Abstract:Globally, both obesity and underweight are severe health risks for various diseases. The current study systematically examined the emerging evidence to identify an association between body mass index (BMI) and COVID-19 disease outcome. Online literature databases (e.g., Google Scholar, PubMed, MEDLINE, EMBASE, Scopus, Medrixv and BioRixv) were screened following standard search strategy having the appropriate keyword such as “Obesity”, “Underweight”, “BMI”, “Body Mass Index”, “2019-nCov”, “COVID-19, “novel cor… Show more
“…The strong correlation observed here between advanced BMI-years and greater propensity to generate respiratory droplets ( Fig. 2 ) may be significant in the light of the recognized risk of those with high BMI ( 18 , 19 ), advanced age ( 20 ), or both ( 21 ) (the elderly, the obese, and the obese elderly) developing severe symptoms upon COVID-19 infection. Promiscuity of respiratory droplets in the airways heightens the probability that upper airway infection transports deeper into the lungs, promoting severe symptoms, as is observed, with remarkable speed, following intranasal and intratracheal instillation of SARS = CoV-2 in NHPs ( 22 ).…”
COVID-19 transmits by droplets generated from surfaces of airway mucus during processes of respiration within hosts infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. We studied respiratory droplet generation and exhalation in human and nonhuman primate subjects with and without COVID-19 infection to explore whether SARS-CoV-2 infection, and other changes in physiological state, translate into observable evolution of numbers and sizes of exhaled respiratory droplets in healthy and diseased subjects. In our observational cohort study of the exhaled breath particles of 194 healthy human subjects, and in our experimental infection study of eight nonhuman primates infected, by aerosol, with SARS-CoV-2, we found that exhaled aerosol particles vary between subjects by three orders of magnitude, with exhaled respiratory droplet number increasing with degree of COVID-19 infection and elevated BMI-years. We observed that 18% of human subjects (35) accounted for 80% of the exhaled bioaerosol of the group (194), reflecting a superspreader distribution of bioaerosol analogous to a classical 20:80 superspreader of infection distribution. These findings suggest that quantitative assessment and control of exhaled aerosol may be critical to slowing the airborne spread of COVID-19 in the absence of an effective and widely disseminated vaccine.
“…The strong correlation observed here between advanced BMI-years and greater propensity to generate respiratory droplets ( Fig. 2 ) may be significant in the light of the recognized risk of those with high BMI ( 18 , 19 ), advanced age ( 20 ), or both ( 21 ) (the elderly, the obese, and the obese elderly) developing severe symptoms upon COVID-19 infection. Promiscuity of respiratory droplets in the airways heightens the probability that upper airway infection transports deeper into the lungs, promoting severe symptoms, as is observed, with remarkable speed, following intranasal and intratracheal instillation of SARS = CoV-2 in NHPs ( 22 ).…”
COVID-19 transmits by droplets generated from surfaces of airway mucus during processes of respiration within hosts infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. We studied respiratory droplet generation and exhalation in human and nonhuman primate subjects with and without COVID-19 infection to explore whether SARS-CoV-2 infection, and other changes in physiological state, translate into observable evolution of numbers and sizes of exhaled respiratory droplets in healthy and diseased subjects. In our observational cohort study of the exhaled breath particles of 194 healthy human subjects, and in our experimental infection study of eight nonhuman primates infected, by aerosol, with SARS-CoV-2, we found that exhaled aerosol particles vary between subjects by three orders of magnitude, with exhaled respiratory droplet number increasing with degree of COVID-19 infection and elevated BMI-years. We observed that 18% of human subjects (35) accounted for 80% of the exhaled bioaerosol of the group (194), reflecting a superspreader distribution of bioaerosol analogous to a classical 20:80 superspreader of infection distribution. These findings suggest that quantitative assessment and control of exhaled aerosol may be critical to slowing the airborne spread of COVID-19 in the absence of an effective and widely disseminated vaccine.
“…The mean BMI of COVID-19 patients were 29 ± 6 kg/m 2 , which lies within the overweight class as per the WHO classification (Pi-Sunyer, 2000). Population and patients with high BMI have moderate to high risk of medical complications with COVID-19 (Malik et al, 2020), with increased adiposity destabilizes the pulmonary function and contribute to viral pathogenesis (Dorner et al, 2010).…”
Section: Aci Ak I Liver Injury Acidos Ismentioning
IntroductionCOVID-19 is raising with a second wave threatening many countries. Therefore, it is important to understand COVID-19 characteristics across different countries.MethodsThis is a cross-sectional descriptive study of 525 hospitalized symptomatic COVID-19 patients, from the central federal hospital in Dubai-UAE during period of March to August 2020.ResultsUAE’s COVID-19 patients were relatively young; mean (SD) of the age 49(15) years, 130 (25%) were older than 60 and 4 (<1%) were younger than 18 years old. Majority were male(47; 78%). The mean (SD) BMI was 29 (6) kg/m2. While the source of contracting COVID-19 was not known in 369 (70%) of patients, 29 (6%) reported travel to overseas-country and 127 (24%) reported contact with another COVID-19 case/s. At least one comorbidity was present in 284 (54%) of patients and 241 (46%) had none. The most common comorbidities were diabetes (177; 34%) and hypertension (166; 32%). The mean (SD) of symptoms duration was 6 (3) days. The most common symptoms at hospitalization were fever (340; 65%), cough (296; 56%), and shortness of breath (SOB) (243; 46%). Most of the laboratory values were within normal range, but (184; 35%) of patients had lymphopenia, 43 (8%) had neutrophilia, and 116 (22%) had prolong international normalized ratio (INR), and 317 (60%) had high D-dimer. Chest x ray findings of consolidation was present in 334 (64%) of patients and CT scan ground glass appearance was present in 354 (68%). Acute cardiac injury occurred in 124 (24%), acute kidney injury in 111 (21%), liver injury in 101 (19%), ARDS in 155 (30%), acidosis in 118 (22%), and septic shock in 93 (18%). Consequently, 150 (29%) required ICU admission with 103 (20%) needed mechanical ventilation.ConclusionsThe study demonstrated the special profile of COVID-19 in UAE. Patients were young with diabetes and/or hypertension and associated with severe infection as shown by various clinical and laboratory data necessitating ICU admission.
“…The imbalances in the mentioned factors could cause dysregulation of immune cells function that in turn may affect the viral infection progression. Besides, both obese patients and COVID-19 cases have an increased risk of hypercoagulation and thrombosis [2,[17][18][19].…”
Background Identifying the non-survived patients' characteristics compared to survived subjects and introducing the critical risk factors of COVID-19 mortality would help enhance patients' prognosis and treatment. Methods In the current case-control study, medical records of 103 non-survived COVID-19 patients (cases) and 147 sexmatched survivors (controls) who admitted to Razi University Hospital in Rasht, Guilan, Northern Iran from April 21 to August 21, 2020, were explored. Data on demographic, anthropometric, clinical, and laboratory assessment was extracted from the electronic medical records. To estimate the association between variables of interest and mortality odds due to COVID-19 logistic regression was carried out. Results The patients who died (mean age = 62.87 years) were older than the discharged patients (57.33 years; P value = 0.009). According to the results of multivariable regression adjusted for potential confounders, elevated BMI (OR = 2.49; 95% CI = 1.15-5.41), higher CRP levels (OR = 2.28; 95% CI = 1.08-4.78), increased FBS levels (OR = 2.88; 95% CI = 1.35-6.17), higher levels of total cholestrol (OR = 2.55; 95% CI = 1.19-5.45) and LDL (OR = 2.27; 95% CI = 1.07-4.79), elevated triglyceride (OR = 5.14; 95% CI = 2.28-11.56), and raised levels of D-dimer (OR = 5.68; 95% CI = 2.22-14.49) were identified as independent risk factors of COVID-19 mortality. No significant association was detected regarding HDL level, QTc interval or heart size, and COVID-19 fatality odds. Conclusion The present findings demonstrated that obesity, higher levels of CRP, blood sugar, D-dimer, and lipid markers were likely to be predictive factors of COVID-19-related mortality odds.
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