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ORIGINAL ARTICLE
Year : 2022  |  Volume : 11  |  Issue : 1  |  Page : 29-36

Study of clinical profile, laboratory parameters and outcomes of COVID-19 Patients in a Tertiary Care Centre in North India


1 Department of Pathology, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi, India
2 Department of Pulmonary Medicine, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi, India
3 Department of Preventive and Social Medicine, Atal Bihari Vajpayee Institute of Medical Sciences, Dr. Ram Manohar Lohia Hospital, New Delhi, India

Date of Submission25-Aug-2021
Date of Acceptance15-Dec-2021
Date of Web Publication23-May-2022

Correspondence Address:
Dr. Vijay Kumar
Head of Unit, Haematology, Department of Pathology, Dr. Ram Manohar Lohia Hospital, Delhi
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jdrntruhs.jdrntruhs_116_21

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  Abstract 


Introduction: The coronavirus disease 2019 (COVID-19) pandemic has rapidly spread to many countries around the world and is still spreading due to newer variants. The clinico-hematological characteristics of COVID-19 have been reported from different countries but only a few large-scale studies have been conducted in India. This study aims to describe the clinical-laboratory data and outcome of COVID-19 patients admitted to tertiary care COVID center in North India.
Method: This is a cross-sectional observational study. Data were collected from the medical records department regarding the epidemiological parameters, comorbidities, symptoms, laboratory parameters, and outcomes of patients with the COVID-19 disease admitted to our hospital over 4 months. The follow-up of the laboratory parameters (in a subset of patients) was also evaluated.
Result: The mean age of the patients was 46.5 years with a male preponderance (male: female ratio: 2:1). The comorbidities were present in 103 (60.6%) patients, of which diabetes mellitus (n = 65; 38.2%) was the most common. A significant proportion of the patients were symptomatic (n = 148; 87.1%); the most common symptom being fever followed by dyspnea in 65 and 60% of the patients. Anemia was present in 36.5% of the patients, leukocytosis in 15.3% of the patients while lymphopenia was noted in 41.2% of the patients; 12.9% of the patients had thrombocytopenia. A majority of the patients were managed with supportive treatment. Seventy-five (46.5%) patients required oxygen supplementation and 29 (17%) patients had severe disease. Mortality occurred in 20 (11.8%) patients.
Conclusion: In this single-center study of hospitalized COVID-19 patients, most of the patients were symptomatic having comorbidities. The most common symptoms were fever and shortness of breath. Many patients had lymphopenia and neutrophilia.

Keywords: Clinico-hematological, comorbidities, COVID-19, lymphopenia


How to cite this article:
Rahar S, Misra S, Kannappan A, Kumar V, Deepak D, Panesar S. Study of clinical profile, laboratory parameters and outcomes of COVID-19 Patients in a Tertiary Care Centre in North India. J NTR Univ Health Sci 2022;11:29-36

How to cite this URL:
Rahar S, Misra S, Kannappan A, Kumar V, Deepak D, Panesar S. Study of clinical profile, laboratory parameters and outcomes of COVID-19 Patients in a Tertiary Care Centre in North India. J NTR Univ Health Sci [serial online] 2022 [cited 2022 Jul 2];11:29-36. Available from: https://www.jdrntruhs.org/text.asp?2022/11/1/29/345797




  Introduction Top


The coronavirus disease 2019 (COVID-19) has taken a global toll, with its impact seen everywhere in the world. The Chinese Center For Disease Control and Prevention (CCDC) detected a novel coronavirus, on January 7, 2020, from a patient's throat swab, which the World Health Organization (WHO) named as the 2019-novel corona virus (2019- nCoV) on January 12, 2020.[1] Following this, the novel coronavirus-infected pneumonia (NCIP) spread rampantly across the globe leading the WHO to declare NCIP as a Public Health Emergency of International Concern on January 30, 2020.[2] It was renamed coronavirus disease 2019 (COVID-19) on February 11, 2020.[3] In India, the first case of COVID-19 was reported on January 30, 2020, in Kerala.[4]

It is vital to understand and identify the main clinical and laboratory parameters of the COVID-19 patients which can help in the early detection and isolation of the infected individuals, to minimize the spread of the disease, and to better manage patients who are likely to have severe outcomes. This large study aims to present the clinico-hematological parameters of the patients affected by COVID-19 in the Indian scenario which can be used as a reference for future research and can help in clinical decision-making as well as risk stratification and prognostication of the patients.


  Materials and Methods Top


In this cross-sectional retrospective observational study, all real-time reverse-transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19-positive patients admitted to a tertiary care hospital in North India, from July 10, 2020, to October 25, 2020, were included. The Institute's Ethics Committee approval was obtained before data collection.

The following data were retrieved from the case history files of the patients by manual as well as electronic data record keeping system: demographic parameters (age, gender); presenting symptoms; presence of any comorbidities like diabetes mellitus (DM), hypertension, chronic kidney disease (CKD), chronic liver disease (CLD), chronic lung diseases, coronary artery disease (CAD), neurological disorder, malignancy, other chronic diseases (autoimmune), immunosuppressed state (transplant recipient/retrovirus positive); vital parameters like temperature, SpO2 (oxygen saturation at room air), pulse rate, respiratory rate (RR), and blood pressure at the time of admission were recorded; the hematological and laboratory parameters—complete blood count (CBC) including—hemoglobin, total leukocyte count (TLC), differential leukocyte count including neutrophils and lymphocytes, neutrophil-lymphocyte ratio (NLR), liver function tests including total bilirubin, direct bilirubin, serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic-pyruvic transaminase (SGPT) and kidney function tests including urea, creatinine, serum electrolytes including sodium, potassium, chlorine were evaluated at the time of admission (baseline) and at the time of discharge or death (endpoint). Blood glucose, C- reactive protein (CRP), ferritin, procalcitonin, prothrombin time (PT), activated partial thromboplastin time (aPTT), creatinine kinase (CKMB), lactate dehydrogenase (LDH) were monitored once; the chest X-ray findings; whether intensive care unit (ICU) admission was required; the number of days for which the patient was admitted in hospital; duration between the first positive real-time RT-PCR to the first negative RT-PCR was recorded to calculate the duration of the infectivity; the treatment and outcome (discharge or death) of the patient was recorded. The severity of the disease was categorized as mild, moderate, or severe.[5]

The mild category had patients with uncomplicated upper respiratory tract infection with or without symptoms with normal SpO2; the moderate category had clinical features of hypoxia or dyspnea with SpO2 90–94% at room air or respiratory rate of ≥24 per minute or evidence of pneumonia on radiology without the signs of severe disease; a severe disease had clinical signs of pneumonia plus either of these, that is, RR >30 per minute, SpO2 <90 percent at room air, acute respiratory distress syndrome, and sepsis.

Statistics

The data collected were entered in MS Excel and analyzed by the SPSS software (SPSS Inc., Chicago, IL). Descriptive tables were drawn. The quantitative data were expressed as mean ± SD while the qualitative data were expressed as a percentage. Appropriate statistical tests were applied for analysis such as Pearson's Chi-square test for qualitative data, and Analysis of Variance (ANOVA) /Student's t-test for quantitative data. A P-value of <0.05 was considered significant.


  Result Top


Data from 170 patients were studied with ages ranging from 5 months to 98 years; the mean age being 46.5 ± 16.5 years; 67.1% of the patients were males with a male: female ratio of 2:1. The maximum number of patients were in the middle age group. Only 4.1% of the patients were in the pediatric age group and 25.3% of the patients were in the >60 years old group. Only 4.7% of the patients gave a history of close contact with a COVID-19-positive patient.

Comorbidities were present in 103 (60.6%) patients, of which DM (n = 65; 38.2%) was most commonly observed, while 19 (11.2%) had CAD and 39 (22.9%) had hypertension. Thirty-seven (21.76%) patients had more than one comorbidity. One hundred and forty-eight (87.1%) patients were symptomatic with the most common symptoms being fever (n = 111; 65.3%), shortness of breath (n = 102, 60%), and cough (n = 87; 51.2%). Gastrointestinal symptoms like nausea or vomiting and diarrhea were reported in 4.12 and 2.35%, respectively. Twenty-two (12.9%) patients were asymptomatic, of which 4 patients were admitted for surgical intervention and 13 were pregnant females; 60 (35.3%) patients had more than two symptoms at the time of presentation.

The mean duration of the hospital stay was 15.05 ± 7.86 days ranging from 3 to 48 days. The duration of the hospital stay was shorter in those patients who were in the severe category at the time of admission and succumbed to death.

The chest X-ray was normal in 35.3% of the patients while bilateral infiltrates were noticed in 49.4% and pneumonia was present in 14.7% of the patients. One patient had malignant mesothelioma and pleural effusion. Various clinical characteristics of the patients are highlighted in [Table 1].
Table 1: Baseline Characteristics, Clinical Outcomes, and Treatment of Covid-19 Patients (N=170)

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At the time of admission, 35 (20.6%) patients had fever >38°C or 100.4°F. Only 29 (17.1%) patients had severe disease at admission while the remaining were in the mild or moderate category. Twelve (7.1%) patients were admitted to the ICU. Anemia was present in 62 (36.5%) patients. Leukocytosis was noted in 26 (15.3%) patients of which lymphopenia was noted in 70 (41.2%) patients while neutrophilia was noted in 45 (26.5%) patients. Twenty-two (12.9%) patients had thrombocytopenia. However, it was noted that PT and aPTT were increased in only 25 and 16.6% of the patients. Among the inflammatory markers, procalcitonin was increased in 100%, LDH in 96%, and ferritin in 75% of the patients, respectively. Other laboratory parameters recorded are tabulated in [Table 2].
Table 2: Baseline Hematological and Laboratory Parameters of COVID-19 Patients

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Forty-one (24.1%) patients were treated with supportive care and required only symptomatic treatment, that is, antihistamines, vitamin C, and paracetamol. Azithromycin was prescribed to 121 (71.2%) patients, hydroxychloroquine was administered to 32 (18.8%) patients; 44.7% of the patients were also given tamiflu and only 4.1% of the patients were prescribed steroids. Apart from the above treatment, the patients were continued on treatment for their pre-existing diseases. Seventy-nine (46.5%) patients required oxygen supplementation and were provided that with the help of a nasal prong or face mask or a non-rebreathing mask as clinically indicated. Out of the 170 patients, 20 died, giving a mortality rate of 11.8%. Eighteen deaths were in the severe group, mortality being 90% in the severe category. Fifteen patients (8.8%) had type 1 respiratory failure, seven of which expired. The mean time to RT-PCR negativity, calculated as the duration from the first positive report to the first negative report, was 11.78 ± 4.93 days.

Comparison of clinical and laboratory parameters of asymptomatic and symptomatic patients: The asymptomatic patients were in the younger age group with a mean age of 35.32 ± 13.41, while among the symptomatic patients, the mean age was 48.23 ± 16.26 (P < 0.001). The comorbidities were also higher in the symptomatic group (110/148), while in the asymptomatic group, only 3 of the 22 patients had comorbidity (P < 0.001). There was also a significant difference in the number of days to RT-PCR conversion from positive to negative (P = 0.001), however, there was no significant difference in the duration of hospital stay between the two groups (P = 0.67). The SpO2 was also lower in the symptomatic group (P = 0.001). The hemoglobin level was higher in the symptomatic group as compared to the asymptomatic group (P = 0.025).

There was no significant difference in the baseline laboratory parameters such as TLC, NLR, platelet counts, creatinine, uric acid, total bilirubin, direct bilirubin, total protein, albumin, alkaline phosphatase, sodium, and potassium levels between the symptomatic and asymptomatic patients. However, a significant difference was found in the urea levels, alanine aminotransferase/SGPT, aspartate aminotransferase/SGOT, and chloride levels between the two groups as shown in [Table 3].
Table 3: Comparison of Clinical and Laboratory Parameters between Asymptomatic and Symptomatic COVID-19 Patients

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Comparison of baseline and endpoint laboratory parameters of the patients: When the patients' laboratory parameters were compared using the paired T-test at the time of admission to the endpoint, that is, the time of discharge or death, a significant difference was found in the following parameters: neutrophils, lymphocytes, platelet count, urea, uric acid, SGOT, and chloride levels while there was no significant difference in the hemoglobin, TLC, creatinine, total bilirubin SGPT, alkaline phosphatase, sodium, and potassium levels [Table 4].
Table 4: Comparison of Laboratory Parameters of The Patients at The Time of Admission and at The Time of Discharge/Death

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Comparison of clinical and laboratory parameters between the mild, moderate, and severe disease: When the parameters were compared between the three groups, that is, mild, moderate, and severe groups using the Analysis of Variance (ANOVA) test and Pearson's Chi-square test, a significant difference was found between the age, presence of comorbidities and symptoms, outcome of disease, duration of hospital stay, RT-PCR negativity, hemoglobin, neutrophil, and lymphocyte count, NLR, red blood cell (RBC) count, urea, creatinine, uric acid, and albumin levels [Table 5].
Table 5: Comparison of Parameters among The Mild, Moderate, and Severe Groups

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  Discussion Top


This is a descriptive study on the epidemiology and clinical characteristics of 170 COVID-19 patients admitted to a tertiary care hospital in North India. Many disparities in the clinical and demographic parameters have been noted between different countries and even within the same country. [Table 6] highlights the comparison of a few of the parameters between some Indian and International studies.[6],[7],[8],[9],[10],[11]
Table 6: Comparison of Different Parameters of Previous Studies With The Current Study

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The mean age (46.55 years) in this study is similar to the studies in China[6],[12] though it is slightly higher as compared to other Indian studies.[9],[10],[11] About 4.1% were in the pediatric age group. The youngest patient was a 5-month female who presented with loose stools and not with the typical respiratory symptoms of COVID-19, therefore, there is a need to be vigilant regarding the unusual symptoms that can be confused with other diseases, especially in pediatric patients.[13] The other four children had some pre-existing comorbidity (bone marrow transplant, ependymoma recurrence, and bacterial pneumonia). The rest of the children had mild symptoms.

The disease was more commonly seen in males compared to females which is similar to other Indian and worldwide studies.[6],[7],[8],[9],[10],[11] A hypothesis put forward for this male preponderance is a larger male population working in disease-exposed areas. Another hypothesis is attributed to protection from the X chromosome and the female hormones playing an essential role in innate and adaptive immunity.[14]

A significant number of patients were symptomatic at the time of admission with the most common symptom being fever akin to the previous studies.[6],[7],[8],[11] The majority of the patients had comorbidities (60.6%), of which DM was the most common in this study which is similar to the Indian studies[9],[11] while hypertension was more common in the International studies.[6],[8] Sixty-seven (39.4%) patients had no comorbidities, of which 13 patients were pregnant females and the other 4 had come for some surgical intervention like gastrointestinal surgery and fracture. Pregnant women infected with COVID-19 disease were in the mild category. All the neonates tested were found to be negative for COVID-19. Proper separate delivery rooms and operation theaters are essential for managing such patients.[13]

The mean time to RT-PCR conversion from positive to negative was only 11.8 ± 4.9 days which was lower than the other studies.[9],[15] This could be because most patients presented late to the hospital and got themselves tested many days after the appearance of the first symptom.

The hemoglobin levels were higher in the symptomatic group which could be due to the smaller number of patients in the asymptomatic group (n = 22) compared to the symptomatic group (n = 148). Also, there were 13 pregnant females in the asymptomatic group. In this study, neutrophilia was found in 26.5% of the patients at the time of admission while lymphopenia was found in 41.2% of the patients. Lymphopenia has been commonly reported in many studies in patients with severe and fatal COVID-19 disease.[16] The mechanism of lymphopenia could be due to the deranged cytokine environment leading to increased apoptosis or direct cytopathic effects.[17],[18] Recent evidence has suggested that neutrophils might play a more important role in the pathogenesis of the COVID-19 disease by promoting organ injury and coagulopathy by direct tissue infiltration and formation of neutrophil extracellular traps (NETs).[19],[20] Increased neutrophils may be caused by deranged immune homeostasis or due to secondary bacterial infection and/or glucocorticoid release which could be either endogenous in response to stress or exogenous administration. Lymphopenia and neutrophilia at the time of admission are associated with poor outcomes in patients with COVID-19.[21] In this study, the neutrophil count was higher and the lymphocyte count was lower at the time of admission while at the time of discharge, the neutrophil count decreased and the lymphocyte count increased.

In this study, the requirement of ICU care was seen in only 7.1% of the patients unlike in the other Indian studies.[10],[11] Severe disease was seen in 17.1% of the patients, similar to the studies in China.[6],[7] SpO2 at room air at the time of admission was lower. The respiratory and pulse rates were higher in severe category patients. Also, the incidence of respiratory failure was higher, requiring intubation in severe cases. The mortality rate was 11.8% out of which 45% had more than one comorbidity.


  Conclusion Top


This is one of the largest Indian studies that compares the clinical and laboratory parameters among the Indian studies and studies from China and the USA. It is the only study which also evaluates the follow-up hematological and laboratory parameters of patients to assess the changes that can occur from the time of admission to the point of discharge or death. Though the vaccination drive has started but questions regarding the efficacy remain unanswered so such studies are important for future references and research.

Acknowledgments

Authors acknowledge the COVID-19 Management Team consisting of faculties and medical technologists from the departments of Anaesthesia & Intensive Care, Internal Medicine, Pulmonary Medicine, Microbiology, Biochemistry, Hematology, Radiodiagnosis, Paediatrics and Hospital Administration.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727-33.  Back to cited text no. 1
    
2.
World Health Organization. WHO Director-General's opening remarks at the media briefing on COVID-19-11 March 2020. Available from: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on covid-19-11-march-2020. [Last accessed on 2020 Jun 01].  Back to cited text no. 2
    
3.
WHO. WHO Director-General's remarks at the media briefing on 2019-nCoV on 11 February 2020. Available from: https://www.who.int/dg/speeches/detail/who-director-general-s-remarks-at-the-media-briefing-on-2019-ncov- on-11-february-2020. [Last accessed on 2020 Apr 07].  Back to cited text no. 3
    
4.
Andrews MA, Areekal B, Rajesh KR, Krishnan J, Suryakala R, Krishnan B, et al. First confirmed case of COVID-19 infection in India: A case report. Indian J Med Res 2020;151:490-2.  Back to cited text no. 4
[PUBMED]  [Full text]  
5.
Ministry of Health & Family Welfare, Government of India. Revised guidelines on clinical management of COVID-19. Available from: https://www. mohfw.gov.in/pdf/Revised National Clinical Management Guideline for COVID 1931032020.pdf. [Last accessed on 2020 Jun 20].  Back to cited text no. 5
    
6.
Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20.  Back to cited text no. 6
    
7.
Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020;395:507-13.  Back to cited text no. 7
    
8.
Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York city area. JAMA 2020;323:2052-9.  Back to cited text no. 8
    
9.
Mohan A, Tiwari P, Bhatnagar S, Patel A, Maurya A, Dar L, et al. Clinico-demographic profile & hospital outcomes of COVID-19 patients admitted at a tertiary care centre in north India. Indian J Med Res 2020;152:61-9.  Back to cited text no. 9
[PUBMED]  [Full text]  
10.
Gupta N, Ish P, Kumar R, Dev N, Yadav SR, Malhotra N, et al. Evaluation of the clinical profile, laboratory parameters and outcome of two hundred COVID-19 patients from a tertiary centre in India. Monaldi Arch Chest Dis 2020;90:193-6. doi: 10.4081/monaldi. 2020.1507.  Back to cited text no. 10
    
11.
Soni SL, Kajal K, Yaddanapudi LN, Malhotra P, Puri GD, Bhalla A, et al. Demographic & clinical profile of patients with COVID-19 at a tertiary care hospital in north India. Indian J Med Res. 2021;153:115-25.  Back to cited text no. 11
    
12.
Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.  Back to cited text no. 12
    
13.
Kuttiatt VS, Abraham PR, Menon RP, Vaidya PC, Rahi M. Coronavirus disease 2019 in children: Clinical & epidemiological implications. Indian J Med Res 2020;152:21-40.  Back to cited text no. 13
[PUBMED]  [Full text]  
14.
Jaillon S, Berthenet K, Garlanda C. Sexual dimorphism in innate immunity. Clin Rev Allergy Immunol 2019;56:308–21.  Back to cited text no. 14
    
15.
Wölfel R, Corman VM, Guggemos W, Seilmaier M, Zange S, Müller MA, et al. Virological assessment of hospitalized patients with COVID-2019. Nature 2020;581:465-9.  Back to cited text no. 15
    
16.
Henry BM. COVID-19, ECMO, and lymphopenia: A word of caution. Lancet Respir Med 2020;8:e24.  Back to cited text no. 16
    
17.
Wang X, Xu W, Hu G, Xia S, Sun Z, Liu Z, et al. Retraction Note to: SARS-CoV-2 infects T lymphocytes through its spike protein-mediated membrane fusion. Cell Mol Immunol 2020;17:894. doi: 10.1038/s41423-020-0498-4.  Back to cited text no. 17
    
18.
Tan L, Wang Q, Zhang D, Ding J, Huang Q, Tang YQ, et al. Lymphopenia predicts disease severity of COVID-19: A descriptive and predictive study. Signal Transduct Target Ther. 2020;5:33. doi: 10.1038/s41392-020-0148-4. Erratum in: Signal Transduct Target Ther. 2020;5:61.  Back to cited text no. 18
    
19.
Henry BM, Vikse J, Benoit S, Favaloro EJ, Lippi G. Hyperinflammation and derangement of renin-angiotensinaldosterone system in COVID-19: A novel hypothesis for clinically suspected hypercoagulopathy and microvascular immunothrombosis. Clin Chim Acta 2020;507:167-73.  Back to cited text no. 19
    
20.
Zuo Y, Yalavarthi S, Shi H, Gockman K, Zuo M, Madison JA, et al. Neutrophil extracellular traps in COVID-19. JCI Insight 2020;5:e138999. doi: 10.1172/jci.insight. 138999.  Back to cited text no. 20
    
21.
Henry B, Cheruiyot I, Vikse J, Mutua V, Kipkorir V, Benoit J, et al. Lymphopenia and neutrophilia at admission predicts severity and mortality in patients with COVID-19: A meta-analysis. Acta Biomed 2020;91:e2020008.  Back to cited text no. 21
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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