Complete blood count as a tool for risk stratification in COVID-19

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BACKGROUND

The COVID-19 pandemic officially ended on May 5, 2023; however, the causative agent of coronavirus infection continues to circulate among the population and cause severe cases [1–4]. A favorable outcome largely depends on adequate and comprehensive initial assessment of the patient’s condition, timely hospitalization, and adjustment of ongoing therapy [1–3]. The generally accepted clinical criteria for severe COVID-19 are:

• body temperature ≥39 °С;
• decreased level of consciousness;
• agitation;
• respiratory rate ≥30 per minute;
• oxygen saturation (SpO₂) ≤93%;
• oxygenation index (PaO₂/FiO₂) ≤300 mm Hg;
• unstable hemodynamics (systolic and diastolic blood pressure: less than 90 and 60 mm Hg, respectively); and
• urine output < 20 mL/h.

During the first wave of SARS-CoV-2 coronavirus infection, in addition to common severity criteria characteristic of many infectious diseases, pathognomonic typical lung lesions based on computed tomography (CT) data were considered [4, 5]. According to statistics, with >50% lung lesion on CT, patient mortality reached 85% [1, 6]. Continuous virus mutation and emergence of new, less pneumotropic strains required more accessible multifactorial analysis of clinical and laboratory parameters, which may be used as predictors of disease severity and outcome [7, 8]. Complete blood count (CBC) is among the most accessible, inexpensive basic laboratory tests in clinical practice. With correct and timely assessment, its results can serve as a “diagnostic navigator” for appropriate strategic decisions when selecting a therapy [9–11]. Existing publications have repeatedly suggested using specific CBC laboratory parameters such as white blood count, lymphocyte count, platelet count, or erythrocyte sedimentation rate (ESR) to predict coronavirus infection severity [6, 12–15]. However, interpreting isolated blood cell parameters is insufficient for a comprehensive understanding of pathogenetic mechanisms or predicting disease course risks and outcomes. A multifactorial and comprehensive assessment of hematopoietic lineage parameters, their ratios, and qualitative changes in formed elements is necessary. This will enable sufficiently accurate early-stage prediction of complication risks and long-term COVID-19 consequences under limited laboratory capabilities.

AIM

To evaluate quantitative and calculated complete blood count parameters depending on disease severity at hospital admission and over time, and to identify predictors of adverse outcomes.

METHODS

Study Design

This was an observational, single-center, retrospective study of medical records of 122 patients admitted and treated between March and July 2021 in the intensive care unit of the N.V. Sklifosovsky Research Institute of Emergency Medicine with confirmed COVID-19 diagnosis (severe course).

Eligibility Criteria

The inclusion criteria in the study were:

• Medical records of patients with confirmed severe COVID-19 diagnosis;
• Diagnosis confirmed no later than three days from disease onset.

COVID-19 diagnosis was confirmed by detecting SARS-CoV-2 RNA in oropharyngeal swabs using polymerase chain reaction. All hospitalized patients received standard comprehensive drug therapy according to the Temporary Methodological Recommendations of the Ministry of Health of the Russian Federation [4].

Study Setting

The study was conducted at the N.V. Sklifosovsky Research Institute of Emergency Medicine.

Study Duration

Medical records from patients admitted and treated at the N.V. Sklifosovsky Research Institute of Emergency Medicine between March and July 2021 were analyzed for one month, in September 2021.

Intervention

For all patients, venous blood was drawn upon admission and on hospitalization day 7 into BD Vacutainer^® tubes [Becton Dickinson, United States of America (USA)] with K2 EDTA anticoagulant (dipotassium ethylenediaminetetraacetic acid salt), followed by analysis using a hematology analyzer connected to a laboratory information system for direct result transfer, eliminating registration error risks.

Main Study Outcome

Quantitative and computational analysis of CBC parameters was performed in comparison with reference normal values and between the two formed groups during the observation period (first and seventh day of hospitalization).

Additional Study Outcomes

Additionally, the morphometric characteristics of blood cells were studied.

Subgroup Analysis

Depending on the disease outcome, all patients were divided into two groups:

• Group 1, survivors;
• Group 2, deceased persons.

Outcomes Registration

The following patient blood parameters were assessed using the ADVIA^® 2120i hematology analyzer (Siemens Healthineers, USA):

• red blood cell count (×10¹²/L)
• platelet count (×10⁹/L)
• white blood count (×10⁹/L)
• hemoglobin concentration (g/dL)
• hematocrit (%)
• mean corpuscular volume (fL)
• mean corpuscular hemoglobin (pg)
• red cell distribution width (%)
• ESR (mm/h).

The WBC differential values were calculated, including relative (%) and absolute (×10⁹/L) counts of neutrophils, lymphocytes, monocytes, and eosinophils. Additionally, neutrophil-to-lymphocyte ratio (NEU/LYM) and platelet-to-lymphocyte ratio (PLT/LYM) were calculated, as well as the systemic inflammation index (SII), which represents the ratio of the product of absolute neutrophil and platelet counts to the absolute lymphocyte count [10, 16–17].

Morphometric characteristics of blood cells were studied by light microscopy (Romanowsky–Giemsa staining, immersion, ×1000) using an MT biological microscope with accessories, model MT53001 (Meiji Techno, Japan).

Ethics Approval

The study protocol was reviewed by the Biomedical Ethics Committee of the N.V. Sklifosovsky Research Institute for Emergency Medicine (Protocol No. 4-25 dated March 25, 2025). The committee concluded that ethics approval was not required because the study was retrospective in nature; all patient data were anonymized, and informed consent was not necessary.

Statistical Analysis

Sample size calculation principles: patient sample size was not pre-calculated.

Statistical Methods. The data were processed using SPSS^® 20.0 (SPSS Inc., Chicago, IL, USA) and MedCalc^® 11.5.00 (Medcalc Software, Belgium). Distribution type was assessed using the Shapiro–Wilk test (Shapiro–Wilk W-test) [18]. As the data distribution was non-normal, positional measures were selected: median Q2 (Me) and interquartile range represented by Q1 and Q3, corresponding to the 50th, 25th, and 75th percentiles, respectively [15, 19]. The Mann–Whitney U test was used to evaluate intergroup differences. Correlation analysis employed Spearman’s coefficient (r). Differences were considered statistically significant at p < 0.05.

RESULTS

Participants

The study included 122 patients, among them 42.6% women and 57.4% men, median age of 62.0 years [53.0; 75.0]. Depending on the disease outcome, all patients were divided into two groups comparable by sex:

• Group 1, survivors (n = 61). Among them, 45.9% were women and 54.1% were men.
• Group 2, deceased persons (n = 61). Among them, 39.5% were women and 60.5% were men.

Patients in group 2 were significantly older than those in group 1: 73.0 [62.0; 83.0] and 57.0 years [46.8; 63.0], respectively.

Primary Results

Data obtained during statistical processing of hemograms from patients with severe COVID-19 are presented in Table 1. Analysis of the distribution pattern of CBC parameters indicated in Table 1 revealed that group 1 patients exhibited elevated ESR, absolute lymphopenia (with no correlation between them; r = −0.063), and relative eosinopenia upon admission. In 27.9% of cases, total lymphocyte counts decreased below 1.0×10⁹/L. Additionally, increased NEU/LYM and PLT/LYM ratios were observed, with the latter being most indicative. SII also showed an upward trend, though median values remained within reference ranges. Correlation coefficients between NEU/LYM, PLT/LYM, SII, and ESR were r = 0.065, 0.239, and 0.114, respectively.

 

Table 1. Changes in complete blood count parameters in patients with severe COVID-19 with favorable and fatal outcomes

Reference values	Day 1 of hospitalization		Day 7 of hospitalization
	Group 1	Group 2	Group 1	Group 2
Hemoglobin, g/L
11.7–15.5	13.0 [12.2; 13.8]	11.3 [9.6; 12.8]2	12.2 [11.4; 13.2]	9.8 [8.6; 11.2]4
Red blood cells, 1012/L
3.8–5.1	4.4 [4.0; 4.6]	3.9 [3.4; 4.4]2	4.2 [3.9; 4.5]	3.4 [3.0; 4.0]4
Hematocrit, %
35–45	37.2 [34.7; 40.9]	33.6 [29.2; 36.7]2	35.8 [33.0; 38.1]	29.3 [26.2; 33.4]4
Red cell distribution width, %
11.6–14.8	14.1 [13.8; 14.7]	15.6 [14.4; 17.1]2	14.5 [13.8; 15.2]	15.6 [14.8; 16.7]
Mean corpuscular volume, fL
81–100	86.4 [83.3; 89.9]	86.6 [84.2; 90.5]	86.9 [84.1; 90.4]	87.1 [83.9; 90.0]
Mean corpuscular hemoglobin, pg
27–34	29.8 [28.5; 31.1]	29.3 [28.1; 30.6]	30.0 [28.1; 31.0]	29.2 [27.6; 30.0]
Platelets, ×109/L
150–400	196.0 [153.8; 273.7]	189.0 [108.0; 256.0]2	312.0 [236.0; 390.0]4	178.0 [128.0; 269.0]
White blood cells, 109/L
4.5–9.0	5.2 [3.8; 7.7]	9.5 [6.5; 14.1]2	6.1 [4.7; 7.7]	8.6 [5.0; 14.3]
Neutrophils, %
48–78	66.3 [54.9; 77.6]	87.0 [77.5; 91.6]2	60.3 [52.3; 71.5]	88.7 [84.3; 90.5]
Lymphocytes, %
19–37	22.4 [14.8; 29.9]	7.4 [3.3; 11.4]3	24.5 [17.5; 32.9]	5.6 [4.4; 8.8]4
Monocytes, %
3–11	6.6 [4.3; 8.2]	3.4 [2.2; 5.7]2	7.5 [4.9; 9.5]	3.4 [2.7; 5.0]
Eosinophils, %
1–5	0.8 [0.3; 1.6]1	0.2 [0.1; 0.3]2	1.9 [1.2; 3.0]4	0.2 [0.1; 0.6]
Neutrophils, abs.
1.56–6.13	3.2 [2.3; 5.1]	7.9 [5.1; 12.9]2	3.7 [2.5; 4.9]	8.1 [4.1; 12.9]
Lymphocytes, abs.
1.18–3.74	1.05 [0.74; 1.40]1	0.66 [0.48; 1.01]2	1.6 [0.9; 1.9]4	0.63 [0.39; 0.78]4
Monocytes, abs.
0.2–0.95	0.31 [0.21; 0.46]	0.31 [0.20; 0.50]	0.41 [0.28; 0.54]	0.28 [0.19; 0.45]
Eosinophils, abs.
< 0.7	0.03 [0.02; 0.11]	0.02 [0.01; 0.03]2	0.12 [0.07; 0.19]4	0.02 [0.01; 0.06]
Erythrocyte sedimentation rate, mm/h
< 20	30 [18; 42]1	29 [20; 44]	21 [11; 31]4	37 [16; 51]4
Neutrophil-to-lymphocyte ratio
0.8–3.0	2.94 [1.82; 5.24]1	11.26 [6.24; 23.20]2	2.41 [1.62; 4.02]4	15.44 [9.76; 20.58]4
Platelet-to-lymphocyte ratio
88.9–150.0	193.3 [144.1; 273.1]1	282.2 [167.7; 484.0]2	211.0 [150.5; 294.8]	362.5 [201.3; 519.74
Systemic inflammation index
270–711	542.8 [370.9; 1194.2]1	2206.5 [919.7; 5013.8]2	728.5 [437.7; 1178.5]	2271.3 [1124.7; 5162.0]4

Note. Results are presented as Me [Q25; Q75], where Me is the median, and Q25 and Q75 are the 25th and 75th percentiles, respectively.¹, significant differences compared to reference values, р < 0.05; ², significant differences compared with group 1, р < 0.05; ³, significant differences compared with group 1, р < 0.001; ⁴, significant differences compared to data from hospitalization day 1, р < 0.05.

 

Comparing group 2 parameters upon admission (see Table 1), we observed decreased total lymphocyte and eosinophil counts alongside increased absolute neutrophil counts. Lymphocyte counts below the critical threshold (1.0×10⁹/L) were noted in 72.1% of cases. No correlation existed between ESR and lymphocyte count (r = −0.215). These changes manifested in elevated NEU/LYM and PLT/LYM ratios, as well as SII. The most significant changes occurred in SII (see Table 1). No correlation was found between ESR and these parameters (r = 0.212, 0.189, and 0.213, respectively). Decreased hematocrit combined with low erythrocyte indices and increased red cell distribution width indicated emerging anisocytosis.

On day 7 of hospitalization, group 1 patients demonstrated significant positive changes in hemogram parameters (see Table 1). Lymphocyte, eosinophil, and platelet counts returned to normal alongside substantial ESR reduction. Early clinical improvement correlated with decreased NEU/LYM ratio, increased PLT/LYM ratio, and stable SII relative to reference values.

In group 2 patients, hemogram parameters on day 7 of hospitalization showed almost no change from admission values. However, progressive anemia was noted, with decreased hemoglobin, hematocrit, and red blood cell count alongside increased anisocytosis. Concurrently, NEU/LYM, PLT/LYM ratios, SII, and ESR showed significant increases.

Secondary Results

Blood smear microscopy in patients with severe COVID-19 at admission revealed specific morphological features of lymphocytes (Fig. 1): most cells had polymorphic nuclei of irregular round shape, with blurred chromatin structure without coarse clumping; cytoplasm varied in volume and staining, appearing blue with marginal basophilia.

 

Fig. 1. Lymphocyte morphology in patients with severe COVID-19 at admission. Romanowsky–Giemsa staining, immersion, ×1000: 1, polymorphic nuclei of irregular rounded shape; 2, blue cytoplasm with marginal basophilia.

 

Smear microscopy also identified changes in neutrophil morphology (Fig. 2), manifested by hypogranularity and pelgerization of neutrophil nuclei, indicating dysplasia of the granulocytic lineage that developed during the disease.

 

Fig. 2. Morphology of neutrophils and erythrocytes in patients with severe COVID-19 at admission. Romanowsky–Giemsa staining, immersion, ×1000. 1, cytoplasmic hypogranularity; 2, neutrophil nuclear hyposegmentation (Pelger–Huët anomaly); 3, echinocytes.

 

Moreover, alterations in erythrocyte morphology manifested as poikilocytosis with a predominance of abnormal forms, such as echinocytes, were frequently observed¹.

DISCUSSION

Summary of Primary Results

In patients with severe COVID-19 and unfavorable outcomes, more pronounced changes in CBC were observed at all follow-up periods: neutrophilia, lymphopenia, eosinopenia, thrombocytopenia, and a sharp increase in ESR by day 7. The values of NEU/LYM and PLT/LYM ratios, as well as the SII, were significantly higher compared to similar parameters in patients with severe COVID-19 and favorable outcomes.

Discussion of Primary Results

The primary goal of treating severe COVID-19 is to prevent the cytokine storm and acute respiratory distress syndrome, as well as associated coagulation complications leading to multiple organ failure. Proper interpretation of CBC becomes particularly important in these conditions, as its results become available to physicians quickly and can serve as a “diagnostic navigator” for making adequate strategic decisions. Direct damage to immune system cells and organs by the SARS-CoV-2 virus, its toxic effects, and cytokine-induced apoptosis of lymphocytes lead to lymphopenia, which is a pathognomonic sign of coronavirus infection present in all COVID-19 patients [3, 20–22]. Our study results indicate that the degree of lymphocyte count reduction depends on COVID-19 severity, being an accurate indicator of patient status. There is no association between lymphopenia and ESR changes; therefore, ESR values alone should not be relied upon when assessing the risk of adverse events. An isolated decrease in lymphocyte count below the critical value of 1.0×10⁹/L during the second week of illness, established in some studies, is not an obligatory criterion for poor prognosis but serves as a marker of complicated COVID-19 [2, 12, 13, 23]. The probability of adverse events increases when lymphocyte count falls below 0.74×10⁹/L.

However, comprehensive assessment of all CBC parameters is necessary for complete understanding of pathogenetic mechanisms and predicting COVID-19 progression risks. Thus, mortality risk significantly increases when the following combination is present during the second week of illness: severe lymphopenia (< 0.74 × 10⁹/L) with adverse changes in other CBC parameters:

• Concurrent increase in total white blood count;
• Imbalance in WBC differential manifested by simultaneous decrease in lymphocytes and increase in neutrophils, which is a key indicator of inflammatory process intensity in various pathological conditions [17, 24].

Many studies have demonstrated a correlation between cellular ratio indices and the likelihood of certain adverse events. The NEU/LYM ratio is of particular importance for determining disease prognosis in patients, as its increase is associated with higher risks of complications and increased mortality rates in various pathologies, including COVID-19 [10, 14–16]. NEU/LYM ratio values in COVID-19 primarily reflect the degree of lung tissue damage, lymphocytic infiltration, secondary bacterial infection, and the inflammation prevalence in other organs and tissues. Disorders of granulocytic myelopoiesis, manifested as absolute and relative neutrophilia combined with myeloid-type leukemoid reaction, indicate systemic inflammation and high levels of inflammatory cytokines [25]. Increased neutrophil counts enhance phagocytosis and degradation of vascular tissues, leading to progressive changes in vessel walls, reduced blood flow, and elevated thrombosis risk. Massive cytokine release and uncontrolled inflammatory response combined with coagulation complications result in multiple organ failure [26]. This study demonstrates that the NEU/LYM ratio correlates with COVID-19 severity, and values ≥6.24 indicate a risk of fatal outcomes in patients with severe disease progression.

Further deterioration of patients’ conditions is associated with suppression of bone marrow progenitors caused by direct SARS-CoV-2 viral cell damage, its toxic effects, cytokine hyperproduction, and progressive disease-related hypoxia. Hematopoietic impairment manifests as cytopenic syndrome. Reduced percentage and absolute counts of monocytes and eosinophils in patients with severe COVID-19 and unfavorable outcomes are associated with adaptive immune suppression, significantly worsening disease prognosis [27]. According to Pereira et al. [8], patients with extremely severe COVID-19 exhibit leukopenia due to profound hematopoietic suppression.

Decreased hemoglobin levels and red blood cell count, along with reduced hematocrit, indicated dysplastic disorders in erythroid lineage cells in patients with severe COVID-19 and unfavorable outcomes. An increased number of abnormally sized erythrocytes was recorded. Anemia not only exacerbates existing hypoxia and ischemia of organs and tissues but also promotes hypercoagulation progression, consequently increasing the risk of thrombotic complications and mortality [28].

A significant factor worsening the COVID-19 prognosis is concomitant thrombocytopenia, attributed not only to suppressed platelet production but also, to a greater extent, to abnormal coagulopathy observed in severe disease cases [29, 30]. A substantial decrease in platelet count in patients with severe COVID-19 and unfavorable outcomes indicates secondary microthrombosis in the microvasculature of the lungs and other organs, resulting from capillary wall inflammation, endothelial dysfunction, and hemostasis system disruptions in COVID-19. Disorders of the blood coagulation system combined with systemic vasculitis become the primary factor driving multiorgan failure and high mortality risk [31–34].

In our study, pronounced shifts in platelet, lymphocyte, and neutrophil counts were accompanied by changes in the PLT/LYM ratio and SII. At values ≥282.2 and ≥2206.5, respectively, patients showed a significantly increased probability of unfavorable prognosis. Hemogram characteristics associated with elevated lethal outcome risk in severe COVID-19 patients are presented in Fig. 3.

 

Fig. 3. Hemogram characteristics associated with increased risk of lethal outcome in patients with severe COVID-19. ESR, erythrocyte sedimentation rate.

 

These findings demonstrate that identifying predictors of adverse outcomes will enable early detection of patients with severe and prognostically unfavorable COVID-19 progression at hospital admission, as well as facilitate personalized treatment planning. Our data are fully consistent with results from multicenter studies in other countries [2, 5–10, 14, 17, 23, 34].

Observation has shown that an independent prognostic factor for lethal outcome in patients with severe COVID-19 is the absence of positive changes in lymphocyte count by the beginning of the second week of illness, which is consistent with data from Zhou et al. [23]. Significant criteria for poor prognosis include:

• progressive increase in ESR
• increased SII
• increased NEU/LYM and PLT/LYM ratios
• progression of cytopenic syndrome.

The introduction of a criterion involving two significant time points (days 1–3 of the disease and days 8–10 from symptom onset) and active monitoring of CBC parameters in patients with severe COVID-19 will enable timely correction of therapeutic measures and prevent adverse outcomes. The results confirm the important pathogenetic role of blood cells in severe COVID-19 and substantiate the informativeness and significance of laboratory monitoring of hematological parameters. Given the fundamental role of inflammatory reactions in the COVID-19 pathogenesis, incorporating this simple and cost-effective indicator into the rapid assessment of severe COVID-19 patients’ condition, enabling risk stratification for adverse outcomes, represents undoubted scientific-practical interest and necessitates further study of its applications across diverse patient cohorts.

Study Limitations

This study had certain limitations due to its retrospective design. Furthermore, when planning and conducting the study, the sample size needed to achieve the required statistical power of the results was not calculated. Consequently, the study sample obtained in this study cannot be considered adequately representative, precluding extrapolation of the results and their interpretation to the general population of similar patients beyond this study.

CONCLUSION

A complete blood count is an inexpensive, accessible, yet highly valuable prognostic tool for managing COVID-19 patients. Comprehensive assessment of all hematopoietic lineage parameters, their ratios, and qualitative changes in formed elements allows predicting risks for severe disease progression and complications. Our study demonstrates that lymphocyte count and NEU/LYM ratio serve as early sensitive biomarkers indicating infection severity, therapy effectiveness, and COVID-19 outcome prognosis.

ADDITIONAL INFORMATION

Author contributions: V. B. Poluektova, E. V. Klychnikova: conceptualization, investigation, formal analysis, writing—original draft; S. S. Petrikov: conceptualization, writing—review & editing; M. V. Sankova: formal analysis, resources search and analysis, writing—original draft; S. N. Larina: formal analysis, writing—review & editing; E. V. Tazina: writing—review & editing, formal analysis; E. V. Volchkova: writing—review & editing. All the authors approved the version of the manuscript to be published and agreed to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethics approval: The study protocol was reviewed by the Biomedical Ethics Committee of the N. V. Sklifosovsky Research Institute for Emergency Medicine (Protocol No. 4-25 dated March 25, 2025). The committee concluded that ethics approval was not required because the study was retrospective in nature, all patient data were anonymized, and informed consent was not necessary.

Funding sources: No funding.

Disclosure of interests: The authors have no relationships, activities, or interests for the last three years related to for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality: No previously published material (text, images, or data) was used in this work.

Data availability statement: The editorial policy regarding data sharing does not apply to this work.

Generative AI: No generative artificial intelligence technologies were used to prepare this article.

Provenance and peer-review: This paper was submitted unsolicited and reviewed following the standard procedure. The peer review process involved two members of the editorial board.

 

¹ Echinocytes are cells that have lost their biconcave disk shape and feature numerous uniformly distributed short spines with blunt ends of approximately equal size on their surface.

About the authors

Victoria B. Poluektova

Sechenov First Moscow State Medical University (Sechenov University); Sklifosovsky Research Institute for Emergency Medicine

Author for correspondence.
Email: viktoriya211@mail.ru
ORCID iD: 0000-0002-5053-0312
SPIN-code: 7290-8377

MD, Cand. Sci. (Medicine)

Russian Federation, 8 Trubetskaya st, bldg 2, Moscow, 119992; Moscow

Sergey S. Petrikov

Sklifosovsky Research Institute for Emergency Medicine

Email: petrikovss@sklif.mos.ru
ORCID iD: 0000-0003-3292-8789

MD, Dr. Sci. (Medicine), Professor, Corresponding Member of the Russian Academy of Sciences

Russian Federation, Moscow

Elena V. Klychnikova

Sklifosovsky Research Institute for Emergency Medicine

Email: klychnikovaev@mail.ru
ORCID iD: 0000-0002-3349-0451
SPIN-code: 6311-6795

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

Maria V. Sankova

Sechenov First Moscow State Medical University (Sechenov University)

Email: cankov@yandex.ru
ORCID iD: 0000-0003-3164-9737
SPIN-code: 2212-5646

MD

Russian Federation, Moscow

Svetlana N. Larina

Sechenov First Moscow State Medical University (Sechenov University)

Email: snlarina07@yandex.ru
ORCID iD: 0000-0003-0188-543X
SPIN-code: 2906-0605

Cand. Sci. (Biology)

Russian Federation, Moscow

Elizaveta V. Tazina

Sklifosovsky Research Institute for Emergency Medicine

Email: ltazina@yandex.ru
ORCID iD: 0000-0001-6079-1228
SPIN-code: 1994-3086

Cand. Sci. (Pharmacy)

Russian Federation, Moscow

Elena V. Volchkova

Sechenov First Moscow State Medical University (Sechenov University)

Email: antononina@rambler.ru
ORCID iD: 0000-0003-4581-4510
SPIN-code: 3342-4681

Dr. Sci. (Medicine), Professor

Russian Federation, Moscow

References

Supplementary files