Nouh, M., Elgamal, A., Ali, H., Elkhayat, M. (2024). Predictors of ICU Admission in Covid 19 Patients. Afro-Egyptian Journal of Infectious and Endemic Diseases, 14(1), 21-31. doi: 10.21608/aeji.2023.240168.1326
Mohamed A Nouh; Ayman A Elgamal; Heba RA Ali; Mohsen M Elkhayat. "Predictors of ICU Admission in Covid 19 Patients". Afro-Egyptian Journal of Infectious and Endemic Diseases, 14, 1, 2024, 21-31. doi: 10.21608/aeji.2023.240168.1326
Nouh, M., Elgamal, A., Ali, H., Elkhayat, M. (2024). 'Predictors of ICU Admission in Covid 19 Patients', Afro-Egyptian Journal of Infectious and Endemic Diseases, 14(1), pp. 21-31. doi: 10.21608/aeji.2023.240168.1326
Nouh, M., Elgamal, A., Ali, H., Elkhayat, M. Predictors of ICU Admission in Covid 19 Patients. Afro-Egyptian Journal of Infectious and Endemic Diseases, 2024; 14(1): 21-31. doi: 10.21608/aeji.2023.240168.1326
1Department of Tropical Medicine, Faculty of Medicine, Menoufia University, Menoufia, Egypt.
2Menoufia University Hospitals, Faculty of Medicine, Menoufia University, Menoufia, Egypt.
3Shiben Elkom Fever Hospital, Menoufia, Egypt
Abstract
Background and study aim: The global spread of the SARS-CoV-2 virus imposes an enormous burden on medical health systems.The aim of this study was to detect the predictors of ICU admission in COVID 19 patients. Patients and Methods: This was a retrospective study on patients files involving 258 patients with COVID 19. Patients were classified to Group I: Included 186 patients who need ICU care. Then classified into two subgroups Group Ia 134 patient needed mechanical ventilation, Group Ib: Includes 52 patients did not need mechanical ventilation Group II: include72 patient who did not need ICU. All patients subjected to full history taking, clinical examination, O2 saturation, complete blood count, liver and renal function tests, lipid profile inflammatory markers electrolytes, and imaging study. Results: ICU admission showed significant positive correlation with smoking, age, body weight ,respiratory rate(RR), heart rate(HR), blood pressure, random blood sugar(RBS), Hb,total leucocytic count (TLC),procalcitonin(PCT), Na, kidney function, IL6, total bilirubin and ferritin. And significant negative correlation with albumin and O2 saturation on room temperature. MV showed significant positive correlation with smoking, age, RR, HR, SBP, DBP, RBS, Hb, TLC, PCT, Na, IL6 and ferritin. And significant negative correlation with albumin, K, total bilirubin and saturation on room temperature. Conclusion: Obesity, increase age, hypertension, diabetes, chest disease, cardiac disease, liver disease and renal disease, High LDH, RR, HR, Bps, DBP, RBS, TLC, CRP, PCT, Na, kidney function, IL6, total bilirubin, ferritin, D dimer and Psychological status are considered predictors of admission to ICU in COVID 19 patients.
Highlights
The global spread of the SARS-CoV-2 virus imposes an enormous burden on medical health systems.
Predictors of ICU admission in COVID 19 patients are needed.
Obesity, increase age, hypertension, diabetes, chest disease, cardiac disease, liver disease and renal disease, high LDH, RR, HR, Bps, DBP, RBS, TLC, CRP, PCT, Na, kidney function, IL6, total bilirubin, ferritin, D dimer and psychological status are considered predictors of admission to ICU in COVID 19 patients.
The severe acute respiratory syndrome corona virus 2 (SARS COV- 2) that causes corona virus disease 2019 (COVID 19) poses multiple challenges to our health care. This virus originally identified in Wuhan, China and has forced several countries to take unprecedented public health measures as health professionals and policy makers try to shield those at highest risk [1].
The requirement of intensive care among COVID 19 hospitalized patients varies between countries from 5% to 32%. Many factors including age, sex, and comorbidities are associated with the severity of disease and ICU admission. According to these studies, severe disease is accompanied by acute kidney injury, acute respiratory distress syndrome (ARDS), myocarditis , cardiac and septic shock. Hence, ICU admission plays a crucial role in the care of COVID 19 patients and also is effective in decreasing the mortality rate [2].
The aim of the present study was to detect the predictors of ICU admission in COVID 19 patients.
PATIENTS AND METHODS
This was a retrospective study from patients’ files involved 258 patients admitted to Shebin Elkom fever hospital who are diagnosed positive of covid 19 according to WHO criteria in the period between February and May2021. The studied patients were classified into the following groups according to the need of ICU admission Group I: include186 patient who need ICU care on admission or at some point during hospital stay, Group II: Included 72 patients who did not need ICU care. GI patients were reclassified into two subgroups according to the need of mechanical ventilation: GIa: Included 134 patient which undergo mechanical ventilation either invasive (123) IMV patients or not NIMV Group (11 patients), 52 patients admitted to ICU did not undergo mechanical ventilation.GI b
Prognostic effects of variables on admission among patients who received intensive care unit (ICU) support and those who didn’t require ICU care were studied. Adults more than18 years who are Covid 19 confirmed with any one item of serological or radiological evidence , real time PCR test positive for SARS-COV2 or radiological findings in the form of ground glass opacity or vascular were included in our study. Patients less than18 years old, Pregnant women and asymptomatic and normal x-ray finding subjects were excluded from our study.
All patients were subjected to full history taking: With special emphasis on constitutional and chest symptom. Full clinical examination (General examination, Local chest examination), Routine laboratory investigations, Complete blood count, Liver Function Tests including serum albumin, serum alkaline phosphatase (ALP), prothrombin concentration, prothrombin time and INR, blood urea and serum creatinine lipid profile inflammatory markers, electrolytes, and Imaging study.
Statistical analyses:
Data was statistically analyzed using SPSS (statistical package for social science) program version 13 for windows and for all the analysis a p value < 0.05 was considered statistically significant: Data are shown as mean, range, or value and 95% confidence interval (95% CI) and frequency and percent. Chi square test was done for qualitative variable analysis and p-value < 0.05 was considered p significant. Student t- test was done for normally distributed quantitative variables to measure mean and standard deviation and p-value < 0.05 was considered significant. Pearson correlation test was done to study correlation between one qualitative variable and one quantitative variable or two quantitative variables of not normally distributed data and p- value less than 0.05 was considered significant. All these tests were used as tests of significance at P
RESULTS
They were 145 males (56.2 %) and 113 females (43.8%) and their ages ranged between 30 and 82 years with mean value (61.57 ± 14.58 years). Sex had no effect on ICU admission (p>0.05). However, Obesity, age, hypertension, diabetes, chest disease, cardiac disease, liver disease and renal disease showed significant association with ICU admission (P 0.001, 0.006). However, autoimmune diseases had no association with admission to ICU (p >0.05) (table 1).
RR(respiratory rate), HR(heart rate, SBP(systolic blood pressure) and DBP(diastolic pressure), showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU (P= 0.001 each). However, saturation on room air showed significant decrease in patients admitted to ICU when compared to patients not admitted to ICU (P= 0.001) (table 2). Advanced CT and abnormal ABG were significantly associated with admission to ICU (P= 0.001). (table 3).
This table shows that TLC(total leucocytic count), CRP(c-reactive protein), PCT (procalcitonin), Na, kidney function, IL6, total bilirubin, ferritin, D dimer High LDH were significantly associated with ICU admission (p= 0.001). when compared to patients not admitted to ICU (P= 0.001) K level showed no significant difference between the two groups (p>0.05) (table 4).
There was significant difference between the studied groups (IMN, NIMV and no MV groups ) regarding sex, age, smoking and weight (0.001, 0.001, 0.002, 0.001). significant difference between the studied groups (IMN, NIV MV and no MV groups ) regarding Bp, diabetes, Chest Diseases, Cardiac history, Kidney diseases and kidney function (p =0.001, 0.001, 0.001, 0.001, 0.004, 0.022). However, no significant difference was found regarding liver diseases and auto immune diseases (table 5).There is significant difference between studied groups ( IMN , NIV MV and no MV groups ) regarding CT, ABG, LDH (p=0.001 each). There is significant difference between studied groups (IMN , NIV MV and no MV groups ) regarding RR, HR, SPB, DBP and RBS (0.001, 0.001, 0.001, 0.002 and 0.001) (table 5).
Significant difference between studied groups (IMN, NIMV and no MV groups ) regarding Hb, TLC, PCT, K, Il6, albumin, ferritin, D dimmer and saturation on room air. However, no significant difference was found regarding CRP, kidney function and total bilirubin (table 7).
MV has significant difference between studied groups (IMN, NIMV and no MV groups ) regarding ICU admission (p=0.001) ( table 6).
There is a significant difference between studied groups (IMN, NIMV and no MV groups ) regarding mortality among studied patients (p=0.001) ( table 7).
Table (1): Relation between demographic data, medical history and ICU admission among studied group.
X2
P.value
G I
GII
Sex
Male
104
55.9%
41
56.9%
0.02
0.881
Female
82
44.1%
31
43.1%
Age
mean±SD
66.8±10.2
48.06±15.6
11.33
0.001
Smoking
No
145
78.0%
31
43.1%
29.16
0.001
yes
41
22.0%
41
56.9%
Weight
Morbid obesity
41
22.0%
0
0.0%
Fisher's Exact Test 21.39
0.001
obese
51
27.4%
20
27.8%
over weight
31
16.7%
21
29.2%
normal weight
62
33.3%
30
41.7%
Thin
1
0.5%
1
1.4%
BP
Normal
31
16.7%
50
69.4%
67.13
0.001
HTN
155
83.3%
22
30.6%
Diabetes
Normal
94
50.5%
61
84.7%
25.29
0.001
DM
92
49.5%
11
15.3%
Chest Diseases
No history
141
75.8%
59
81.9%
37.33
0.001
bronchial asthma
21
11.3%
1
1.4%
COPD
24
12.9
2
2.8
TB
0
0
10
13.9
Cardiac history
No history
116
62.4%
61
84.7%
Fisher's Exact Test 59.29
0.001
AF
21
11.3%
0
0.0%
cardiomyopathy
38
20.4%
0
0.0%
IHD and AF
11
5.9%
0
0.0%
IHD
0
0.0%
11
15.3%
Kidney diseases
No History
42
22.6%
40
55.6%
26.03
0.001
CKD
144
77.4%
32
44.4%
Liver diseases
No history
163
87.6%
71
98.6%
7.41
0.006
CLD
23
12.4%
1
1.4%
Auto Immune diseases
No history
171
91.9%
65
90.3%
4.38
0.357
SLE
5
2.7%
5
6.9%
rheumatoid arthritis
5
2.7%
2
2.8%
auto immune thyroiditis
4
2.2%
0
0.0%
sjogrin syndrome
1
0.5%
0
0.0%
This table shows that sex,auto immune diseases had no effect on ICU admission (p>0.05). However, Obesity and increase age showed significant association with ICU admission (P=0.001 each).
Table (2): Relation between vital signs and ICU admission among studied group
Vital signs
GI
GII
X2
P.value
RR
34.54±5.71
29.13±5.32
6.96
0.001
HR
90.58±15.54
82.78±13.65
3.74
0.001
SBP
144.89±20.38
121.25±8.38
9.53
0.001
DPB
87.58±13.51
78.33±14.04
4.88
0.001
Saturation on room air
82.73±7.59
90.46±1.76
8.54
0.001
RR, HR, Bps, BPD, showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU (P= 0.001 each). However, saturation on room air showed significant decrease in patients admitted to ICU when compared to patients not admitted to ICU (P= 0.001).
Table (3): Relation between (CT,ABG and LDH ) and admission among studied groups
investigation
ICU admission
X2
P.value
GI N=186
GII N=72
CT
Corad 1
0
0.0%
20
27.8%
107.66
0.001
Corad 3
21
11.3%
31
43.1%
Corad 4
31
16.7%
10
13.9%
Corad 5
134
72.0%
11
15.3%
ABG
Normal
51
27.4%
42
58.3%
76.7
0.001
R alkalosis with M acidosis
42
22.6%
0
0.0%
M acidosis
42
22.6%
0
0.0%
R alkalosis
41
22.0%
20
27.8%
M alkalosis
0
0.0%
10
13.9%
R acidosis
10
5.4%
0
0.0%
LDH
Normal
44
23.7%
51
70.8%
49.66
0.001
High
142
76.3%
21
29.2%
High LDH was significantly associated with ICU admission (p= 0.001). Advanced CT and abnormal ABG were significantly associated with admission to ICU (P= 0.001)
Table (4): Relation between investigation and ICU admission among studied group.
investigation
Groups
T test
P.value
GI N=186
GII N=72
Hb
11.24±1.84
12.84±2.05
6.06
0.001
Tlc
14.24±6.22
7.53±5.27
8.09
0.001
CRP
45.16±27.30
37.33±17.96
2.25
0.001
PCT
2.10±1.51
1.12±1.13
4.99
0.001
Na
139.68±7.43
136.43±4.61
3.46
0.001
K
4.06±0.66
4.14±0.47
0.926
0.355
Kidney function
2.09±1.10
1.77±1.10
2.13
0.034
Il6
57.51±33.33
10.01±8.04
11.94
0.001
Albumin
3.07±0.60
3.40±0.46
4.15
0.001
Total bilirubin
1.18±0.87
0.78±0.21
3.82
0.001
RBS
242.42±114.7
172.50±98.82
4.56
0.001
Ferritin
253.56±165.75
160.76±134.75
4.24
0.001
D dimmer
403.86±213.50
178.40±256.42
7.18
0.001
TLC, CRP, PCT, Na, kidney function, IL6, total bilirubin, ferritin, D dimer showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU (P= 0.001 each K level showed no significant difference between the two groups (p>0.05)
The present study was retrospective study aimed to detect the predictors of ICU admission in COVID 19 patients.
Most studied cases were male (56.2%), The mean age was 61.57± 14.58, Most cases were nonsmoker (68.2%). 35.7% of cases were normal weight, 27.5% were obese, 20.2% were overweight and 15.9%were morbid obesity. These results could be attributed to the fact that sex hormones play an important role in various immunoinflammatory responses [3].
In line with our finding, The study of Akbari et al.,(2020) conducted in Shiraz city (southern Iran) showed that 56.6% of patients were male and 38.4% were in the age range of 40-60 years [4].In 2020, Guan et al. examined the demographic characteristics and clinical signs of patients with coronavirus infection in China; 58% of the patients were male and the mean age of the patients was 47 years [5].
The present study revealed that sex and smoking had no effect on ICU admission. However, obesity and increase age showed significant association with ICU admission. In agreement with our finding, Hatamiet al suggested that patients aged 60-80 years (and over 80 years are at higher risk of disease deterioration and ICU admission independently from other cofounders, such as underlying comorbidities [6].
Petrilli et al., (2020) showed that smoking was not associated with an increased risk of hospitalization or critical illness. Medical history of diabetes mellitus (DM), HTN, CVD, cerebrovascular accident (CVA), and COPD have been cited as predictive factors for severe outcomes in COVID-19 patients[7].
The present study revealed that Hypertension, diabetes, chest disease, cardiac disease, liver disease and renal disease showed significant association with ICU admission. Similarly, Hatami et al.,(2020) found significantly higher rates of HTN, CVD, and, CVA in ICU rather than non-ICU patients [6].Alsaad et al., (2020) showed that the comorbidities that demonstrated a statistically significant association with ICU admission were heart failure, chronic obstructive pulmonary disease, and chronic kidney disease [10].
Diabetes mellitus and hypertension have been reported to increase the risk of ICU admission in previous studiesbut were not reported in the present study In previous study, 66% of the patients were known type 2 diabetics and 48% suffered from hypertension. Diabetes is associated with a worse outcome in COVID-19 with a higher proportion of ICU admission, ARDS and mechanical ventilation being observed [11,12,13].
Current evidence suggests that patients with COPD have a higher risk of ICU admission and severe COVID-19 because they are prone to viral infections, including SARS-CoV-2. This outcome is primarily due to the increased expression of ACE2 receptors in the small airways and could also be related to a poor lung reserve [14].
Moreover, we showed that autoimmune diseases had no association with admission to ICU. Similarly, in certain cases patients with autoimmune diseases may have better sepsis-related clinical outcomes [15]. Contrarily, Godeau et al included 69 patients with SLE, necrotizing vasculitis, AR, and other rheumatic diseases. The main reasons for admission were infections and acute exacerbation of the disease [16].
The present study revealed that High LDH was significantly associated with ICU admission. In line with our finding, high LDH was significantly associated with ICU admission. Elevated LDH indicates cell death and injury and is associated with a poor host immune response, resulting in a higher susceptibility to severe viral infections [17]. Also, Hatami et al showed that Lactate dehydrogenase (LDH) level was also significantly higher among the ICU group[7].
The present study showed that worse CT and abnormal ABG were significantly associated with admission to ICU. Similarly, previous studies showed that increased rate of consolidations, along with increasing percentages of lung involvement in patients is associated with disease progression and could partially explain the observed association [18, 19].
Also, Kanne et al showed that a higher proportion of cases who mandated ICU admission had worse CT signs of infection [19] Numerous studies have illustrated the practical value of CT chest not just as a detector of disease severity but also as a diagnostic instrument in areas with limited resources [18].
Regarding vital signs we found that RR, HR, DPB, SBP, RBS showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU. However, saturation on room air showed significant decrease in patients admitted to ICU when compared to patients not admitted to ICU.
In agreement with our study, Elsharawy et al.,(2021) demonstrated that ICU patients had significantly higher respiratory rates, body temperatures, and pulse rates. Furthermore, only two ICU admitted patients had bradycardia, while the majority had either normal or increased pulse rates. So pulse rate can be used as a rapid, simple, and bedside indicator of disease severity. Therefore, this finding highlights the importance of conducting ECG as a routine for COVID-19 infected patients [20]. This increase in pulse rate can be attributed to many influences, including increased body temperature (as pulse increases 9.46 beats/min/°C in female patients and 7.24 beats/min/°C in male patients for every 1°C increase in body temperature), cardiac affection caused by COVID-19 infection, and associated inflammation.
The present study showed that CRP showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU. CRP, in our study, was considerably higher in the ICU group and revealed an evident correlation with both oxygen saturation and severities, it could not be considered an independent forecaster of ICU admission since it was one of the crucial variables in univariate but not multivariate analysis, in contrast to previous studies [21, 22].
The present study showed that TLC, PCT, Na, kidney function, IL6, total bilirubin, ferritin, D dimer showed significant increase in patients admitted to ICU when compared to patients not admitted to ICU. However, K level showed no significant difference between the two groups.
Previous studies showed that patients at high risk for ARDS development are those older than 65 years old, presenting high fever (T > 39ºC), neutrophilia, lymphocytopenia, elevated markers of hepatic and renal failure (aspartate aminotransferase, alanine aminotransferase, creatinine, and urea), elevated acute-phase proteins as markers of inflammation (high-sensitivity C-reactive protein, procalcitonin, and serum ferritin), and elevated coagulation function-related indicators (prothrombin time, fibrinogen, and D-dimer) [23, 24]. Huang et al in meta-analysis showed that an elevated serum CRP, PCT, D-dimer, and ferritin were associated with a poor outcome in COVID-19[23].
The present study revealed that ICU admission not associated with presence of cancers. Contrarily, other study showed that suffering from cancer could increase the prevalence of ICU admission among COVID-19 infected patients [26]
The present study showed that psychological status showed significant association with admission to ICU. Similarly, other study estimated that the risk for psychiatric sequelae is higher in COVID-19 patients and in those admitted to ICU using electronic health records data [28].
Our study revealed that ICU admission showed significant positive correlation with, Hb, TLC, PCT, Na, kidney function, IL6, total bilirubin and ferritin. And significant negative correlation with albumin and saturation on room temperature.
In line with our finding, previous studies showed that the level of serum ferritin had been posited as one of the predictors of poor outcome in COVID 19 sufferers. Higher levels of serum ferritin were associated with higher odds of ICU admission through both univariate and multivariate analyses in this work, which was comparable to earlier studies that found an association between raised ferritin count and fatality, but with a lower cut off value (300 ng/ml) vs (368 ng/ml) in our study [29].
Sadeghi et al., (2020) showed that the admission O2 saturation, HCT, CRP levels at first admission and myalgia presentation could be considered as the valuable predictors of ICU admission [27].
D-dimer elevation was associated with a hypercoagulable state, however, its specificity on the main cause of elevation may not be known as D-dimer elevations were associated with several unfavorable events including occlusion, sepsis, micro-thrombosis, and intravascular coagulation[28] Zhao et al. (2020) shows that COVID 19 survivors and non-survivors had normal WBCs, non-survivors had higher WBC counts and slightly reduced lymphocyte counts [29].
The present study revealed that there was significant difference between the IMN, NIV MV and no MV groups regarding sex, age, smoking and weight. men might be more susceptible to receive IMV and NIMV than women. Jackson et al reported that advanced age is one of the strongest predictors of the mortality-related to mechanical ventilation in COIVD19 patients [30].
Cummings et al(2020) showed that among demographical variables, increasing age was significantly associated with a higher duration of MV and ICU mortality [31].
Moreover, we demonstrated significant difference between the IMN, NIV MV and no MV groups regarding Bp, diabetes, chest diseases, cardiac history, kidney diseases and kidney function. However, no significant difference was found regarding liver diseases and auto Immune diseases.
Previous studies showed that acute kidney injury is a known risk factor for prolonged mechanical ventilation in critically ill patients, regardless of the underlying disease [32, 25].
Our study showed that there is a significant difference between IMN, NIV MV and no MV groups regarding CT, ABG, LDH. In line with our finding, Fang et al showed that patients with COVID-19 who require PMV exhibit fibrosis on computed tomography (CT)[32].Factors to be independently predictive for mechanical ventilation requirement (diabetes mellitus, SpO2:FiO2 ratio, C-reactive protein, and lactate dehydrogenase) [33].
Previous studies demonstrated that the presence of comorbidities, age, absolute lymphocyte count, LDH, oxygen saturation, respiratory rate, and bilateral opacities on CT scan in order to identify patients at risk of adverse outcomes. Zhou et al. showed thatCT at the time of reintubation showed progressive lung fibrosis [29].
We found that there is a significant difference between studied groups (IMN, NIV, MV and no MV groups) regarding RR, HR, SBP, DBP and RBS. Seetharam et al showed that mechanically ventilated patients had a higher incidence of tachycardia (heart rate > 125), elevated respiratory rate > 24 cycles per minute, shortness of breath, and headaches. In addition, mechanically ventilated patients had a lower serum albumin (g/dl) ≤3 units, elevated serum creatinine, elevated serum CRP-HS, serum LDH, SGOT IU/L or AST IU/L, SGPT or ALT, and WBC count [33].
The present study showed that there is significant difference between studied groups (IMN , NIV MV and no MV groups ) regarding Hb, Tlc, PCT, K, Il6, albumin, ferritin, D dimmer and saturation on room air. However, no significant difference was found regarding CRP, kidney function and total bilirubin.
Our study showed that there is significant difference between studied groups (IMN, NIV MV and no MV groups) regarding associated oncology. Péron (2021) showed that the risk of intubation and mechanical ventilation was lower among cancer patients [35].
The current study showed that there is significant difference between studied groups (IMN, NIV MV and no MV groups) regarding psychological status. Similarly, Melamed et al.,(2022) demonstrated an increased need for critical care interventions and specialized post-discharge care as well as longer ICU and hospital LOS in COVID-19 patients with prolonged mechanical ventilation [36].
Moreover, we found that there is a significant difference between studied groups (IMN , NIV MV and no MV groups ) regarding mortality among studied patients.
In line with our finding, studies of invasive mechanical ventilation to treat COVID-19 respiratory failure have shown a mortality rate greater than 85% [37].
Regarding the notable limitations of the present study, one can refer to limited generalizability of the results since it was a retrospective study based on a single institution. Moreover, relatively limited sample size; this could limit the generalizability of our results.
Conclusion
Obesity, increase age, Hypertension, diabetes, chest disease, cardiac disease, liver disease and renal disease, High LDH, RR, HR, Bps, DBP, RBS, TLC, CRP, PCT, Na, kidney function, IL6, total bilirubin, ferritin, D dimer and Psychological status are considered predictors of admission to ICU in COVID 19 patients. Also study showed that there is significant difference between studied groups ( IMN , NIV MV and no MV groups ) regarding Hb, TLC, PCT, K, Il6, albumin, ferritin, D dimmer and saturation on room air. However, no significant difference was found regarding CRP, kidney function and total bilirubin for the need for mechanical ventilation.
Ethical considerations All procedures were carried out in accordance with the ethical standards. Approval from the ethics committee of the Faculty of Medicine, Menoufia University was taken.
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