Analysis of risk factors of severe COVID-19 patients

doi:10.21203/rs.3.rs-23272/v2

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Analysis of risk factors of severe COVID-19 patients

https://doi.org/10.21203/rs.3.rs-23272/v2

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Objective: To explore relevant risk factors for severity of patients diagnosed with novel coronavirus pneumonia (COVID-19).

Methods: The clinical data of 292 patients with COVID-19 admitted to Hubei Provincial Hospital of Integrated Chinese & Western Medicine from January 1, 2020 to February 29, 2020 were analyzed retrospectively. Patients were divided into mild or severe group according to the Guidance for Corona Virus Disease 2019 (7^th version) released by the Chinese National Health Committee. The clinical data were collected at the time of admission, including demographics, clinical characteristics, laboratory tests, imaging characteristics and outcomes of treatments. We applied univariable and multivariable logistic regression methods to explore the risk factors associated with severity of the disease.

Results: The median age of patients in the severe group ((68.19±12.51) years) was significantly older than mild group ((54.14 ± 13.62) years). The male sex was more predominant in severe group (63.45%) than that of mild group (38.1%). There were more smokers (8.97% vs 1.36%) and drinkers (4.14% vs 0%) in severe group than that of mild group. Patients in the severe group had more underlying diseases. Hypertension（48.97% vs 23.81%），coronary heart disease (22.07% vs 1.36%, P<0.0001) , chronic obstructive pulmonary disease (6.21% vs 1.36%), malignant tumor (7.59% vs 2.04%) and chronic kidney disease (3.45% vs 0%) were more frequent in severe group than in mild group. The dyspnea, chest tightness and dry cough were more common in severe group (43.45%, 66.9% and 66.21%) than in mild group (23.13%, 44.22% and 53.74%). Abnormality of chest radiography were more frequent in the severe group, there were more ground glass opacities, consolidation of lung and white lung in the severe cases (88.97%, 44.07% and 46.21%) than in mild cases (78.91%, 19.05% and 2.04%). Patients in the severe group were more likely to receive methylprednisolone, oxygen therapy and mechanical ventilation. Lasso algorithm showed that age, C-reactive protein (CRP), creatine kinase (CK) and α-hydroxybutyrate dehydrogenase (α-HBDB) were independent risk factors for severe COVID-19, but the count of CD₄⁺T lymphocyte was the protective factor.

Conclusion: This retrospective study of 292 COVID-19 patients revealed that age, CRP, CK, α-HBDB and the count of CD₄⁺T lymphocyte were independent risk factors for severity of COVID-19. Identifying patients with risk factors at an early stage of the disease are helpful for outcome prediction and clinical management.

Infectious Diseases

Severe

COVID-19

Infection

Risk Factors

Coronavirus, a single strand positive strand RNA virus, widely exists in natural world ^[1]. Coronavirus included highly pathogenic acute respiratory syndrome coronavirus and Middle East respiratory syndrome (MERS) coronavirus, as well as four other coronaviruses (HCoV-229E, HCoV-0C43, HCoV-NL63, HCoV-HKU1) that can cause upper respiratory tract infection ^[2,3]. The newly discovered 2019 novel coronavirus (2019-nCoV) is the seventh coronavirus ^[4,5] known to infect humans. 2019-nCoV was officially named as severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) by the international virus classification committee ^[6]. Most of patients with COVID-19 were mild to moderate. However, some patients with COVID-19 could progress to critical severity, which are acute respiratory failure, ARDS, septic shock, multiple organ failure, with a high risk of death. The early reported mortality rate was 11% -15% ^[5].

The world health organization declared that the outbreak of SARS-Cov-2 constituted a public health emergency of international concern on 30th January 2020. The global situation was very grave. One research had suggested that the SARS-Cov-2 infection caused severe pneumonia, which clinical manifestations are similar to sars-cov infection, associating with admissions to intensive care units and high mortality rate ^[7]. The other study published in the lancet shows that older age, D-dimer greater than 1 μg/mL and higher Sequential Organ Failure Assessment (SOFA) score could predict severe COVID-19 in the early stage ^[8].

The purpose of this study is to compare the clinical and laboratory characteristics of patients with different clinical types of COVID-19 who admitted to the isolation ward of Hubei Provincial Hospital of Integrated Chinese & Western Medicine, which is one of the designated hospitals assigned by Chinese government. We aimed to explore the risk factors of severe patients, and to provide scientific basis for reducing the incidence and mortality of severe COVID-19.

Study Design and Participants

292 patients diagnosed with COVID-19 in our hospital from January 1, 2020 to February 29, 2020 were selected as the study objects. Diagnostic and clinical typing criteria were according to the Guidance for Corona Virus Disease 2019 (7^th version) released by the Chinese National Health Committee^[9]. Exclusion criteria as follows: (1) patients with psychiatric diseases who did not cooperate with the treatment. (2) patients with incomplete data or transferred to other hospitals. (3) patients with pneumonia caused by other pathogens. This study had been approved by the ethics committee of our hospital. This case series were approved by the institutional ethics board of Hubei Provincial Hospital of Integrated Chinese & Western Medicine (No. 2020011). Written informed consents were waived because of the rapid emergence of this serious epidemic.

Data collection

The following data were collected and recorded: (1) The basic data included epidemiological history, demographic characteristics, signs and symptoms. (2) The results of laboratory examination included blood routine, C-reactive protein, SAA (Serum amyloid A protein), biochemistry, immunity, inflammation, coagulation function and other indicators. (3) The chest radiography characteristics. (4) Treatments. (5) Outcomes. The data collection tables were independently reviewed by two researchers.

Statistical analyses

Continuous variables were presented as ± standard error of mean (SEM) or medians (interquartile range, IQR) depending on whether they fitted the normal distribution, and the comparisons between two groups were performed by using Wilcoxon rank sum test. For qualitative variables, statistical description was expressed as frequency (percentage), and Fisher exact probability method was chosen for comparisons between two groups. To explore risk factors with the association of the severity of COVID-19 in our subjects, univariable and multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% CIs, adjusting for confounders including age, sex, comorbidities, COVID-19 treatments. Cox proportional-hazards models were applied to determine hazard ratios (HRs) and 95% CIs for disease outcome, adjusted for the aforementioned confounders. Sensitivity analyses were done for all adjustment variables, comparing the results between univariable analysis without adjusting confounders and multivariable analysis with adjusting confounders for disease severity in patients with COVID-19. Statistical software was R version 3.6.3 (The R Foundation), and all hypothesis tests were two-sided tests with a significance level of 0.05.

General information

145 patients with severe and critical COVID-19 were set as the severe group and 147 patients with common COVID-19 were set as the mild group. Compared to mild group, patients in severe group were more likely to be male (63.9% vs 38.1%, P<0.001) and older age (67.97 ± 12.69 vs 54.14 ± 13.62, P<0.001). There were more smokers (8.84% vs 1.36%, P=0.006) and drinkers (4.08% vs 0%, P=0.0297) in the severe group than in the mild group. Meanwhile, patients in severe group had more comorbidities such as Hypertension（48.97% vs 23.81%, P<0.0001）, coronary heart disease (22.07% vs 1.36%, P<0.0001) , chronic obstructive pulmonary disease (6.21% vs 1.36%, p=0.0342), malignant tumor (7.59% vs 2.04%, P=0.0301) and chronic kidney disease (3.45% vs 0% P=0.0291) than that in the mild group. Details of other relevant information were shown in Table 1.

Regarding clinical symptoms, the dyspnea, chest tightness and dry cough were more common in severe group (43.45%, 66.9% and 66.21%) than in mild group (23.13%, 44.22% and 53.74%). Details of other relevant information were shown in Table 1.

Laboratory tests

After admission, tests of patients’ first blood routine, biochemical, immune and coagulation were performed in the two groups. Substantial differences in laboratory findings from the two groups were displayed in Table 2.

The patients in severe group had persistent and more severe lymphopenia (0.72 (IQR, 0.5-1.05)) than the mild ones (1.11 (IQR, 0.74-1.46)); Median counts of platelet were significantly lower in severe group (170 (IQR, 135-241)) than mild group (211 (IQR, 163.5-280)). The patients in severe group had more leukocytosis (6.14 (IQR, 4.71-8.68)) than that of the mild group (5.08 (IQR, 3.71-6.08)). Concentrations of procalcitonin, high sensitivity C-reactive protein were obviously higher in severe group than in mild group (0.08 (IQR, 0.04-0.23) vs 0.02(IQR, 0.02-0.05), P<0.0001), (300 (IQR, 153.03-300) vs 114.65(IQR, 19.41-300), P<0.0001).

Concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin, Direct bilirubin, alkaline phosphatase, and Gamma glutamyl transferase were especially higher in severe group than in mild group. Albumin concentrations were significantly lower in severe group than in mild group (33.8 (IQR,30.7- 36.6) vs 36.5 (IQR,34.25- 40.2), P<0.0001). Concentrations of blood urea nitrogen, creatinine, creatine kinase, α-hydroxybutyrate dehydrogenase and lactate dehydrogenase were markedly higher in severe group than in mild group.

Patients in the severe group had significantly lower concentrations of CD₄⁺T lymphocyte, CD₈⁺ T lymphocyte and total T lymphocyte count more often than those of patients in the mild group. Concentrations of interleukin 1, interleukin 6 and interleukin 10 were significantly higher in severe group than in mild group. Median prothrombin time was significantly longer in severe group (13.2 (IQR, 12.6-14.3)) than in mild group (12.5 (IQR, 12-13.35)), D-dimer and fibrinogen concentrations were markedly greater in severe group than in mild group. Details of other relevant information were shown in Table 2.

Radiological characteristics

The lung lesions in the two groups were mostly distributed under the pleura, accompanied by multiple patchy or lumpy ground glass opacities, with or without pulmonary consolidation or white lung. In the severe group, the lung lesions were mainly distributed in two lungs, with multiple ground glass opacities (88.97% vs 78.91%, P=0.0252), pulmonary consolidation (42.07% vs 19.05%, P<0.0001) and white lung (46.21% vs 2.04%, P<0.0001,) more common than in the mild group，which were summarized in Table 3.

Treatment and outcome

All patients in the two groups were treated with antiviral, anti-bacteria, nutrition, traditional Chinese medicine and symptomatic support. Compared with the mild group, the patients in the severe group received more methylprednisolone, oxygen therapy, noninvasive mechanical ventilation and invasive mechanical ventilation, which were significantly higher than that in the mild group. In 145 severe cases, 96 patients were cured and discharged, accounting for 65.31%, 51 patients died, accounting for 34.69%. For the mild group, no dead patients were found and all of them were cured and discharged. There was statistical significance between this two groups, P<0.0001, displaying in Table 3.

Analysis of related risk factors

Multivariate analysis revealed that age, CRP, CD₄⁺ T lymphocyte count, CK and α-HBDB were independent risk factors for severity of COVID-19. Multivariable regression showed increasing the risk of exacerbation associated with older age (HR 1.15, 95% CI 1.07-1.24, per five year increment; P <0.0001), CRP (HR 1.18, 95% CI 1.03-1.34, per 20 mg/L increment; P =0.0167), CK (HR 1.08, 95% CI 1.00-1.16, per 100 u/L increment; P =0.0467), α-HBDB (HR 1.15, 95% CI 1.06-1.26, per 100 u/L increment; P =0.0012) and CD₄⁺ T cell counts (HR 0.74, 95% CI 0.68-0.81, per 50 u/L reduction; P <0.0001).The details could be seen in Table 4.

A recent epidemiological study made by China CDC showed that the mortality rate of critical COVID-19 patients could be as high as 49% ^[10], aroused especial awareness in clinical management.

In this study, all 292 patients with COVID-19 were from Wuhan. Lasso algorithm concluded that age was the risk factor of severe patients. The risk of severe patients increased by 15.15% when the age increased 5 years. In the severe group, most of the patients with COVID-19 were elderly patients with basic diseases. Hypertension, coronary heart disease, chronic obstructive pulmonary disease, malignant tumor and chronic kidney disease were more frequent among severe group than that in the mild group. In 145 severe cases, 51 patients died, accounting for 34.69% and 90.2% of the dead patients were over 60 years. Additionally, 40 patients of the 51 deaths had underlying disease. The death rate of the patients with basic diseases was higher, accounting for 78.43%. The recent reports show that advanced age (>60) and comorbidities (particularly hypertension) were believed to be risk factors for severe disease and death from SARS-Cov-2 infection ^[4,5,7], which was consistent with the results of previous studies ^[5,7,11] and our findings.

In this study, C-reactive protein (CRP) in the severe group was higher than that in the mild group. CRP was selected as a risk factor of severe patients by lasso algorithm. The risk of severe patients increased 17.55% when CRP increased 20mg/L. Furthermore, we found that inflammatory markers such as SAA, IL-1, IL-6, IL-10, peripheral blood leukocytes, neutrophils and procalcitonin were significantly higher in severe patients, which indicated that severe patients might have had secondary bacterial infection. This might be closely related to death. Severe patients might also suffer from inflammatory cytokine storms, which caused fatal organ dysfunction and closely related to mortality ^[12].

Through the lasso algorithm, we found that creatine kinase (CK) and α - hydroxybutyrate dehydrogenase (α - HBDB) were independent risk factors for patients with severe illness. The risk of severe patients increased 7.86% and 15.31% when CK increased 100u/L and α - HBDB increased 100u/L respectively. The CK mainly existed in skeletal muscle, cardiac muscle and smooth muscle. α - HBDH mainly existed in cardiac muscle and liver. We also found that the liver enzyme, LDH, Blood urea nitrogen and creatinine in the severe group were significantly higher than those in the mild group. These might be the results of multiple organ dysfunction caused by SARS-CoV-2 infection ^[13]. Recent research reported that severe and critical patients more often developed multi-organ dysfunction than that in mild patients^[14]. A research reported that α - HBDH was an independent risk factor of SLE related to the liver injury ^[15].

We found that CD₄⁺ T lymphocyte count was the risk factor of severe patients. The risk of severe patients increased 25.58% when CD₄⁺ T lymphocyte count reduced 50/UL. In this study, CD₄⁺ T lymphocyte count for 95.24% of these140 patients in the severe group was lower than the normal lower limiting value and the phenomenon indicated that the decrease of lymphocyte count might be an important factor to cause the aggravation of the patient's condition, which is consistent with the report of Central South Hospital^[5]. Because of the continuous inflammatory reaction, lymphocyte apoptosis increased, the number rapidly decreased and the body entered the state of "immunosuppression" or "immune paralysis" ^[16]. In this situation, the proper use of immunosuppressive glucocorticoids might yield better results^[17].

The level of D-dimer, fibrinogen and PT in severe group were higher than that in mild group. The rise of D-dimer was influenced by many factors. Acute inflammatory response caused by severe infection could affect coagulation and fibrinolysis via many ways. Studies have shown that high levels of D-dimer were related to the 4-week mortality ^[18]and its mechanism might be related to hemodynamic changes caused by systemic pro-inflammatory cytokine response^[19]. Recent study showed that elevated level of D-dimer might be associated with the fatal outcome of COVID-19 infection^[8]. In our study, D-dimer elevation occurred in 47 of the 51 deaths in the severe group, similar to the outcomes as previous.

The patients in the severe group showed multiple ground glass opacities of both lungs on the image, lung consolidation and white lung were more common than those in the mild group, similar to the research of Guan WJ ^[20], about 30% of patients with COVID-19 would rapidly progress to ARDS ^[20]. These patients were more likely to develop to respiratory failure, severe pneumonia and ARDS.

This study found that α-HBDB was one of the independent risk factors for the onset of severe COVID-19 patients for the first time which was not reported by any other relevant literatures before. But there are some limitations in this study, it was a single center retrospective study and no external validation cohort. It is hoped that the risk factors of severe COVID-19 can be verified through multi-center clinical research in the future.

Several limitations should be noted in our study. First, the samples is not too large, however, we did a power analysis for severity of COVID-19 in patients with or without cancer using the Pearson χ² test for two proportions method, and the power was more than 0·95.Second, less than 3% patients were exclude from our study sample because the are asymptomatic carrier so that they will not be more likely to die or more sick than others and will not introduce significant bias although they are missing data in our study.

In a word, as found by the cox regression, age, CRP, CK ,α-HBDB and CD₄⁺ T lymphocyte count were the independent risk factors for the onset of severe COVID-19 patients. Therefore, early attention to the above factors might be very helpful to improve the prognosis of COVID-19 in the future.

Availability of data and materials

The datasets generated and analyzed during the current study are included in this published article and its supplementary information files. More datasets are not publicly available due to the need for further research, but are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Hubei Provincial Hospital of Integrated Chinese & Western Medicine (No. 2020011).

Written informed consent was waived because of the rapid emergence of this serious epidemic.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no conflict of interest.

Funding

N/A

Authors' contributions

YY and JZ are responsible for the whole manuscript. QY and JX helped with data entry and manuscript writing. ZF helped with study conception and data analysis. JY and FL helped with collection of laboratory data. All authors participated in the revision of this manuscript and approved the content.

Acknowledgements

We thank all the authors for their contributions to this article.

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Analysis of risk factors of severe COVID-19 patients

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