Journal List > Diabetes Metab J > v.44(3) > 1144798

Chung, Lee, Ha, Yoon, Won, Lee, Hur, Hong, Jang, Jin, Choi, Shin, Chung, Lee, Ahn, and Moon: The Risk of Diabetes on Clinical Outcomes in Patients with Coronavirus Disease 2019: A Retrospective Cohort Study

Abstract

Background

To determine the role of diabetes mellitus (DM) in the coronavirus disease 2019 (COVID-19), we explored the clinical characteristics of patients with DM and compared risk factors such as age, glycemic control, and medications to those without DM.

Methods

This was a retrospective cohort study of 117 confirmed patients with COVID-19 which conducted at a tertiary hospital in Daegu, South Korea. The primary outcome was defined as the severe and critical outcome (SCO), of which the composite outcomes of acute respiratory distress syndrome, septic shock, intensive care unit care, and 28-day mortality. We analyzed what clinical features and glycemic control-related factors affect the prognosis of COVID-19 in the DM group.

Results

After exclusion, 110 participants were finally included. DM patients (n=29) was older, and showed higher blood pressure compared to non-DM patients. DM group showed higher levels of inflammation-related biomarkers and severity score, and highly progressed to SCO. After adjustment with other risk factors, DM increased the risk of SCO (odds ratio [OR], 10.771; P<0.001). Among the DM patients, SCO was more prevalent in elderly patients of ≥70 years old and age was an independent risk factor for SCO in patients with DM (OR, 1.175; P=0.014), while glycemic control was not. The use of medication did not affect the SCO, but the renin-angiotensin system inhibitors showed protective effects against acute cardiac injury (OR, 0.048; P=0.045).

Conclusion

The COVID-19 patients with DM had higher severity and resulted in SCO. Intensive and aggressive monitoring of COVID-19 clinical outcomes in DM group, especially in elderly patients is warranted.

INTRODUCTION

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic virus, which causes pneumonia, originated in Wuhan, China, in 2019 and is spreading rapidly to other countries [1]. By April 11, 2020, 1,610,909 cases of coronavirus disease 2019 (COVID-19) had been confirmed in 213 countries, and 99,690 COVID-19 patients had died worldwide. The Chinese Center for Disease Control and Prevention reported 81% as mild cases, 14% as severe cases, and 5% as critical cases [2].
Diabetes mellitus (DM) has an estimated prevalence of 9.3% globally, and is a serious disease that impacts the health status associated with other diseases [3]. In a population-based cohort study, DM was clearly shown to be associated with increased mortality from pneumonia [4], and hyperglycemia on admission is associated with poor clinical outcome for both diabetic and nondiabetic patients with community-acquired pneumonia [5]. Respiratory tract infections, including bacterial pneumonia, influenza, and tuberculosis, are more common, and are more serious in patients with DM than in those without DM [6]. The pathophysiology of increased mortality in diabetic patients with pneumonia is as follows: (1) decreased T lymphocyte response; (2) decreased neutrophil function; (3) depression of the antioxidant system; and (4) disorders of humoral immunity by the complement system [6].
Previous studies reported that 25% to 45% of patients with COVID-19 have more than one coexisting disorder. Among them, about 10% of patients in China have DM [78]. A recent study showed that diabetic patients are more susceptible to an inflammatory storm, eventually leading to rapid progression and poor prognosis in COVID-19 patients [9].
In this study, we determined the clinical characteristics of COVID-19 patients with DM compared to those without DM. In addition, we analyzed the severity and clinical outcomes of COVID-19 patients with DM according to age, glycemic control status, and medications.

METHODS

Study design and subjects

We performed a retrospective cohort study of 117 patients with SARS-CoV-2 infection hospitalized at Yeungnam University Medical Center, in Daegu, South Korea. This study was conducted in accordance with the tenets of the Declaration of Helsinki, and was reviewed and approved by the Institutional Review Board of Yeungnam University Hospital (YUH IRB 2020-03-057). The requirement for informed consent was waived because of the retrospective study design.
During the study period, all consecutive adult patients (age >18 years) with SARS-CoV-2 infection admitted to the hospital were eligible for inclusion. SARS-CoV-2 infection was confirmed by real-time reverse transcriptase-polymerase chain reaction assay of nasal and pharyngeal swab samples. Patients who were taken to other hospitals and whose final clinical results were unknown were excluded from the analysis. After excluding seven patients, 110 patients were finally included in this study, and 26.4% (n=29) had DM (Fig. 1).

Data collection and definitions

The patients' electronic medical records were reviewed. Data on patients' age, sex, comorbidities, symptoms, vital signs, radiological findings, severity based on the National Early Waring Score (NEWS), treatment, and clinical outcomes were collected. DM was defined as any of the following criteria: (1) a known history of diabetes; (2) taking oral or injected antihyperglycemic agents; (3) history of abnormal blood glucose levels based on diagnostic criteria for type 2 DM of the Korean Diabetes Association [10]. Data on glycosylated hemoglobin (HbA1c) level, DM duration, oral antihyperglycemic agents (OHAs), insulin, and renin-angiotensin system (RAS) inhibitors were collected from patients with DM.
NEWS [11] is an early warning score facilitating the early detection of and response to deterioration of patient's condition and consists of seven parameters: pulse oximetry, oxygen, pulse, systolic blood pressure, respiration rate, temperature, and central nervous system status. Each parameter is assigned a score of 0 to 3 points. The score reflects the degree to which the parameters differ from the normal range.
Acute respiratory distress syndrome (ARDS) was diagnosed according to the Berlin definition [12]. Septic shock was defined according to the Third International Consensus Definitions for sepsis and septic shock (Sepsis-3) [13]. Acute cardiac injury was defined as a serum troponin I level above the 99th percentile upper reference limit or new abnormal electrocardiography and echocardiography findings [14]. Acute kidney injury was defined according to the Kidney Disease Improving Global Guidelines (KDIGO) for acute kidney injury [15].
In this study, we used the term “severe and critical outcome (SCO)” as an index of poor clinical outcome. SCO was defined as the composite outcome of ARDS, septic shock, intensive care unit (ICU) care, and 28-day mortality, referring to the classification of the Chinese Center for Disease Control and Prevention [2].

Statistical analysis

Continuous variables are expressed as mean±standard deviation and were compared by Student's t-test or the Mann-Whitney U test. Categorical variables were compared by the chi-squared test or Fisher's exact test. To determine the effects of DM and medications on SCO, multiple logistic regression analysis was performed after adjusting for covariates. In all analyses, two-tailed P<0.05 was taken to indicate statistical significance. All statistical analyses were performed using SPSS software version 24.0 (IBM Co., Armonk, NY, USA).

RESULTS

Baseline characteristics and clinical outcomes of COVID-19 patients according to the presence of DM

Table 1 shows the baseline characteristics of all patients and a comparison of patients with and without DM. The mean age of the total patient population was 56.9 years and the male to female ratio was 1:1.3. Smokers accounted for 14.5%. A total of 29 patients had DM (26.4%). DM patients had a higher mean age than patients without DM (n=81) (66.3±8.9 years vs. 53.5±17.9 years, respectively; P<0.001). Systolic and diastolic blood pressures were higher in patients with DM than in those without DM (both P<0.05). Hypertension was the most common comorbidity among all participants (33.6%), and more than half of the DM patients had a diagnosis or were taking medication for hypertension. On physical examination, there were no differences in symptoms between groups, except headaches were more frequent among non-DM patients (P=0.020). Bilateral pneumonia was common in DM patients, but the difference in radiologic findings (unilateral pneumonia, bilateral pneumonia, and multiple ground-glass opacity) compared to non-DM patients was not statistically significant (P=0.191). DM patients had higher white blood cell counts, neutrophil counts, lactate dehydrogenase, serum glucose, and C-reactive protein levels and lower albumin level compared to non-DM patients (all P<0.05).
Table 2 shows the severity, clinical outcomes, and treatment strategy of COVID-19 patients with and without DM. DM patients, compared to subjects without DM, had higher NEWS (4.0±4.2 vs. 1.9±2.1, P=0.015) and rates of progression to mortality (17.2% vs. 1.2%), ARDS (37.9% vs. 8.6%), septic shock (24.1% vs. 1.2%), ICU care (27.6% vs. 6.2%), and acute cardiac injury (27.6% vs. 6.2%) (all P<0.01). In addition, DM patients had higher rates of oxygen and invasive mechanical ventilation treatments (both P<0.01) and prescription of hydroxychloroquine medication (P=0.022).
The rates of progression to SCO were significantly higher with patients aged ≥70 years old compared to subjects <70 years old (42.3% vs. 9.6%, P=0.01), and in DM patients compared to subjects without DM (44.8% vs. 7.5%, P<0.001). The effect of age and DM on the risk of SCO in COVID-19 was analyzed (Fig. 2A). After adjustments for age, sex, smoking status, and the presence of comorbidities, age of ≥70 years old (odds ratio [OR], 7.106; P=0.005) and DM (OR, 10.771; P<0.001) significantly increased the risk of SCO, whereas hypertension, chronic lung disease, and malignancy had no effect on severity of outcomes.

Analysis of factors affecting SCO in COVID-19 patients with DM

We extracted diabetic patients (n=29) and explored the effects of age, DM control status, and medications on clinical outcomes. Twelve were newly diagnosed with DM on admission. Comparisons of clinical characteristics and outcomes according to age with a cutoff of 70 years are presented in Table 3. Compared to DM patients <70 years old (n=18), older DM patients (≥70 years old, n=11) were significantly older (60.9±6.2 years vs. 75.3±3.6 years, respectively; P<0.001) but there was no difference in sex ratio (P=0.702). The HbA1c and serum glucose levels, DM duration, and medication histories of OHAs, insulin and RAS inhibitors were not different between groups (all P>0.05). NEWS was not different between groups (3.3±4.1 vs. 5.3±4.5, respectively; P=0.204), but SCO was more frequent in DM patients ≥70 years old (27.8% vs. 72.7%, respectively; P=0.027).
The effects of age, HbA1c, and serum glucose level on SCO in COVID-19 patients with DM were evaluated (Fig. 2B). After adjustments, age significantly increased the risk of SCO (OR, 1.175; P=0.014), whereas HbA1c and serum glucose had no effect on SCO. We also evaluated the effects of medications on SCO, acute cardiac injury, and acute kidney injury in COVID-19 patients with DM (Fig. 3). The usage of metformin or RAS inhibitors had no effect on SCO, but RAS inhibitors showed protective effects against acute cardiac injury (OR, 0.048; P=0.045).
We investigated whether poor glycemic control affects the prognosis of COVID-19 patients (Supplementary Table 1). Compared to diabetic patients with HbA1c <8% (n=21), poorly controlled (HbA1c ≥8%, n=8) patients had higher levels of HbA1c (6.9±0.5 vs. 10.0±1.9, respectively) and serum glucose (163.9±56.0 vs. 266.4±133.5, respectively), and had longer duration of DM (2.5±3.9 vs. 11.4±12.5, respectively) (all P<0.05). However, age, sex ratio, medication histories, NEWS, and SCO were not different between groups (all P>0.05).

DISCUSSION

The results of the present study showed that the elderly over 70 years old and the presence of DM significantly impacted the clinical course of COVID-19. Patients with DM showed higher severity scores (NEWS) and more frequently progressed to SCO than patients without DM. Among DM patients, age significantly affected SCO, and RAS inhibitors showed beneficial effects against acute cardiac injury.
In recent reports of COVID-19 from China, the prevalence of comorbid DM was 7.4% to 20%, and patients with cardiometabolic disease had a severe clinical course [16]. Various results have been reported as to whether DM is a significant risk factor for disease progression of COVID-19. Guo et al. [9] reported higher levels of inflammation-related biomarkers in DM patients compared to non-DM patients. Zhou et al. [17] reported significant numbers of patients with DM in the non-survivor group, but the presence of DM did not significantly increase the risk of mortality. Wu et al. [8] reported that, after 40 days of follow-up, the presence of DM increased the risk of progressing to ARDS but did not affect mortality rate. In the present study, patients with DM had high levels of inflammation-related biomarkers and increased risk of SCO, including 28-day mortality. These data indicate that special attention should be paid to COVID-19 patients with comorbid DM.
The impacts of DM on the clinical course of SARS and Middle East respiratory syndrome (MERS) have been verified previously. The presence of DM and fasting plasma glucose level ≥126 mg/dL increased the risk of death in SARS by 6.3 and 3.3 times, respectively, and emphasized that adequate blood glucose control during treatment could improve prognosis [18]. In a meta-analysis in MERS cases, DM patients had 1.8 times increased risk of death [19]. In diabetic mice exposed to MERS-CoV, the duration of the severe disease phase was prolonged and the recovery was delayed, independently of viral titer, which was due to dysregulation of the immune response [20]. Previous reports and the results of the present study indicated that the progression of COVID-19 is also affected by DM.
Angiotensin-converting enzyme 2 (ACE2) acts as a cellular receptor for SARS-CoV and SARS-CoV2 [21], enabling acute viral replication. Accordingly, the causes of increased susceptibility to COVID-19 in diabetic patients was suggested to be related to diminished T cell function, increased susceptibility to cytokine storm, and increased ACE2 expression [22]. In addition, there is emerging evidence that the usage of drugs that increase ACE2 expression, such as RAS inhibitors (ACE inhibitors and angiotensin II receptor blockers), thiazolidinediones, and ibuprofen, may accelerate the development of COVID-19 [23]. In addition, glucagon like peptide-1 agonist [24] and atorvastatin [25] upregulate ACE2, so they should be used with caution. In the case of MERS-CoV, dipeptidyl peptidase 4 (DPP4) was shown to be a functional cellular receptor [26], so it was suggested that the use of DPP4 inhibitors may slow the progression of COVID-19 infection [27]. In the present study, neither RAS inhibitors nor metformin exacerbated the course of COVID-19, so the discontinuation or modification of these drugs does not appear to be necessary.
This study had some limitations. First, we included only our experience in a single tertiary center in Korea and recognize that there are limitations to generalizing these findings to other situations. However, the proportion of moderate to high-risk (NEWS ≥5) patients among the participants in this study was about 20%, which was a similar pattern to those of previous studies. Amidst the global pandemic of COVID-19, each country and city is showing quite different outcomes, depending on their healthcare systems and resources [28]. These findings may provide insight for the operation of healthcare systems that are similar to those of South Korea. Second, we cannot exclude the effects of glycemic control or DM complications on prognosis of COVID-19 patients. There are no data regarding the optimal glycemic target for patients with COVID-19 and DM, and our study only showed the clinical outcomes according to HbA1c level. In the present study, the poorly controlled group, as defined by HbA1c ≥8%, did not show different outcomes with regard to severity or mortality. Surprisingly, however, we found that about 40% of the patients in the DM group had been newly diagnosed with DM, indicating heterogeneity within the DM group. Further large-scale studies on glycemic control and COVID-19 prognosis would provide more insight. Meanwhile, healthcare providers should pay attention to the possibility of “hidden diabetes” in COVID-19 patients.
This study had some strengths. To our knowledge, this is the first study suggesting effects of antidiabetic medications or glycemic control (indicated by HbA1c) on the clinical course of COVID-19. These findings provide insight into factors that affect the course of COVID-19 in patients with DM. In contrast to concerns raised previously, OHA and RAS inhibitors did not significantly affect the severity of COVID-19, suggesting that patients with DM do not have to stop taking their medications.
In conclusion, COVID-19 patients with DM had higher severity and higher rates of severe outcomes, including 28-day mortality, than those without DM. After adjustment for other risk factors, DM was an independent risk factor for SCO in COVID-19 patients. Among patients with DM, older age significantly increased the risk of SCO but RAS inhibitors and OHA did not affect the outcomes. Given these potentially devastating effects of DM, especially in older patients, intensive and aggressive monitoring is needed in COVID-19.

ACKNOWLEDGMENTS

The present study was supported by a National Research Foundation of Korea grant funded by the Korean government (grant no. NRF-2019M3E5D1A02068242, NRF-2019M3E5D1A02068104). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
We thank the staff who helped to care for the COVID-19 patients at Yeungnam University Medical Center, Daegu, Korea.

Notes

CONFLICTS OF INTEREST: No potential conflict of interest relevant to this article was reported.

AUTHOR CONTRIBUTIONS:

  • Conception or design: J.H.A., J.S.M.

  • Acquisition, analysis, or interpretation of data: S.M.C., Y.Y.L., E.H., K.S.H., J.G.J., J.H.A., J.S.M.

  • Drafting the work or revising: S.M.C., J.H.A., J.S.M.

  • Final approval of the manuscript: J.S.Y., K.C.W., H.W.L., J.H., H.J.J., E.Y.C., K.C.S., J.H.C., K.H.L.

References

1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395:497–506. PMID: 31986264.
[Google Scholar]
2. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72,314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020; 2. 24. DOI: 10.1001/jama.2020.2648. [Epub].
[Google Scholar]
3. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R. IDF Diabetes Atlas Committee. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019; 157:107843. PMID: 31518657.
[Google Scholar]
4. Kornum JB, Thomsen RW, Riis A, Lervang HH, Schonheyder HC, Sorensen HT. Type 2 diabetes and pneumonia outcomes: a population-based cohort study. Diabetes Care. 2007; 30:2251–2257. PMID: 17595354.
[Google Scholar]
5. McAlister FA, Majumdar SR, Blitz S, Rowe BH, Romney J, Marrie TJ. The relation between hyperglycemia and outcomes in 2,471 patients admitted to the hospital with community-acquired pneumonia. Diabetes Care. 2005; 28:810–815. PMID: 15793178.
[Google Scholar]
6. Casqueiro J, Casqueiro J, Alves C. Infections in patients with diabetes mellitus: a review of pathogenesis. Indian J Endocrinol Metab. 2012; 16 Suppl 1(Suppl1):S27–S36. PMID: 22701840.
[Google Scholar]
7. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS. China Medical Treatment Expert Group for Covid-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020; 382:1708–1720. PMID: 32109013.
[Google Scholar]
8. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, Huang H, Zhang L, Zhou X, Du C, Zhang Y, Song J, Wang S, Chao Y, Yang Z, Xu J, Zhou X, Chen D, Xiong W, Xu L, Zhou F, Jiang J, Bai C, Zheng J, Song Y. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020; e200994.
[Google Scholar]
9. Guo W, Li M, Dong Y, Zhou H, Zhang Z, Tian C, Qin R, Wang H, Shen Y, Du K, Zhao L, Fan H, Luo S, Hu D. Diabetes is a risk factor for the progression and prognosis of COVID-19. Diabetes Metab Res Rev. 2020; e3319. PMID: 32233013.
[Google Scholar]
10. Kim MK, Ko SH, Kim BY, Kang ES, Noh J, Kim SK, Park SO, Hur KY, Chon S, Moon MK, Kim NH, Kim SY, Rhee SY, Lee KW, Kim JH, Rhee EJ, Chun S, Yu SH, Kim DJ, Kwon HS, Park KS. Committee of Clinical Practice Guidelines, Korean Diabetes Association. 2019 Clinical practice guidelines for type 2 diabetes mellitus in Korea. Diabetes Metab J. 2019; 43:398–406. PMID: 31441247.
[Google Scholar]
11. Smith GB, Prytherch DR, Meredith P, Schmidt PE, Featherstone PI. The ability of the National Early Warning Score (NEWS) to discriminate patients at risk of early cardiac arrest, unanticipated intensive care unit admission, and death. Resuscitation. 2013; 84:465–470. PMID: 23295778.
[Google Scholar]
12. ARDS Definition Task Force. Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, Camporota L, Slutsky AS. Acute respiratory distress syndrome: the Berlin Definition. JAMA. 2012; 307:2526–2533. PMID: 22797452.
[Google Scholar]
13. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent JL, Angus DC. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016; 315:801–810. PMID: 26903338.
[Google Scholar]
14. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020; 323:1061–1069.
[Google Scholar]
15. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012; 120:c179–c184. PMID: 22890468.
[Google Scholar]
16. Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, Bi Z, Zhao Y. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020; 109:531–538. PMID: 32161990.
[Google Scholar]
17. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020; 395:1054–1062. PMID: 32171076.
[Google Scholar]
18. Yang JK, Feng Y, Yuan MY, Yuan SY, Fu HJ, Wu BY, Sun GZ, Yang GR, Zhang XL, Wang L, Xu X, Xu XP, Chan JC. Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS. Diabet Med. 2006; 23:623–628. PMID: 16759303.
[Google Scholar]
19. Matsuyama R, Nishiura H, Kutsuna S, Hayakawa K, Ohmagari N. Clinical determinants of the severity of Middle East respiratory syndrome (MERS): a systematic review and meta-analysis. BMC Public Health. 2016; 16:1203. PMID: 27899100.
[Google Scholar]
20. Kulcsar KA, Coleman CM, Beck SE, Frieman MB. Comorbid diabetes results in immune dysregulation and enhanced disease severity following MERS-CoV infection. JCI Insight. 2019; 4:e131774.
[Google Scholar]
21. Li W, Moore MJ, Vasilieva N, Sui J, Wong SK, Berne MA, Somasundaran M, Sullivan JL, Luzuriaga K, Greenough TC, Choe H, Farzan M. Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature. 2003; 426:450–454. PMID: 14647384.
[Google Scholar]
22. Muniyappa R, Gubbi S. COVID-19 pandemic, coronaviruses, and diabetes mellitus. Am J Physiol Endocrinol Metab. 2020; 318:E736–E741. PMID: 32228322.
[Google Scholar]
23. Fang L, Karakiulakis G, Roth M. Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? Lancet Respir Med. 2020; 8:e21. PMID: 32171062.
[Google Scholar]
24. Romani-Perez M, Outeirino-Iglesias V, Moya CM, Santisteban P, Gonzalez-Matias LC, Vigo E, Mallo F. Activation of the GLP-1 receptor by liraglutide increases ACE2 expression, reversing right ventricle hypertrophy, and improving the production of SP-A and SP-B in the lungs of type 1 diabetes rats. Endocrinology. 2015; 156:3559–3569. PMID: 26196539.
[Google Scholar]
25. Tikoo K, Patel G, Kumar S, Karpe PA, Sanghavi M, Malek V, Srinivasan K. Tissue specific up regulation of ACE2 in rabbit model of atherosclerosis by atorvastatin: role of epigenetic histone modifications. Biochem Pharmacol. 2015; 93:343–351. PMID: 25482567.
[Google Scholar]
26. Raj VS, Mou H, Smits SL, Dekkers DH, Müller MA, Dijkman R, Muth D, Demmers JA, Zaki A, Fouchier RA, Thiel V, Drosten C, Rottier PJ, Osterhaus AD, Bosch BJ, Haagmans BL. Dipeptidyl peptidase 4 is a functional receptor for the emerging human coronavirus-EMC. Nature. 2013; 495:251–254. PMID: 23486063.
[Google Scholar]
27. Iacobellis G. COVID-19 and diabetes: can DPP4 inhibition play a role? Diabetes Res Clin Pract. 2020; 162:108125. PMID: 32224164.
[Google Scholar]
28. World Health Organization. Coronavirus disease (COVID-2019) situation reports. updated 2020 May 15. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.

SUPPLEMENTARY MATERIALS

Supplementary materials related to this article can be found online at https://doi.org/10.4093/dmj.2020.0105.

Supplement Table 1

Comparison of clinical characteristics and outcomes in coronavirus disease 2019 patients with controlled (HbA1c <8%) vs. poorly controlled (HbA1c ≥8%) diabetes
dmj-44-405-s001.pdf
Fig. 1

Patient selection. COVID-19, coronavirus disease 2019; DM, diabetes mellitus.

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Fig. 2

Diabetes mellitus (DM) and age as a risk factor for severe and critical outcomes in patients with coronavirus disease 2019. Severe and critical outcomes: composite outcome of acute respiratory distress syndrome, septic shock, intensive care unit care, and mortality within 28 days. Multivariate logistic regression analysis was adjusted by (A) age (<70:≥70 years old), sex, smoking status, and the presence of comorbidities (diabetes mellitus, hypertension, chronic lung disease, and malignancy) in the total number of patients and (B) age (continuous), sex, smoking status, and glycosylated hemoglobin (HbA1c), and serum glucose levels among diabetic patients. The odds ratios (ORs) are presented in log10. CI, confidence interval.

dmj-44-405-g002
Fig. 3

Effects of (A) metformin and (B) RAS inhibitors on severe and critical outcomes, acute cardiac injury, and acute kidney injury in diabetic patients with coronavirus disease 2019. Severe and critical outcomes: composite outcome of acute respiratory distress syndrome, septic shock, intensive care unit care, and mortality within 28 days. Multivariate logistic regression analysis was adjusted by age, sex, smoking status, and glycosylated hemoglobin level. The odds ratios (ORs) are presented in log10. CI, confidence interval.

dmj-44-405-g003
Table 1

Comparison of baseline anthropometric, symptom, and laboratory characteristics between coronavirus disease 2019 patients with and without diabetes

dmj-44-405-i001
Variable All patients (n=110) With DM (n=29) Without DM (n=81) P value
Age, yr 56.9±17.0 66.3±8.9 53.5±17.9 <0.001
Male sex 48 (43.6) 14 (48.3) 34 (42.0) 0.664
Smoker 16 (14.5) 7 (24.1) 9 (11.1) 0.123
 Packs per year 29.2±26.7 26.6±17.9 31.2±32.9 0.918
Vital signs on admission
 Body temperature, ℃ 37.2±0.7 37.1±0.7 37.2±0.6 0.501
 Heart rate, beats/min 86.0±13.8 86.8±15.2 85.7±13.3 0.719
 Respiratory rate 21.0±2.8 22.1±4.4 20.6±1.9 0.085
 Systolic BP, mm Hg 128.1±18.6 136.2±19.9 125.2±17.4 0.006
 Diastolic BP, mm Hg 79.9±12.2 84.0±13.2 78.5±11.6 0.038
Comorbidities
 Hypertension 37 (33.6) 16 (55.2) 21 (25.9) 0.006
 Chronic lung disease 4 (3.6) 2 (6.9) 2 (2.5) 0.283
 Malignancy 6 (5.5) 2 (6.9) 4 (4.9) 0.653
 Cardiovascular disease 10 (9.1) 5 (17.2) 5 (6.2) 0.125
 Cerebrovascular disease 4 (3.6) 3 (10.3) 1 (1.2) 0.055
Symptoms on admission
 Fever 62 (56.4) 16 (55.2) 46 (56.8) 1.000
 Cough 58 (52.7) 11 (37.9) 47 (58.0) 0.083
 Sputum 38 (34.5) 7 (24.1) 31 (38.3) 0.183
 Myalgia 37 (33.6) 8 (27.6) 29 (35.8) 0.497
 Dyspnea 37 (33.6) 12 (41.4) 25 (30.9) 0.362
 Headache 26 (23.6) 2 (6.9) 24 (29.6) 0.020
 Diarrhea 11 (10.0) 1 (3.4) 10 (12.3) 0.282
Radiological findings 0.191
 Unilateral pneumonia 17 (15.5) 2 (6.9) 15 (18.5)
 Bilateral pneumonia 46 (41.8) 18 (62.1) 28 (34.6)
 Multiple ground-glass opacity 39 (35.5) 9 (31.0) 30 (37.0)
Laboratory results
 White blood cell count, ×109/L 6.7±3.3 7.8±2.9 6.3±3.4 0.040
 Neutrophil count, ×109/L 4.7±3.3 6.0±3.1 4.3±3.3 0.022
 Platelets, ×109/L 244.1±103.5 237.7±92.0 246.3±107.8 0.700
 Albumin, g/dL 3.7±0.6 3.4±0.6 3.9±0.5 <0.001
 Lactate dehydrogenase, IU/L 625.9±331.7 801.4±453.3 559.0±243.7 0.010
 Serum glucose, mg/dL 133.6±61.8 192.1±94.2 112.7±20.3 <0.001
 eGFR, mL/min/1.73 m2 (MDRD) 89.9±23.5 82.6±23.8 92.5±23.0 0.050
 C-reactive protein, mg/dL 5.8±8.4 9.9±10.2 4.3±7.1 0.011
 Procalcitonin, ng/mL 0.5±2.6 1.2±4.6 0.2±1.3 0.260

Values are presented as mean±standard deviation or number (%).

DM, diabetes mellitus; BP, blood pressure; eGFR, estimated glomerular filtration rate; MDRD, modification of diet in renal disease.

Table 2

Comparison of clinical outcomes and treatment between coronavirus disease 2019 patients with and without diabetes

dmj-44-405-i002
Variable All patients (n=110) With DM (n=29) Without DM (n=81) P value
Severity scoring
 NEWS 2.5±3.0 4.0±4.2 1.9±2.1 0.015
Clinical outcomes
 28-day mortality 6 (5.5) 5 (17.2) 1 (1.2) 0.005
 ARDS 18 (16.4) 11 (37.9) 7 (8.6) 0.001
 Septic shock 8 (7.3) 7 (24.1) 1 (1.2) <0.001
 ICU care 13 (11.8) 8 (27.6) 5 (6.2) 0.005
 Acute cardiac injury 13 (11.8) 8 (27.6) 5 (6.2) 0.005
 Acute kidney injury 9 (8.2) 5 (17.2) 4 (4.9) 0.052
Treatment
 Oxygen 38 (34.5) 18 (62.1) 20 (24.7) 0.001
 HFNC 10 (9.1) 4 (13.8) 6 (7.4) 0.451
 IMV 11 (10.0) 8 (27.6) 3 (3.7) 0.001
 CRRT 3 (2.7) 2 (6.9) 1 (1.2) 0.169
 ECMO 4 (3.6) 3 (10.3) 1 (1.2) 0.055
 Antibiotics 108 (98.2) 27 (93.1) 81 (100.0) 0.068
 Lopinavir/ritonavir 106 (96.4) 27 (93.1) 79 (97.5) 0.283
 Hydroxychloroquine 91 (82.7) 28 (96.6) 63 (77.8) 0.022
 Glucocorticoid 21 (19.1) 8 (27.6) 13 (16.0) 0.270

Values are presented as mean±standard deviation or number (%).

NEWS, National Early Warning Score; ARDS, acute respiratory distress syndrome; ICU, intensive care unit; HFNC, high flow nasal cannula; IMV, invasive mechanical ventilation; CRRT, continuous renal replacement therapy; ECMO, extracorporeal membrane oxygenation.

Table 3

Comparison of clinical characteristics and outcomes between younger (<70 years) and older (≥70 years) coronavirus disease 2019 patients with diabetes

dmj-44-405-i003
Variable Age <70 yr (n=18) Age ≥70 yr (n=11) P value
Age, yr 60.9±6.2 75.3±3.6 <0.001
Male sex 9 (50) 4 (36.4) 0.702
HbA1c, % 7.8±1.7 7.36±2.0 0.611
Serum glucose, mg/dL 178.9±69.0 213.6±126.1 0.465
DM duration, yr 2.8±4.4 9.0±11.6 0.133
Newly diagnosed DM 9 (50.0) 3 (27.3) 0.317
Medications
 Oral anti-hyperglycemic drugs
  No medication 10 (58.8) 3 (30.0) 0.236
  On Medication 7 (41.2) 7 (70.0)
   Metformin 6 (35.3) 5 (50.0) 0.687
   DPP4i 5 (29.4) 1 (10.0) 0.363
   Sulfonylurea 2 (11.8) 2 (20.0) 0.613
   Others (TZD, SGLT2i, AGI) 2 (11.8) 2 (20.0) 0.613
 Insulin 1 (10.0) 0 0.675
 RAS inhibitors 8 (47.1) 6 (60.0) 0.695
NEWS 3.3±4.1 5.3±4.5 0.204
Severe and critical outcomea 5 (27.8) 8 (72.7) 0.027

Values are presented as mean±standard deviation or number (%).

HbA1c, glycosylated hemoglobin; DM, diabetes mellitus; DPP4i, dipeptidyl peptidase 4 inhibitor; TZD, thiazolidinedione; SGLT2i, sodium-glucose transport protein 2 inhibitor; AGI, α-glucosidase inhibitor; NEWS, National Early Warning Score.

aComposite outcome of acute respiratory distress syndrome, septic shock, intensive care unit care, and mortality within 28 days.