In total, 819 hospital-admitted COVID-19 patients were enrolled in this study with 546 male and 273 female patients (66.77% M and 33.33% F). The comparison for each of the variables presented in Tables 1a and 1b showed no difference between male and female groups, with admission ratio being 1/3 female to male, suggesting that gender does not influence these variables in our population. Table 1b shows that there were more intubated males with shortness of breath than female (23.18 vs 16.42 %, and 72.48 vs 59.78 %, respectively). Males who presented with anosmia were almost double than females (3.30% vs 1.48%), albeit anosmia constituted a very small percentage of the hospitalized patients. Female patients were four times more likely to have autoimmune disease than males (8.21% vs 2.94%).
Overall, the intubation of COVID-19 subjects was highly associated with fatality (OR 71.20, CI[41.33-122.64], p <0.001) and with the oxygen consumption volume (OR, 3.18 CI[0.02-0.06], p<0.001) (Table 1c).
The fatality rate between male and female COVID-19 patients however was not significant (27% and 23% respectively, Figure 1) .
Applying a Cox regression of time to death on the time-constant covariates (age, WBC, asthma and overweight) revealed a significant implication of these factors as shows in the predictive survival proportion, at any given point, for the above-mentioned covariates shown in Figure 2.
Common comorbidities for intubation and fatality
We interrogated hypertension, diabetes, being overweight (BMI ≥ 25kg/m2), kidney disease, CVD, autoimmune disease, sex, asthma, and age against the prevalence of intubation in COVID-19 patients. We found that diabetes (OR 1.57, CI[1.07-2.32], p=0.02), being overweight (OR 0.65, CI[0.46-0.94], p=0.02), kidney disease (OR 1.70, CI[1.01-2.84], p=0.04), and sex (OR 0.61, CI[0.41-0.91], p=0.016) are independent risk factors for intubation, with age conferring the most significant intubation risk (OR 2.03, CI[1.34-3.08], p=0.001) (Table 2a). When assessing for Fatality as an outcome variable (Table 2b), a similar trend was noticed, with age (≥ 65 years) scoring the highest significance as an independent risk factor (OR 2.93, CI[1.97-4.34], p=0.000). However, being overweight did not show significance (p=0.07) in this analysis.
Correlation of symptoms at presentation with intubation and fatality
We further evaluated abdominal pain/diarrhea, fever/chills, fatigue, myalgia, headaches, cough, rhinorrhea, sore throat, and shortness of breath in our group of COVID-19 patients. Having shortness of breath (OR 2.97, CI[1.87-4.70], p=0.000), age (OR 2.60, CI[1.78-3.80], p=0.000), and gender (OR 0.64, CI[0.43-0.96], p=0.03) significantly correlated with intubation of these patients (Table 3a). Shortness of breath on admission was one of the most important risk factors driving patients into intubation. Further, when probing for fatality, data in table 3b showed that death of COVID-19 patients significantly correlated with shortness of breath (OR 2.63, CI [1.76-3.93], p=0.000).
Biomarkers of intubation and COVID-19 fatality
We investigated serum levels of platelets, ferritin, CRP, Hb, creatinine, WBC, SGOT and SGPT and analyzed these using intubation as an independent variable. CRP (OR 1.48, CI [1.21-1.81], p=0.000), WBC (OR 2.70, CI [1.68-4.32], p=0.000), SGOT (OR 3.08, CI [1.88-5.03], p=0.000), and SGPT (OR 0.44, CI [0.23-0.81], p=0.01) emerged as independent biomarkers for the intubation of these patients, while platelets, ferritin, Hb, and creatinine did not score significance. Out of these biomarkers WBC and SGOT (AST) were the most significantly correlated with intubation (Table 4a). These same biomarkers were interrogated against fatality as an independent variable. Platelets (OR 0.78, CI [0.61-0.97], p=0.029), CRP (OR 1.39, CI [1.14-1.69], p=0.001), creatinine (OR 2.02, CI [1.30-3.12], p=0.002), WBC (OR 3.25, CI [2.07-5.08], p=0.000), and SGOT (AST) (OR 2.18, CI [1.35-3.5], p=0.001) emerged as independent biomarkers of fatality in COVID-19 patients. WBC, platelets, and creatinine levels were among the most significant biomarkers correlating with fatality (Table 4b).
Data in Table 5 show that creatinine and/or diabetes are strongly correlated with hypertension in our group of patients. Similarly, diabetes and hypertension were associated with high creatinine levels, while hypertension strongly correlates with kidney disease. It is worth noting that diabetes and hypertension together did not show a significant association neither with kidney disease nor with high creatinine levels. Therefore, creatinine levels, hence, kidney injury, remain as the most significant risk factor for fatality namely in hypertensive subjects.