María C Martín1, Aurora Jurado2, Cristina Abad-Molina3, Antonio Orduña3, Oscar Yarce4, Ana M Navas4, Vanesa Cunill5, Danilo Escobar5, Francisco Boix6, Sergio Burillo-Sanz6, María C Vegas-Sánchez7, Yesenia Jiménez-de Las Pozas7, Josefa Melero8, Marta Aguilar8, Oana Irina Sobieschi8, Marcos López-Hoyos9, Gonzalo Ocejo-Vinyals9, David San Segundo9, Delia Almeida10, Silvia Medina10, Luis Fernández11, Esther Vergara11, Bibiana Quirant12, Eva Martínez-Cáceres12, Marc Boiges12, Marta Alonso13, Laura Esparcia-Pinedo14, Celia López-Sanz14, Javier Muñoz-Vico15, Serafín López-Palmero15, Antonio Trujillo4, Paula Álvarez4, Álvaro Prada16, David Monzón16, Jesús Ontañón17, Francisco M Marco18, Sergio Mora18, Ricardo Rojo19, Gema González-Martínez20, María T Martínez-Saavedra20, Juana Gil-Herrera21, Sergi Cantenys-Molina21, Manuel Hernández22, Janire Perurena-Prieto22, Beatriz Rodríguez-Bayona23, Alba Martínez24, Esther Ocaña24, Juan Molina4. 1. Centro de Hemoterapia y Hemodonación de Castilla y León, Valladolid, Spain. 2. Department of Immunology and Allergology, Hospital Universitario Reina Sofía-Instituto de Investigación Biomédica de Córdoba (IMIBIC), Avd. Menéndez Pidal s/n, 14004, Córdoba, Spain. aurora.jurado.sspa@juntadeandalucia.es. 3. Department of Microbiology and Immunology, Hospital Clínico Universitario, Valladolid, Spain. 4. Department of Immunology and Allergology, Hospital Universitario Reina Sofía-Instituto de Investigación Biomédica de Córdoba (IMIBIC), Avd. Menéndez Pidal s/n, 14004, Córdoba, Spain. 5. Department of Immunology, Hospital Universitario Son Espases-Human Immunopathology Research Laboratory, Institut d'Investigació Sanitària de les Illes Balears (IdISBa), Palma de Mallorca, Spain. 6. Department of Immunology, Hospital Clínico Universitario, Salamanca, Spain. 7. Department of Immunology, Fundación Jiménez Díaz, Madrid, Spain. 8. Department of Immunology, Hospital Universitario de Badajoz, Badajoz, Spain. 9. Department of Immunology, Hospital Universitario Marqués de Valdecilla, Santander, Spain. 10. Laboratory of Immunology, Complejo Hospitalario Nuestra Señora de la Candelaria, Santa Cruz de Tenerife, Spain. 11. Laboratoy of Immunology and Genetics, Hospital San Pedro de Alcántara, Cáceres, Spain. 12. Department of Immunology, Hospital Germans Trias i Pujols, Barcelona, Spain. 13. Department of Immunology, Hospital de Cruces, Baracaldo, Spain. 14. Department of Immunology, Hospital Universitario La Princesa, Madrid, Spain. 15. Department of Immunology, Hospital Torrecárdenas, Almería, Spain. 16. Department of Immunology, Hospital de Donostia, San Sebastián, Spain. 17. Unit of Immunology, Hospital General Universitario, Albacete, Spain. 18. Laboratory Unit, Hospital General, Alicante, Spain. 19. Department of Immunology, Complejo Hospitalario, La Coruña, Spain. 20. Unit of Immunology, Hospital Universitario Insular-Materno Infantil, Las Palmas de Gran Canaria, Spain. 21. Department of Immunology, Hospital General Universitario e Instituto de Investigación Sanitaria, "Gregorio Marañón", Madrid, Spain. 22. Department of Immunology, Hospital Universitario Vall d'Hebron, Barcelona, Spain. 23. Laboratory Unit, Hospital Juan Ramón Jiménez, Huelva, Spain. 24. Laboratory Unit, Complejo Hospitalario, Jaén, Spain.
Abstract
BACKGROUND: One hundred fifty million contagions, more than 3 million deaths and little more than 1 year of COVID-19 have changed our lives and our health management systems forever. Ageing is known to be one of the significant determinants for COVID-19 severity. Two main reasons underlie this: immunosenescence and age correlation with main COVID-19 comorbidities such as hypertension or dyslipidaemia. This study has two aims. The first is to obtain cut-off points for laboratory parameters that can help us in clinical decision-making. The second one is to analyse the effect of pandemic lockdown on epidemiological, clinical, and laboratory parameters concerning the severity of the COVID-19. For these purposes, 257 of SARSCoV2 inpatients during pandemic confinement were included in this study. Moreover, 584 case records from a previously analysed series, were compared with the present study data. RESULTS: Concerning the characteristics of lockdown series, mild cases accounted for 14.4, 54.1% were moderate and 31.5%, severe. There were 32.5% of home contagions, 26.3% community transmissions, 22.5% nursing home contagions, and 8.8% corresponding to frontline worker contagions regarding epidemiological features. Age > 60 and male sex are hereby confirmed as severity determinants. Equally, higher severity was significantly associated with higher IL6, CRP, ferritin, LDH, and leukocyte counts, and a lower percentage of lymphocyte, CD4 and CD8 count. Comparing this cohort with a previous 584-cases series, mild cases were less than those analysed in the first moment of the pandemic and dyslipidaemia became more frequent than before. IL-6, CRP and LDH values above 69 pg/mL, 97 mg/L and 328 U/L respectively, as well as a CD4 T-cell count below 535 cells/μL, were the best cut-offs predicting severity since these parameters offered reliable areas under the curve. CONCLUSION: Age and sex together with selected laboratory parameters on admission can help us predict COVID-19 severity and, therefore, make clinical and resource management decisions. Demographic features associated with lockdown might affect the homogeneity of the data and the robustness of the results.
BACKGROUND: One hundred fifty million contagions, more than 3 million deaths and little more than 1 year of COVID-19 have changed our lives and our health management systems forever. Ageing is known to be one of the significant determinants for COVID-19 severity. Two main reasons underlie this: immunosenescence and age correlation with main COVID-19 comorbidities such as hypertension or dyslipidaemia. This study has two aims. The first is to obtain cut-off points for laboratory parameters that can help us in clinical decision-making. The second one is to analyse the effect of pandemic lockdown on epidemiological, clinical, and laboratory parameters concerning the severity of the COVID-19. For these purposes, 257 of SARSCoV2 inpatients during pandemic confinement were included in this study. Moreover, 584 case records from a previously analysed series, were compared with the present study data. RESULTS: Concerning the characteristics of lockdown series, mild cases accounted for 14.4, 54.1% were moderate and 31.5%, severe. There were 32.5% of home contagions, 26.3% community transmissions, 22.5% nursing home contagions, and 8.8% corresponding to frontline worker contagions regarding epidemiological features. Age > 60 and male sex are hereby confirmed as severity determinants. Equally, higher severity was significantly associated with higher IL6, CRP, ferritin, LDH, and leukocyte counts, and a lower percentage of lymphocyte, CD4 and CD8 count. Comparing this cohort with a previous 584-cases series, mild cases were less than those analysed in the first moment of the pandemic and dyslipidaemia became more frequent than before. IL-6, CRP and LDH values above 69 pg/mL, 97 mg/L and 328 U/L respectively, as well as a CD4 T-cell count below 535 cells/μL, were the best cut-offs predicting severity since these parameters offered reliable areas under the curve. CONCLUSION:Age and sex together with selected laboratory parameters on admission can help us predict COVID-19 severity and, therefore, make clinical and resource management decisions. Demographic features associated with lockdown might affect the homogeneity of the data and the robustness of the results.
Entities:
Keywords:
Area under the curve; COVID-19; Cut-off points; Immunity; Immunosenescence; Lockdown; Lymphocytes; Renin-angiotensin-aldosterone system inhibitors; Severe acute respiratory syndrome coronavirus 2
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