Keywords

Obesity, BMI, COVID-19, Severity, Mortality, Risk factors

Introduction

The SARS-CoV-2 coronavirus pneumonia outbreak has rapidly spread globally and COVID-19 was classified as a pandemic by the World Health Organization in March 2020 [1].

COVID-19 is responsible for very broad expressions ranging from mild upper respiratory tract symptoms to acute respiratory distress syndrome (ARDS), hypercoagulability and cytokine storm [2].

However, the analysis of the clinical and demographic characteristics of COVID-19 patients around the world has made it possible to observe a rich semiology, which differs from one region to another and an estimated mortality rate of 3.2% [ 3]. Current literature suggests that complications from obesity potentially increase the severity of COVID-19, particularly in people under the age of 60 [4]. Previous studies have implicated obesity as a factor in the severity of COVID-19 pneumonia [5] increased hospitalizations [6,7] and the risk of invasive mechanical ventilation [8]. Various mechanisms may be involved, namely restrictive ventilatory deficit, lipotoxicity and induction of a pro-inflammatory state [9]. Other studies suggest that overweight and obese patients have a higher risk of more serious clinical symptoms during SARS-CoV-2 infection [10-13]. Overweight and obese patients require more frequent hospitalizations in intensive and semi-intensive care units, regardless of age. In addition, overweight and obese patients have a more frequent need for assisted ventilation due to SARS-CoV-2 pneumonia [8].

It suggest that obesity contributes to clinical manifestations and may influence the progression and prognosis of COVID-19 and it is considered as a potential risk factor of the prognosis of COVID-19 [14].

Algeria like the rest of the world is facing the spread of this pathology, and the first patient carrying this virus was detected on February 25, 2020. Obesity is reaching epidemic proportions in Algeria, and weighs heavily on the system of Algerian health. In 2010, the TAHINA study reported a prevalence of total obesity in Algeria of 9.1% in men and 30.1% in women [15,16]. To effectively fight this epidemic, the Algerian health authorities need to identify the risk factors for severe forms of patients hospitalized for Covid-19 [17,18]. Some authors have suggested that overweight and obese patients should be classified as high risk and should be minimally protected from infection and monitored more closely for SARS-CoV-2 pneumonia [10].

Symptoms of COVID-19 can include fever, cough, breathing difficulties, and organ failure, the severity of the disease can lead patients to intensive care or even death [19]. old age, certain biomarkers such as LDH and D-Dimer, have been identified as risk factors for mortality [18,20]. The aim of this study is to evaluate the association between obesity and the clinical, biological, CT, and prognosis profile of Algerian patients hospitalized for COVID-19 and their mortality risk factors.

Patients and Methods

Study design

This study is the third part of a project analyzing clinical, biological and radiological data from Algerian patients with Covid-19. The first part published, consists of a descriptive study [16], the second part concerned the Analysis of the clinical, biological and radiological severity factors of Algerian patients hospitalized for Covid-19: Comparison between patients with normal and low pulsed oxygen saturation of hemoglobin (SpO ₂ ). As a large part of the methodology of this study was previously described [16,21] only the main points of the methodology will be treated in this paper.

This was a single-center prospective study, which was carried out at Rouiba University Hospital, Algiers (Algeria) (period: March 19, 2020 to September 30, 2021). Only patients with a positive diagnosis of Covid-19 [real-time PCR, antigen test [22-25] and pulmonary CT signs compatible with the infection were included in the study. Lack of BMI on admission was a non-inclusion criterion.

Data sources

The following clinical data were collected from a pre-established observation sheet and hospitalized patient records: Age (year), BMI groups (≥ 30 and < 30 kg/m ² ), sex, active smoking, notion of contact with a suspected or confirmed case of Covid-19, medical history, clinical complaints, Peripheral oxygen saturation (SpO ₂ ) at admission, length of hospital stay. Body weight was measured, height was self-reported, and indeed it was difficult to measure the height of the patients due to the clinical condition of the patients and to prevent any risk of SARS-CoV-2 transmission. Body mass index (BMI) was calculated using the usual formula (weight [kilograms]/height squared [square meters]) and categorized into five standard groups on the basis of National Heart, Lung, and Blood Institute criteria [26]: Insufficient BMI, < 18.5 kg/m ² ; reference category, 18.5 kg/m ² at < 25 kg/m ² ; overweight, 25 kg/m ² to < 30 kg/m ² ; and obesity was defined as a BMI ≥ 30 kg/m ² .

A standard laboratory assessment and a chest CT without a contrast agent were performed [ 16 ]. The prognostic was verified, and the healing, death, or transfers to intensive care were noted.

Statistical analysis

Quantitative and qualitative data were expressed as means ± standard deviations, and number (%), respectively. Missing data were removed from statistical analyzes [27]. Student's T-test and Pearson's Chi-square test were used to compare quantitative and qualitative data from the two groups, respectively. The results were entered using the Statistica software (Statistica Kernel version 6; Stat Soft. France). A significance level < 5% was retained.

Results

Among the 705 patients hospitalized and were confirmed Covid-19, in the department of pulmonology. Of these, 194 were excluded because anthropometric data was missing at admission. The 511 patients selected were divided into two groups: obese-group (137 patients) and non-obese group (374 patients).

Clinical profile and medical complaints

Table 1 exposes the characteristics and medical background of patients. Compared to the non-obese group, the obese-group included higher percentages of females and patients aged < 50 years. However, the two groups were age matched. Included lower percentage of smokers, have higher percentage of hypertendue and have similar medical background.

Table 2 exposes the clinical complaints and physical exam data of patients. The two groups have similar clinical complaints and similar physical exam’ data (except for dyspnea: Compared to the non-obese group, the obese-group included a higher percentage of patients with dyspnea, with anosmia and her with hemoptysis), and lower oxygen saturation level at admission.

Table 3 presents the biological (ESR and CRP) and hematological data of patients. The two groups had similar biological and hematological data and included similar percentage of patients having anemia, polycythemia, lymphopenia, basocythemia, hyperleukocytosis, thrombocytopenia, thrombocytosis, biological inflammatory syndrome, high CRP or ESR, but a lower level of leucopenia.

Table 4 presents the biochemical data of patients. Compared to the non-obese group, the obese-group have a higher value of LDH, a higher value of sodium, and to a lesser degree AST and creatinine.

Table 5 presents the CTs’ data of patients, length of hospitalization and patients’ issues.

The two groups have radiological data without significant differences, except for the CT extension of more than 75% more marked in the obese group.

The two groups have a similar duration of hospitalization also have an equal frequency of death and include identical percentages of patients transferred to intensive care.

Table 6 exposes the characteristics, and factors associated with in-hospital mortality.

Compared to the survivor group, the non-survivor group had higher percentages of men, older ages, and more comorbidities (heart disease, hypertension, diabetes COPD, and chronic kidney disease, but the same percentage of asthma. The non-survivor group included a higher frequency of dyspnea and a lower level of saturation. Based on the biological profile, the non-survivor group included a higher level of polynuclear neutrophils, LDH, and C-reactive protein, and a higher number of patients with D-dimers greater than 1600 ng/ml and a higher level of kaliemia. On the other hand, the same group included more patients with an extent of lesions greater than 50%.

Discussion

A few studies were available in the North African environment to assess the risk factors of dying during hospitalizations of patients with COVID-19. Our results could give a model to evaluate risk and use it at convenience in acute care settings.

In this study, we collected data from 511 cases of COVID-19. The cohort was a random group of patients representing the real situation of patients hospitalized in our department with 26.8% of obese patients, although obesity represents according to the tahina study [15] 21.24% of the Algerian population. In a large New York study of patients hospitalized for COVID-19, 41.7% had a body mass index (BMI) > 30 kg/m ² and 19.0% a BMI > 35 kg/m ² [28]. Analysis of the data by BMI identified 2 groups with an average BMI of (33.7 versus 25.7) in the whole sample, and of (33.8 versus 25.8) in subjects less than 50-years-old. In our study, the obese vs. non-obese group had higher percentages of women and patients under the age of 50. Comparable results were found in an Italian study, where the relationship between obesity and COVID-19 does not appear evident in the general population, on the other hand it was particularly clear in the youngest subjects [29].

In our study of patients under 50 infected with COVID-19, BMI was similar to the mean BMI of the entire sample, while in other studies in patients of under 50 years infected with SARS-CoV-2 the average BMI was higher, and this index seemed to decrease with age in COVID-19 patients [30-32]. The results suggest that obesity may be more prominent in young patients with COVID-19.

The comorbidities in the high BMI group were particularly less pronounced in the cohort of patients under 50, with fewer underlying illnesses such as hypertension, metabolic disease, diabetes and dysthyroidism, contrary to some studies already reported [6,33-35].

The literature data precise, that the effect of obesity on COVID-19 was independent of comorbidities, such as diabetes, hypertension, and cardiovascular disease. This assumes a significant pathophysiological link between excessive adiposity and severe COVID-19 disease [11,30,36,], according to Gao, et al. [37] Obesity has tripled the risk of worsening COVID-19.

Obesity induces T cell depletion through constant low-grade inflammation, which impairs the immune response and the ability to eradicate the virus from the host [37,38]. The lack of activity in obesity may also interfere with the activation of immune cells [39].

Deng, et al. [40] have suggested that visceral, hepatic, epicardial, and perirenal adiposity may predict the risk of severe COVID-19 in young obese patients.

On analysis of chest imaging in obese and non-obese patients, we found that the distribution and frequency of lung lesions were slightly different. The cases of obesity also manifested a higher proportion of specific opacity in ground glass (98% against 93%). Lung damage involvement was slightly more extensive in obese patients, this difference becomes more pronounced, especially for CT lesions greater than 50%. Similar results have been described in the literature [14,41].

Indeed, obesity is the result of abnormal energy metabolism, leading to weight gain and metabolic disturbances, which in turn lead to stress and tissue dysfunction [42,43]. In our study, obese patients showed a slightly high rate of CRP and erythrocytic sedimentation levels than those who were not obese Table 3, these markers of inflammation influence the progression and poor prognosis of COVID-19 disease. Obesity provides a favorable environment for disease pathogenesis and is characterized by a chronic, low-inflammatory condition, which can lead to the production of depleted immune cells, and the body becomes more vulnerable to infections [8,44,45]. The excessive immune response to SARS-CoV-2 is the main reason for the severe forms of illness and the mortality of patients with COVID-19 [2]. The CRP was slightly higher in obese COVID-19 patients compared to non-obese patients in previous studies [46,47]. In addition, significantly higher levels of LDH and hypernatremia in obese patients, are associated with a slight, less pronounced elevation of transaminases mainly AST and hypokalaemia (Table 4).

BMI, ALAT and ASAT were independently and inversely associated with being discharged from hospital in time for these patients. one study found that obesity and abnormal liver function (ALF) predispose patients with COVID-19 to prolonged hospitalization [48], in our study we found the same trend with more patients staying longer than 10 days among obese subjects and subjects with a high ALT level.

In our study, kalaemia was slightly greater in the group of obese patients (3.82 versus 3.92).

Sodium ion disorder, particularly hyponatremia, is a common occurrence in hospitalized patients with COVID-19 in a Chinese study, and is associated with a higher risk of serious illness and increased hospital mortality [49]. In our study, we found a correlation between hyponatremia and the duration of hospitalization, particularly beyond 10 days, and a correlation between hypernatremia high BMI, and mortality (Table 6).

Indeed, the high prevalence of hypokalaemia in patients with COVID-19 in a Mediterranean cohort suggests the presence of a disturbance in the activity of the renin angiotensin system due to severe infection of SARS-CoV-2 [50,51]. Additionally, this sensitive biomarker may reflect the progression of COVID-19. Hypokalaemia has been shown to be independently associated with the need for invasive mechanical ventilation [50]. Obesity can disrupt immune responses, making obese patients susceptible to infections, both bacterial and viral [52,53]. This increased risk had already been described for infections with the influenza virus, [54] with a longer duration of contagiousness in obese people compared to that in non-obese [50].

In our study, the mean hospital stay was similar to 10 days versus 10.4 days, in fact, the hospital stay was the same in previous studies [35]. In our work, obese patients had lower oxygen saturation on admission (88% versus 91%). In our work, obese patients had lower oxygen saturation on admission (88% versus 91%) [35].

We found no higher mortality or transfer rate to the intensive care unit for obese patients compared to those who were not obese in our sample (5.3 versus 5.1) for mortality, (11.7 versus 8.8) for transfer to the intensive care units. Identical results with a BMI were not found to be an independent predictor of mortality [55].

However in previous viral pandemics, it has been shown that obesity, especially severe obesity (BMI > 40 kg/m ² ), is associated with an increased risk of hospitalization, admission to intensive care and death [56,57].

A systematic review and meta-analysis of 22 studies showed that obesity was associated with a poor prognosis for SARS-CoV-2 infection, marked by more cases of severe COVID-19, admission to intensive care, recourse to mechanical ventilation and rapid progression of the disease, especially in younger subjects (OR 3.30 versus 1.72). However, this meta-analysis did not find an association between obesity and hospital mortality [30].

Current literature suggests an association between obesity and increased mortality in patients with COVID-19 pneumonia in the general population, particularly in younger patients [10,13,55,58]. However, a lower BMI ≤ 25 was associated with a decrease in the need for mechanical ventilation [55]. Obesity was significantly associated with a greater likelihood of occurrence of the primary endpoint (death), and a maximum percentage of death (32.61%) was noted in obesity Classes II and III (BMI ≥ 35 Kg/m ² ) [59]. Group Class I (BMI 18.5-24.9 Kg/m ² ) had the least percentage of meeting the primary endpoint [59]. Severe obesity is a relevant risk factor for COVID-19 hospitalization and severity in young adults, having a magnitude similar to that of aging [60]. Higher BMI in early adulthood was associated with severe COVID-19 many years later with a risk increase starting already at BMI ≥ 22.5 [61]. Study show that having a BMI that is ≥ 30 kg/m ²  is a significant risk factor in COVID-19 morbidity and mortality [62].

Comparing the survivor group with the non-survivor group in Table 6, the latter had higher percentages of males, older ages, and more comorbidities (heart disease, hypertension, diabetes COPD, and chronic kidney disease, but the same percentage of asthma), the results were found by Kyoung Min Kim [63-65]. The non-survivor group had a higher frequency of dyspnea and a lower level of oxygen saturation. Based on the biological profile, the non-survivor group included a higher level of polymorphonuclear neutrophils, LDH, and C-reactive protein, and a higher number of patients with D-dimer greater than 1600 ng/ml, which indicated that D-dimer could be an early marker to improve the management of Covid-19 patients [66], in fact, hospital mortality was significantly higher in patients with high neutrophil count, lower lymphocyte count, elevated CRP, and D-dimer ≥ 2.0 μg/ml than those who had D-dimer < 2.0 μg/ml on admission [67]. On the other hand, the same group included more patients with an CT extent of lesions greater than 50%. The risk of mortality for COVID-19 patients could be evaluated using a lung CT-scan extent cutoff [68,69].

Strengths and Limitations

The strength of this study is prospective study included a single center with the same team of investigators, over 18 months, in a pulmonology department. There were some limitations to the current study. First, our study cannot be considered exhaustive, and might be possible other factors that affect COVID-19 mortality, is the retrieval of clinical data was difficult for severely ill patients.

In summary , obesity contributes to clinical manifestations and can influence the progression and prognosis of COVID-19, with an accumulated risk of serious complications for obese subjects. Our cohort showed an obesity rate (26.8%) and a mortality rate (5.3%), and warned that obesity increases the risk of severity but not mortality in hospitalized patients for COVID-19. Therefore, the inclusion of obesity in prognostic scores and therapeutic management strategy will be essential to improve the prognosis of hospitalized patients with COVID-19. risk factors for death from COVID-19 were a history of underlying chronic diseases including diabetes, COPD, renal failure and cardiovascular disease, hypoxia on admission, elevated serum LDH, CRP and D.Dimer linked to the survival status of COVID-19 patients.

Further studies are needed to assess the association between age, obesity, frailty, and clinical outcome in adults with COVID-19 disease.

What is already know on this topic

• It suggest that obesity contributes to clinical manifestations and may influence the progression and prognosis of COVID-19 and it is considered as a potential risk factor of the prognosis of COVID-19

• old age, certain biomarkers such as LDH and D-Dimer, have been identified as risk factors for mortality

What this study adds

• Obesity contributes to clinical manifestations and can influence the progression and prognosis of COVID-19, with an accumulated risk of serious complications for obese subjects.

• Our study showed, that obesity increases the risk of severity but not mortality in hospitalized patients for COVID-19.

• The inclusion of obesity in prognostic scores and therapeutic management strategy will be essential to improve the prognosis of hospitalized patients with COVID-19. The risk factors for death from COVID-19 were a history of underlying chronic diseases including diabetes, COPD, renal failure and cardiovascular disease, hypoxia on admission, elevated serum LDH, CRP and D-Dimer linked to the survival status of COVID-19 patients.

Funding

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

Establishment Where the Work was Performed

Department of Pneumology, Phthisiology and Allergology, Rouiba Hospital, University of Algiers, Faculty of Medicine, Algiers, Algeria.

Authors Contributions

KA conceived the study, participated in its design, performed the spirometry tests and the statistical analysis, and helped to draft the manuscript and coordinated the study; RY participated in the lung high-resolution CT scan interpretation, helped to draft the manuscript; GM participated in the diagnosis of connective tissue disease, helped to draft the manuscript; RT participated in its design, helped to draft the manuscript.

Both authors read and approved the final version of the manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest concerning this article.

Data Availability Statement

Data are available upon a request from the corresponding author (ketfiabdelbassat@gmail.com).

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