%0 Journal Article
%A Martín, María C
%A Jurado, Aurora
%A Abad-Molina, Cristina
%A Orduña, Antonio
%A Yarce, Oscar
%A Navas, Ana M
%A Cunill, Vanesa
%A Escobar, Danilo
%A Boix, Francisco
%A Burillo-Sanz, Sergio
%A Vegas-Sánchez, María C
%A Jiménez-de Las Pozas, Yesenia
%A Melero, Josefa
%A Aguilar, Marta
%A Sobieschi, Oana Irina
%A López-Hoyos, Marcos
%A Ocejo-Vinyals, Gonzalo
%A San Segundo, David
%A Almeida, Delia
%A Medina, Silvia
%A Fernández, Luis
%A Vergara, Esther
%A Quirant, Bibiana
%A Martínez-Cáceres, Eva
%A Boiges, Marc
%A Alonso, Marta
%A Esparcia-Pinedo, Laura
%A López-Sanz, Celia
%A Muñoz-Vico, Javier
%A López-Palmero, Serafín
%A Trujillo, Antonio
%A Álvarez, Paula
%A Prada, Álvaro
%A Monzón, David
%A Ontañón, Jesús
%A Marco, Francisco M
%A Mora, Sergio
%A Rojo, Ricardo
%A González-Martínez, Gema
%A Martínez-Saavedra, María T
%A Gil-Herrera, Juana
%A Cantenys-Molina, Sergi
%A Hernández, Manuel
%A Perurena-Prieto, Janire
%A Rodríguez-Bayona, Beatriz
%A Martínez, Alba
%A Ocaña, Esther
%A Molina, Juan
%T The age again in the eye of the COVID-19 storm: evidence-based decision making.
%D 2021
%@ 1742-4933
%U https://hdl.handle.net/10668/28339
%X 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. 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. 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.
%K Area under the curve
%K COVID-19
%K Cut-off points
%K Immunity
%K Immunosenescence
%K Lockdown
%K Lymphocytes
%K Renin-angiotensin-aldosterone system inhibitors
%K Severe acute respiratory syndrome coronavirus 2
%~