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Routine laboratory parameters, including complete blood count, predict COVID-19 in-hospital mortality in geriatric patients.
Olivieri, Fabiola; Sabbatinelli, Jacopo; Bonfigli, Anna Rita; Sarzani, Riccardo; Giordano, Piero; Cherubini, Antonio; Antonicelli, Roberto; Rosati, Yuri; Del Prete, Simona; Di Rosa, Mirko; Corsonello, Andrea; Galeazzi, Roberta; Procopio, Antonio Domenico; Lattanzio, Fabrizia.
  • Olivieri F; Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Center of Clinical Pathology and Innovative Therapy, IRCCS INRCA, Ancona, Italy.
  • Sabbatinelli J; Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Laboratory Medicine Unit, Azienda Ospedaliero Universitaria Ospedali Riuniti, Ancona, Italy.
  • Bonfigli AR; Scientific Direction, IRCCS INRCA, Ancona, Italy. Electronic address: a.bonfigli@inrca.it.
  • Sarzani R; Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Internal Medicine and Geriatrics, Italian National Research Centre on Aging, Hospital "U. Sestilli", IRCCS INRCA, Ancona, Italy.
  • Giordano P; Internal Medicine and Geriatrics, Italian National Research Centre on Aging, Hospital "U. Sestilli", IRCCS INRCA, Ancona, Italy.
  • Cherubini A; Geriatria, Accettazione geriatrica e Centro di Ricerca Per l'invecchiamento, IRCCS INRCA, Ancona, Italy.
  • Antonicelli R; Cardiology Unit, IRCCS INRCA, Ancona, Italy.
  • Rosati Y; Pneumologia, IRCCS INRCA, Osimo, Italy.
  • Del Prete S; Medicina Interna, IRCCS INRCA, Osimo, Italy.
  • Di Rosa M; Unit of Geriatric Pharmacoepidemiology and Biostatistics, IRCCS INRCA, Cosenza, Italy.
  • Corsonello A; Unit of Geriatric Pharmacoepidemiology and Biostatistics, IRCCS INRCA, Cosenza, Italy; Geriatric Medicine, IRCCS INRCA, 87100 Cosenza, Italy.
  • Galeazzi R; Clinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy.
  • Procopio AD; Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona, Italy; Clinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy.
  • Lattanzio F; Scientific Direction, IRCCS INRCA, Ancona, Italy.
Mech Ageing Dev ; 204: 111674, 2022 06.
Article in English | MEDLINE | ID: covidwho-2015815
ABSTRACT
To reduce the mortality of COVID-19 older patients, clear criteria to predict in-hospital mortality are urgently needed. Here, we aimed to evaluate the performance of selected routine laboratory biomarkers in improving the prediction of in-hospital mortality in 641 consecutive COVID-19 geriatric patients (mean age 86.6 ± 6.8) who were hospitalized at the INRCA hospital (Ancona, Italy). Thirty-four percent of the enrolled patients were deceased during the in-hospital stay. The percentage of severely frail patients, assessed with the Clinical Frailty Scale, was significantly increased in deceased patients compared to the survived ones. The age-adjusted Charlson comorbidity index (CCI) score was not significantly associated with an increased risk of death. Among the routine parameters, neutrophilia, eosinopenia, lymphopenia, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein, procalcitonin, IL-6, and NT-proBNP showed the highest predictive values. The fully adjusted Cox regressions models confirmed that high neutrophil %, NLR, derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), and low lymphocyte count, eosinophil %, and lymphocyte-to-monocyte ratio (LMR) were the best predictors of in-hospital mortality, independently from age, gender, and other potential confounders. Overall, our results strongly support the use of routine parameters, including complete blood count, in geriatric patients to predict COVID-19 in-hospital mortality, independent from baseline comorbidities and frailty.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Frailty / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Aged / Humans Language: English Journal: Mech Ageing Dev Year: 2022 Document Type: Article Affiliation country: J.mad.2022.111674

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Frailty / COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Aged / Humans Language: English Journal: Mech Ageing Dev Year: 2022 Document Type: Article Affiliation country: J.mad.2022.111674