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Changes in hematological and other laboratory parameters in COVID-19 infection
*Corresponding author: Dr. Rishu Vidhatri, Department of Hematology, Nil Ratan Sircar Medical College, Kolkata, West Bengal, Kolkata, India. rishuvidhatrib19@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Mandal PK, Vidhatri R. Changes in hematological and other laboratory parameters in COVID-19 infection. J Hematol Allied Sci 2021;1:99-106.
Abstract
Severe acute respiratory syndrome-CoV-2 was declared as a pandemic by the World Health Organization in March 2020. The virus belongs to the family Coronaviridae and causes infection of varying severity ranging from mild respiratory tract infection to severe pneumonia or acute respiratory disease syndrome. Several laboratory parameters are deranged in COVID-19 infection. The gold standard of diagnosis of COVID-19 infection is polymerase chain reaction (PCR) from the nasopharyngeal and oropharyngeal swab. However, at remote places, where PCR reports are made available to patients after a time gap laboratory parameters may guide the treating physician regarding diagnosis, disease severity, and prognosis.
Keywords
COVID-19 infection
Laboratory parameters
Disease severity
INTRODUCTION
Coronavirus belongs to the family Coronaviridae. It has caused two major pandemics in the past 20 years, one in 2002 severe acute respiratory syndrome (SARS-CoV) and the other in 2012 Middle East respiratory syndrome-CoV.[1] This time the pandemic is caused by SARSCoV-2 which is the seventh known coronavirus to infect humans. The novel virus infection was first reported in Wuhan, China, in December 2019 and then rapidly spread worldwide. SARSCoV-2 was declared as an emergency on January 30, 2020, by the World Health Organization (WHO) and shortly on March 11 was declared a pandemic by the WHO.[2] It has ravaged the whole world over the past 2 years and recently by new mutant more virulent strains. In India, the first case was detected on January 30, 2020, in a student who returned from Wuhan University to Thrissur, Kerala.[3] Since then, millions of infected cases have been reported from India. The clinical manifestation of the disease varies from asymptomatic cases to severe cases with multiorgan dysfunction. The key to controlling the pandemic is early diagnosis, containment, disease stratification, and proper management.
PATHOPHYSIOLOGY
The SARS-CoV-2 virus is an enveloped single-stranded (ss) ribonucleic acid (RNA) virus and belongs to the family Coronaviridae.[4] Bats are believed to be the animal reservoir of the virus.[5] The virus is transmitted from person to person through a respiratory droplet. The coronavirus is made of four proteins, the spike proteins (S), membrane (M), envelop (E), and nucleocapsid (N) proteins.[6] These S proteins bind to the angiotensin-converting enzyme receptor 2 present on pulmonary epithelial cells of the host and multiple copies of ssRNAs are formed by enzyme RNA-dependent RNA polymerase. The viral RNA integrates with the host ribosome and translates to form a complete virion which is released from the pneumocyte. The injured pneumocyte releases various inflammatory cytokines, leading to disease complications. The incubation period of COVID-19 is 5–6 days but can be up to 14 days. The virus can infect patients of any age, most seen in 40–70 years, and present with fever, body aches, breathlessness, dry cough, abdominal pain, vomiting, and loose stools. According to disease severity, it can be asymptomatic, mild, moderate, or severe disease.[7,8]
CURRENT DIAGNOSTICS OF COVID-19
Confirmatory test for COVID-19 infection is molecular identification of SARS-CoV-2 using nucleic acid amplification tests such as the reverse transcriptase-quantitative polymerase chain reaction (RT-PCR) or viral gene sequencing.[9] Samples used are nasopharyngeal, oropharyngeal swab, sputum, or bronchoalveolar fluid. Rapid diagnosis of infection can also be done using rapid antigen test kits. However, in the developing countries, where laboratories are not well equipped and there is a lack of trained technicians to perform massive molecular tests in this pandemic which may lead to delay in results, during which clinical assessment is crucial for patient management. During this period, the patient history, hematological and biochemical laboratory parameters, and imaging in selected cases aid in the clinical confirmation of diagnosis. Chest X-ray is typically inconclusive in the early stages of the disease; as the infection progresses bilateral multifocal alveolar opacities are observed, which can even be associated with pleural effusion. High-resolution computed tomography is extremely sensitive even in the early phase of the disease and shows multifocal bilateral “ground-glass” areas associated with consolidation and patchy peripheral distribution, with greater involvement of the lower lobes.[10]
HEMATOLOGICAL INDICES
Hematological indices vary in COVID-19 patients according to disease severity. In the developing countries with resource constraint settings where molecular reports may take several days to come, these parameters at least may give some clue to treating physicians toward diagnosis and disease severity. In the COVID-19 pandemic, the clinical and laboratory findings may help the treating physician to narrow down the differential diagnosis, facilitate early isolation of patients, and provide symptomatic treatment based on the laboratory parameters which are the treatment option available for this novel viral infection. Published literature has shown that there are leukopenia, lymphopenia, high neutrophilto-lymphocyte ratio, and thrombocytopenia.[11-26] [Table 1] shows alteration in hematological parameters published in various studies. Thrombocytopenia with significant bleeding is unusual. Hemoglobin remains normal in most cases until there is a severe infection. Whether these alterations in hematological parameters are associated with morbidity and mortality in COVID-19 infection is not well established and there is conflicting evidence for the same.
| References | Sample size | Platelet | WBC | Hemoglobin |
|---|---|---|---|---|
| Ding et al.[11] |
n=72 15 (20.8%) severe 57 (79.2%) non-severe |
Thrombocytopenia Severe – 26.7% Non-severe – 10.5% (P=0.108) |
Lymphopenia in severe 73.3% and 49.1% of non-severe cases (P=0.09) –Leukocyte (P=0.05), Neutrophil: lymphocyte ratio (P=0.002) was increased Lymphocyte: monocyte ratio was decreased (P=0.102) in severe patients |
Hb Severe – 13.9 Non-severe – 14 (P=0.51) |
| Chen et al.[12] | Single-center study on RT-PCR confirmed cases (n=99) | Thrombocytopenia 12% Thrombocytosis – 4% |
Leucopenia 9% Leukocytosis 24% Neutrophilia 38% Lymphopenia 35% |
Decrease in hemoglobin – 51% |
| Fan et al.[13] |
n=67 58 – non-ICU 9 – ICU |
Thrombocytopenia ICU – 21% Non-ICU – 11% (P=0.67) |
Leukopenia 29.2% (P=0.87) Lymphopenia 36.9% (P=0.0002) |
Hb slightly decreased in ICU patients. Difference non-significant (P=0.07) |
| Huang et al.[14] |
n=41 ICU=13 Non-ICU=28 |
Thrombocytopenia ICU – 8% Non-ICU – 4% (P=0.45) |
Leucopenia ICU – 8% Non-ICU – 33% Leukocytosis ICU – 54% Non-ICU – 19% (P=0.04) Lymphopenia ICU – 85% Non-ICU – 54% (P=0.04) Median absolute neutrophil count ICU – 10·6×109/L (IQR 5.0–11.8) non-ICU – 4.4×109 (IQR 2·0–6·1) (P=0·00069) |
Hb slightly decreased in ICU patients. (P=0.2) |
| Liu et al.[15] |
n=78 Disease progression – 11 Disease improvement/stabilized 67 |
Disease progression –143.9±64.81× 109/L Disease stabilized –173.2±55.37× 109/L (P=0.116) |
TLC in disease progression – 6.08±2.56 x109/L Stabilization groups –5.18±1.63×109/L (P=0.294). Lymphocytes are slightly lower in disease progression Group (P=0.075) |
|
| Qian et al.[16] | n=91 | Severe – 152 (127–208)×109/L Non-severe – 198 (144–248) ×109/L P=0.51 |
TLC Severe – 5.23 (4.74–6.8)×109/L Non-severe – 4.97 (4.02–5.65)×109/L (P=0.010) Lymphocyte Severe – 0.9 (0.7–1.3)×109/L Non-severe – 1.4 (1.05–1.75)×109/L (P=0.027) Neutrophil severe – 3.32 (3–5.82) Non-severe – 2.8 (2.18–3.49) (P=0.0004) |
Hb severe – 130 (118–142) Non-severe – 135 (126–147) (P=0.27) |
| Qin et al.[17] |
n=452 Non-severe – 166 Severe – 286 |
Thrombocytopenia more significant in severe infection (P=0.001) | Severe cases had higher leukocyte (5.6 vs. 4.9×109;P<0.001), neutrophil (4.3 vs. 3.2×109;P<0.001) counts, lower lymphocytes count (0.8 vs. 1.0×109;P<0.001), higher neutrophil-to-lymphocyte ratio (5.5 vs. 3.2;P<0.001), lower percentages of monocytes (6.6 vs. 8.4%;P<0.001), eosinophils (0.0 vs. 0.2%;P<0.001), and basophils (0.1 vs. 0.2%;P=0.015) |
|
| Ruan et al.[18] |
n=150 Survivor – 82 Non-survivor – 68 |
Platelet count significantly lower in non-survivors than in survivors | Leukocytosis and lymphopenia were significantly more in non-survivors | |
| Wang et al.[19] | 69 cases SpO2>90% n=55 SpO2<90% n=14 |
Normal in both groups | Leukopenia severe –21% Non-severe – 62% (P=0.007) Leukocytosis Severe – 7% Non-severe Lymphocytopenia Severe – 79% Non-severe – 32% (P=0.002) |
Normal |
| Wang et al.[20] |
n=138 ICU – 36 Non-ICU – 102 |
Median platelet count was slightly lower in ICU patients than in non-ICU patients (P=0.78) | Higher TLC ICU –6.6 (3.6–9.8)×109/L Non-ICU – 4.3 (3.3–5.4)×109/L;P=0.003, higher neutrophil count in ICU patients than in non-ICU patients (P<0.001) Lymphocytopenia more in ICU patients difference (non-significant) | |
| Wu et al.[21] |
n=201 84 (41.8%) developed ARDS |
Thrombocytopenia 18.8% | Leukocytosis 23.4% Lymphopenia 64.0% Neutrophilia 34.5% |
|
| Yang et al.[22] | 52 Critically ill 20 Survivors 32 Non-survivors |
Median platelet count was normal in survivors and non-survivors | Lymphocytopenia 85% No association between survivors and non-survivors |
|
| Zachariah et al.[23] |
n=50 Non-severe – 41 Severe – 9 |
Leukocytosis (P=0.003) Severe – 23.2% Non-severe – 4.9% Leukopenia (P=0.16) Severe – 16.1% Non-severe – 22% Lymphopenia 72% Non-significant between severe and non-severe (P=0.160) |
||
| Zhang et al.[24] |
n=140 Non-severe – 58 Severe – 82 |
Leukopenia – 19.6% (P=0.001) Lymphocytopenia –75.4% (P=0.001) Eosinophil lowered 51.9% (P=0.06) Significantly difference between severe and non-severe |
||
| Zhou et al.[25] |
n=191 Survivors – 137 Non-survivors – 54 |
Thrombocytopenia 7% More non-survivors showed thrombocytopenia than survivors. (P<0.0001) |
Lymphocytopenia 40% Leukocytopenia 17% Significant difference between non-survivors and survivors (P<0.0001) |
Hb: Hemoglobin, TLC: Total leukocyte count, ICU: Intensive care unit, ARDS: Acute respiratory distress syndrome, and RT-PCR: Reverse transcriptase polymerase chain reaction
In severe infection, Tang et al.[26] found that thrombocytopenia negatively correlated with 28-day mortality. Our experience with this novel viral infection is new and published literature has shown that there is an increase in leukocyte, high neutrophil-to-lymphocyte ratio, lymphocytopenia, and thrombocytopenia with the progression of the disease.[17,18] Lymphocytopenia is a common abnormal laboratory parameter found in COVID-19 infection and may give a clue about disease prognosis in the initial phase of infection. Out of 1099 patients studied by Guan et al.,[28] 83.2% of patients had lymphocytopenia, and leukocytosis was associated with severe disease. Qin et al.[17] studied 452 patients of which 286 had a severe infection and found a significant (P < 0.001) higher leukocytosis, neutrophilia, high neutrophil-to-lymphocyte ratio, and lymphocytopenia in the severe group when compared to the non-severe group. Huang et al.[14] and Wang et al.[20] found a significant association between lymphopenia and intensive care unit (ICU) admission. Like the above-mentioned studies, Fan et al.[13] also found that on admission, low lymphocyte count was significantly (P < 0.001) associated with ICU admissions. While the above discussed published literature found an association between hematological parameters and disease severity or prognosis, other studies reveal conflicting results. Fan et al.[13] showed that there was no association between thrombocytopenia at either admission or during hospitalization and ICU admission. Wu et al.[21] found a non-significant difference in platelet count between survivors and non-survivors complicated by acute respiratory distress syndrome. Young et al.[8] found that platelet count was not different in patients requiring oxygen support and those who did not, but the statistical comparison was not done. Wang et al.[20] and Wu et al.[21] also found that there was a non-significant difference in platelet count between hospitalized patients infected with SARS-CoV-2 in ICU and non-ICU patients. Liu et al.[15] found a non-significant difference in platelet, leukocyte, and lymphocyte count in patients with progressive and stable SARS-CoV2 infection.
THROMBOTIC BIOMARKERS
Apart from hematological indices, thrombotic biomarkers are also frequently abnormal in SARS-CoV-2 infection. Coagulation parameters abnormalities found in COVID-19 infection published in the literature are summarized in Table 2. A D-dimer level may help in the prognostication of disease and available literature has shown an association with disease severity.[14,19,21] Prothrombin time (PT) and activated partial thromboplastin time (a PTT) were more in severe SARS-CoV-2 infection; however, the difference was non-significant.[14,22] Han et al.[27] did a study to assess abnormalities of coagulation parameters in COVID-19 infection and found that D-dimer, fibrin/ fibrinogen degradation products (FDPs), and fibrinogen were increased in all patients, and D-dimer and FDP values were higher in patients with severe infections compared to those with mild infection. Tang et al.[26] found significantly increased D-dimer and FDP levels, and prolonged PT and aPTT in non-survivors compared to survivors. Zhou et al.[25] found that D-dimer greater than 1 μg/mL on admission was predictive of in-hospital mortality (P = 0.0033). Wang et al.[20] found a significant difference between D-dimer values in ICU as compared to non-ICU patients while there was a non-significant increase in PT in COVID patients and a PTT was normal and there was no significant difference between ICU and non-ICU patients.
| Reference | PT (s) | aPTT (s) | D Dimer (mg/L) |
|---|---|---|---|
| Chen et al.[12] | Increased 5% Decreased 30% |
Increased 6% Decreased 16% |
Increased 36% |
| Huang et al.[14] | Median ICU – 12.2 s (IQR 11.2–13.4) Non-ICU – 10.7 (IQR 9.8–12.1) (P=0.012) |
Median ICU – 26.2 s (IQR 22.5-33.9) Non-ICU – 27.7 s (IQR 24.8–34.1) (P=0.57) |
Median ICU – 2.4 (0.6–14.4) Non-ICU – 0.5 (0.3–0.8) (P=0.0042) |
| Liu et al.[15] | D-dimer more in disease progression however difference non-significant (P=0.501) |
||
| Qian et al.[16] | Severe – 450 (160–485) ng/ml Non-severe – 300 (106–400) ng/ml (P=0.591) |
||
| Wang et al.[20] | Raised in both arms (non-significant) | Normal | Significant increase in ICU group (P<0.001) |
| Wu et al.[21] | Prolonged 2.1% | Prolonged 9.7% | Increased 23.3% |
| Zachariah et al.[23] | Non-severe – 0.2 (0.1–0.3) μg/mL Severe – 0.4 (0.2–2.4) μg/mL (P≤0.001) |
PT: Prothrombin time; aPTT: activated partial thromboplastin time, ICU: Intensive care unit
BIOCHEMICAL PARAMETERS
COVID-19 infection causes activation of the immune system and release of various cytokines which cause injury to vital organs such as the lung, kidney, heart, and liver, resulting in derangement of many biochemical parameters. Biochemical parameters deranged in SARSCoV-2 infection are enlisted in Table 3. Hypoalbuminemia was significantly more common in severe disease as reported in various studies.[14,15,18,19] Increased lactatedehydrogenase (LDH) level was significantly associated with severe disease.[19-21] Liver enzymes were increased in patients with SARS-CoV-2 infection although the rise was marginal.[12,14,20,22] Many studies have reported aspartate transaminase to be significantly raised in severe cases compared to non-severe.[19,21] Total bilirubin was marginally more in patients with severe disease.[12,14,19,22]
| Reference | Albumin (gm/L) | ALT (IU/L) | AST (IU/L) | Bilirubin (mg/L) | BUN | Creatinine | LDH (IU/L) | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Chen et al.[12] |
Decreased 98% | Increase d 98% | Increase d 35% | Increased 18% | Increased 6% Decrease d 17% |
Increase d 3% Decreased 21% | Increased in 76% | |||
| Fan et al.[13] |
Increased in 43.6% ICU patients (P=0.005) | |||||||||
| Huang et al.[14] |
Median ICU – 27.9 (26.3–30.9) Non-ICU – 34.7 (30.2–36.5) (P=0.00066) | Median ICU – 49 (29–115) Non-ICU – 27 (19.5–40) (P=0.038) | <40 ICU – 38% Non-ICU – 75% (P=0.025) | ICU – 14.0 (11.9–32.9) Non-ICU – 10.8 (9.4–12.3) (P=0.011) | >245 ICU (92%) Non-ICU – 635 (P=0.03) | |||||
| Liu et al.[15] |
Progression group – 36.62±6.60 Stabilization group – 41.27±4.55 (P=0.006) |
No significant difference (P=0.77) | No significant difference (P=0.78) | |||||||
| Qian GQ16 | Severe – 38.55 (36.33–39.25) g/l Non-severe – 40.2 (38–42.4) g/l (P=0.133) | Severe – 19.9 (14–26) U/l Non-severe – 18 (13–29) U/l (P=0.75) | Severe – 27 (23.75–27) U/l Non-severe – 21 (17–29) U/l (P=0.89) | Severe – 5.19 (4.66–6.14) mmol/L Non-severe – 3.83 (3.25–4.4) mmol/L (P=0.0001) | Severe – 81.5 (70.75–90.5) umol/l Non-severe – 66 (57–76) umol/l (P=0.03) | |||||
| Ruan et al.[18] |
Significantly lower in non-survivors | Significantly high in non survivors | ||||||||
| Wan et al.[19] |
Slightly more in the severe group (P=0.11) | More in the severe group (P<0.03) | Significantly higher in severe cases (P=0.001) | |||||||
| Wang et al.[20] |
Normal | Increase in ICU (P<0.001) | Normal | Increased in ICU (P<0.001) | More in ICU patients (P=0.04) | Increase in ICU (P<0.001) | ||||
| Wu et al.[21] |
Decreased 98.5% | Increase d 21.7% | Increase d 29.8% | Increased 5.1% | Increased 4.5% | Increased 4.5% | Raised 68.2% | |||
ALT: Alanine transaminase, AST: Aspartate transaminase, BUN: Blood urea creatinine, LDH: Lactate dehydrogenase; and ICU: Intensive care unit
Blood urea nitrogen and creatinine levels were increased more in severe infection.[21,22]
IMMUNOLOGICAL PARAMETERS
The most common immunological abnormality in COVID-19 infection was interleukin 6 (IL-6), erythrocyte sedimentation rate, ferritin, and C-reactive protein (CRP). Immunological parameters deranged in COVID-19 infection are summarized in Table 4. Many studies have documented that CRP is significantly elevated in severe disease as compared to non-severe disease and is an important marker of disease progression and response to treatment.[15,17-20] Ferritin was increased more in patients who were severely infected compared to those with non-severe infection.[17,18] Procalcitonin is not commonly increased in COVID-19 patients and is often raised in patients with a secondary bacterial infection. Huang et al.[14] did a study on 41 patients and found that procalcitonin levels were raised in four patients and all four had a secondary bacterial infection. Qin et al.,[17] in a study on 452 patients, found that procalcitonin was significantly elevated in ICU admitted patients who were severely infected with COVID-19 infection than in non-ICU patients (0.1 vs. 0.05 ng/mL; P < 0.001), and many inflammatory cytokines were significantly raised in severe infection than the non-severe ones, including IL-2R, IL-6, IL-8, IL-10, and tumor necrosis factor-alpha. Immunoglobulins such as IgA, IgG, and IgM and complement proteins (C3 and C4) were not affected or they were within the normal range. T lymphocytes are significantly decreased in severe COVID-19 infection as compared to non-severe. Both helper T lymphocytes and suppressor T lymphocytes were below normal in all patients and helper T cells were significantly decreased in the severe group. Naïve helper T cells were increased in severe infection, and the number of memory helper T cells decreased in severe cases.[17]
| Reference | Procalcitoni n | IL-6 | ESR | Ferritin | CRP (mg/L) |
|---|---|---|---|---|---|
| Chen et al.[12] | Increased 6% | Increased 52% | Increased 85% | Increased 63% | Increased 86% |
| Huang et al.[14] | >0.5 ng/ml ICU-25% Non-ICU-Nil |
||||
| Liu et al.[15] | Non-significant difference between progressive and stable disease (P=0.195) | Non-significant difference between progressive and stable disease (P=0.794) |
Progression group versus improvement/stabilization group (38.9 [14.3, 64.8] vs. 10.6 [1.9, 33.1] mg/L, U = 1.315, P= 0.024) | ||
| Qian et al.[16] | Severe – 0 (0) Non-severe – 0.03 (0–0.04) ng/m (P=0.003) |
Severe – 30.63 (12.5–103.4) mg/l Non-severe – 5.98 (1.4–11.3) mg/l (P≤0.0001) |
|||
| Qian et al.[16] | Increased in severe infection (0.1 vs. 0.05 ng/mL;P<0.001) |
IL-6, 8, and 10 Significantly more in severe cases |
Non-significant difference between severe and non-severe | Increased in severe (800.4 vs. 523.7 ng/ml;P<0.001) | |
| Ruan et al.[18] | Significantly higher in non-survivors | Significantly higher in non-survivors | Significantly higher in non-survivors | ||
| Wang et al.[19] | Increased in severe cases (P=0.78) | Significantly higher in severe infection (P=0.001) | |||
| Wang et al.[20] | Procalcitonin ≥0.05 ng/ml severe – 75% non-severe – 21.6% (P≤0.001) |
||||
| Wu et al.[21] | Raised in 85.6% | Raised in 48.8% | Raised in 93.8% | Raised in 78.5% | Raised in 85.6% |
| Zachariah et al.[23] |
Severe – 0.1 (0.06–0.3) ng/mL Non-severe-0.05 (0.03–0.1) ng/mL |
Severe – 47.6 (20.6–87.1) mg/l Non-severe – 28.7 (9.5–52.1) mg/l P=0.001 |
IL-6: Interleukin 6, ESR: Erythrocyte sedimentation rate, CRP: C-reactive protein, and ICU: Intensive care unit
CONCLUSION
Several laboratory parameters are affected in COVID-19 infection. Total leukocyte count, lymphocytopenia, thrombocytopenia, CRP, D-dimer, albumin, and LDH have been shown in published literature to have prognostic implications. The above-mentioned studies highlight the necessity and importance of laboratory tests to be done in COVID-19 infection. The gold standard diagnostic test for COVID-19 is RT-PCR.
Test for COVID-19 is RT-PCR, however, in resource constraint countries, where molecular test results are made available after a few days, these laboratory parameters may at least give a minimum diagnostic and prognostic clue to treating physicians.
Declaration of patient consent
Patient’s consent not required as patients identity is not disclosed or compromised.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References
- From SARS and MERS to COVID-19: A brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses. Respir Res. 2020;21:224.
- [CrossRef] [PubMed] [Google Scholar]
- World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19) Int J Surg. 2020;76:71-6.
- [CrossRef] [PubMed] [Google Scholar]
- An outbreak of coronavirus (COVID-19) epidemic in India: Challenges and preventions. J Infect Dis Ther. 2020;8:421.
- [Google Scholar]
- Coronaviruses: Important emerging human pathogens. J Virol. 2014;88:5209-12.
- [CrossRef] [PubMed] [Google Scholar]
- COVID-19: Current understanding of its pathophysiology, clinical presentation, and treatment. Postgrad Med J. 2021;97:312-20.
- [CrossRef] [PubMed] [Google Scholar]
- Epidemiological determinants of spread of causal agent of severe acute respiratory syndrome in Hong Kong. Lancet. 2003;361:1761-6.
- [CrossRef] [Google Scholar]
- Epidemiologic features, and clinical course of patients infected with SARS-CoV-2 in Singapore. JAMA. 2020;323:1488-94.
- [CrossRef] [PubMed] [Google Scholar]
- Laboratory diagnosis of emerging human coronavirus infections the state of the art. Emerg Microbes Infect. 2020;9:747-56.
- [CrossRef] [PubMed] [Google Scholar]
- Coronavirus disease 2019 (COVID-19): Role of chest CT in diagnosis and management. AJR Am J Roentgenol. 2020;214:1280-6.
- [CrossRef] [PubMed] [Google Scholar]
- Dynamic profile and clinical implications of hematological parameters in hospitalized patients with coronavirus disease 2019. Clin Chem Lab Med. 2020;58:1365-71.
- [CrossRef] [PubMed] [Google Scholar]
- Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet. 2020;395:507-13.
- [CrossRef] [Google Scholar]
- Hematologic parameters in patients with COVID-19 infection. Am J Hematol. 2020;95:E131-4.
- [CrossRef] [Google Scholar]
- Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506.
- [CrossRef] [Google Scholar]
- Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J (Engl). 2020;133:1032-8.
- [CrossRef] [PubMed] [Google Scholar]
- Epidemiologic and clinical characteristics of 91 hospitalized patients with COVID-19 in Zhejiang, China: A retrospective, multicenter case series. QJM. 2020;113:474-81.
- [CrossRef] [PubMed] [Google Scholar]
- Dysregulation of immune response in patients with coronavirus 2019 (COVID-19) in Wuhan, China. Clin Infects Dis. 2020;71:762-8.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46:846-8.
- [CrossRef] [Google Scholar]
- Clinical features of 69 cases with coronavirus disease 2019 in Wuhan, China. Clin Infect Dis. 2020;71:769-77.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061-9.
- [CrossRef] [PubMed] [Google Scholar]
- Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180:934-43.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: A single-centered, retrospective, observational study. Lancet Respir Med. 2020;8:475-81.
- [CrossRef] [Google Scholar]
- Epidemiology, clinical features, and disease severity in patients with coronavirus disease 2019 (COVID-19) in a children's hospital in New York City, New York. JAMA Pediatr. 2020;174:e202430.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical characteristics of 140 patients infected with SARSCoV-2 in Wuhan, China. Allergy. 2020;75:1730-41.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet. 2020;395:1054-62.
- [CrossRef] [Google Scholar]
- Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost. 2020;18:1094-9.
- [CrossRef] [Google Scholar]
- Prominent changes in blood coagulation of patients with SARS-CoV-2 infection. Clin Chem Lab Med. 2020;58:1116-20.
- [CrossRef] [PubMed] [Google Scholar]
- Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382:1708-20.
- [CrossRef] [PubMed] [Google Scholar]
