Blood Count Abnormalities Associated with Death in Patients Infected with SARS-COV-2 at the Ziguinchor EpidemicTreatment Center (ETC) ()
1. Introduction
Since December 2019, a SARS-COV-2 pandemic still called COVID-19 [1] has been raging in the world. This pandemic has spread in less than two months across the globe forcing the World Health Organization to develop recommendations in the direction of restricting human-to-human interactions [1] [2] [3] . These measures were aimed at limiting the spread of the virus and its definitive eradication [1] . The scientific world has been looking for epidemiological, clinical, biological and therapeutic factors associated with susceptibility to this disease and its complications [4] [5] . Among the studies performed, several have concluded that there is a higher risk of death from COVID-19 when the patient is elderly or has other comorbidities [6] [7] [8] . Other studies have shown that the virus, although having a tropism for angiotensin II receptors, in its pathophysiology had hematological repercussions [9] [10] [11] . Thus, abnormalities of the hemogram and hemostasis have been described in patients with COVID-19 [12] [13] . In Ziguinchor, there is an epidemic treatment center (ETC) whose role is the management of cases diagnosed in our region. An initial study was conducted by Diallo K et al. [14] in our region. It revealed the epidemiological, clinical, therapeutic and prognostic characteristics of patients with COVID-19 in Ziguinchor. In a second study, we examined the blood count abnormalities associated with death in patients with COVID-19 admitted to the CTE of Ziguinchor.
2. Methods
Type, setting, patients, place and study period:
In the period of COVID-19 pandemic disease, there was an epidemic treatment center (ETC) in our area in Ziguinchor. We conducted a cross-sectional, descriptive, and analytical study over an 18-month period (March 26, 2020, to September 30, 2021). It included all patients infected with COVID-19 diagnosed by RT-PCR and hospitalized in the ETC.
Criteria of inclusion:
All the patients hospitalized and who had a complete blood count test in the beginning of their admission where included in the study.
Criteria of non-inclusion:
All the patients who did not have a complete blood count test in the beginning of their admission were excluded
Data collection and analysis:
All patients with a blood count at entry were included in our study. We collected 263 records. The parameters included were age, sex, comorbidities, blood count abnormalities, and death rate. All data were entered on EPI data stat version 11.3. We used the chi-square test to establish the correlations between the occurrence of death and the blood count abnormalities found.
We considered the following parameters as blood count abnormalities in adults:
- Anemia: a hemoglobin level below 12 g/dl in women and 13 g/dl in men;
- Polyglobulia: a hemoglobin level above 16 g/dl;
- Thrombocytosis: a platelet count of less than 150 Giga/L;
- Thrombocytosis: a platelet count greater than 450 Giga /L;
- Hyperleukocytosis: a leukocyte count greater than 10,000/mm3;
- Neutrophilia: a neutrophil count greater than 7500/mm3;
- Neutropenia: a neutrophil count below 1500/mm3;
- Lymphocytosis: a lymphocyte count greater than 4000/mm3;
- Lymphopenia: a lymphocyte count below 1500/mm3.
3. Results
Sociodemographic profiles of patients:
The total number of patients was two hundred and sixty-three (263). The mean age was 63.77 years (range 12 - 90 years). The male sex represented 54.75% (n = 144) while the female sex was 45, 25% (n = 119) which makes a sex ratio = 1.21. The age range of 61 - 75 was predominant (42.58%).
Clinical profiles:
The most common pathologies were: Diabetes: 30.03% (n = 79), high blood pressure: 41.04% (n = 108), tuberculosis: 3.80% (n = 10), Chronic kidney disease: 7.98 (n = 21).
The most common symptoms the patients presented were dyspnea (82.82%), fever (67.16%) and cough (64.24%). The proportion of severe cases was around 56.38%.
Death occurred in 37.79% of patients (n = 99), while 59.92% (n = 158) were declared cured and discharged. Relapse occurred in 2.29% (n = 6).
Blood count abnormalities:
For a total number of 263 patients, the blood count abnormalities found were mainly:
- anemia occurring in 121 patients;
- hyperleukocytosis with a predominance of neutrophils in 126;
- lymphopenia in 148 patients;
- Thrombocytopenia in 35 patients.
One hundred and sixty-seven (167) patients had at least two abnormalities of the hemogram.
Among the ninety-nine (99) patients who died, we noted a total of 290 blood count abnormalities.
We noted a significant difference for lymphopenia and hyperleukocytosis.
4. Discussion
The occurrence of the COVID-19 pandemic has led to numerous studies that have resulted in a better understanding of the epidemiology, clinical and biological signs and therapeutic modalities. This work has been carried out on various populations with individual or collective intrinsic characteristics [4] [5] [8] . This updated knowledge has allowed us to discuss our results and to compare them with results from elsewhere. In Ziguinchor, the first study was conducted at the epidemic treatment center (CTE) by Diallo K et al. [14] . It identified the epidemiological, clinical and biological profiles as well as the criteria for severity, prognosis and evolution of hospitalized patients. The present study, conducted in the same ETC, focused on the haemogram abnormalities associated with the death of patients. It gave the following results.
Socio-demographic profiles of patients:
In this study, we noted a male predominance and the average age was 60 ± 14 years [12 - 93 years] (Table 1). However, the majority of people were aged at least 60 (64.63%). These demographic aspects were found in several studies in Africa [15] [16] [17] . Other studies in China and the USA have found similar results [5] [18] [19] [20] . In all these studies, infected patients were relatively old. This could be explained by the vulnerability of the elderly to the disease, probably due to the decline of their immune defenses. The male sex represented 54.75% (n = 144) while the female sex was 45.25% (n = 119) which makes a sex ratio = 1.21 (The study by Diallo K et al. [14] showed a mean age of 45 ± 21 years of which 56.49% were male. The male predominance could be linked to the risky behavior of men who are more inclined to develop certain comorbidities or to become infected. Several studies carried out in different countries have shown that ACE2 would play a decisive role in the higher vulnerability of men, due to higher blood concentrations of ACE2. Certain organs would play the role of “containers” for the virus: the lungs, the digestive system, the kidneys or the testicles.
Clinical profiles:
In this study, the most common symptoms on admission were: dyspnea (82.82%), fever (67.16%) and cough (64.24%) (Table 2). Our results were similar to those of Wu et al. Guan et al. and Zhou et al. who had found cardinal signs occurring in the first days of infection: fever above 37.5˚C (88.7% - 4%), cough (67.8% - 81.1%), sputum (23% - 41.3%) and dyspnea (18.7% - 39.8%) [20] [21] [22] .
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Table 1. Age range of the patients.
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Table 2. Clinical profiles of the patients.
High blood pressure was the most frequent comorbidity (41.04%), followed by diabetes (30.03) (Table 3) This trend was similar to data reported by Zhou et al. [23] in China and by Goyal et al. [24] in the USA. The proportion of severe cases was around 56.38%. This result was close to the one found in the study [25] . Death occurred in 37.79% of patients (n = 99). This relatively high death rate could be explained by the comorbidities described in the literature. A meta-analysis performed by, Osman.M et al. [6] gave the following conclusions: COVID-19-related mortality factors identified in published prognostic studies were age, male gender, presence of comorbidities especially diabetes, severe obesity, cardiovascular disease and chronic lung disease, and presence of biological abnormalities.
Blood count abnormalities associated with SARS-COV-2:
Among the biological abnormalities most commonly found in most studies of SARS-COV-2 disease are those of the blood count and hemostasis [9] [26] [27] . The aim of this first study conducted in our region was to describe the profile of blood count abnormalities in our patients hospitalized for COVID-19 and to compare them with other populations. We obtained the following abnormalities: anemia: 28.13% (n = 121), hyperleukocytosis with neutrophilic predominance: 29.3% (126), lymphopenia: 34.41% (n = 148), thrombocytopenia: 8.16% (n = 35). One hundred and sixty-seven (167) patients had at least two abnormalities of the hemogram (Table 4). Other abnormalities such as hypereosinophilia and thrombocytosis not found in our study were found in others [28] [29] .
Blood count abnormalities associated with SARS-COV-2 death:
Although SARS-COV-2 disease is accompanied by blood count abnormalities, not all of them are life-threatening [10] . This finding was made after studies showed the imputability of certain types of blood count abnormalities in the occurrence of patients hospitalized for COVID-19 [27] [30] . In our study, the abnormalities associated with death were predominantly neutrophilic hyperleukocytosis (p < 0.001) and lymphopenia (p = 0.0001) (Table 4). We did not find any association with anemia or thrombocytopenia. The study by Violetis O.A et al. [7] showed an association between predominantly neutrophilic hyperleukocytosis, thrombocytopenia and lymphopenia with disease severity. A study by Bellan
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Table 3. Clinical outcomes of the patients.
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Table 4. Blood count abnormalities associated with death.
M et al. [31] did not find an association between anemia and mortality with COVID-19, whereas it confirmed an association with lymphopenia and thrombocytopenia. All these findings lead us to understand the usefulness of the blood count in prognosis and therapeutic decisions for patients with COVID-19.
5. Limits
This study has many limitations as it is a retrospective study and therefore based on an established database. Blood count abnormalities can occur in several types of disease. In addition, several clinical data were not available because some of the caregivers were unaware of the existence of a previous comorbidity in their patient. Another limitation was the existence of a language barrier that did not facilitate the taking of history in some patients.
6. Conclusion
Our study was conducted in a context where COVID-19 is rampant in our country with an acceptable cure rate. However, it allowed us to identify the comorbidities associated with severe prognosis and mortality in our patients. We suggest that practitioners have a critical eye for blood count abnormalities that can help establish prognosis and influence management modalities.
Acknowledgements
We extend our thanks to all the staff at the Ziguinchor Epidemic Treatment Center.