Selected article for: "blood cell count and cell distribution"

Author: Bellan, Mattia; Azzolina, Danila; Hayden, Eyal; Gaidano, Gianluca; Pirisi, Mario; Acquaviva, Antonio; Aimaretti, Gianluca; Aluffi Valletti, Paolo; Angilletta, Roberto; Arioli, Roberto; Avanzi, Gian Carlo; Avino, Gianluca; Balbo, Piero Emilio; Baldon, Giulia; Baorda, Francesca; Barbero, Emanuela; Baricich, Alessio; Barini, Michela; Barone-Adesi, Francesco; Battistini, Sofia; Beltrame, Michela; Bertoli, Matteo; Bertolin, Stephanie; Bertolotti, Marinella; Betti, Marta; Bobbio, Flavio; Boffano, Paolo; Boglione, Lucio; Borrè, Silvio; Brucoli, Matteo; Calzaducca, Elisa; Cammarata, Edoardo; Cantaluppi, Vincenzo; Cantello, Roberto; Capponi, Andrea; Carriero, Alessandro; Casciaro, Giuseppe Francesco; Castello, Luigi Mario; Ceruti, Federico; Chichino, Guido; Chirico, Emilio; Cisari, Carlo; Cittone, Micol Giulia; Colombo, Crizia; Comi, Cristoforo; Croce, Eleonora; Daffara, Tommaso; Danna, Pietro; Della Corte, Francesco; De Vecchi, Simona; Dianzani, Umberto; Di Benedetto, Davide; Esposto, Elia; Faggiano, Fabrizio; Falaschi, Zeno; Ferrante, Daniela; Ferrero, Alice; Gagliardi, Ileana; Galbiati, Alessandra; Gallo, Silvia; Garavelli, Pietro Luigi; Gardino, Clara Ada; Garzaro, Massimiliano; Gastaldello, Maria Luisa; Gavelli, Francesco; Gennari, Alessandra; Giacomini, Greta Maria; Giacone, Irene; Giai Via, Valentina; Giolitti, Francesca; Gironi, Laura Cristina; Gramaglia, Carla; Grisafi, Leonardo; Inserra, Ilaria; Invernizzi, Marco; Krengli, Marco; Labella, Emanuela; Landi, Irene Cecilia; Landi, Raffaella; Leone, Ilaria; Lio, Veronica; Lorenzini, Luca; Maconi, Antonio; Malerba, Mario; Manfredi, Giulia Francesca; Martelli, Maria; Marzari, Letizia; Marzullo, Paolo; Mennuni, Marco; Montabone, Claudia; Morosini, Umberto; Mussa, Marco; Nerici, Ilaria; Nuzzo, Alessandro; Olivieri, Carlo; Padelli, Samuel Alberto; Panella, Massimiliano; Parisini, Andrea; Paschè, Alessio; Patrucco, Filippo; Patti, Giuseppe; Pau, Alberto; Pedrinelli, Anita Rebecca; Percivale, Ilaria; Ragazzoni, Luca; Re, Roberta; Rigamonti, Cristina; Rizzi, Eleonora; Rognoni, Andrea; Roveta, Annalisa; Salamina, Luigia; Santagostino, Matteo; Saraceno, Massimo; Savoia, Paola; Sciarra, Marco; Schimmenti, Andrea; Scotti, Lorenza; Spinoni, Enrico; Smirne, Carlo; Tarantino, Vanessa; Tillio, Paolo Amedeo; Tonello, Stelvio; Vaschetto, Rosanna; Vassia, Veronica; Zagaria, Domenico; Zavattaro, Elisa; Zeppegno, Patrizia; Zottarelli, Francesca; Sainaghi, Pier Paolo
Title: Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19
  • Cord-id: qh5wibcz
  • Document date: 2021_5_13
  • ID: qh5wibcz
    Snippet: INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalize
    Document: INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. RESULTS: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ(2) 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ(2) 7.6; p = 0.006), and platelet count (χ(2) 5.39; p = 0.02), along with age (χ(2) 87.6; p < 0.001) and gender (χ(2) 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/μL was, conversely, protective (OR: 0.45 (0.32-0.63)). CONCLUSION: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

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