To the Editor,
Since December 2019, a series of pneumonia cases caused by a novel coronavirus have been reported in Wuhan, Hubei Province, China. The coronavirus soon raised intense attention not only within China but also internationally, and was initially named 2019-nCoV by the World Health Organization (WHO) [1]. Shortly after that, the disease was renamed by the WHO as coronavirus disease 2019 (COVID-19) and the virus was renamed as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the Coronavirus Study Group (CSG) [2], [3]. Up to March 1, 2020, COVID-2019 has caused tens of thousands of human infections and thousands of deaths in and out of China.
As a highly infectious disease, the early detection, isolation and treatment of COVID-2019 are of great importance. However, the initial symptoms of COVID-2019 are similar to other respiratory virus infections with cough, fever and muscle ache [4]. These clinical symptoms confounded early detection of infected cases, especially against a background of ongoing influenza and other respiratory viruses like respiratory syncytial virus and adenovirus. Reliable rapid tests and feasible differential diagnosis are crucial for clinicians in their first contact with suspected patients.
Several studies have taken advantage of calculated hematology parameters, such as neutrophil (NEU)-to-lymphocyte (LYM) ratio (NLR), LYM-to-monocyte ratio (LMR) and platelet-to-LYM ratio (PLR), in the diagnosis and prognosis of inflammatory response-related virus infection [5]. These parameters are not only readily available but also cost-effective. As a newly discovered virus, information regarding the hematology parameters of COVID-19 patient is limited [1], [4]. Although there have been studies showing the use of calculated hematology parameters to help with distinguishing disease severities and predict the prognosis for COVID-19 [6], [7], the application of these parameters in the diagnosis and differential diagnosis is none.
A retrospective study on complete blood count (CBC) with differential results of patients who presented to the fever clinic of Tongji Hospital with symptoms of COVID-19-like illness between February 1, 2020 and February 20, 2020 was performed through case reviewing. Inclusion criteria were fever with a body temperature above 37.3 °C, accompanied or not accompanied by cough, chest tightness, muscle ache, shortness of breath and diarrhea. Patients with hematopathy, cancer and sepsis were excluded. The SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) testing of throat swab was performed in the laboratory of Tongji Hospital. These patients with COVID-19-like symptoms were divided into two groups. Patients diagnosed with COVID-19 according to the WHO interim guidance and confirmed by RT-PCR testing were included in the SARS-CoV-2-positive patient group (SPPG). Patients with two or more consecutive negative RT-PCR test results were included in the SARS-CoV-2-negative patient group (SNPG). Patients with co-infection of SARS-CoV-2 and other respiratory viruses including influenza A/B, respiratory syncytial virus and adenovirus were also excluded in SPPG. Sysmex XN-9000 hematology analyzer was used to obtain the CBC with differential results for patients in each group. CBC with differential results at the request of clinicians at the initial evaluations was recorded along with age and gender for each patient.
We used the Statistical Package for Social Sciences (SPSS) Version 15.0 (SPSS Inc., Chicago, IL, USA) for statistical analysis and a p-value ≤0.05 was considered statistically significant. Compared with patients in SNPG, the white blood cell count (WBC), NEU, LYM, monocyte, platelet count and thrombocytocrit were significantly lower for patients in SPPG (Table 1). Thus, these six parameters were chosen as candidates. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of selected parameters. Among those parameters, WBC and LYM were recognized as they produced the largest two areas under the curve (AUC). In order to increase the diagnostic values, a combination parameter of LYM and WBC, i.e. WBC*LYM (formula: WBC multiplied by LYM), was then calculated. As shown in Table 2, using WBC*LYM to distinguish SARS-CoV-2-positive from -negative patients produced the largest AUC (p<0.05) among all parameters. The sensitivity (73.40%) and specificity (63.36%) for WBC*LYM are highest if 8.47 was used as the cut-off value (Table 2).
Age, gender and complete blood count with differential results of SARS-COV-2-positive patient and SARS-CoV-2-negative patient groups with similar symptoms.
| Parameters | Total | SARS-CoV-2-negative patient group | SARS-CoV-2-positive patient group | χ2/t/Z | p-Value |
|---|---|---|---|---|---|
| n | 225 | 131 | 94 | – | – |
| Age, years | 52.0 (36.0–62.5) | 50.0 (36.0–57.0) | 56.0 (39.7–68.0)a | −2.861 | 0.004 |
| Males | 107 (47.6%) | 62 (47.3%) | 45 (47.9%) | 0.006 | 0.936 |
| WBC, 109/L | 6.00 (4.50–7.27) | 6.34 (5.09–7.97) | 5.07 (3.86–6.62)a | −4.318 | 0.000 |
| <3.5b | 19 (8.4%) | 3 (2.3%) | 16 (17.0%)a | 13.459 | 0.000 |
| >9.5b | 22 (9.8%) | 19 (14.5%) | 3 (3.2%)a | 6.692 | 0.010 |
| NEU, 109/L | 3.68 (2.71–5.18) | 3.81 (2.89–5.60) | 3.35 (2.28–4.89)a | −3.051 | 0.002 |
| <1.8b | 13 (5.8%) | 3 (2.3%) | 10 (10.6%)a | 5.494 | 0.019 |
| >6.3b | 30 (13.3%) | 21 (16.0%) | 9 (9.6%) | 1.426 | 0.232 |
| LYM, 109/L | 1.38 (0.99–1.87) | 1.62 (1.22–2.02) | 1.14 (0.86–1.58)a | −4.736 | 0.000 |
| <1.1b | 68 (30.2%) | 25 (19.1%) | 43 (45.7%)a | 17.126 | 0.000 |
| MON, 109/L | 0.47 (0.33–0.64) | 0.50 (0.38–0.69) | 0.42 (0.31–0.59)a | −2.582 | 0.010 |
| >0.6b | 66 (29.3%) | 44 (33.6%) | 22 (23.4%) | 2.277 | 0.131 |
| RBC, 1012/L | 4.53 (4.22–4.87) | 4.59 (4.25–4.93) | 4.42 (4.19–4.80) | −1.463 | 0.143 |
| Decreasedc | 26 (11.6%) | 13 (9.9%) | 13 (13.8%) | 0.479 | 0.489 |
| HGB, g/L | 138.5±16.3 | 139.5±17.9 | 137.2±13.8 | −1.070 | 0.286 |
| Decreasedc | 18 (8.0%) | 10 (7.6%) | 8 (8.5%) | 0.000 | 0.997 |
| HCT, % | 40.62±4.56 | 40.90±4.90 | 40.23±4.05 | −1.094 | 0.275 |
| Decreasedc | 32 (14.2%) | 16 (12.2%) | 16 (17.0%) | 0.678 | 0.410 |
| MCV, fL | 90.07±3.53 | 89.92±3.36 | 90.27±3.77 | 0.743 | 0.458 |
| MCH, pg | 30.6 (29.4–31.6) | 30.5 (29.2–31.7) | 30.6 (29.7–31.6) | −0.295 | 0.768 |
| MCHC, g/L | 339 (332–346) | 339 (333–346) | 340 (332–346) | −0.046 | 0.964 |
| RDW-SD, fL | 41.0 (39.0–42.7) | 40.9 (39.0–42.6) | 41.1 (39.1–43.2) | −1.024 | 0.306 |
| PLT, 109/L | 229 (177–279) | 237 (190–288) | 206 (157–268)a | −2.473 | 0.013 |
| <125b | 13 (5.8%) | 5 (3.8%) | 8 (8.5%) | 1.445 | 0.229 |
| >350b | 19 (8.4%) | 13 (9.9%) | 6 (6.4%) | 0.474 | 0.491 |
| PDW, fL | 13.2 (11.6–15.0) | 13.3 (11.6–15.2) | 13.2 (11.6–14.9) | −0.186 | 0.853 |
| MPV, fL | 11.07±1.11 | 11.03±1.12 | 11.13±1.10 | −0.695 | 0.488 |
| PCT, L/L | 0.25 (0.19–0.30) | 0.26 (0.21–0.32) | 0.23 (0.18–0.30)a | −2.381 | 0.017 |
| WBC*LYM, 1018/L2 | 8.25 (5.32–12.94) | 9.96 (6.63–14.64) | 6.04 (3.69–9.15)a | −5.843 | 0.000 |
n, number; WBC, white blood cell count; NEU, neutrophil; LYM, lymphocyte; MON, monocyte; RBC, red blood cell; HGB, hemoglobin; HCT, hematocrit; MCV, mean corpuscular volume; MCH, mean corpuscular hemoglobin; MCHC, mean corpuscular hemoglobin concentration; RDW-SD, red blood cell distribution width standard deviation; PLT, platelet; PDW, platelet distribution width; MPV, mean platelet volume; PCT, thrombocytocrit; WBC*LYM, white blood cell count multiplied by lymphocyte count. Continuous variables were defined as mean±standard deviation for Gaussian distribution data and median (interquartile range) for non-Gaussian distribution data; categorical variables were given as number and percentages; an unpaired t-test was used for normal distribution data; the Mann-Whitney U test was used for non-normal distribution data; chi-square (χ2) test was used for the comparison of rates. aCompared with the SARS-CoV-2-negative patient group, p<0.05. bAll cut-off values adopted in Table 1 were from the reference ranges recommended in WS/T 405-2012 “Reference intervals for blood cell analysis” in China available from http://www.nhc.gov.cn/ewebeditor/uploadfile/2013/01/20130109171100186.pdf. cRBC decreased is defined as male <4.3×1012/L or female <3.8×1012/L; HGB decreased is defined as male <130 g/L or female <115 g/L; HCT decreased is defined as male <40.0% or female <35.0%.
Diagnostic values of WBC, NEU, LYM, MON, PLT, PCT and WBC*LYM for distinguishing SARS-CoV-2-positive patients from SARS-CoV-2-negative patients with similar symptoms.
| Parameters | Cut-off valuea | Sensitivity, % | Specificity, % | LR+ | LR− | AUC (95% CI) | p-Valueb |
|---|---|---|---|---|---|---|---|
| WBC, 109/L | ≤5.07 | 51.06 | 77.10 | 2.23 | 0.63 | 0.669 (0.603–0.730) | 0.023 |
| NEU, 109/L | ≤2.72 | 38.30 | 83.21 | 2.28 | 0.74 | 0.619 (0.552–0.683) | 0.003 |
| LYM, 109/L | ≤1.20 | 55.32 | 75.57 | 2.26 | 0.59 | 0.685 (0.620–0.745) | 0.031 |
| MON, 109/L | ≤0.4 | 47.87 | 72.52 | 1.74 | 0.72 | 0.601 (0.534–0.665) | 0.001 |
| PLT, 109/L | ≤189 | 45.74 | 76.34 | 1.93 | 0.71 | 0.597 (0.529–0.661) | 0.001 |
| PCT, L/L | ≤0.18 | 31.91 | 86.26 | 2.32 | 0.79 | 0.593 (0.526–0.658) | 0.000 |
| WBC*LYM, 1018/L2 | ≤8.47 | 73.40 | 63.36 | 2.00 | 0.42 | 0.729 (0.665–0.785) | \ |
WBC, white blood cell count; NEU, neutrophil; LYM, lymphocyte; MON, monocyte; PLT, platelet; PCT, thrombocytocrit; WBC*LYM, white blood cell count multiplied by lymphocyte count; LR+, positive likelihood ratio; LR−, negative likelihood ratio; AUC (95% CI), area under the receiver operating characteristic curve (95% confidence interval). aThe Youden index of receiver operating characteristic curve was the largest when this cut-off value was used. bUsing the method recommended by Delong et al., the AUC of WBC*LYM was compared with other parameters, and p<0.05 was considered statistically significant.
The SARS-CoV-2 RT-PCR testing of respiratory tract specimen was recommended by the WHO to confirm COVID-19 [8]. However, clinicians are usually unable to obtain the RT-PCR result in their first contact with suspected patients. Additionally, during the pandemic, the RT-PCR testing was often restricted. Serology for diagnostic purposes is recommended only when RT-PCR is not available [8]. Whereas it takes time for the immune system to produce antibodies, serology may be suitable for a retrospective analysis, but not for an early diagnosis. We undertook this study with the aim of exploring hematology parameters to help identify COVID-19 among patients presenting with similar symptoms while awaiting RT-PCR results. To the best of our knowledge, this is the first study on applying calculated hematology parameters to identify COVID-19 in suspected patients.
Lymphopenia has been previously reported by a series of studies on SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV) infections as well as SARS-CoV-2 [1], [4], [9], [10]. It was also observed in our study with a proportion of 45.7% in SPPG. Insufficient T-cell priming, lack of virus-specific T cells and cytokine-induced T-cell apoptosis were the major reasons for the lymphopenia in SARS-CoV [9], while MERS-CoV was found to be able to infect T cells directly and induce T-cell apoptosis by extrinsic and intrinsic apoptosis pathways [10]. As for SARS-CoV-2, the mechanism is still unclear for now. Liu et al. analyzed the changes in LYM subsets in mild and severe COVID-19 cases, and found that the development of lymphopenia in severe patients was mainly related to the significantly decreased absolute counts of T cells, especially CD8+ T cells, but not to B cells and NK cells [6]. This may provide clues to the mechanism of lymphopenia in SARS-CoV-2 infection.
Increased NLR was reported to be related to severe COVID-19 and NLR was chosen as a useful prognostic factor for COVID-19 by studies before [6], [7]. However, the diagnostic value of NEU in COVID-19 was shown to be disappointing in this study (AUC: 0.619). Reasons for the poor diagnosis value for NEU in this study may be that the parameter may depend on the stage of the disease in which the CBC analysis is performed or on the type of population assessed. On the contrary, except for LYM, WBC seemed to have the best diagnostic value in the differential diagnosis of COVID-19 among all parameters. However, the AUC of WBC*LYM is only 0.729. This reminds us that hematology parameters can be affected by a lot of factors inside and outside the human bodies. When using these parameters, epidemiological history, clinical symptoms and computerized tomography scans should be combined together to make a reasonable decision. Nevertheless, as CBC with differential results is the most widely used laboratory test for patients with cold symptoms and it is readily available even in primary hospitals, this parameter can still provide clues for clinicians in their first contact with suspected patients without available SARS-CoV-2 RT-PCR results.
There are several limitations in this study. First, relatively few cases were enrolled in this study and they are all patients from Wuhan, and large-scale multicenter clinical studies are required to corroborate this evidence. Second, there are no routine medical examinations available for healthy people due to COVID-19 outbreak, so no healthy controls are included in the study. Third, although we have excluded patients with co-infection of SARS-CoV-2 and other respiratory viruses including influenza A/B, respiratory syncytial virus and adenovirus in SPPG, confounding factors still exist and may produce a certain degree of deviation. Last, there is a probability of false-negative SARS-CoV-2 RT-PCR results depending on the reagent sensitivity and specimen sampling skills. Although the inclusive criteria are two or more consecutive negative results for SNPG, false negatives are still inevitable.
In summary, decreased WBC*LYM was observed in SARS-CoV-2-infected patients compared with SARS-CoV-2-negative patients with suspected symptoms in this study. WBC*LYM can be used as a supplementary parameter to help clinicians in their first contact with suspected patients awaiting SARS-CoV-2 RT-PCR results.
Research funding: None declared.
Author contributions: Chi Zhang and Yei Fang contributed to the intellectual content of this paper and drafted and revised the manuscript. Linjing Zhang, Xing Chen and Hui Zhang contributed to collection and analysis of the experiment data. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
Informed consent: Informed consent was obtained from all individuals included in this study.
Ethical approval: The study protocol was approved by the Tongji Hospital Ethics Committee for Research in Health.
References
1. Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727–33.10.1056/NEJMoa2001017Search in Google Scholar
2. WHO. Coronavirus disease 2019. https://www.who.int/emergencies/diseases/novel-coronavirus-2019 [accessed Feb 18, 2020].Search in Google Scholar
3. Gorbalenya AE, Baker SC, Baric RS, de Groot RJ, Drosten C, Gulyaeva AA, et al. Severe acute respiratory syndrome-related coronavirus: the species and its viruses – a statement of the Coronavirus Study Group. bioRxiv 2020; published online Feb 11. DOI: 2020.02.07.937862 (preprint).10.1101/2020.02.07.937862Search in Google Scholar
4. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020;395:507–13.10.1016/S0140-6736(20)30211-7Search in Google Scholar
5. Cunha BA, Connolly JJ, Irshad N. The clinical usefulness of lymphocyte: monocyte ratios in differentiating influenza from viral non-influenza-like illnesses in hospitalized adults during the 2015 influenza A (H3N2) epidemic: the uniqueness of HPIV-3 mimicking influenza A. Eur J Clin Microbiol Infect Dis 2016;35:155–8.10.1007/s10096-015-2521-8Search in Google Scholar PubMed PubMed Central
6. Liu J, Li S, Liu J, Liang B, Wang X, Wang H, et al. Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. MedRxiv 2020; posted online Feb 22. DOI: 2020.02.16.20023671 (preprint).Search in Google Scholar
7. Liu J, Liu Y, Xiang P, Pu L, Xiong H, Li C, et al. Neutrophil-to-lymphocyte ratio predicts severe illness patients with 2019 novel coronavirus in the early stage. MedRxiv 2020; posted online Feb 12. DOI: 2020.02.10.20021584 (preprint).10.1101/2020.02.10.20021584Search in Google Scholar
8. World Health Organization. Clinical management of severe acute respiratory infection when novel coronavirus (nCoV) infection is suspected. Interim guidance, World Health Organization (WHO). 2020. https://www.who.int/publications-detail/clinical-management-of-severe-acute-respiratory-infection-when-novel-coronavirus-(ncov)-infection-is-suspected.10.15557/PiMR.2020.0003Search in Google Scholar
9. Channappanavar R, Perlman S. Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology. Semin Immunopathol 2017;3:529–39.10.1007/s00281-017-0629-xSearch in Google Scholar PubMed PubMed Central
10. Chu H, Zhou J, Wong BH, Li C, Chan JF, Cheng ZS, et al. Middle East respiratory syndrome coronavirus efficiently infects human primary T lymphocytes and activates the extrinsic and intrinsic apoptosis pathways. J Infect Dis 2016;213:904–14.10.1093/infdis/jiv380Search in Google Scholar PubMed PubMed Central
©2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial
- Critical role of laboratory medicine in the global response to the COVID-19 pandemic
- Reviews
- Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis
- COVID-19: progression of disease and intravascular coagulation – present status and future perspectives
- IFCC Recommendations
- Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC taskforce evaluation of the latest evidence
- Biosafety measures for preventing infection from COVID-19 in clinical laboratories: IFCC Taskforce Recommendations
- Opinion Papers
- The critical role of laboratory medicine during coronavirus disease 2019 (COVID-19) and other viral outbreaks
- Potential preanalytical and analytical vulnerabilities in the laboratory diagnosis of coronavirus disease 2019 (COVID-19)
- Laboratory diagnostics within a modular hospital at the time of Coronavirus disease 2019 (COVID-19) in Wuhan
- Original Articles
- Analytical performances of a chemiluminescence immunoassay for SARS-CoV-2 IgM/IgG and antibody kinetics
- Comparison of throat swabs and sputum specimens for viral nucleic acid detection in 52 cases of novel coronavirus (SARS-Cov-2)-infected pneumonia (COVID-19)
- Routine blood tests as a potential diagnostic tool for COVID-19
- Laboratory predictors of death from coronavirus disease 2019 (COVID-19) in the area of Valcamonica, Italy
- The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study
- Prominent changes in blood coagulation of patients with SARS-CoV-2 infection
- The value of urine biochemical parameters in the prediction of the severity of coronavirus disease 2019
- Letters to the Editor
- COVID-19 infections are also affected by human ACE1 D/I polymorphism
- No significant correlation between ACE Ins/Del genetic polymorphism and COVID-19 infection
- ACE Ins/Del genetic polymorphism and epidemiological findings in COVID-19
- Laboratory abnormalities in patients with COVID-2019 infection
- Laboratory abnormalities in children with novel coronavirus disease 2019
- Clinical laboratory and SARS-CoV-2 infection: where do we stand?
- Clinical chemistry tests for patients with COVID-19 – important caveats for interpretation
- Antibody tests for COVID-19: drawing attention to the importance of analytical specificity
- Erythrocyte sedimentation rate is associated with severe coronavirus disease 2019 (COVID-19): a pooled analysis
- One disease, different features: COVID-19 laboratory and radiological findings in three Italian patients
- Decreased “WBC*LYM” was observed in SARS-CoV-2-infected patients from a fever clinic in Wuhan
- Assessment of immune response to SARS-CoV-2 with fully automated MAGLUMI 2019-nCoV IgG and IgM chemiluminescence immunoassays
- Coinfection of SARS-CoV-2 and multiple respiratory pathogens in children
- The friendly use of chloroquine in the COVID-19 disease: a warning for the G6PD-deficient males and for the unaware carriers of pathogenic alterations of the G6PD gene
- Potential interference of hydroxychloroquine-glucuronide metabolite on therapeutic drug monitoring of hydroxychloroquine using a mass spectrometry detector
Articles in the same Issue
- Frontmatter
- Editorial
- Critical role of laboratory medicine in the global response to the COVID-19 pandemic
- Reviews
- Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis
- COVID-19: progression of disease and intravascular coagulation – present status and future perspectives
- IFCC Recommendations
- Molecular, serological, and biochemical diagnosis and monitoring of COVID-19: IFCC taskforce evaluation of the latest evidence
- Biosafety measures for preventing infection from COVID-19 in clinical laboratories: IFCC Taskforce Recommendations
- Opinion Papers
- The critical role of laboratory medicine during coronavirus disease 2019 (COVID-19) and other viral outbreaks
- Potential preanalytical and analytical vulnerabilities in the laboratory diagnosis of coronavirus disease 2019 (COVID-19)
- Laboratory diagnostics within a modular hospital at the time of Coronavirus disease 2019 (COVID-19) in Wuhan
- Original Articles
- Analytical performances of a chemiluminescence immunoassay for SARS-CoV-2 IgM/IgG and antibody kinetics
- Comparison of throat swabs and sputum specimens for viral nucleic acid detection in 52 cases of novel coronavirus (SARS-Cov-2)-infected pneumonia (COVID-19)
- Routine blood tests as a potential diagnostic tool for COVID-19
- Laboratory predictors of death from coronavirus disease 2019 (COVID-19) in the area of Valcamonica, Italy
- The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study
- Prominent changes in blood coagulation of patients with SARS-CoV-2 infection
- The value of urine biochemical parameters in the prediction of the severity of coronavirus disease 2019
- Letters to the Editor
- COVID-19 infections are also affected by human ACE1 D/I polymorphism
- No significant correlation between ACE Ins/Del genetic polymorphism and COVID-19 infection
- ACE Ins/Del genetic polymorphism and epidemiological findings in COVID-19
- Laboratory abnormalities in patients with COVID-2019 infection
- Laboratory abnormalities in children with novel coronavirus disease 2019
- Clinical laboratory and SARS-CoV-2 infection: where do we stand?
- Clinical chemistry tests for patients with COVID-19 – important caveats for interpretation
- Antibody tests for COVID-19: drawing attention to the importance of analytical specificity
- Erythrocyte sedimentation rate is associated with severe coronavirus disease 2019 (COVID-19): a pooled analysis
- One disease, different features: COVID-19 laboratory and radiological findings in three Italian patients
- Decreased “WBC*LYM” was observed in SARS-CoV-2-infected patients from a fever clinic in Wuhan
- Assessment of immune response to SARS-CoV-2 with fully automated MAGLUMI 2019-nCoV IgG and IgM chemiluminescence immunoassays
- Coinfection of SARS-CoV-2 and multiple respiratory pathogens in children
- The friendly use of chloroquine in the COVID-19 disease: a warning for the G6PD-deficient males and for the unaware carriers of pathogenic alterations of the G6PD gene
- Potential interference of hydroxychloroquine-glucuronide metabolite on therapeutic drug monitoring of hydroxychloroquine using a mass spectrometry detector