Literature DB >> 32537954

Prognostic Factors for Severe Coronavirus Disease 2019 in Daegu, Korea.

Jong Geol Jang1, Jian Hur2, Eun Young Choi1, Kyung Soo Hong1, Wonhwa Lee3, June Hong Ahn4.   

Abstract

BACKGROUND: Since its first detection in December 2019, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 infection has spread rapidly around the world. Although there have been several studies investigating prognostic factors for severe COVID-19, there have been no such studies in Korea.
METHODS: We performed a retrospective observational study of 110 patients with confirmed COVID-19 hospitalized at a tertiary hospital in Daegu, Korea. Demographic, clinical, laboratory, and outcome data were collected and analyzed. Severe disease was defined as a composite outcome of acute respiratory distress syndrome, intensive care unit care, or death.
RESULTS: Diabetes mellitus (odds ratio [OR], 19.15; 95% confidence interval [CI], 1.90-193.42; P = 0.012), body temperature ≥ 37.8°C (OR, 10.91; 95% CI, 1.35-88.36; P = 0.025), peripheral oxygen saturation < 92% (OR, 33.31; 95% CI, 2.45-452.22; P = 0.008), and creatine kinase-MB (CK-MB) > 6.3 (OR, 56.84; 95% CI, 2.64-1,223.78, P = 0.010) at admission were associated with higher risk of severe COVID-19. The likelihood of development of severe COVID-19 increased with an increasing number of prognostic factors.
CONCLUSION: In conclusion, we found that diabetes mellitus, body temperature ≥ 37.8°C, peripheral oxygen saturation < 92%, and CK-MB > 6.3 are independent predictors of severe disease in hospitalized COVID-19 patients. Appropriate assessment of prognostic factors and close monitoring to provide the necessary interventions at the appropriate time in high-risk patients may reduce the case fatality rate of COVID-19.
© 2020 The Korean Academy of Medical Sciences.

Entities:  

Keywords:  COVID-19; Korea; Prognostic Factor; Severe Disease

Mesh:

Year:  2020        PMID: 32537954      PMCID: PMC7295599          DOI: 10.3346/jkms.2020.35.e209

Source DB:  PubMed          Journal:  J Korean Med Sci        ISSN: 1011-8934            Impact factor:   2.153


INTRODUCTION

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in December 2019 in Wuhan, Hubei Province, China.1 This disease has spread rapidly to other regions around the world, including the Western Pacific, Europe, Eastern Mediterranean, Americas, and Southeast Asia. The World Health Organization declared COVID-19 a pandemic on March 12, 2020. By April 19, 2020, approximately 2.28 million cases had been diagnosed with 155,124 deaths worldwide. Although 81% of COVID-19 cases are mild, 14% are severe, and 5% are critical. The fatality rate is about 50.0% in critical cases.2 A number of factors associated with severe COVID-19 have been identified from China. Older age, male sex, presence of comorbidities, low oxygen saturation, and abnormal lab findings (high lactate dehydrogenase [LDH], high procalcitonin, low CD4 cell count, low albumin level) were shown to be risk factors for severe COVID-19.345678 However, patient- and disease-related factors vary from region to region, and these factors may be associated with the clinical severity of COVID-19. There have been no studies regarding prognostic factors for severe disease in COVID-19 patients in Korea. This study was performed to identify prognostic factors for severe disease in patients with COVID-19 in Daegu, Korea.

METHODS

Study design and participants

This was a retrospective observational study of 110 patients with confirmed COVID-19 at Yeungnam University Medical Center, Daegu, Korea, from February 19, 2020 to April 15, 2020. During the study period, all adult patients (age ≥ 18 years) with COVID-19 who were hospitalized via the emergency room or outpatient department were eligible for inclusion.

Data collection and definitions

Demographic, clinical, laboratory, treatment, and outcome data were collected from the electronic medical records of the participants. Demographic and clinical data included age, sex, comorbidities, symptoms and vital signs on admission, and treatment in the hospital. Laboratory data consisted of complete blood count, blood biochemistry, and infection-related biomarkers. Peripheral oxygen saturation was measured by pulse oximetry immediately on hospitalization of the patient. In-hospital case fatality rate was monitored until the final date of follow-up. The data were collected and analyzed by all authors. Severe disease was defined as a composite outcome of acute respiratory distress syndrome (ARDS), intensive care unit care, or death. ARDS was diagnosed according to the Berlin definition.9 SARS-CoV-2 infection was confirmed by real-time reverse transcription polymerase chain reaction assay of nose and/or throat swap samples.

Statistical analysis

Continuous variables are expressed as means ± standard deviation and were compared by Student's t-test or the Mann-Whitney U test. Categorical variables are described as number (%) and were compared by the χ2 test or Fisher's exact test. Univariable logistic regression analysis was performed to identify prognostic factors of severe COVID-19. Multivariable logistic regression analysis was conducted with variables that showed P < 0.05 in univariable analysis. We excluded variables from the univariable analysis if the number of events was too small for calculation and if there was no marked difference between two groups. In all analyses, two-tailed P < 0.05 was taken to indicate statistical significance. All statistical analyses were performed using SPSS software (ver. 24.0; SPSS Inc., Chicago, IL, USA).

Ethics statement

This study was conducted in accordance with the tenets of the Declaration of Helsinki and was reviewed and approved by the Institutional Review Board (IRB) of Yeungnam University Hospital (YUH IRB 2020-03-057). The requirement for informed consent was waived because of the retrospective study design. The final follow-up date was April 15, 2020.

RESULTS

Demographic and clinical characteristics

After excluding seven patients who were transferred to other hospitals, 110 hospitalized patients with confirmed COVID-19 were included in this study (Fig. 1). Baseline characteristics of all patients are summarized in Table 1. The mean age was 56.9 ± 17.0 and 62 patients (56.4%) were women. Forty-nine patients (44.5%) had comorbidities, of which hypertension was the most common (33.6%) followed by diabetes mellitus (26.4%). The most frequently presenting symptoms were fever (56.4%) and cough (52.7%).
Fig. 1

Flow chart.

COVID-19 = coronavirus disease 2019.

Table 1

Baseline characteristics of the study participants with COVID-19

CharacteristicsAll patients (n = 110)Severe patients (n = 23)Non-severe patients (n = 87)P value
Age, yr56.9 ± 17.068.0 ± 11.953.9 ± 17.0< 0.001
Sex0.051
Male48 (43.6)14 (60.9)34 (39.1)
Female62 (56.4)9 (39.1)53 (60.9)
Comorbidities49 (44.5)13 (57)36 (57)0.144
Cardiovascular disease10 (9.1)1 (4.3)9 (10.3)0.352
Cerebrovascular disease4 (3.6)1 (4.3)3 (3.4)0.614
Chronic lung disease4 (3.6)2 (8.7)2 (2.3)0.192
Dementia4 (3.6)2 (8.7)2 (2.3)0.614
Diabetes mellitus29 (26.4)14 (60.9)15 (17.2)< 0.001
Hypertension37 (33.6)12 (52.2)25 (28.7)0.033
Connective tissue disease1 (0.9)0 (0)1 (1.1)0.791
Liver disease1 (0.9)0 (0)1 (1.1)0.192
Malignancy6 (5.5)1 (4.3)5 (5.7)0.633
Parkinson's disease1 (0.9)0 (6.7)1 (1.1)0.209
Symptoms on admission
Fever62 (56.4)14 (60.9)48 (55.2)0.402
Cough58 (52.7)10 (43.4)48 (55.2)0.222
Sputum38 (34.5)6 (26.1)32 (36.8)0.241
Dyspnea37 (33.6)13 (56.5)24 (27.6)0.010
Diarrhea11 (10.0)1 (4.3)10 (11.5)0.453
Nausea/vomiting3 (2.7)1 (4.3)2 (2.3)0.509
Sore throat13 (11.8)0 (0)13 (14.9)0.066
Chest pain5 (4.5)0 (0)5 (5.7)0.582
Altered smell or taste loss0 (0)0 (0)0 (0)1.000
Skin lesion1 (0.9)1 (4.3)0 (0)0.209
Vital signs on admission
Body temperature, °C37.2 ± 0.737.9 ± 1.037.3 ± 0.70.002
Heart rate, beats/min86.0 ± 13.887.6 ± 12.785.5 ± 14.10.532
Respiratory rate21.0 ± 2.823.1 ± 4.720.4 ± 1.70.013
Systolic BP, mmHg128.1 ± 18.6134.9 ± 18.6126.3 ± 18.40.058
Peripheral oxygen saturation, %94.1 ± 5.787.7 ± 7.495.8 ± 3.6< 0.001
Radiologic findings
Chest X-ray only34 (30.9)6 (26.1)28 (32.2)
Chest X-ray and CT76 (69.1)17 (73.9)59 (67.8)
Unilateral pneumonia17 (15.5)1 (4.3)16 (18.4)0.078
Bilateral pneumonia46 (41.8)13 (56.5)33 (37.9)
Multiple ground-glass opacity39 (35.5)9 (39.1)30 (34.5)
Treatment in hospital
Antibiotics108 (98.2)23 (100)85 (97.7)0.624
Lopinavir/ritonavir106 (96.4)22 (95.7)84 (96.6)0.614
Hydroxychloroquine91 (82.7)23 (100)68 (78.2)0.011
Glucocorticoid21 (19.1)15 (65.2)6 (16.6)< 0.001
Clinical outcomes
Death8 (7.3)8 (34.8)0 (0)1.000
Causes of mortality
Respiratory failure4 (3.6)4 (17.4)0 (0)1.000
Septic shock4 (3.6)4 (17.4)0 (0)1.000

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

COVID-19 = coronavirus disease 2019, BP = blood pressure, CT = computed tomography.

Flow chart.

COVID-19 = coronavirus disease 2019. Data are presented as the mean ± standard deviation or number (%). COVID-19 = coronavirus disease 2019, BP = blood pressure, CT = computed tomography. The patients in the severe group were significantly older than the patients in the non-severe group (68.0 ± 11.9 vs. 53.9 ± 17.0, respectively, P < 0.001). The severe group was significantly more likely to have diabetes mellitus (60.9% vs. 17.2%, respectively, P = 0.001) and hypertension (52.2% vs. 28.7%, respectively, P = 0.033). On admission, body temperature (37.9°C ± 1.0°C vs. 37.3°C ± 0.7°C, respectively, P = 0.002) and respiration rate (23.1 ± 4.7 vs. 20.4 ± 1.7 breaths per minute, respectively, P = 0.013) were significantly higher in the severe group than the non-severe group. Peripheral oxygen saturation was significantly lower in the severe group than the non-severe group (87.7 ± 7.4 vs. 95.8 ± 3.6, respectively, P < 0.001). It was difficult to detect meaningful differences in radiologic findings between patients in the severe group and those who were not.

Laboratory findings

Laboratory findings on hospital admission are summarized in Table 2. In complete blood counts, white blood cell count (8.2 ± 3.4 vs. 6.3 ± 3.2, respectively, P = 0.017) and neutrophil count (7.1 ± 3.4 vs. 4.1 ± 3.0, respectively, P < 0.001) were higher in the severe group than the non-severe group. Lymphocyte count (0.7 ± 0.3 vs. 1.6 ± 0.7, respectively, P < 0.001) and platelet count (184.7 ± 75.3 vs. 259.8 ± 104.6, respectively, P = 0.002) were significantly lower in the severe group than the non-severe group. With regard to blood chemistry, albumin level was significantly lower in the severe group than the non-severe group (3.1 ± 0.4 vs. 3.9 ± 0.5 g/dL, respectively, P < 0.001). Concentrations of aspartate aminotransferase, total bilirubin, blood urea nitrogen, LDH, and creatine kinase-MB (CK-MB) were significantly higher in the severe group than the non-severe group. With regard to infection-related markers, C-reactive protein level was significantly higher in the severe group than the non-severe group (15.5 ± 8.8 vs. 3.3 ± 6.2 mg/L, respectively, P < 0.001), although procalcitonin level was not significantly different between the two groups (2.2 ± 5.6 vs. 0.1 ± 0.1 ng/mL, respectively, P = 0.094). Three cases of bacterial co-infection (2 cases of Klebsiella pneumonia, 1 case of Clostridium difficile) were identified in the non-severe group. Duration of viral shedding was not different between the two groups.
Table 2

Laboratory findings on admission in patients with COVID-19

VariablesAll patients (n = 110)Severe group (n = 23)Non-severe group (n = 87)P value
Complete blood count (normal range)
White blood cell count, ×109/L (4–10)6.7 ± 3.38.2 ± 3.46.3 ± 3.20.017
< 416 (14.5)1 (4.3)15 (17.2)0.007
4–1081 (73.6)15 (65.2)66 (75.9)
> 1013 (11.8)7 (30.4)6 (6.9)
Neutrophil count, ×109/L (1.8–6.3)4.7 ± 3.37.1 ± 3.44.1 ± 3.0< 0.001
> 6.324 (21.8)13 (56.5)11 (12.6)< 0.001
Lymphocyte count, ×109/L (1.1–3.2)1.4 ± 0.70.7 ± 0.31.6 ± 0.7< 0.001
< 0.824 (21.8)15 (65.2)9 (10.3)< 0.001
Hemoglobin, g/dL (12–16)13.0 ± 1.513.2 ± 1.812.9 ± 1.40.385
< 1222 (20.0)4 (17,4)18 (20.7)0.491
Platelets, ×109/L (140–440)244.1 ± 103.5184.7 ± 75.3259.8 ± 104.60.002
< 14019 (17.3)10 (43.5)9 (10.3)< 0.001
Blood chemistry (normal range)
Albumin, g/dL (3.5–5)3.7 ± 0.63.1 ± 0.43.9 ± 0.5< 0.001
< 3.538 (35.2)20 (87)18 (21.2)< 0.001
Alanine aminotransferase, IU/L (0–40)36.6 ± 46.654.5 ± 84.131.9 ± 28.90.215
> 4031 (28.2)13 (56.6)18 (20.7)0.001
Aspartate aminotransferase, IU/L (10–35)45.1 ± 47.881.3 ± 83.335.5 ± 26.00.016
> 3529 (26.4)6 (26.1)23 (22.9)0.973
Total bilirubin, mg/dL (0.1–1.2)0.9 ± 0.51.1 ± 0.60.8 ± 0.40.014
> 1.218 (16.8)7 (30.4)11 (13.1)0.054
Blood urea nitrogen, mg/dL (8–23)15.6 ± 9.021.7 ± 15.613.9 ± 5.40.027
> 2313 (11.8)8 (34.8)5 (5.7)0.001
Creatinine, mg/dL (0.5–0.9)0.9 ± 0.51.1 ± 0.90.8 ± 0.20.174
> 0.936 (32.7)11 (47.8)25 (28.7)0.083
Creatinine phosphokinase, IU/L (1–145)108.4 ± 155.2152.2 ± 182.095.0 ± 145.00.150
> 1459 (10.6)4 (20.0)5 (7.7)0.127
Lactate dehydrogenase, IU/L (150–550)625.9 ± 331.7996.7 ± 497.3527.7 ± 171.9< 0.001
> 55051 (48.6)21 (95.5)30 (36.1)< 0.001
CK-MB, ng/mL (0.6–6.3)3.2 ± 3.35.3 ± 4.11.9 ± 1.80.003
> 6.37 (15.6)6 (33.3)1 (3.7)0.012
Coagulation function
Prothrombin time, sec (10.4–13.3)13.0 ± 17.416.3 ± 26.710.7 ± 4.20.278
> 13.310 (20.4)7 (35.0)3 (10.3)0.068
D-dimer, μg/mL (0–0.5)4.4 ± 16.58.6 ± 25.31.4 ± 1.80.029
> 0.529 (76.3)16 (100.0)13 (59.1)0.005
Infection biomarkers (normal range)
C-reactive protein, mg/dL (0–0.5)5.8 ± 8.415.5 ± 8.83.3 ± 6.2< 0.001
> 0.568 (66.7)21 (100)47 (58.0)< 0.001
Procalcitonin, ng/mL (0–0.5)0.49 ± 2.62.2 ± 5.60.1 ± 0.10.094
> 0.57 (6.5)6 (27.3)1 (1.2)< 0.001
Co-infection
Bacteria3 (2.7)0 (0)3 (3.4)1.000
Other viruses0001.000
Viral shedding
Duration of viral shedding, days33.1 ± 10.034.2 ± 10.132.9 ± 10.00.659

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

COVID-19 = coronavirus disease 2019, CK-MB = creatine-kinase MB.

Data are presented as the mean ± standard deviation or number (%). COVID-19 = coronavirus disease 2019, CK-MB = creatine-kinase MB.

Prognostic factors for severe COVID-19

Multivariable analysis using variables with P < 0.05 in univariable analysis (Table 3) and the final logistic regression model demonstrated that diabetes mellitus (odds ratio [OR], 19.15; 95% confidence interval [CI], 1.90–193.42; P = 0.012), body temperature ≥ 37.8°C (OR, 10.91; 95% CI, 1.35–88.36; P = 0.025), peripheral oxygen saturation < 92% (OR, 33.31; 95% CI, 2.45–452.22; P = 0.008), and CK-MB > 6.3 (OR, 56.84; 95% CI, 2.64–1,223.78; P = 0.010) on admission were associated with greater risk of severe COVID-19 (Table 4). The rates of severe disease increased for patients with diabetes mellitus, body temperature ≥ 37.8°C, peripheral oxygen saturation ≤ 92%, and CK-MB > 6.3 (Fig. 2). The likelihood of development of severe COVID-19 increased with increasing number of prognostic factors (P < 0.001, test for trend) (Fig. 3).
Table 3

Univariable analysis of prognostic factors for severe COVID-19

Prognostic factorsOR (95% CI)P value
Age, yr1.07 (1.03–1.11)0.001
0–39Reference
40–490.00 (0.0–0.0)1.000
50–590.40 (0.03–4.70)0.463
60–693.46 (0.65–18.29)0.145
≥ 708.14 (1.57–42.33)0.013
Male, sex2.43 (0.95–6.22)0.065
Diabetes mellitus7.47 (2.73–20.40)< 0.001
Hypertension2.71 (1.06–6.93)0.038
Body temperature, °C2.54 (1.35–4.78)0.004
< 37.8Reference
≥ 37.86.36 (2.32–17.43)< 0.001
Respiratory rate1.42 (1.14–1.76)< 0.001
≤ 20Reference
> 208.11 (2.94–22.36)< 0.001
Peripheral oxygen saturation, %0.75 (0.66–0.85)< 0.001
≥ 92Reference
< 9217.71 (5.82–53.87)< 0.001
Albumin0.03 (0.01–0.13)< 0.001
≥ 3.5Reference
< 3.524.82 (6.63–92.92)< 0.001
Total bilirubin3.19 (1.22–8.35)0.018
≤ 1.2Reference
> 1.22.71 (1.05–7.00)0.040
CK-MB1.52 (1.12–2.01)0.007
≤ 6.3Reference
> 6.313.0 (1.41–120.27)0.024

COVID-19 = coronavirus disease 2019, OR = odds ratio, CI = confidence interval, CK-MB = creatine-kinase MB.

Table 4

Multivariable logistic regression analysis of prognostic factors for severe COVID-19

Prognostic factorsMultivariable model 1aMultivariable model 2b
OR (95% CI)P valueOR (95% CI)P value
Age, yr
≥ 703.37 (0.26–43.58)0.352
Male, sex2.98 (0.23–38.81)0.404
Diabetes mellitus6.53 (2.26–18.87)0.00119.15 (1.90–193.42)0.012
Hypertension1.44 (0.49–4.26)0.5081.00 (0.09–10.78)0.999
Body temperature ≥ 37.8°C8.27 (2.62–26.09)< 0.00110.91 (1.35–88.36)0.025
Peripheral oxygen saturation < 92%15.39 (4.83–48.98)< 0.00133.31 (2.45–452.22)0.008
Albumin < 3.527.21 (6.98–106.10)< 0.0015.36 (0.49–59.32)0.171
Total bilirubin > 1.22.53 (0.92–6.97)0.0735.92 (0.69–51.01)0.106
CK-MB > 6.313.00 (1.41–120.27)0.02456.84 (2.64–1,223.78)0.010

COVID-19 = coronavirus disease 2019, OR = odds ratio, CI = confidence interval, CK-MB = creatine-kinase MB.

aAdjusted for age, sex; bAdjusted for age, sex, diabetes mellitus, hypertension, body temperature, peripheral oxygen saturation, albumin, total bilirubin, and CK-MB.

Fig. 2

Comparison of rates of severe COVID-19 using categorical variables.

DM = diabetes mellitus, COVID-19 = coronavirus disease 2019, CK-MB = creatine-kinase MB.

Fig. 3

Rate of patients with severe COVID-19 according to the presence of prognostic factors.

COVID-19 = coronavirus disease 2019.

COVID-19 = coronavirus disease 2019, OR = odds ratio, CI = confidence interval, CK-MB = creatine-kinase MB. COVID-19 = coronavirus disease 2019, OR = odds ratio, CI = confidence interval, CK-MB = creatine-kinase MB. aAdjusted for age, sex; bAdjusted for age, sex, diabetes mellitus, hypertension, body temperature, peripheral oxygen saturation, albumin, total bilirubin, and CK-MB.

Comparison of rates of severe COVID-19 using categorical variables.

DM = diabetes mellitus, COVID-19 = coronavirus disease 2019, CK-MB = creatine-kinase MB.

Rate of patients with severe COVID-19 according to the presence of prognostic factors.

COVID-19 = coronavirus disease 2019.

DISCUSSION

Among the 110 patients with COVID-19, 23 (20.9%) had severe disease and the in-hospital case fatality rate was 7.3% in this study. We showed that the presence of diabetes mellitus, body temperature ≥ 37.8°C, peripheral oxygen saturation < 92%, and CK-MB > 6.3 were independent predictors of severe disease in hospitalized COVID-19 patients. To our knowledge, this is the first study to evaluate the prognostic factors of severe COVID-19 in Korea. Diabetes mellitus is a major public health issue, with an estimated global prevalence of 9.3% in 2019.10 A population-based cohort study showed that type 2 diabetes increased the risk of death associated with pneumonia, and hyperglycemia on admission was associated with increased mortality for both diabetic and nondiabetic patients with community-acquired pneumonia.11 Yang et al.12 reported that diabetes and ambient hyperglycemia are independent risk factors for death and morbidity in SARS patients. Diabetes also results in immune dysregulation and more severe and prolonged lung pathology in Middle East respiratory syndrome.13 The main mechanisms underlying the poorer clinical outcomes in cases of infections associated with diabetes mellitus are as follows: 1) decreased T lymphocyte response; 2) decreased neutrophil function; 3) disorders of humoral immunity; and 4) depression of the antioxidant system.14 In a recent study, COVID-19 patients without other comorbidities but with diabetes were shown to be at greater risk of severe disease as assessed by organ damage, inflammatory factors, and hypercoagulability. In addition, COVID-19 patients with diabetes are at high risk for disease progression.15 The results of the present study suggested that the progression of COVID-19 is influenced by diabetes mellitus. Physicians should pay close attention to whether diabetic patients with COVID-19 show rapid clinical deterioration. Body temperature is one of the variables included in the pneumonia severity index16 and systemic inflammatory response syndrome (SIRS),17 which can predict clinical outcomes in pneumonia. The febrile response is thought to be mediated by endogenous factors, called endogenous pyrogens. Pyrogenic cytokines, such as tumor necrosis factor (TNF), interleukin (IL)-1, IL-6, and interferons (IFNs), are released in response to exogenous stimuli, such as bacterial or viral products and toxins.18 In COVID-19, the levels of the proinflammatory cytokines IL-1β, IL-4, IL-6, IL-10, IFN-γ, and TNF-α are significantly higher in severe cases than in mild cases.19 The results of the present study suggested that critical COVID-19 patients have elevated levels of inflammatory cytokines, which increase body temperature. Low peripheral oxygen saturation was shown to be an independent prognostic factor for severe COVID-19.8 Many COVID-19 patients experience rapid respiratory failure and hypoxemia without any signs of dyspnea, which is referred to as silent hypoxemia.20 This unique characteristic of COVID-19 makes it difficult to predict clinical deterioration accurately using traditional scores, such as quick sequential organ failure assessment and SIRS. As COVID-19 is a highly contagious infectious disease, medical staff tend to have less contact with patients. Therefore, the discovery of a worsening condition in patients may be delayed. From this viewpoint, peripheral oxygen saturation measured immediately upon hospitalization through pulse oximetry can be used as a convenient and accurate marker for the prediction of clinical deterioration in COVID-19. Cardiac injury is associated with death, and severity of COVID-19 is associated with acute cardiac injury. In the systemic review of the 28 studies with 4,189 confirmed COVID-19 patients, severe COVID-19 infection was associated with high cardiac injury related markers, such as troponin, CK-MB, and myoglobin. And also cardiac injury in COVID-19 were related with higher mortality (OR, 3.85; 95% CI, 2.13–6.96; P < 0.001).21 It has been known that, the SARS-CoV-2 invades human cells via the receptor angiotensin converting enzyme II (ACE2). ACE2 is expressed in the lung, heart, esophagus, kidney, bladder, and ileum. Thus, organs that express ACE2 are vulnerable to SARS-CoV-2 infection.22 Therefore, the measurement of cardiac damage markers on admission is needed in patients with COVID-19, which predict the prognosis of COVID-19. There are several Chinese studies demonstrating the risk factors for severity of COVID-19. Li et al.5 reported that elder age, hypertension, high cytokine levels, and high LDH levels were associated with severe COVID-19 inpatients in Wuhan. A study in Anhui, China revealed that low fingertip oxygen saturation, and decreased CD4 cell count were independent risk factors for severe COVID-19 patients.8 Diabetes, and maximum body temperature admission were risk factors for progression of COVID-19.1523 The predictors of severe disease progression on Korean patients and those in Chinese patients were not much different. This study had several limitations. First, this was a retrospective study conducted in a single center in Korea, which subjected only hospitalized patients. Therefore, these results cannot be generalized to all COVID-19 patients. Second, antiviral agents and corticosteroid usage were not included as variables in this study. Our research focused on the baseline clinical characteristics and laboratory findings related to worsening of the patients' condition due to severe disease and not on treatment. Third, selection bias could not be avoided because population-based data were not used. The disease severity of patients may vary between hospitals in the same region. Fourth, proinflammatory cytokines and early CD8+ T-cell response that can be associated with disease severity, were not measured in this study. In conclusion, we found that the presence of diabetes mellitus, body temperature ≥ 37.8°C, peripheral oxygen saturation < 92%, and CK-MB > 6.3 are independent predictors of severe disease in hospitalized COVID-19 patients. The likelihood of progression to severe COVID-19 increased with an increasing number of prognostic factors. Appropriate assessment of prognostic factors and close monitoring to provide the necessary interventions at the appropriate time in high-risk patients may reduce the case fatality rate of COVID-19.
  23 in total

1.  Plasma glucose levels and diabetes are independent predictors for mortality and morbidity in patients with SARS.

Authors:  J K Yang; Y Feng; M Y Yuan; S Y Yuan; H J Fu; B Y Wu; G Z Sun; G R Yang; X L Zhang; L Wang; X Xu; X P Xu; J C N Chan
Journal:  Diabet Med       Date:  2006-06       Impact factor: 4.359

2.  Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition.

Authors:  Pouya Saeedi; Inga Petersohn; Paraskevi Salpea; Belma Malanda; Suvi Karuranga; Nigel Unwin; Stephen Colagiuri; Leonor Guariguata; Ayesha A Motala; Katherine Ogurtsova; Jonathan E Shaw; Dominic Bright; Rhys Williams
Journal:  Diabetes Res Clin Pract       Date:  2019-09-10       Impact factor: 5.602

3.  Type 2 diabetes and pneumonia outcomes: a population-based cohort study.

Authors:  Jette B Kornum; Reimar W Thomsen; Anders Riis; Hans-Henrik Lervang; Henrik C Schønheyder; Henrik T Sørensen
Journal:  Diabetes Care       Date:  2007-06-26       Impact factor: 19.112

4.  Early antiviral treatment contributes to alleviate the severity and improve the prognosis of patients with novel coronavirus disease (COVID-19).

Authors:  J Wu; W Li; X Shi; Z Chen; B Jiang; J Liu; D Wang; C Liu; Y Meng; L Cui; J Yu; H Cao; L Li
Journal:  J Intern Med       Date:  2020-04-20       Impact factor: 8.989

5.  Acute respiratory distress syndrome: the Berlin Definition.

Authors:  V Marco Ranieri; Gordon D Rubenfeld; B Taylor Thompson; Niall D Ferguson; Ellen Caldwell; Eddy Fan; Luigi Camporota; Arthur S Slutsky
Journal:  JAMA       Date:  2012-06-20       Impact factor: 56.272

6.  Clinical Characteristics and Outcomes of Older Patients with Coronavirus Disease 2019 (COVID-19) in Wuhan, China: A Single-Centered, Retrospective Study.

Authors:  TieLong Chen; Zhe Dai; Pingzheng Mo; Xinyu Li; Zhiyong Ma; Shihui Song; Xiaoping Chen; Mingqi Luo; Ke Liang; Shicheng Gao; Yongxi Zhang; Liping Deng; Yong Xiong
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2020-09-16       Impact factor: 6.053

7.  Clinical Characteristics of Coronavirus Disease 2019 in China.

Authors:  Wei-Jie Guan; Zheng-Yi Ni; Yu Hu; Wen-Hua Liang; Chun-Quan Ou; Jian-Xing He; Lei Liu; Hong Shan; Chun-Liang Lei; David S C Hui; Bin Du; Lan-Juan Li; Guang Zeng; Kwok-Yung Yuen; Ru-Chong Chen; Chun-Li Tang; Tao Wang; Ping-Yan Chen; Jie Xiang; Shi-Yue Li; Jin-Lin Wang; Zi-Jing Liang; Yi-Xiang Peng; Li Wei; Yong Liu; Ya-Hua Hu; Peng Peng; Jian-Ming Wang; Ji-Yang Liu; Zhong Chen; Gang Li; Zhi-Jian Zheng; Shao-Qin Qiu; Jie Luo; Chang-Jiang Ye; Shao-Yong Zhu; Nan-Shan Zhong
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

8.  Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China.

Authors:  J Zhang; X Wang; X Jia; J Li; K Hu; G Chen; J Wei; Z Gong; C Zhou; H Yu; M Yu; H Lei; F Cheng; B Zhang; Y Xu; G Wang; W Dong
Journal:  Clin Microbiol Infect       Date:  2020-04-15       Impact factor: 8.067

9.  Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan.

Authors:  Xiaochen Li; Shuyun Xu; Muqing Yu; Ke Wang; Yu Tao; Ying Zhou; Jing Shi; Min Zhou; Bo Wu; Zhenyu Yang; Cong Zhang; Junqing Yue; Zhiguo Zhang; Harald Renz; Xiansheng Liu; Jungang Xie; Min Xie; Jianping Zhao
Journal:  J Allergy Clin Immunol       Date:  2020-04-12       Impact factor: 10.793

10.  Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection.

Authors:  Xin Zou; Ke Chen; Jiawei Zou; Peiyi Han; Jie Hao; Zeguang Han
Journal:  Front Med       Date:  2020-03-12       Impact factor: 4.592

View more
  23 in total

1.  Mental and neurological disorders and risk of COVID-19 susceptibility, illness severity and mortality: A systematic review, meta-analysis and call for action.

Authors:  Lin Liu; Shu-Yu Ni; Wei Yan; Qing-Dong Lu; Yi-Miao Zhao; Ying-Ying Xu; Huan Mei; Le Shi; Kai Yuan; Ying Han; Jia-Hui Deng; Yan-Kun Sun; Shi-Qiu Meng; Zheng-Dong Jiang; Na Zeng; Jian-Yu Que; Yong-Bo Zheng; Bei-Ni Yang; Yi-Miao Gong; Arun V Ravindran; Thomas Kosten; Yun Kwok Wing; Xiang-Dong Tang; Jun-Liang Yuan; Ping Wu; Jie Shi; Yan-Ping Bao; Lin Lu
Journal:  EClinicalMedicine       Date:  2021-09-08

Review 2.  Heterogeneity and Risk of Bias in Studies Examining Risk Factors for Severe Illness and Death in COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Abraham Degarege; Zaeema Naveed; Josiane Kabayundo; David Brett-Major
Journal:  Pathogens       Date:  2022-05-10

3.  Experience of Treating Critically Ill COVID-19 Patients in Daegu, South Korea.

Authors:  Kyeong-Cheol Shin
Journal:  Tuberc Respir Dis (Seoul)       Date:  2021-03-17

4.  Academic exchange in the COVID-19 era.

Authors:  Yong-Ha Kim
Journal:  Arch Plast Surg       Date:  2020-07-15

5.  Clinical Features of COVID-19 in Uzbekistan.

Authors:  KyungHee Kim; Jae Wook Choi; Juyoung Moon; Habibulla Akilov; Laziz Tuychiev; Bakhodir Rakhimov; Kwang Sung Min
Journal:  J Korean Med Sci       Date:  2020-11-23       Impact factor: 2.153

6.  A Well-Structured Follow-Up Program is Required after Recovery from Coronavirus Disease 2019 (COVID-19); Release from Quarantine is Not the End of Treatment.

Authors:  Keun-Mi Lee; Hae-Jin Ko; Geon Ho Lee; A-Sol Kim; Dong-Wook Lee
Journal:  J Clin Med       Date:  2021-05-26       Impact factor: 4.241

7.  Evaluation of the Prognosis of COVID-19 Patients According to the Presence of Underlying Diseases and Drug Treatment.

Authors:  Ejin Kim; Yong Chul Kim; Jae Yoon Park; Jiyun Jung; Jung Pyo Lee; Ho Kim
Journal:  Int J Environ Res Public Health       Date:  2021-05-17       Impact factor: 3.390

Review 8.  Serum CK-MB, COVID-19 severity and mortality: An updated systematic review and meta-analysis with meta-regression.

Authors:  Angelo Zinellu; Salvatore Sotgia; Alessandro G Fois; Arduino A Mangoni
Journal:  Adv Med Sci       Date:  2021-07-07       Impact factor: 3.287

9.  The Importance of Happy Hypoxemia in COVID-19.

Authors:  Katayoun Haryalchi; Abtin Heidarzadeh; Mahmood Abedinzade; Sepehr Olangian-Tehrani; Samaneh Ghazanfar Tehran
Journal:  Anesth Pain Med       Date:  2021-02-14

10.  Impact of cardiovascular disease on clinical outcomes in hospitalized patients with Covid-19: a systematic review and meta-analysis.

Authors:  Ernesto Maddaloni; Luca D'Onofrio; Antonio Siena; Cecilia Luordi; Carmen Mignogna; Rocco Amendolara; Ilaria Cavallari; Francesco Grigioni; Raffaella Buzzetti
Journal:  Intern Emerg Med       Date:  2021-07-17       Impact factor: 3.397

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.