
:
117839
.
[PubMed]
0024-3205
3.
Petrilli
CM
,
Jones
SA
,
Yang
J
,
Rajagopalan
H
,
O’Donnell
L
,
Chernyak
Y
, et al
Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study
.
BMJ
.
2020
May
;
369
:
m1966
.
[PubMed]
0959-8138
4.
Huang
I
,
Lim
MA
,
Pranata
R
.
Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia - A systematic review, meta-analysis, and meta-regression
.
Diabetes Metab Syndr
.
2020
Jul - Aug
;
14
(
4
):
395
403
.
[PubMed]
1871-4021
5.
Santoso
A
,
Pranata
R
,
Wibowo
A
,
Al-Farabi
MJ
,
Huang
I
,
Antariksa
B
. Cardiac injury is associated with mortality and critically ill pneumonia in COVID-19: A meta-analysis [published online ahead of print April 19, 2020]. Am J Emerg Med.
2020
Apr
; S0735-6757(20)30280-1.
6.
Aggarwal
G
,
Cheruiyot
I
,
Aggarwal
S
,
Wong
J
,
Lippi
G
,
Lavie
CJ
, et al
Association of Cardiovascular Disease With Coronavirus Disease 2019 (COVID-19) Severity: A Meta-Analysis
.
Curr Probl Cardiol
.
2020
Aug
;
45
(
8
):
100617
.
[PubMed]
0146-2806
7.
Zhao
Q
,
Meng
M
,
Kumar
R
,
Wu
Y
,
Huang
J
,
Lian
N
, et al
The impact of COPD and smoking history on the severity of COVID-19: A systemic review and meta-analysis
.
J Med Virol
.
2020
Apr
;
92
(
10
):
1915
21
.
[PubMed]
0146-6615
8.
Ng
JJ
,
Luo
Y
,
Phua
K
,
Choong
AM
.
Acute kidney injury in hospitalized patients with coronavirus disease
.
2019
(COVID-19): A meta-analysis. J Infect. 2020 May; S0163-4453(20)30280-2.
9.
Zheng
Z
,
Peng
F
,
Xu
B
,
Zhao
J
,
Liu
H
,
Peng
J
, et al
Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis
.
J Infect
.
2020
Aug
;
81
(
2
):
e16
25
.
[PubMed]
0163-4453
10.
Ali
H
,
Daoud
A
,
Mohamed
MM
,
Salim
SA
,
Yessayan
L
,
Baharani
J
, et al
Survival rate in acute kidney injury superimposed COVID-19 patients: a systematic review and meta-analysis
.
Ren Fail
.
2020
Nov
;
42
(
1
):
393
7
.
[PubMed]
0886-022X
11.
Stroup
DF
,
Berlin
JA
,
Morton
SC
,
Olkin
I
,
Williamson
GD
,
Rennie
D
, et al
Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group
.
JAMA
.
2000
Apr
;
283
(
15
):
2008
12
.
[PubMed]
0098-7484
12.
Levey
AS
,
Eckardt
KU
,
Dorman
NM
,
Christiansen
SL
,
Hoorn
EJ
,
Ingelfinger
JR
, et al
Nomenclature for kidney function and disease: report of a Kidney Disease: Improving Global Outcomes (KDIGO) Consensus Conference
.
Kidney Int
.
2020
Jun
;
97
(
6
):
1117
29
.
[PubMed]
0085-2538
13.
National Health and Family Planning Commission of the People’s Republic of China
. Guideline for Diagnosis and Treatment of SARS-CoV-2 (the sixth edition). http://www.nhc.gov.cn/yzygj/s7653p/202002/8334a8326dd94d329df351d7da8aefc2.shtml (accessed Feb 19, 2020).
14.
Stang
A
.
Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses
.
Eur J Epidemiol
.
2010
Sep
;
25
(
9
):
603
5
.
[PubMed]
0393-2990
15.
Higgins
JP
,
Green
S
. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration. http://www.cochrane-handbook.org (accessed May 15, 2020).
16.
Aggarwal
S
,
Garcia-Telles
N
,
Aggarwal
G
,
Lavie
C
,
Lippi
G
,
Henry
BM
.
Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): early report from the United States
.
Diagnosis (Berl)
.
2020
May
;
7
(
2
):
91
6
.
[PubMed]
2194-8011
17.
Cao
J
,
Tu
WJ
,
Cheng
W
,
Yu
L
,
Liu
YK
,
Hu
X
, et al
Clinical Features and Short-term Outcomes of 102 Patients with Coronavirus Disease 2019 in Wuhan, China
.
Clin Infect Dis
.
2020
Jul
;
71
(
15
):
748
55
.
[PubMed]
1058-4838
18.
Chen
Q
,
Zheng
Z
,
Zhang
C
,
Zhang
X
,
Wu
H
,
Wang
J
, et al
Clinical characteristics of 145 patients with corona virus disease 2019 (COVID-19) in Taizhou, Zhejiang, China
.
Infection
.
2020
Aug
;
48
(
4
):
543
51
.
[PubMed]
0300-8126
19.
Chen
T
,
Wu
D
,
Chen
H
,
Yan
W
,
Yang
D
,
Chen
G
, et al
Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study
.
BMJ
.
2020
Mar
;
368
:
m1091
.
[PubMed]
0959-8138
20.
Colaneri
M
,
Sacchi
P
,
Zuccaro
V
,
Biscarini
S
,
Sachs
M
,
Roda
S
, et al;
COVID19 IRCCS San Matteo Pavia Task Force
.
Clinical characteristics of coronavirus disease (COVID-19) early findings from a teaching hospital in Pavia, North Italy, 21 to 28 February 2020
.
Euro Surveill
.
2020
Apr
;
25
(
16
):
2000460
.
[PubMed]
1025-496X
21.
Huang
C
,
Wang
Y
,
Li
X
,
Ren
L
,
Zhao
J
,
Hu
Y
, et al
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
.
Lancet
.
2020
Feb
;
395
(
10223
):
497
506
.
[PubMed]
0140-6736
22.
Qin
C
,
Zhou
L
,
Hu
Z
,
Zhang
S
,
Yang
S
,
Tao
Y
, et al
Dysregulation of immune response in patients with COVID-19 in Wuhan, China
.
Clin Infect Dis
.
2020
Jul
;
71
(
15
):
762
8
.
[PubMed]
1058-4838
23.
Shi
Y
,
Yu
X
,
Zhao
H
,
Wang
H
,
Zhao
R
,
Sheng
J
.
Host susceptibility to severe COVID-19 and establishment of a host risk score: findings of 487 cases outside Wuhan
.
Crit Care
.
2020
Mar
;
24
(
1
):
108
.
[PubMed]
1364-8535
24.
Sun
L
,
Shen
L
,
Fan
J
,
Gu
F
,
Hu
M
,
An
Y
, et al
Clinical features of patients with coronavirus disease 2019 from a designated hospital in Beijing, China
.
J Med Virol
.
2020
May
;
92
(
10
):
2055
66
.
[PubMed]
0146-6615
25.
Wan
S
,
Xiang
Y
,
Fang
W
,
Zheng
Y
,
Li
B
,
Hu
Y
, et al
Clinical features and treatment of COVID-19 patients in northeast Chongqing
.
J Med Virol
.
2020
Jul
;
92
(
7
):
797
806
.
[PubMed]
0146-6615
26.
Wang
D
,
Hu
B
,
Hu
C
,
Zhu
F
,
Liu
X
,
Zhang
J
, et al
Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China
.
JAMA
.
2020
Mar
;
323
(
11
):
1061
9
.
[PubMed]
0098-7484
27.
Wang
D
,
Yin
Y
,
Hu
C
,
Liu
X
,
Zhang
X
,
Zhou
S
, et al
Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan, China
.
Crit Care
.
2020
Apr
;
24
(
1
):
188
.
[PubMed]
1364-8535
28.
Yan
Y
,
Yang
Y
,
Wang
F
,
Ren
H
,
Zhang
S
,
Shi
X
, et al
Clinical characteristics and outcomes of patients with severe covid-19 with diabetes
.
BMJ Open Diabetes Res Care
.
2020
Apr
;
8
(
1
):
e001343
.
[PubMed]
2052-4897
29.
Zhang
G
,
Hu
C
,
Luo
L
,
Fang
F
,
Chen
Y
,
Li
J
, et al
Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China
.
J Clin Virol
.
2020
Jun
;
127
:
104364
.
[PubMed]
1386-6532
30.
Zhang
JJ
,
Dong
X
,
Cao
YY
,
Yuan
YD
,
Yang
YB
,
Yan
YQ
, et al
Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China
.
Allergy
.
2020
Jul
;
75
(
7
):
1730
41
.
[PubMed]
0105-4538
31.
Zhao
XY
,
Xu
XX
,
Yin
HS
,
Hu
QM
,
Xiong
T
,
Tang
YY
, et al
Clinical characteristics of patients with 2019 coronavirus disease in a non-Wuhan area of Hubei Province, China: a retrospective study
.
BMC Infect Dis
.
2020
Apr
;
20
(
1
):
311
.
[PubMed]
1471-2334
32.
Zheng
S
,
Fan
J
,
Yu
F
,
Feng
B
,
Lou
B
,
Zou
Q
, et al
Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study
.
BMJ
.
2020
Apr
;
369
:
m1443
.
[PubMed]
0959-8138
33.
Zhou
F
,
Yu
T
,
Du
R
,
Fan
G
,
Liu
Y
,
Liu
Z
, et al
Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study
.
Lancet
.
2020
Mar
;
395
(
10229
):
1054
62
.
[PubMed]
0140-6736
34.
Zhang
F
,
Yang
D
,
Li
J
,
Gao
P
,
Chen
T
,
Cheng
Z
, et al
Myocardial injury is associated with in-hospital mortality of confirmed or suspected COVID-19 in Wuhan, China: A single center retrospective cohort study.
Preprint at https://www.medrxiv.org/content/10.1101/2020.03.21.20040121v1. Accessed May 15, 2020.
35.
Zhang
J
,
Ding
D
,
Cao
C
,
Zhang
J
,
Huang
X
,
Fu
P
, et al
Myocardial characteristics as the prognosis for COVID-19 patients.
Preprint at https://www.medrxiv.org/content/10.1101/2020.05.06.20068882v1. Accessed May 15, 2020.
36.
Ma
KL
,
Liu
ZH
,
Cao
CF
,
Liu
MK
,
Liao
J
,
Zou
JB
, et al
COVID-19 Myocarditis and Severity Factors: An Adult Cohort Study.
Preprint at https://www.medrxiv.org/content/10.1101/2020.03.19.20034124v1. Accessed May 15, 2020.
37.
Hu
L
,
Chen
S
,
Fu
Y
,
Gao
Z
,
Long
H
,
Ren
HW
, et al
Risk Factors Associated with Clinical Outcomes in 323 COVID-19 Patients in Wuhan, China.
Preprint at https://www.medrxiv.org/content/10.1101/2020.03.25.20037721v2. Accessed May 15, 2020.
38.
Argenziano
MG
,
Bruce
SL
,
Slater
CL
,
Tiao
JR
,
Baldwin
MR
,
Barr
RG
, et al
Characterization and clinical course of 1000 Patients with COVID-19 in New York: retrospective case series.
Preprint at https://www.medrxiv.org/content/10.1101/2020.04.20.20072116v2. Accessed May 15, 2020.
39.
Cao
M
,
Wang
D
,
Wang
Y
,
Lu
Y
,
Zhu
X
,
Li
Y
, et al
Clinical Features of Patients Infected with the
.
2019
Novel Coronavirus (COVID-19) in Shanghai, China. Preprint at https://www.medrxiv.org/content/10.1101/2020.03.04.20030395v1. Accessed May 15, 2020.
40.
Shabrawishi
M
,
Al-Gethamy
MM
,
Naser
AY
,
Ghazawi
MA
,
Alsharif
GF
,
Obaid
EF
, et al
Clinical, Radiological and Therapeutic Characteristics of Patients with COVID-19 in Saudi Arabia.
Preprint at https://www.medrxiv.org/content/10.1101/2020.05.07.20094169v2. Accessed May 15, 2020.
41.
Mei
Q
,
Wang
AY
,
Yang
Y
,
Li
M
,
Wang
F
,
Du
S
, et al
Survival Factors and Metabolic Pathogenesis in Elderly Patients (≥65) with COVID-19: A multi- center study of 223 Cases. Preprint at https://www.researchsquare.com/article/rs-23199/v1. Accessed May 15, 2020.
42.
Bi
Q
,
Hong
C
,
Meng
J
,
Wu
Z
,
Zhou
P
,
Ye
C
, et al
Characterizing clinical progression of COVID-19 among patients in Shenzhen, China: an observational cohort study.
Preprint at https://www.medrxiv.org/content/10.1101/2020.04.22.20076190v2. Accessed May 15, 2020.
43.
Cai
Q
,
Huang
D
,
Ou
P
,
Yu
H
,
Zhu
Z
,
Xia
Z
, et al
COVID-19 in a Designated Infectious Diseases Hospital Outside Hubei Province, China.
Preprint at https://www.medrxiv.org/content/10.1101/2020.02.17.20024018v1. Accessed May 15, 2020.
44.
Anti-2019-nCoV Volunteers, Li Z, Wu M, Yao J, Guo J, Liao X, et al. Caution on Kidney Dysfunctions of COVID-19 Patients.
Preprint at https://www.medrxiv.org/content/10.1101/2020.02.08.20021212v2. Accessed May 15, 2020.
45.
Zhao
W
,
Yu
S
,
Zha
X
,
Wang
N
,
Pang
Q
,
Li
T
, et al
Clinical characteristics and durations of hospitalized patients with COVID-19 in Beijing: a retrospective cohort study.
Preprint at https://www.medrxiv.org/content/10.1101/2020.03.13.20035436v2. Accessed May 15, 2020.
46.
Wang
L
,
Cheng
X
,
Dong
Q
,
Zhou
C
,
Wang
Y
,
Song
B
, et al
The Characteristics of Laboratory Tests at Admission and the Risk Factors for Adverse Clinical Outcomes of Severe and Critical COVID-19.
Preprint at https://www.researchsquare.com/article/rs-24018/v1. Accessed May 15, 2020.
47.
Feng
X
,
Li
P
,
Ma
L
,
Liang
H
,
Lei
J
,
Li
W
, et al
Clinical Characteristics and Short-Term Outcomes of Severe Patients with COVID-19 in Wuhan, China.
Preprint at https://www.medrxiv.org/content/10.1101/2020.04.24.20078063v1. Accessed May 15, 2020.
48.
Jiang
X
,
Tao
J
,
Wu
H
,
Wang
Y
,
Zhao
W
,
Zhou
M
, et al
Clinical features and management of severe COVID-19: A retrospective study in Wuxi, Jiangsu Province, China.
Preprint at https://www.medrxiv.org/content/10.1101/2020.04.10.20060335v1. Accessed May 15, 2020.
49.
Yin
Q
,
Fu
Z
,
Xie
J
,
Yang
J
,
Li
F
,
Zhu
W
, et al
Analysis of Risk Factors of Severe COVID-19 Patients.
Preprint at https://www.researchsquare.com/article/rs-23272/v1. Accessed May 15, 2020.
50.
Liu
Y
,
Sun
W
,
Li
J
,
Chen
L
,
Wang
Y
,
Zhang
L
, et al
Clinical features and progression of acute respiratory distress syndrome in coronavirus disease
.
2019
. Preprint at https://www.medrxiv.org/content/10.1101/2020.02.17.20024166v3. Accessed May 15, 2020.
51.
Liao
Y
,
Feng
Y
,
Wang
B
,
Wang
H
,
Huang
J
,
Wu
Y
, et al
Clinical Characteristics and Risk factors for developed COVID-19 patients transferring to designated hospital from Jianghan Fangcang shelter Hospital: a retrospective, observational study.
Preprint at https://www.medrxiv.org/content/10.1101/2020.04.21.20074724v1. Accessed May 15, 2020.
52.
Bai
T
,
Tu
S
,
Wei
Y
,
Xiao
L
,
Jin
Y
,
Zhang
L
, et al
Clinical and Laboratory Factors Predicting the Prognosis of Patients with COVID-19: An Analysis of 127 Patients in Wuhan, China. Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3546118. Accessed May 15, 2020.
53.
Chen
M
,
Fan
Y
,
Wu
X
,
Zhang
L
,
Guo
T
,
Deng
K
, et al
Clinical Characteristics and Risk Factors for Fatal Outcome in Patients with
.
2019
-Coronavirus Infected Disease (COVID-19) in Wuhan, China. Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3546069. Accessed May 15, 2020.
54.
Liu
S
,
Luo
H
,
Wang
Y
,
Wang
D
,
Ju
S
,
Yang
Y
. Characteristics and associations with severity in COVID-19 patients: a multicentre cohort study from Jiangsu province, China. Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3548753. Accessed May 15, 2020.
55.
Luo
X
,
Zhou
W
,
Xia
H
,
Yang
W
,
Yan
X
,
Wang
B
, et al
Characteristics of SARS-CoV-2 infected patients with clinical outcome during epidemic ongoing outbreak in Wuhan, China. Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3552812. Accessed May 15, 2020.
56.
Regina
J
,
Papadimitriou-Olivgeris
M
,
Burger
R
,
Filippidis
P
,
Tschopp
J
,
Desgranges
F
, et al
Epidemiology, risk factors and clinical course of SARS-CoV-2 infected patients in a Swiss university hospital: an observational retrospective study.
Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3578783. Accessed May 15, 2020.
57.
Yan
X
,
Wang
C
,
Peng
D
,
Han
X
,
Fan
Y
,
Fang
Z
, et al
Clinical features, treatment and outcomes of 218 patients with COVID-19: a retrospective, multicenter study based on clinical classification.
Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3559594. Accessed May 15, 2020.
58.
Potere
N
,
Valeriani
E
,
Candeloro
M
,
Tana
M
,
Porreca
E
,
Abbate
A
, et al
Acute complications and mortality in hospitalized patients with coronavirus disease 2019: a systematic review and meta-analysis
.
Crit Care
.
2020
Jul
;
24
(
1
):
389
.
[PubMed]
1364-8535
59.
Lim
MA
,
Pranata
R
,
Huang
I
,
Yonas
E
,
Soeroto
AY
,
Supriyadi
R
.
Multiorgan Failure With Emphasis on Acute Kidney Injury and Severity of COVID-19: Systematic Review and Meta-Analysis
.
Can J Kidney Health Dis
.
2020
Jul
;
7
:
2054358120938573
.
[PubMed]
2054-3581
60.
Betjes
MG
.
Immune cell dysfunction and inflammation in end-stage renal disease
.
Nat Rev Nephrol
.
2013
May
;
9
(
5
):
255
65
.
[PubMed]
1759-5061
61.
Ishigami
J
,
Grams
ME
,
Chang
AR
,
Carrero
JJ
,
Coresh
J
,
Matsushita
K
.
CKD and Risk for Hospitalization With Infection: The Atherosclerosis Risk in Communities (ARIC) Study
.
Am J Kidney Dis
.
2017
Jun
;
69
(
6
):
752
61
.
[PubMed]
0272-6386
62.
Cohen-Hagai
K
,
Rozenberg
I
,
Korzets
Z
,
Zitman-Gal
T
,
Einbinder
Y
,
Benchetrit
S
.
Upper Respiratory Tract Infection among Dialysis Patients
.
Isr Med Assoc J
.
2016
Sep
;
18
(
9
):
557
60
.
[PubMed]
1565-1088
63.
Sibbel
S
,
Sato
R
,
Hunt
A
,
Turenne
W
,
Brunelli
SM
.
The clinical and economic burden of pneumonia in patients enrolled in Medicare receiving dialysis: a retrospective, observational cohort study
.
BMC Nephrol
.
2016
Dec
;
17
(
1
):
199
.
[PubMed]
1471-2369
64.
Vanmassenhove
J
,
Kielstein
J
,
Jörres
A
,
Biesen
WV
.
Management of patients at risk of acute kidney injury
.
Lancet
.
2017
May
;
389
(
10084
):
2139
51
.
[PubMed]
0140-6736
65.
Cheng
Y
,
Luo
R
,
Wang
K
,
Zhang
M
,
Wang
Z
,
Dong
L
, et al
Kidney disease is associated with in-hospital death of patients with COVID-19
.
Kidney Int
.
2020
May
;
97
(
5
):
829
38
.
[PubMed]
0085-2538
66.
Wrapp
D
,
Wang
N
,
Corbett
KS
,
Goldsmith
JA
,
Hsieh
CL
,
Abiona
O
, et al
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
.
Science
.
2020
Mar
;
367
(
6483
):
1260
3
.
[PubMed]
0036-8075
67.
Su
H
,
Yang
M
,
Wan
C
,
Yi
LX
,
Tang
F
,
Zhu
HY
, et al
Renal histopathological analysis of 26 postmortem findings of patients with COVID-19 in China
.
Kidney Int
.
2020
Jul
;
98
(
1
):
219
27
.
[PubMed]
0085-2538

B. Wang and Q. Luo contributed equally to this work.

Open Access License / Drug Dosage / Disclaimer
This article is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND). Usage and distribution for commercial purposes as well as any distribution of modified material requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.