The Characteristics of Laboratory Tests at Admission and the Risk Factors for Adverse Clinical Outcomes of Severe and Critical COVID-19

doi:10.21203/rs.3.rs-24018/v1

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The Characteristics of Laboratory Tests at Admission and the Risk Factors for Adverse Clinical Outcomes of Severe and Critical COVID-19

https://doi.org/10.21203/rs.3.rs-24018/v1

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published 20 Apr, 2021

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Background COVID-19 is a worldwide pandemic. In this study, we aimed to evaluate the risk of death from severe and critical COVID-19.

Method A retrospective study of patients diagnosed with severe and critical COVID-19 from four hospitals , describing the clinical characteristics and laboratory results, and using Cox survival analysis to study the risk factors was conducted.

Results Four hundred and forty-six patients with COVID-19 showed a high mortality rate (20.2%). All patients required oxygen therapy, and 52(12%) patients required invasive mechanical ventilation, of which 50(96%) patients died. The univariate Cox proportional hazard model showed a white blood cell count of more than 10 × 10⁹/L （HR4.3, 95% CI 2.8 to6.9）,which is a risk factor .The multivariate Cox proportional hazard model demonstrated that advanced age (HR 1.1, 95% CI 1.0 to 1.1) and high white blood cell count on admission (HR 1.1, 95% CI 1.0 to 1.2) were independent risk factors for patient death.

Conclusions COVID-19 is a new disease entity that carries significant risk of morbidity and mortality.Advanced age and high white blood cell count were found to be independent risk factors for patient death.

Infectious Diseases

COVID-19

Laboratory tests

Cox survival analysis

Risk factors

In December 2019, an unidentified pneumonia appeared in Wuhan City, Hubei Province. By isolating and sequencing airway epithelial cells from patients with pneumonia, an unknown beta coronavirus infection[1],officially named COVID-19 on February 12, 2020[2]was found.The virus spread internationally within 1 month after the first identification, and it can be spread through close contact between people[3]. Severe acute respiratory syndrome (caused by SARS-CoV) [4–6], which occurred in 2003, and Middle East respiratory syndrome coronavirus (MERS), which occurred in 2013, were previously known to belong to the beta coronavirus genus[7,8].They are highly pathogenic and the infection manifests as a severe acute respiratory disease[9].The virus is introduced into host cells through the human angiotensin-converting enzyme 2(ACE2) receptor according to bioinformatics prediction methods and in vitro testing[10,11].

As of April 18, 2020, more than 2 million cases of COVID-19 have been reported to WHO, and more than 135,000 people have lost their lives. The virus has now established itself in many countries, and the threat of a pandemic has become very real[12].

To explore the onset characteristics of the disease and assess the prognostic risk factors for patients, we conducted laboratory tests for 446 patients ,described the short-term results, and tried to identify possible clinical consequences and final performance factors of 446 patients.

Study Design and Participants

This study was approved by the Ethics Commission of Hubei Provincial Hospital of Traditional Chinese Medicine(HBZY2020-C14-01. The requirement for informed consent was waived by the Ethics Commission. All cases came from Hubei Provincial Hospital of Traditional Chinese Medicine, Renmin Hospital of Wuhan University, Hubei Provincial Hospital of Integrated Chinese & Western Medicine ,and Wuhan Jin -yin-tan Hospital. The follow-up deadline was March 1, 2020.

All patients who were enrolled in this study were diagnosed with COVID-19 according to the guidance provided by the Chinese National Health Commission. They were either severe or critical. The clinical classification was based on the fifth trial version of the Diagnosis and Treatment Scheme for Pneumonitis with COVID-19 Infection, released by China’s National Health Commission. Based on this scheme, one of the following conditions must be met for a patient to be classified as severe:①shortness of breath, respiratory rate ≥ 30 beats / min;②resting state, oxygen saturation ≤ 93%;③arterial blood oxygen partial pressure (PaO2) / oxygen concentration(FiO2) ≤ 300 mm Hg or ④pulmonary imaging of blood showing significant progression of lesions > 50%; critical patients must show either:①respiratory failure, requiring mechanical ventilation;②shock;or③combined failure of other organs requiring ICU monitoring and treatment(Table 1).

Table 1

Criteria for diagnosis of severe and critical illness
Severe	Critical
①Shortness of breath, respiratory rate ≥ 30 beats / min	①Respiratory failure, requiring mechanical ventilation
②Resting state, oxygen saturation ≤ 93%	②Shock
③Arterial blood oxygen partial pressure(PaO2)/oxyg- enconcentration(FiO2) ≤ 300 mm Hg	③Combined failure of other organs requiring ICU monitoring and treatment.
④Pulmonary imaging of blood showing significant progression of lesions > 50%

Outcome indicators included discharge after treatment (survival) and death. The patient was discharged based on meeting the following four criterias :①no fever for at least three days;②significant improvement in both lungs on chest computed tomography(CT);③clinical relief of respiratory symptoms;④two SARS-CoV-2 RNA negative throat swab samples obtained at least 24 h apart(Table 2).

Table 2

Discharge diagnosis criteria
①No fever for at least three days
②Significant improvement in both lungs on chest computed tomography(CT)
③Clinical relief of respiratory symptoms
④Two SARS-CoV-2 RNA negative throat swab samples obtained at least 24 h apart.
λ The above four conditions must be met at the same time

Data Collection

All data were collected by specialists with extensive clinical experience. Electronic medical records were used to collect date on general vital signs, clinical symptoms, past history (diabetes, hypertension, and coronary heart disease), laboratory tests, and treatment outcomes of patients at the time of admission. The collected data were collated and reviewed by a team of professionally trained doctors. The collated experimental data included blood analysis [(white blood cell count, lymphocyte count, and lymphocyte percentage], liver function (glutamate transferase and aspartate transferase), renal function (urea nitrogen, creatinine, Uric acid), and the levels glucose, triglyceride,cholesterol,High-sensitivity cardiac troponin I,interleukin(IL)-6, procalcitonin, hyper-sensitive C-reactive protein(hs-Crp).

Statistical analysis

Statistical analysis was performed using the Social Science Statistics Package version 21.0 (SPSS. Inc, Chicago, IL, USA). Categorical variables were described by frequency and percentage, and continuous variables were described by median and interquartile range (IQR)values.Continuous variables were compar-ed using independent group tests when the data were normally distributed; oth-erwise, the Mann-Whitney test was used.

The Cox proportional hazard model was used to analyze baseline variables related to mortality. Variables found to be statistically significant (p < 0.05) in univariate analysis were further analyzed using multivariate analysis. The Kaplan-Meier method was used to analyze the patient's survival rate, and the log-rank test was used to compare these survival rates. All statistical tests were mutual. Statistical significance was set at p < 0.05.

Data Collection

Statistical analysis

General characteristics

The median age of the 446 patients included in the study was 55 years (IQR 42–66); 213 (47.76%) patients were male, 90 (20.2%) patients died during hospitalization, and 356(79.8%) patients were discharged. The median length of hospital stay was 10 days ( IQR 8–14) (Table 3). There were 104 (23.3%) patients that were diagnosed with one or more chronic diseases; 84 (18.83%) patients were diabetic, 104 (23.3%) were hypertensive, and 35 (7.8%) exhibited coronary heart disease. Hypoxemia was a common symptom, so all patients received oxygen therapy, 394 (88%) patients required high-flow nasal cannula oxygen therapy or non-invasive mechanical ventilation, while 52 (17%) patients required invasive mechanical ventilation. Of the 52 patients, 50 (96%) patients died. (Table 3).

Table 3

Demographic, clinical, and laboratory of patients on admission
	Total	Alive	Dead	P value
Sex Male female	213/446(48%) 233/446(52%)	161/356(45%) 195/356(55%)	52/90(58%) 38/90(42%)
Age(years) ≥60	55/446(42–66) 179/446(40%)	50(40–61) 104/356(29%)	69 (62–78) 75/90(83%)	༜0.001
Oxygen therapy HFNC,NVP IVP	394/446(88%) 52/446(12%)	354/356(99%) 2/356(1%)	40/90(44%) 50/90(56%)
Diabetes	84/446(19%)	57/356(16%)	27/90(30%)	0.002
Hypertension	104/446(23%)	73/356(21%)	31/90(34%)	0.005
Coronary heart disease	35/446(7.8%)	22/356(6.18)	13/90(14.44)	0.009
Hospital length of stay, days	10(8–14)	10(8–13)	9(5–12)	༜0.001
White blood cell count (× 10⁹per L) ༜4 4–10 ༞10	5.50(4.10–7.62) 105/446(23%) 289/446(65%) 52/446(12%)	5.18(3.95–7.05) 92/356(26%) 239/356(67%) 25/356(7%)	7.56(5.34–10.95) 13/90(14%) 50/90(56%) 27/90(30%)	༜0.001
Lymphocytes(× 10⁹per L) ༜1 ≥1	1.01(0.68–1.41) 218/446(49%) 228/446(51%)	1.12(0.77–1.58) 145/356(41%) 211/356(59%)	0.66(0.44–0.89) 73/90(81%) 17/90(19%)	༜0.001
Lymphocyte percentage(%) ༜20 ≥20	16.7(3.95–27.60) 253/446(57%) 193/446(43%)	20.75(6.83–29.80 173/356(49%) 183/356(51%)	5.10(0.31–11.50) 80/90(89%) 10/90(11%)	༜0.001
ALT(U/L) ༞40	25 (16–42) 121/446(27%)	24(16–40) 84/356(24%)	26(16–50) 37/90(41%)	0.157
AST(U/L) ༞40	27(19–40) 111/446(25%)	25(18–37) 65/356(18%)	26(16–50) 46/90(51%)	༜0.001
BUN(mmol/L) ༞9.5	4.5(3.5-6.0) 32/446(7%)	4.2(3.3–5.5) 7/356(2%)	6.97(4.8–10.1) 25/90(28%)	༜0.001
Creatinine, (µmol/L) ༞133	63.7(52.1–80.0) 15/446(3%)	4.2(3.3–5.5) 6/356(2%)	73.1 (56.1–99.4) 9/90(10%)	༜0.001
Uric Acid (µmol/L)	245 (187–305)	247(194–315	242.00(153–293)	0.065
Glucose(mmol/L) ༞6.1 3.9–6.1 ༜3.9	5.8(4.9–7.3) 200/446(45%) 235/446(53%) 11/446(2%)	5.6 (4.9–6.7) 136/356(38%) 210/356(59%) 10/356(3%)	7.2 (5.9–9.7) 64/90(71%) 25/90(28%) 1/90(1%)	༜0.001
Triglyceride(mmol/L)	1.3(1.0-1.7)	1.3(1.0-1.7)	1.3(1.1–1.6)	0.864
Cholesterol (mmol/L)	3.9(3.4–4.4)	3.9(3.4–4.5)	3.8(3.2–4.3)	0.061
High-sensitivity cardiac troponin I, ng/mL	0.006(0.02–0.18)	0.006(0.002–0.008)	0.02(0.007–0.038)	0.169
IL-6, pg/mL	9.5(6.1–22.0)	7.8(5.7–15.5)	12.1(8.9–25.4)	0.166
Procalcitonin, ng/mL	0.05(0.05–0.13)	0.05(0.04–0.09)	0.14(0.06–0.34)	༜0.001
hs-Crp(mg/L) ༞3	26.8(5.0-78.5) 327/380(86%)	18.2(5.0–49.0) 254/314(81%)	84.3(28.8-155.5) 82/88(93%)	༜0.001
λ P values indicate differences between alive and dead patients.P < 0.05 was c-onsidered statistically significant

Laboratory Test Results

At the time of admission, 105 (23%) patients presented with leukocyte count below the normal range (white blood cell count less than 4 × 10⁹/L), 52 (12%) with leukocyte count above the normal range (white blood cell count more than 4 × 10⁹/L), and about half of the patients had a decreased lymphocyte count ( lymphocyte count less than 1.0 × 10⁹/L ). One hundred and eleven (24.9%) patients exhibited varying degrees of liver dysfunction, with alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels above the normal range. Renal dysfunction occurred in 36 (7.2%) patients, who showed elevated blood urea nitrogen or serum creatinine. There were 211 (47.3%) patients with abnormal blood glucose levels, and among them, 200 (44.8%) patients showed glucose levels above the normal range (glucose count more than 6.1 mmol/L), while 11 (2%) patients showed levels below the normal range (glucose count less than 3.9 mmol/L). Hyper-sensitive C-reactive protein was increased in 86% of the patients (hs-CRP༞3 mg/L) (Table 3). The results of other laboratory tests are shown in Table 3.

Factors Affecting Mortality Rate

We included 380 patients with complete data for Cox survival analysis. The univariate Cox proportional hazard model showed that the risk of death increased 1.1- fold with an increase in age (95% CI 1.1 to 1.1; p < 0.001). Patients were divided into two groups based on age with a baseline of 60 years. The Kaplan-Meier survival curves are shown in Fig. 1. The risk of death also increased with the presence of chronic diseases, such as diabetes [HR 1.9; 95% CI 1.9 (1.2 to 3.0); p = 0.006], hypertension [HR 1.9; 95% CI 1.9 (1.2 to 3.0) ); p = 0.006], and coronary heart disease [HR 2.5; 95% CI (1.4 to 4.5); p = 0.003]. The risk of death increased 1.2-fold in patients with an increased leukocyte count. The leukocyte count cut-off was at the upper limit of the normal value range. The Kaplan-Meier survival curves are shown in Fig. 2. Other risk factors affecting death included lymphocyte count, and levels of creatinine, urea nitrogen, Crp, and so on, as shown in Table 4.

Table 4

Analysis of factors affecting mortality using the univariate Cox proportional hazards model
	Hazards ratio (95% CI)	p value
Gender(male)	1.7(1.1–2.6)	0.012
Age^# ≥ 60 years	1.1(1.0-1.1) 7.7(4.4–13.3)	༜0.001 ༜0.001
Diabetes	1.9(1.2-3.0)	0.006
Hypertension	1.9(1.2-3.0)	0.003
Coronary heart disease	2.5(1.4–4.5)	0,003
White blood cell count ^# ༞10 × 10⁹per L ^&	1.2(1.1–1.2) 4.3(2.8–6.9)	༜0.001 ༜0.001
Lymphocytes^#	0.3(0.2–0.4)	༜0.001
C-Reactive Protein^#	1.0(1.0–1.0)	༜0.001
Aspartate aminotransferase^#	1.0(1.0–1.0)	༜0.001
Blood urea nitrogen^#	1.1(1.0-1.1)	༜0.001
Creatinine^#	1.0(1.0–1.0)	༜0.001
Glucose^#	1.0(1.0-1.2)	༜0.001
λ P < 0 .05 was considered statistically significant
& Reference group is patients White blood cell count ≤ 10 × 10⁹per L,# Per unit increase of the variable

The multivariate Cox proportional hazard model was used to identify independent risk factors for mortality. We found that advanced age (HR 1.1, 95% CI 1.0 to 1.1, p < 0.001) and high white blood cell count on admission (HR 1.1, 95% CI 1.0 to 1.2, p = 0.034) were the independent risk factors for of patient death (Table 5).

Table 5

Multivariate analysis showing the independent risk factors for mortality using the Cox proportional hazards model
	Hazards ratio (95% CI)	p value
Age (per 1-y increase)	1.1(1.0-1.1)	༜0.001
White blood cell count (per 1 × 10⁹/L increase)	1.1(1.0-1.2)	0.034
λ P < 0 .05 was considered statistically significant

We included 446 patients with COVID-19 in this study, and they showed a high mortality rate (20.2%). Contrary to some previous studies, which considered the disease is still to be in the epidemic period and not reflective of the overall mortality rate, our study demonstrated that advanced age and high white blood cell count were independent risk factors for death by COVID-19. Among patients more than 60 years, the death rate was significantly increased, probably due to lower body tolerance, and the presence of co-morbidities.Zhou et al.[13] also reported that advanced age was an important independent predictor of mortality .

Results of laboratory tests demonstrated that a high white blood cell count was also an independent risk factor for patient death. An elevated white blood cells often indicate a bacterial infection, which aggravates lung damage and causes inflammatory reactions throughout the body. In severe cases, multiple organ failure can occur, hence most patients are given combined antibacterial and antiviral therapy. Thus, the initial white blood cell count could also indicate disease progression. However, due to certain limitations in our research, other research indicators were not included, and the research might be biased. Subsequent research is required to demonstrate the influence of other indicators of infection, such as procalcitonin, IL-6. etc.

Some studies on the characteristics of patients[13–15]. show similar median age at onset.Some studies showed that men were more susceptible to COVID-19 [14–16]. Our study did not demonstrate significant gender differences, but in terms of patient mortality, men were more at risk than women, possibly because females have stronger innate and adaptive immunity, leading to relatively stronger resistance to viral infections [17–20].

Although it was clinically found that the lymphocyte count of most patients was reduced [21–23], it was not found as an independent risk factor in this study. The median number of lymphocytes in patients who later died was significantly lower than that in surviving patients. Hence, lymphopenia might be related to viral invasion of the immune system that leads to immune damage.

Prior to the first outbreak of SARS, a limited number of coronaviruses, causing only mild illnesses such as the common cold, were known to spread in humans[24]. Given the high prevalence, widespread distribution of coronaviruses, the extensive genetic diversity, and frequent genome recombination of coronaviruses,new coronaviruses are likely to be regularly discovered owing to frequent cross-species infections and occasional spillover events that occur in the body[25]. In the past two decades, major infectious diseases caused by coronaviruses included SARS, MERS, and COVID-19. Therefore, it is necessary to follow- up on these cases for a long time.

However, there is insufficient information on demographic characteristics, clinical symptoms, history of exposure, and personal history of the patient in this study. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly discovered virus, and its onset, characteristics, and prognosis is are still being researched. Therefore, it is necessary to conduct a long-term follow-up study. In the later stages, follow-up of surviving patients survived must be continued to understand the disease better.

COVID-19 is currently a global pandemic. In this study, we found that advanced age and high white blood cell count are independent risk factors for patient death. We hope to inform clinicians about this information to aid them in the treatment of patients.

ICU

Intensive care unit

RNA

Ribonucleic acid

ALT

Glutalanine transferase

AST

Aspartate aminotransferase

BUN

Blood urea nitrogen

IL-6

Interleukin-6

hs-Crp

Hyper-sensitive C-reactive protein

HFNC

High-flow nasal cannula

NVP

Noninvasive ventilation

IVP

Invasive mechanical ventilation

Acknowledgments

We thank all people of this study for their insight and technical support.

Competing interests

The authors declare that they have no competing interests.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Availability of data and materials

Not applicable.

Author information

Affiliations

Hubei Provincial Hospital of Tranditional Chinese Medicine, Wuhan, Hubei 430061,China; Hubei Provincial Academy of Tranditional Chinese Medicine, Wuhan,Hubei 430061,China

Liulin Wang,Xiaobin Cheng,Qiufen Dong,Weinan Li,Min Wang,Rui Qin,Qi Long,Juan Liu,Jing Li,Dan Li,Gang Li&Yuanming Ba.

Renmin Hospital of Wuhan University; Wuhan, Hubei 430060,China

Chenliang Zhou

Hubei Provincial Hospital of Integrated Chinese & Western Medicine ; Wuhan, Hubei 430060,China;

Yeming Wang

Wuhan Jin-yin-tan Hospital, Wuhan, Hubei 430060,China;

Bin Song

Contributions

Conceived and designed the study:LLW,XBC and QFD.Collected the data:LLW,XBC,QFD,CLZ,YMW,BS,WNL,MW,RQ,QL,JL,JL,DL.Analyzed the data: LLW,GL and YMB.Wrote the paper:LLW.Interpreted the results:LLW,XBC,QFD,GL andYMB.These authors contributed equally to this work and should be considered as co-first authors:LLW,XBC and QFD.All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Yuanming Ba and Gang Li.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethics Commission of Hubei Provincial Hospital of Traditional Chinese Medicine. The requirement for informed consent was waived by the Ethics Commission.All methods were performed in accorda-nce with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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The Characteristics of Laboratory Tests at Admission and the Risk Factors for Adverse Clinical Outcomes of Severe and Critical COVID-19

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Journal Publication

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Abstract

Figures

Background

Methods

Study Design and Participants

Data Collection

Statistical analysis

Data Collection

Statistical analysis

Results

General characteristics

Laboratory Test Results

Factors Affecting Mortality Rate

Discussion

Conclusions

Abbreviations

Declarations

Rreferences

Status:

Journal Publication

Version 1