|Year : 2021 | Volume
| Issue : 2 | Page : 59-63
Clinical and laboratory profile of COVID-19 patients admitted at a tertiary care center in New Delhi and assessment of factors predicting disease severity
Piyush Jain, Nitin Sinha, M K Hari Prasad, Vaibhav Padole
Department of Medicine, ABVIMS, Dr RML Hospital, New Delhi, India
|Date of Submission||04-Dec-2020|
|Date of Decision||19-Jan-2021|
|Date of Acceptance||20-Jan-2021|
|Date of Web Publication||22-Mar-2021|
Dr. Piyush Jain
Department of Medicine, ABVIMS and RML Hospital, Delhi - 110001
Source of Support: None, Conflict of Interest: None
Background: This study was conducted in nonintensive care unit COVID-19 patients admitted in a tertiary care center, to assess the clinical profile and find surrogate markers to predict the severity of COVID-19 at the time of admission. Methodology: It is a cross-sectional observational study. Clinical and laboratory data were compiled of patients admitted in COVID wards in a tertiary care center. Patients were stratified clinically according to the severity of COVID pneumonia. The admission clinical and laboratory parameters were compared between the severe and nonsevere COVID patients. Results: The study included 63 patients of which 46 were males, with a mean age of 47 years. Patients were classified into mild (32%), moderate (19%), and severe (49%) categories according to national guidelines. Fever (81%), cough (67%), and dyspnea (67%) were the most commonly observed symptoms. In comparative analysis, mean C-reactive protein (CRP), serum ferritin, and neutrophil–lymphocyte ratio (NLR) were significantly higher in severe COVID-19 patients and the admission PaCO2 significantly lower compared to nonsevere patients. Conclusion: The study shows that raised NLR, CRP, serum ferritin, and low PaCO2 levels at the time of admission are important predictors of disease severity.
Keywords: Clinical profile, SARS-CoV-2, severity biomarkers
|How to cite this article:|
Jain P, Sinha N, Prasad M K, Padole V. Clinical and laboratory profile of COVID-19 patients admitted at a tertiary care center in New Delhi and assessment of factors predicting disease severity. Indian J Med Spec 2021;12:59-63
|How to cite this URL:|
Jain P, Sinha N, Prasad M K, Padole V. Clinical and laboratory profile of COVID-19 patients admitted at a tertiary care center in New Delhi and assessment of factors predicting disease severity. Indian J Med Spec [serial online] 2021 [cited 2022 Jan 18];12:59-63. Available from: http://www.ijms.in/text.asp?2021/12/2/59/311696
| Introduction|| |
At the end of December 2019, Wuhan experienced an outbreak of severe respiratory illness infecting over 70,000 people within 50 days. The etiological agent isolated was found to be a single-stranded positive-sense RNA virus that belonged to the Coronaviridae group. It was named SARS-CoV-2 by the International Committee on Taxonomy of Viruses. On February 11, 2020, the WHO named the disease as COVID-19 and then on March 11, 2020, declared it a pandemic. At present, it has turned into an extraordinary catastrophe toward the world's geopolitical scenario, economic structure, and health system. At the time of writing this article, novel coronavirus (2019) has infected about 45 million people worldwide, killing over 1 million people. India alone has over 8 million infected people with more than 120,000 deaths.
SARS-CoV-2 spreads primarily via respiratory droplets that are transmitted from person to person who are in close contact. The median incubation period is around 5.4 days as seen in a Wuhan cohort. The clinical presentation ranges from asymptomatic to severe pneumonia, sepsis, shock, and ARDS. In early reports from Wuhan, mild illness was seen in 81% of the infected cases with around 14% accounting for severe disease. In the same cohort, all deaths occurred among patients with a critical illness, and the overall case fatality rate was 2.3%.
Age is a strong risk factor for severe illness, complications, and death., Patients with no underlying medical comorbid conditions have an overall case fatality rate of <1%. Case fatality is higher for patients with comorbidities. The severe cases are associated with elevated levels of inflammatory biomarkers such as serum lactate dehydrogenase, creatine kinase, C-reactive protein (CRP), D-dimer, procalcitonin, and ferritin.
This study embarks to establish a clinical, laboratory, and radiological profile of COVID-19-positive patients and to ascertain factors associated with severity.
| Methodology|| |
We compiled clinical, laboratory, and radiological data of patients admitted in the COVID-19 wards of ABVIMS and Dr RML Hospital, Delhi, between May 15 and 31, 2020.
A confirmed case of COVID-19 was defined as a positive result by real-time reverse transcriptase–polymerase chain reaction assay of nasal and pharyngeal swab specimens. We assessed clinical, biochemical profile, hematological profile, arterial blood gas values, and biomarkers such as CRP, ferritin, and procalcitonin within 24 h of admission.
An axillary temperature of 37.5°C or higher was taken as a fever. Total lymphocyte count of <1500 and >4000 cells per cubic millimeter was considered lymphocytopenia and lymphocytosis, respectively. Hemoglobin <12 g/dL was considered anemia, serum albumin <3.5 g/dL was considered hypoalbuminemia, and acute kidney injury was considered if serum creatinine increased by 0.3 mg/dL or more within 48 h or urine output decreased to <0.5 mL/kg/h in the last 6 h.
The severity of COVID-19 was assessed as per the Ministry of Health and Family Welfare (MOHFW) guidelines, Government of India.
- Mild cases were those COVID-19 patients who had uncomplicated upper respiratory tract infection with no evidence of hypoxia and breathlessness
- Moderate cases were those with radiological and clinical features of pneumonia with SpO2 in the range of 90%–94%, with a respiratory rate of more or equal to 24 breaths per minute
- Severe cases were those who were meeting any of the following criteria: respiratory distress with respiratory rate ≥30/min and oxygen saturation ≤90% at rest or respiratory rate ≥24 breaths per minute along with features of sepsis and septic shock.
Statistical analysis was carried on IBM SPSS software (version 25.0. Armonk, NY, USA: IBM Corp.). Continuous variables are expressed as mean ± standard deviation, and categorical variables are expressed as a proportion (percentage). For analysis, mild and moderate COVID-19 cases were grouped into one group being called “non-severe COVID-19”. Various demographic, hematological, and laboratory parameters were compared between the nonsevere COVID-19 group and the severe COVID-19 group to ascertain factors that were associated with severity. Univariate logistic regression was used to assess parameters/factors that were associated with severity. Those found to be significantly associated with severity on univariate analysis were further subjected to multiple logistic regressions. P < 0.05 was taken as statistically significant.
| Results|| |
We collected data of 63 patients admitted in COVID-19 wards among which 46 were males and 17 were females.
The mean age of the cohort was 47.03 ± 15.4 years. Forty-six percent of the patients were below the age of 40 and 20.8% above the age of 60 years.
Patients were stratified into mild, moderate, and severe COVID-19 as defined by MOHFW, India. Accordingly, 20 patients had mild, 12 had moderate, and 31 had severe COVID-19.
Seven patients gave a history of close contact with a diagnosed COVID-19 patient. None gave a history of international or regional travel. None of the patients was a health-care worker.
The most common symptom encountered was fever (80%) which was followed by cough (66%) and dyspnea (66%). Other less common symptoms were sputum (30%), sore throat (25%), diarrhea (8%), anosmia (8%), headache, fatigue, and myalgias. The most common comorbidity encountered was hypertension which was observed in 23% of the patients, followed by diabetes and coronary artery disease in 17% each and chronic kidney disease in 3% of the patients.
The laboratory parameters revealed that 39 patients (61.9%) had hypoalbuminemia, 27 patients (42%) had anemia, and 34 patients (53.9%) had lymphopenia [Table 1].
|Table 1: Distribution of abnormal laboratory findings in COVID-19 patients|
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On chest X-ray, the most common pattern observed was bilateral infiltrates in 47.62% (30) whereas 31% (20) of the patients had normal chest X-rays.
Univariate analysis of various demographic, clinical, and laboratory parameters among the nonsevere and severe groups revealed that neutrophil–lymphocyte ratio (NLR), serum CRP, serum ferritin, PaCO2, and PaO2/FiO2 ratio at the time of admission were significantly different between the two groups [Table 2]. On subjecting these parameters to multiple logistic regressions, PaCO2 and PaO2/FiO2 ratio emerged as significant markers for predicting the severity of COVID-19 patients [Table 3].
|Table 2: Comparison of demographic, clinical and laboratory parameters between nonsevere and severe COVID-19 patients along with univariate analysis|
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Receiver operating characteristic (ROC) analysis [Figure 1] revealed that PaCO2 of <34.30 mmHg on admission had 70.4% sensitivity and 83.3% specificity to predict severity in COVID-19 patients.
|Figure 1: Receiver operating characteristic curve plotted for PaO2/FiO2 and PaCO2 for predicting the severity of COVID-19|
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PaO2/FiO2 ratio of <295.21 on admission had 85.2% sensitivity and 66.7% specificity to predict severity in COVID-19 patients.
| Discussion|| |
This is a descriptive study of COVID-19-positive patients admitted in a tertiary care center in India during the early phase of the pandemic when the nationwide lockdown was there and international travel was restricted. The mean age of the study population was 47 years and was comparable to other studies done worldwide.,,
The most common presenting complaints were fever, cough, and breathlessness. Fever was the most common symptom noted in around 80% of the patients. Similar to the present study, a study from China reported fever in 80% of the patients, but in a large study from Europe, fever was found in only 45% of the patients, and the majority (almost 70%) presented with headache, anosmia, and nasal obstruction. COVID-19 can present as asymptomatic to severe disease with varied clinical features. In a study from India by Dosi et al. reported fever as the major symptom among symptomatic patients though majority were asymptomatic. In present study, breathlessness was observed in 74.2% of the severe COVID patients and 59.4% of the nonsevere COVID patients (P = 0.21).This was quite similar to a study by Gurtoo et al. where 89% of the severe cases had breathlessness at presentation compared to 14.7% and 45.2% of the mild and moderate cases respectively.
Hypertension followed by diabetes was the most common comorbidity observed similar to other previous studies.,, There was no statistically significant difference in presence of comorbidities among the severe and nonsevere groups.
Univariate analysis revealed a significant difference in parameters such as NLR, serum ferritin levels, CRP and admission PaCO2, and PaO2/FiO2 ratio among the severe and nonsevere groups. In a meta-analysis by Zeng et al., inflammatory markers such as CRP, procalcitonin, erythrocyte sedimentation rate, and interleukin-6 (IL-6) were positively correlated with the severity of disease. Yang et al. reported an NLR ratio ≥ 3.3 as an independent poor prognostic marker in COVID-19 patients. Similarly, Gurtoo et al. observed that leukocytosis, neutrophilia, lymphopenia, and increased NLR are associated with increased disease severity and poor survival.
In the present study, multiple logistic linear regressions revealed PaO2/FIO2 ratio and PaCO2 were significantly lower in the severe COVID-19 category compared to nonsevere. ROC analysis revealed that the PaO2/FiO2 ratio of <295.2 has 85.2% sensitivity and 66.7% specificity to predict severity in COVID-19 patients.
Turcato et al. in a study on the Italian population, comparing ABG values at emergency admission with computed tomography (CT) findings in lungs, found that PaO2/FiO2 had an inverse correlation with the percent extension of the pulmonary inflammatory changes on CT (r = 0.451, P < 0.001), as did PaCO2 (r = 0.294). They also found a correlation between the lower PaO2/FiO2 ratio with the death of patients.
In the present study, admission PaCO2 was significantly lower among severe COVID-19 patients, and PaCO2 <34 mmHg has 70% sensitivity and 83% specificity in predicting the severity of COVID-19 patients. A study by Yassin et al., on the prognostication of community-acquired pneumonia, revealed higher mortality among the cohort with hypocapnia at admission compared to hypercapnia and normocapnia. In another study from China in COVID-19 patients, 48% (32/67) of the patients had PaCO2 <35 mmHg at the time of admission, of which 75% expired.
The severity of COVID-19 is currently classified based on SpO2 by pulse oximeter and signs of pneumonia. However, at times, it can be misleading as SpO2 may be inappropriately high despite low PaO2. The explanation for this is that hypoxemia in COVID-19 patients causes tachypnea and increased minute ventilation, thus leading to hypocapnia. The respiratory alkalosis associated with hypoxic hypocapnia shifts the oxyhemoglobin dissociation curve to the left, thereby increasing the oxygen affinity of hemoglobin and thus increased SpO2. Hence, the low PaCO2 at admission may be an important marker for the severity of the disease. Further study is required in COVID-19 patients to confirm its role.
The study had few limitations such as a small study population and limited resources for certain tests such as D-dimer and IL-6 levels.
| Conclusion|| |
The most common symptoms in COVID-19 patients are fever, cough, and breathlessness. The patients with severe disease have raised levels of inflammatory markers such as CRP, serum ferritin, and NLR. The low PaCO2 at admission is another important marker for predicting disease severity. These may be used to predict disease severity, especially in resource-limited settings where other markers such as IL-6 and D-dimer are nonaffordable or have limited availability.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]