Role of Hematological Parameters in the Grading of COVID-19 and a Model to Predict the Outcome in Inpatients
IntroductionHuman coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta subgroups, these viruses have the capacity to transition from animal reservoirs to causing severe respiratory ailments in humans. Notable outbreaks li...
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Published in | Curēus (Palo Alto, CA) Vol. 15; no. 9; p. e45276 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Cureus Inc
14.09.2023
Cureus |
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Abstract | IntroductionHuman coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta subgroups, these viruses have the capacity to transition from animal reservoirs to causing severe respiratory ailments in humans. Notable outbreaks like the 2003 severe acute respiratory distress syndrome (SARS) epidemic and the ongoing coronavirus disease 2019 (COVID-19) pandemic underscore the recurring emergence of novel coronaviruses with severe human infection potential. COVID-19, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly become a leading global cause of severe acute respiratory syndrome. Immune system disruptions and cytokine imbalances contribute to severe cases, necessitating early diagnosis and precise severity assessment.MethodologyThis retrospective cross-sectional study encompassed 211 COVID-19 patients admitted to AIIMS Patna from May to July 2020. Clinical and hematological parameters, including neutrophils, eosinophils, basophils, lymphocytes, monocytes, red and white blood cell counts, platelet count, C-reactive protein (CRP), serum ferritin, and d-dimer, were meticulously recorded. Patients were categorized into non-severe and severe groups using the National Early Warning Score (NEWS) 2.Results Our findings underscore the pivotal role of hematological markers in gauging COVID-19 severity. Notably, markers such as neutrophil-to-lymphocyte ratio (NLR), derived NLR, lymphocyte monocyte ratio, platelet lymphocyte ratio, d-dimer, CRP, and serum ferritin exhibited notable elevation in severe cases. Survival analysis further established the predictive potential of these markers in assessing disease progression and mortality risk. We advocate for the integration of these markers into existing severity assessment frameworks to foster objective clinical evaluations.ConclusionIn conclusion, our study unravels the intricate connection between COVID-19 severity and hematological parameters. We emphasize the early warning capabilities of NLR, derived NLR, platelet lymphocyte ratio, and other markers in predicting disease progression. This research underscores the imperative need to incorporate hematological markers into the evaluation of COVID-19 severity, thereby providing invaluable insights for enhancing clinical practice and patient outcomes. |
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AbstractList | IntroductionHuman coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta subgroups, these viruses have the capacity to transition from animal reservoirs to causing severe respiratory ailments in humans. Notable outbreaks like the 2003 severe acute respiratory distress syndrome (SARS) epidemic and the ongoing coronavirus disease 2019 (COVID-19) pandemic underscore the recurring emergence of novel coronaviruses with severe human infection potential. COVID-19, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly become a leading global cause of severe acute respiratory syndrome. Immune system disruptions and cytokine imbalances contribute to severe cases, necessitating early diagnosis and precise severity assessment.MethodologyThis retrospective cross-sectional study encompassed 211 COVID-19 patients admitted to AIIMS Patna from May to July 2020. Clinical and hematological parameters, including neutrophils, eosinophils, basophils, lymphocytes, monocytes, red and white blood cell counts, platelet count, C-reactive protein (CRP), serum ferritin, and d-dimer, were meticulously recorded. Patients were categorized into non-severe and severe groups using the National Early Warning Score (NEWS) 2.Results Our findings underscore the pivotal role of hematological markers in gauging COVID-19 severity. Notably, markers such as neutrophil-to-lymphocyte ratio (NLR), derived NLR, lymphocyte monocyte ratio, platelet lymphocyte ratio, d-dimer, CRP, and serum ferritin exhibited notable elevation in severe cases. Survival analysis further established the predictive potential of these markers in assessing disease progression and mortality risk. We advocate for the integration of these markers into existing severity assessment frameworks to foster objective clinical evaluations.ConclusionIn conclusion, our study unravels the intricate connection between COVID-19 severity and hematological parameters. We emphasize the early warning capabilities of NLR, derived NLR, platelet lymphocyte ratio, and other markers in predicting disease progression. This research underscores the imperative need to incorporate hematological markers into the evaluation of COVID-19 severity, thereby providing invaluable insights for enhancing clinical practice and patient outcomes. Introduction Human coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta subgroups, these viruses have the capacity to transition from animal reservoirs to causing severe respiratory ailments in humans. Notable outbreaks like the 2003 severe acute respiratory distress syndrome (SARS) epidemic and the ongoing coronavirus disease 2019 (COVID-19) pandemic underscore the recurring emergence of novel coronaviruses with severe human infection potential. COVID-19, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly become a leading global cause of severe acute respiratory syndrome. Immune system disruptions and cytokine imbalances contribute to severe cases, necessitating early diagnosis and precise severity assessment. Methodology This retrospective cross-sectional study encompassed 211 COVID-19 patients admitted to AIIMS Patna from May to July 2020. Clinical and hematological parameters, including neutrophils, eosinophils, basophils, lymphocytes, monocytes, red and white blood cell counts, platelet count, C-reactive protein (CRP), serum ferritin, and d-dimer, were meticulously recorded. Patients were categorized into non-severe and severe groups using the National Early Warning Score (NEWS) 2. Results Our findings underscore the pivotal role of hematological markers in gauging COVID-19 severity. Notably, markers such as neutrophil-to-lymphocyte ratio (NLR), derived NLR, lymphocyte monocyte ratio, platelet lymphocyte ratio, d-dimer, CRP, and serum ferritin exhibited notable elevation in severe cases. Survival analysis further established the predictive potential of these markers in assessing disease progression and mortality risk. We advocate for the integration of these markers into existing severity assessment frameworks to foster objective clinical evaluations. Conclusion In conclusion, our study unravels the intricate connection between COVID-19 severity and hematological parameters. We emphasize the early warning capabilities of NLR, derived NLR, platelet lymphocyte ratio, and other markers in predicting disease progression. This research underscores the imperative need to incorporate hematological markers into the evaluation of COVID-19 severity, thereby providing invaluable insights for enhancing clinical practice and patient outcomes. |
Author | Zabihullah, Md Kumari, Amita Kumar, Tribhuwan Jha, Kamlesh Kumar, Yogesh |
AuthorAffiliation | 2 Physiology, All India Institute of Medical Sciences, Deoghar, Deoghar, IND 1 Physiology, All India Institute of Medical Sciences, Patna, Patna, IND |
AuthorAffiliation_xml | – name: 1 Physiology, All India Institute of Medical Sciences, Patna, Patna, IND – name: 2 Physiology, All India Institute of Medical Sciences, Deoghar, Deoghar, IND |
Author_xml | – sequence: 1 givenname: Yogesh surname: Kumar fullname: Kumar, Yogesh – sequence: 2 givenname: Amita surname: Kumari fullname: Kumari, Amita – sequence: 3 givenname: Tribhuwan surname: Kumar fullname: Kumar, Tribhuwan – sequence: 4 givenname: Kamlesh surname: Jha fullname: Jha, Kamlesh – sequence: 5 givenname: Md surname: Zabihullah fullname: Zabihullah, Md |
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Cites_doi | 10.1245/s10434-011-1814-0 10.1002/ajh.25829 10.1007/s00281-017-0629-x 10.1038/s41598-017-11398-4 10.1016/S0140-6736(20)30183-5 10.3389/fimmu.2020.552909 10.1111/jth.14768 10.1016/S0140-6736(20)30628-0 10.4103/aja202278 10.1016/S2352-3026(20)30217-9 10.1080/09537104.2020.1768523 10.1136/bmjopen-2021-056464 10.1186/s13104-016-2335-5 10.1093/cid/ciaa248 10.4103/jfmpc.jfmpc_545_22 10.1002/ajh.25774 10.1097/01.inf.0000188166.17324.60 10.3389/fpubh.2020.00152 10.1186/s13613-020-00689-1 10.1016/j.cca.2020.03.022 |
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Copyright | Copyright © 2023, Kumar et al. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Copyright © 2023, Kumar et al. 2023 Kumar et al. |
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Snippet | IntroductionHuman coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta... Introduction Human coronaviruses, identified in the 1960s, are known culprits of respiratory infections. Classified into alpha, beta, gamma, and delta... |
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SubjectTerms | Allergy/Immunology Blood platelets Blood pressure Clinical outcomes COVID-19 Cytokines Epidemics Hematology Immunology Infections Infectious Disease Leukocytes Lymphocytes Middle East respiratory syndrome Mortality Neutrophils Oxygen saturation Pandemics Patients Public Health Respiratory diseases Respiratory distress syndrome Severe acute respiratory syndrome coronavirus 2 Survival analysis Vital signs |
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Title | Role of Hematological Parameters in the Grading of COVID-19 and a Model to Predict the Outcome in Inpatients |
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