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14 results on '"Percivale, I."'

1. Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Author

Bellan, M, Patti, G, Hayden, E, Azzolina, D, Pirisi, M, Acquaviva, A, Aimaretti, G, Aluffi Valletti, P, Angilletta, R, Arioli, R, Avanzi, G, Avino, G, Balbo, P, Baldon, G, Baorda, F, Barbero, E, Baricich, A, Barini, M, Barone-Adesi, F, Battistini, S, Beltrame, M, Bertoli, M, Bertolin, S, Bertolotti, M, Betti, M, Bobbio, F, Boffano, P, Boglione, L, Borre, S, Brucoli, M, Calzaducca, E, Cammarata, E, Cantaluppi, V, Cantello, R, Capponi, A, Carriero, A, Casciaro, F, Castello, L, Ceruti, F, Chichino, G, Chirico, E, Cisari, C, Cittone, M, Colombo, C, Comi, C, Croce, E, Daffara, T, Danna, P, Della Corte, F, De Vecchi, S, Dianzani, U, Di Benedetto, D, Esposto, E, Faggiano, F, Falaschi, Z, Ferrante, D, Ferrero, A, Gagliardi, I, Gaidano, G, Galbiati, A, Gallo, S, Garavelli, P, Gardino, C, Garzaro, M, Gastaldello, M, Gavelli, F, Gennari, A, Giacomini, G, Giacone, I, Giai Via, V, Giolitti, F, Gironi, L, Gramaglia, C, Grisafi, L, Inserra, I, Invernizzi, M, Krengli, M, Labella, E, Landi, I, Landi, R, Leone, I, Lio, V, Lorenzini, L, Maconi, A, Malerba, M, Manfredi, G, Martelli, M, Marzari, L, Marzullo, P, Mennuni, M, Montabone, C, Morosini, U, Mussa, M, Nerici, I, Nuzzo, A, Olivieri, C, Padelli, S, Panella, M, Parisini, A, Pasche, A, Pau, A, Pedrinelli, A, Percivale, I, Re, R, Rigamonti, C, Rizzi, E, Rognoni, A, Roveta, A, Salamina, L, Santagostino, M, Saraceno, M, Savoia, P, Sciarra, M, Schimmenti, A, Scotti, L, Spinoni, E, Smirne, C, Tarantino, V, Tillio, P, Vaschetto, R, Vassia, V, Zagaria, D, Zavattaro, E, Zeppegno, P, Zottarelli, F, Sainaghi, P, Bellan M., Patti G., Hayden E., Azzolina D., Pirisi M., Acquaviva A., Aimaretti G., Aluffi Valletti P., Angilletta R., Arioli R., Avanzi G. C., Avino G., Balbo P. E., Baldon G., Baorda F., Barbero E., Baricich A., Barini M., Barone-Adesi F., Battistini S., Beltrame M., Bertoli M., Bertolin S., Bertolotti M., Betti M., Bobbio F., Boffano P., Boglione L., Borre S., Brucoli M., Calzaducca E., Cammarata E., Cantaluppi V., Cantello R., Capponi A., Carriero A., Casciaro F. G., Castello L. M., Ceruti F., Chichino G., Chirico E., Cisari C., Cittone M. G., Colombo C., Comi C., Croce E., Daffara T., Danna P., Della Corte F., De Vecchi S., Dianzani U., Di Benedetto D., Esposto E., Faggiano F., Falaschi Z., Ferrante D., Ferrero A., Gagliardi I., Gaidano G., Galbiati A., Gallo S., Garavelli P. L., Gardino C. A., Garzaro M., Gastaldello M. L., Gavelli F., Gennari A., Giacomini G. M., Giacone I., Giai Via V., Giolitti F., Gironi L. C., Gramaglia C., Grisafi L., Inserra I., Invernizzi M., Krengli M., Labella E., Landi I. C., Landi R., Leone I., Lio V., Lorenzini L., Maconi A., Malerba M., Manfredi G. F., Martelli M., Marzari L., Marzullo P., Mennuni M., Montabone C., Morosini U., Mussa M., Nerici I., Nuzzo A., Olivieri C., Padelli S. A., Panella M., Parisini A., Pasche A., Pau A., Pedrinelli A. R., Percivale I., Re R., Rigamonti C., Rizzi E., Rognoni A., Roveta A., Salamina L., Santagostino M., Saraceno M., Savoia P., Sciarra M., Schimmenti A., Scotti L., Spinoni E., Smirne C., Tarantino V., Tillio P. A., Vaschetto R., Vassia V., Zagaria D., Zavattaro E., Zeppegno P., Zottarelli F., Sainaghi P. P., Bellan, M, Patti, G, Hayden, E, Azzolina, D, Pirisi, M, Acquaviva, A, Aimaretti, G, Aluffi Valletti, P, Angilletta, R, Arioli, R, Avanzi, G, Avino, G, Balbo, P, Baldon, G, Baorda, F, Barbero, E, Baricich, A, Barini, M, Barone-Adesi, F, Battistini, S, Beltrame, M, Bertoli, M, Bertolin, S, Bertolotti, M, Betti, M, Bobbio, F, Boffano, P, Boglione, L, Borre, S, Brucoli, M, Calzaducca, E, Cammarata, E, Cantaluppi, V, Cantello, R, Capponi, A, Carriero, A, Casciaro, F, Castello, L, Ceruti, F, Chichino, G, Chirico, E, Cisari, C, Cittone, M, Colombo, C, Comi, C, Croce, E, Daffara, T, Danna, P, Della Corte, F, De Vecchi, S, Dianzani, U, Di Benedetto, D, Esposto, E, Faggiano, F, Falaschi, Z, Ferrante, D, Ferrero, A, Gagliardi, I, Gaidano, G, Galbiati, A, Gallo, S, Garavelli, P, Gardino, C, Garzaro, M, Gastaldello, M, Gavelli, F, Gennari, A, Giacomini, G, Giacone, I, Giai Via, V, Giolitti, F, Gironi, L, Gramaglia, C, Grisafi, L, Inserra, I, Invernizzi, M, Krengli, M, Labella, E, Landi, I, Landi, R, Leone, I, Lio, V, Lorenzini, L, Maconi, A, Malerba, M, Manfredi, G, Martelli, M, Marzari, L, Marzullo, P, Mennuni, M, Montabone, C, Morosini, U, Mussa, M, Nerici, I, Nuzzo, A, Olivieri, C, Padelli, S, Panella, M, Parisini, A, Pasche, A, Pau, A, Pedrinelli, A, Percivale, I, Re, R, Rigamonti, C, Rizzi, E, Rognoni, A, Roveta, A, Salamina, L, Santagostino, M, Saraceno, M, Savoia, P, Sciarra, M, Schimmenti, A, Scotti, L, Spinoni, E, Smirne, C, Tarantino, V, Tillio, P, Vaschetto, R, Vassia, V, Zagaria, D, Zavattaro, E, Zeppegno, P, Zottarelli, F, Sainaghi, P, Bellan M., Patti G., Hayden E., Azzolina D., Pirisi M., Acquaviva A., Aimaretti G., Aluffi Valletti P., Angilletta R., Arioli R., Avanzi G. C., Avino G., Balbo P. E., Baldon G., Baorda F., Barbero E., Baricich A., Barini M., Barone-Adesi F., Battistini S., Beltrame M., Bertoli M., Bertolin S., Bertolotti M., Betti M., Bobbio F., Boffano P., Boglione L., Borre S., Brucoli M., Calzaducca E., Cammarata E., Cantaluppi V., Cantello R., Capponi A., Carriero A., Casciaro F. G., Castello L. M., Ceruti F., Chichino G., Chirico E., Cisari C., Cittone M. G., Colombo C., Comi C., Croce E., Daffara T., Danna P., Della Corte F., De Vecchi S., Dianzani U., Di Benedetto D., Esposto E., Faggiano F., Falaschi Z., Ferrante D., Ferrero A., Gagliardi I., Gaidano G., Galbiati A., Gallo S., Garavelli P. L., Gardino C. A., Garzaro M., Gastaldello M. L., Gavelli F., Gennari A., Giacomini G. M., Giacone I., Giai Via V., Giolitti F., Gironi L. C., Gramaglia C., Grisafi L., Inserra I., Invernizzi M., Krengli M., Labella E., Landi I. C., Landi R., Leone I., Lio V., Lorenzini L., Maconi A., Malerba M., Manfredi G. F., Martelli M., Marzari L., Marzullo P., Mennuni M., Montabone C., Morosini U., Mussa M., Nerici I., Nuzzo A., Olivieri C., Padelli S. A., Panella M., Parisini A., Pasche A., Pau A., Pedrinelli A. R., Percivale I., Re R., Rigamonti C., Rizzi E., Rognoni A., Roveta A., Salamina L., Santagostino M., Saraceno M., Savoia P., Sciarra M., Schimmenti A., Scotti L., Spinoni E., Smirne C., Tarantino V., Tillio P. A., Vaschetto R., Vassia V., Zagaria D., Zavattaro E., Zeppegno P., Zottarelli F., and Sainaghi P. P.

Abstract

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.

Published
2020

2. Simple parameters from complete blood count predict in-hospital mortality in covid-19

Author

Bellan, M., Azzolina, D., Hayden, E., Gaidano, G., Pirisi, M., Acquaviva, A., Aimaretti, G., Valletti, P. A., Angilletta, R., Arioli, R., Avanzi, G. C., Avino, G., Balbo, P. E., Baldon, G., Baorda, F., Barbero, E., Baricich, A., Barini, M., Barone-Adesi, F., Battistini, S., Beltrame, M., Bertoli, M., Bertolin, S., Bertolotti, M., Betti, M., Bobbio, F., Boffano, P., Boglione, L., Borre, S., Brucoli, M., Calzaducca, E., Cammarata, E., Cantaluppi, V., Cantello, R., Capponi, A., Carriero, A., Casciaro, G. F., Castello, L. M., Ceruti, F., Chichino, G., Chirico, E., Cisari, C., Cittone, M. G., Colombo, C., Comi, C., Croce, E., Daffara, T., Danna, P., Corte, F. D., de Vecchi, S., Dianzani, U., Benedetto, D. D., Esposto, E., Faggiano, F., Falaschi, Z., Ferrante, D., Ferrero, A., Gagliardi, I., Galbiati, A., Gallo, S., Garavelli, P. L., Gardino, C. A., Garzaro, M., Gastaldello, M. L., Gavelli, F., Gennari, A., Giacomini, G. M., Giacone, I., Via, V. G., Giolitti, F., Gironi, L. C., Gramaglia, C., Grisafi, L., Inserra, I., Invernizzi, M., Krengli, M., Labella, E., Landi, I. C., Landi, R., Leone, I., Lio, V., Lorenzini, L., Maconi, A., Malerba, M., Manfredi, G. F., Martelli, M., Marzari, L., Marzullo, P., Mennuni, M., Montabone, C., Morosini, U., Mussa, M., Nerici, I., Nuzzo, A., Olivieri, C., Padelli, S. A., Panella, M., Parisini, A., Pasche, A., Patrucco, F., Patti, G., Pau, A., Pedrinelli, A. R., Percivale, I., Ragazzoni, L., Re, R., Rigamonti, C., Rizzi, E., Rognoni, A., Roveta, A., Salamina, L., Santagostino, M., Saraceno, M., Savoia, P., Sciarra, M., Schimmenti, A., Scotti, L., Spinoni, E., Smirne, C., Tarantino, V., Tillio, P. A., Tonello, S., Vaschetto, R., Vassia, V., Zagaria, D., Zavattaro, E., Zeppegno, P., Zottarelli, F., Sainaghi, P. P., Aiosa, G., Airoldi, A., Barco, A., Bargiacchi, O., Bazzano, S., Berni, P., Bianchi, B., Bianco, S., Biffi, S., Binda, V., Bolgeo, T., Bolla, C., Bonato, V., Bonizzoni, G., Bragantini, A., Brustia, D., Bullara, V., Burlone, M., Brustia, F., Caccia, S., Calareso, A., Cammarota, G., Cancelliere, L., Carbone, R., Cassinari, A., Ceriani, E., Cena, T., Clivati, E., Collimedaglia, L., Colombatto, A., Cornella, C., Costanzo, M., Croce, A., de Benedittis, C., Delorenzi, S., Dionisio, R., Donato, P., Esposito, M., Fangazio, S., Feggi, A., Ferrillo, S., Foci, V., Fra, G. P., Gaggino, C., Gambaro, E., Gattoni, E., Gattoni, L., Giacchero, F., Gianfreda, R., Giubertoni, A., Grecu, L., Grossi, F., Guglielmetti, G., Guido, S., Iannantuoni, G., Ingrao, S., Jona, A., Lazzarich, E., Lissandrin, R., Maduli, E., Magne, F., Mantia, E., Marangon, D., Massara, M., Matino, E., Mauri, M. G., Menegatti, M., Moglia, R., Molinari, R., Morelli, S., Morlino, P., Naldi, P., Nebbiolo, C., Omodeo, P., Palmieri, D., Panero, A., Parodi, M., Pedrazzoli, R., Pelazza, C., Penpa, S., Perucca, R., Pirovano, A., Pittau, S., Pochetti, P., Poletti, F., Polla, B., Prandi, P., Prodam, F., Prosperini, P., Puma, A., Quaglia, M., Raie, A., Rapetti, R., Ravera, S., Re, A., Reale, M., Rossati, A., Rossi, M., Rossi, P., Rostagno, R., Salomoni, G., Sama, M. T., Sarchi, E., Sarcoli, M., Sarda, C., Sguazzotti, I., Soddu, D., Sola, D., Stobbione, P., Todoerti, M., Vallese, G. C., Varrasi, C., Veia, A., Vignazia, G. L., Zanotti, I., Zecca, E., Zichittella, D., Zisa, G., and Zoppis, E.

Subjects
Adult, Male, medicine.medical_specialty, Medicine (General), Multivariate analysis, Article Subject, Clinical Decision Rules, COVID-19, Prognosis, Blood Cell Count, Hospital Mortality, Severity of Illness Index, Clinical Biochemistry, Asymptomatic, Severity of Illness Index, NO, R5-920, Internal medicine, Clinical Decision Rules, Severity of illness, Genetics, 80 and over, Medicine, Humans, Hospital Mortality, Molecular Biology, Aged, Retrospective Studies, Aged, 80 and over, medicine.diagnostic_test, business.industry, Biochemistry (medical), Complete blood count, COVID-19, Retrospective cohort study, Red blood cell distribution width, General Medicine, Odds ratio, Middle Aged, Prognosis, Female, Italy, Multivariate Analysis, Blood Cell Count, Cohort, medicine.symptom, business, Research Article
Abstract

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.

Published
2021

6. Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Author

Lucio Boglione, Irene Cecilia Landi, Marinella Bertolotti, Alessandra Galbiati, Luca Lorenzini, Carlo Cisari, Luigia Salamina, Matteo Brucoli, Irene Giacone, Carlo Olivieri, Flavio Bobbio, Marta Betti, Maria Martelli, Paolo Amedeo Tillio, Vanessa Tarantino, Anita R. Pedrinelli, Mario Pirisi, Pietro Luigi Garavelli, Eleonora Croce, Alessandra Gennari, Francesca Zottarelli, Pietro Danna, Marco Invernizzi, Antonio Maconi, Francesca Giolitti, Sofia Battistini, Paolo Marzullo, Roberta Re, Domenico Zagaria, Francesco Gavelli, Federico Ceruti, Ilaria Leone, Greta Maria Giacomini, Leonardo Grisafi, Andrea Parisini, Stephanie Bertolin, Elia Esposto, Vincenzo Cantaluppi, Mattia Bellan, Giuseppe Patti, Emilio Chirico, Matteo Bertoli, Paolo Boffano, Paolo Aluffi Valletti, Alessandro Carriero, Cristoforo Comi, Umberto Dianzani, Eleonora Rizzi, Massimiliano Panella, Marco Sciarra, Edoardo Cammarata, Letizia Marzari, Elisa Zavattaro, Claudia Montabone, Gian Carlo Avanzi, Samuel Alberto Padelli, Massimiliano Garzaro, Pier Paolo Sainaghi, Francesco Barone-Adesi, Carlo Smirne, Gianluca Gaidano, Michela Barini, Francesco Giuseppe Casciaro, Ilaria Inserra, Laura Cristina Gironi, Ilaria Nerici, Clara Ada Gardino, Maria Luisa Gastaldello, Micol Giulia Cittone, Marco Mussa, Umberto Morosini, Andrea Capponi, Davide Di Benedetto, Fabrizio Faggiano, Crizia Colombo, Andrea Rognoni, Elisa Calzaducca, Alessio Paschè, Annalisa Roveta, Gianluca Aimaretti, Roberto Arioli, Giulia Baldon, Roberto Cantello, Ilaria Percivale, Piero Emilio Balbo, Emanuela Barbero, Silvio Borrè, Luigi Mario Castello, Patrizia Zeppegno, Ileana Gagliardi, Emanuela Labella, Alice Ferrero, Marco Krengli, Silvia Gallo, Andrea Schimmenti, Tommaso Daffara, Raffaella Landi, Paola Savoia, Giulia Francesca Manfredi, Valentina Giai Via, Michela Beltrame, Eyal Hayden, Enrico Guido Spinoni, Francesca Baorda, Cristina Rigamonti, Alessandro Nuzzo, Mario Malerba, Carla Gramaglia, Rosanna Vaschetto, Massimo Saraceno, Gianluca Avino, Marco G. Mennuni, Daniela Ferrante, Guido Chichino, Danila Azzolina, Alessio Baricich, Veronica Lio, Veronica Vassia, Alberto Pau, Roberto Angilletta, Simona De Vecchi, Antonio Acquaviva, Lorenza Scotti, Francesco Della Corte, Matteo Santagostino, Zeno Falaschi, Bellan, M, Patti, G, Hayden, E, Azzolina, D, Pirisi, M, Acquaviva, A, Aimaretti, G, Aluffi Valletti, P, Angilletta, R, Arioli, R, Avanzi, G, Avino, G, Balbo, P, Baldon, G, Baorda, F, Barbero, E, Baricich, A, Barini, M, Barone-Adesi, F, Battistini, S, Beltrame, M, Bertoli, M, Bertolin, S, Bertolotti, M, Betti, M, Bobbio, F, Boffano, P, Boglione, L, Borre, S, Brucoli, M, Calzaducca, E, Cammarata, E, Cantaluppi, V, Cantello, R, Capponi, A, Carriero, A, Casciaro, F, Castello, L, Ceruti, F, Chichino, G, Chirico, E, Cisari, C, Cittone, M, Colombo, C, Comi, C, Croce, E, Daffara, T, Danna, P, Della Corte, F, De Vecchi, S, Dianzani, U, Di Benedetto, D, Esposto, E, Faggiano, F, Falaschi, Z, Ferrante, D, Ferrero, A, Gagliardi, I, Gaidano, G, Galbiati, A, Gallo, S, Garavelli, P, Gardino, C, Garzaro, M, Gastaldello, M, Gavelli, F, Gennari, A, Giacomini, G, Giacone, I, Giai Via, V, Giolitti, F, Gironi, L, Gramaglia, C, Grisafi, L, Inserra, I, Invernizzi, M, Krengli, M, Labella, E, Landi, I, Landi, R, Leone, I, Lio, V, Lorenzini, L, Maconi, A, Malerba, M, Manfredi, G, Martelli, M, Marzari, L, Marzullo, P, Mennuni, M, Montabone, C, Morosini, U, Mussa, M, Nerici, I, Nuzzo, A, Olivieri, C, Padelli, S, Panella, M, Parisini, A, Pasche, A, Pau, A, Pedrinelli, A, Percivale, I, Re, R, Rigamonti, C, Rizzi, E, Rognoni, A, Roveta, A, Salamina, L, Santagostino, M, Saraceno, M, Savoia, P, Sciarra, M, Schimmenti, A, Scotti, L, Spinoni, E, Smirne, C, Tarantino, V, Tillio, P, Vaschetto, R, Vassia, V, Zagaria, D, Zavattaro, E, Zeppegno, P, Zottarelli, F, and Sainaghi, P

Subjects
Male, COVID-19, Viral infection, Risk factors, lcsh:Medicine, Comorbidity, Sex Factor, 030204 cardiovascular system & hematology, 0302 clinical medicine, Retrospective Studie, Case fatality rate, Pandemic, Age Factor, 030212 general & internal medicine, lcsh:Science, clinical characteristics, Aged, 80 and over, Multidisciplinary, Reverse Transcriptase Polymerase Chain Reaction, Smoking, Age Factors, Middle Aged, Coronavirus disease, Natural history, Survival Rate, Italy, Cohort, Female, Human, medicine.medical_specialty, Article, NO, 03 medical and health sciences, Sex Factors, Internal medicine, medicine, Humans, Pandemics, Survival rate, Retrospective Studies, Aged, business.industry, SARS-CoV-2, Risk Factor, lcsh:R, Retrospective cohort study, Length of Stay, medicine.disease, Obesity, lcsh:Q, Coronavirus disease, clinical characteristics, business
Abstract

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.

Published
2020

7. Early patello-femoral condropathy assessment through quantitative analyses via T2 mapping magnetic resonance after anterior cruciate ligament reconstruction.

Author

Zagaria D, Costantini P, Percivale I, Abruzzese F, Ghilardi G, Landrino M, Porta M, Leigheb M, and Carriero A

Subjects
Humans, Knee Joint diagnostic imaging, Knee Joint surgery, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Treatment Outcome, Follow-Up Studies, Anterior Cruciate Ligament Injuries diagnostic imaging, Anterior Cruciate Ligament Injuries surgery, Anterior Cruciate Ligament Reconstruction methods, Osteoarthritis
Abstract

Background: Patellar femoral chondropathy (FPC) is a common problem in patients undergoing anterior cruciate ligament reconstruction (ACL-R) surgery, which, if left untreated, predisposes to arthrosis. Magnetic resonance imaging (MRI) is the non-invasive gold standard for morphological evaluation of cartilage, while in recent years advanced MRI techniques (such as T2 mapping) have been developed to detect early cartilage biochemical changes. This study evaluates the different onset of early PFC between B-TP-B and HT through T2 mapping. Secondly, it aims to assess the presence of any concordance between self-reported questionnaires and qualitative MRI., Materials and Methods: 19 patients enrolled were divided into two groups based on the type of intervention: B-PT-B and HT. After a median time of 54 months from surgery, patients were subjected to conventional MRI, T2 mapping, and clinical-functional evaluation through three self-reported questionnaires: Knee Injury and Osteoarthritis index (KOOS); Tegner Lysholm Knee Scoring Scale; International Knee Documentation Committee (IKDC)., Results: There is not statistically significant difference in the comparison between the two MRI techniques and the two reconstructive techniques. KOOS and Tegner Lysholm scales showed significant agreement with MRI results on the grading of chondropathy., Conclusions: There are no differences between B-TP-B and HT techniques in the early development of PFC detectable through non-invasive methods. Due to the large reduction in the frequency of physical activity following ACL-R and the finding of mild PFC (grade I and II) in a substantial proportion of patients, after a relatively short period from ACL-R, all patients should undergo conservative treatment., (© 2023. The Author(s).)

Published
2023
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8. Non-timely clinically applicable ADC ratio in prostate mpMRI: a comparison with fusion biopsy results.

Author

Falaschi Z, Tricca S, Attanasio S, Billia M, Airoldi C, Percivale I, Bor S, Perri D, Volpe A, and Carriero A

Subjects
Biopsy, Humans, Image-Guided Biopsy, Male, Neoplasm Grading, Prostate diagnostic imaging, Prostate pathology, Retrospective Studies, Multiparametric Magnetic Resonance Imaging, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology
Abstract

Purpose: The purpose of the study was to assess the diagnostic accuracy of ADC ratio and to evaluate its efficacy in reducing the number of false positives in prostatic mpMRI., Materials and Methods: All patients who underwent an mpMRI and a targeted fusion biopsy in our institution from 2016 to 2021 were retrospectively selected. Two experienced readers (R1 and R2) independently evaluated the images, blindly to biopsy results. The radiologists assessed the ADC ratios by tracing a circular 10 mm 2 ROI on the biopsied lesion and on the apparently benign contralateral parenchyma. Prostate cancers were divided into non-clinically significant (nsPC, Gleason score = 6) and clinically significant (sPC, Gleason score ≥ 7). ROC analyses were performed., Results: 167 patients and188 lesions were included. Concordance was 0.62 according to Cohen's K. ADC ratio showed an AUC for PCAs of 0.78 in R1 and 0.8 in R2. The AUC for sPC was 0.85 in R1 and 0.84 in R2. The 100% sensitivity cut-off for sPCs was 0.65 (specificity 25.6%) in R1 and 0.66 (specificity 27.4%) in R2. Forty-three benign or not clinically significant lesions were above the 0.65 threshold in R1; 46 were above the 0.66 cut-off in R2. This would have allowed to avoid an equal number of unnecessary biopsies at the cost of 2 nsPCs in R1 and one nsPC in R2., Conclusion: In our sample, the ADC ratio was a useful and accurate tool that could potentially reduce the number of false positives in mpMRI., (© 2022. The Author(s).)

Published
2022
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9. 18 months computed tomography follow-up after Covid-19 interstitial pneumonia.

Author

Barini M, Percivale I, Danna P, Longo V, Costantini P, Paladini A, Airoldi C, Bellan M, Saba L, and Carriero A

Abstract

Background: Our aim is to evaluate the possible persistence of lung parenchyma alterations, in patients who have recovered from Covid-19., Design and Methods: We enrolled a cohort of 115 patients affected by Covid-19, who performed a chest CT scan in the Emergency Department and a chest CT 18 months after hospital discharge. We performed a comparison between chest CT scan 18 months after discharge and spirometric data of patients enrolled. We obtained quantitative scores related to well-aerated parenchyma, interstitial lung disease and parenchymal consolidation. A radiologist recorded the characteristics indicated by the Fleischner Society and "fibrotic like" changes, expressed through a CT severity score ranging from 0 (no involvement) to 25 (maximum involvement)., Results: 115 patients (78 men, 37 women; mean age 60.15 years old ±12.52). On quantitative analysis, after 18 months, the volume of normal ventilated parenchyma was significantly increased (16.34 points on average ±14.54, p<0.0001). Ground-glass opacities and consolidation values tend to decrease (-9.80 and -6.67 points, p<0.0001). On semiquantitative analysis, pneumonia extension, reactive lymph nodes and crazy paving reached statistical significance (p<0.0001). The severity score decreased by 2.77 points on average (SD 4.96; p<0.0001). There were not statistically significant changes on "fibrotic-like" changes correlated with level of treatment and there was not a statistically significant correlation between CT lung score and spirometric results obtained 18 months after discharge., Conclusions: Patients recovered from Covid-19 seem to have an improvement of ventilated parenchyma and "fibrotic-like" alterations. The level of treatment does not appear to influence fibrotic changes.

Published
2022
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10. Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19.

Author

Bellan M, Azzolina D, Hayden E, Gaidano G, Pirisi M, Acquaviva A, Aimaretti G, Aluffi Valletti P, Angilletta R, Arioli R, Avanzi GC, Avino G, Balbo PE, Baldon G, Baorda F, Barbero E, Baricich A, Barini M, Barone-Adesi F, Battistini S, Beltrame M, Bertoli M, Bertolin S, Bertolotti M, Betti M, Bobbio F, Boffano P, Boglione L, Borrè S, Brucoli M, Calzaducca E, Cammarata E, Cantaluppi V, Cantello R, Capponi A, Carriero A, Casciaro GF, Castello LM, Ceruti F, Chichino G, Chirico E, Cisari C, Cittone MG, Colombo C, Comi C, Croce E, Daffara T, Danna P, Della Corte F, De Vecchi S, Dianzani U, Di Benedetto D, Esposto E, Faggiano F, Falaschi Z, Ferrante D, Ferrero A, Gagliardi I, Galbiati A, Gallo S, Garavelli PL, Gardino CA, Garzaro M, Gastaldello ML, Gavelli F, Gennari A, Giacomini GM, Giacone I, Giai Via V, Giolitti F, Gironi LC, Gramaglia C, Grisafi L, Inserra I, Invernizzi M, Krengli M, Labella E, Landi IC, Landi R, Leone I, Lio V, Lorenzini L, Maconi A, Malerba M, Manfredi GF, Martelli M, Marzari L, Marzullo P, Mennuni M, Montabone C, Morosini U, Mussa M, Nerici I, Nuzzo A, Olivieri C, Padelli SA, Panella M, Parisini A, Paschè A, Patrucco F, Patti G, Pau A, Pedrinelli AR, Percivale I, Ragazzoni L, Re R, Rigamonti C, Rizzi E, Rognoni A, Roveta A, Salamina L, Santagostino M, Saraceno M, Savoia P, Sciarra M, Schimmenti A, Scotti L, Spinoni E, Smirne C, Tarantino V, Tillio PA, Tonello S, Vaschetto R, Vassia V, Zagaria D, Zavattaro E, Zeppegno P, Zottarelli F, and Sainaghi PP

Subjects
Adult, Aged, Aged, 80 and over, COVID-19 diagnosis, Female, Humans, Italy epidemiology, Male, Middle Aged, Multivariate Analysis, Prognosis, Retrospective Studies, Blood Cell Count, COVID-19 blood, COVID-19 mortality, Clinical Decision Rules, Hospital Mortality, Severity of Illness Index
Abstract

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/ μ L 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., Competing Interests: The authors have no conflict of interest to declare., (Copyright © 2021 Mattia Bellan et al.)

Published
2021
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11. Diagnostic Accuracy of the Magnetic Resonance Imaging in Adult Post-Ganglionic Brachial Plexus Traumatic Injuries: A Systematic Review and Meta-Analysis.

Author

Leigheb M, Tricca S, Percivale I, Licandro D, Paladini A, Barini M, Guzzardi G, Grassi FA, Stecco A, and Carriero A

Abstract

Background: Traumatic brachial plexus injuries are rare but serious consequences of major traumas. Pre-ganglionic lesions are considered irreparable, while post-ganglionic injuries can be potentially treated if an early diagnosis is available. Pre-surgical diagnosis is important to distinguish low-grade from high-grade lesions and to identify their location. The aim of the review is to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in the identification of adult post-ganglionic lesions due to traumatic brachial plexus injuries, compared to intraoperative findings., Methods: Research on the main scientific electronic databases was conducted. Studies of adults with traumatic post-ganglionic brachial plexus injuries were included. The index test was preoperative MRI and the reference standard was surgical exploration. Pooled sensitivity and specificity were calculated., Results: Four studies were included for the systematic review, of which three articles met the inclusion criteria for the meta-analysis. Pooled sensitivity and pooled specificity values resulted high. The sensitivity value is associated with a high heterogeneity index of the selected literature., Conclusion: MRI can be considered, despite the limits, the gold standard exam in morphological evaluation of brachial plexus injuries, particularly in the diagnosis of post-ganglionic traumatic injuries.

Published
2021
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12. Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients.

Author

Bellan M, Patti G, Hayden E, Azzolina D, Pirisi M, Acquaviva A, Aimaretti G, Aluffi Valletti P, Angilletta R, Arioli R, Avanzi GC, Avino G, Balbo PE, Baldon G, Baorda F, Barbero E, Baricich A, Barini M, Barone-Adesi F, Battistini S, Beltrame M, Bertoli M, Bertolin S, Bertolotti M, Betti M, Bobbio F, Boffano P, Boglione L, Borrè S, Brucoli M, Calzaducca E, Cammarata E, Cantaluppi V, Cantello R, Capponi A, Carriero A, Casciaro FG, Castello LM, Ceruti F, Chichino G, Chirico E, Cisari C, Cittone MG, Colombo C, Comi C, Croce E, Daffara T, Danna P, Della Corte F, De Vecchi S, Dianzani U, Di Benedetto D, Esposto E, Faggiano F, Falaschi Z, Ferrante D, Ferrero A, Gagliardi I, Gaidano G, Galbiati A, Gallo S, Garavelli PL, Gardino CA, Garzaro M, Gastaldello ML, Gavelli F, Gennari A, Giacomini GM, Giacone I, Giai Via V, Giolitti F, Gironi LC, Gramaglia C, Grisafi L, Inserra I, Invernizzi M, Krengli M, Labella E, Landi IC, Landi R, Leone I, Lio V, Lorenzini L, Maconi A, Malerba M, Manfredi GF, Martelli M, Marzari L, Marzullo P, Mennuni M, Montabone C, Morosini U, Mussa M, Nerici I, Nuzzo A, Olivieri C, Padelli SA, Panella M, Parisini A, Paschè A, Pau A, Pedrinelli AR, Percivale I, Re R, Rigamonti C, Rizzi E, Rognoni A, Roveta A, Salamina L, Santagostino M, Saraceno M, Savoia P, Sciarra M, Schimmenti A, Scotti L, Spinoni E, Smirne C, Tarantino V, Tillio PA, Vaschetto R, Vassia V, Zagaria D, Zavattaro E, Zeppegno P, Zottarelli F, and Sainaghi PP

Subjects
Age Factors, Aged, Aged, 80 and over, COVID-19 virology, Comorbidity, Female, Humans, Italy epidemiology, Length of Stay, Male, Middle Aged, Retrospective Studies, Reverse Transcriptase Polymerase Chain Reaction, Risk Factors, Sex Factors, Smoking, Survival Rate, COVID-19 epidemiology, COVID-19 mortality, Pandemics, SARS-CoV-2 genetics
Abstract

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO 2 /FiO 2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.

Published
2020
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13. Chest CT accuracy in diagnosing COVID-19 during the peak of the Italian epidemic: A retrospective correlation with RT-PCR testing and analysis of discordant cases.

Author

Falaschi Z, Danna PSC, Arioli R, Pasché A, Zagaria D, Percivale I, Tricca S, Barini M, Aquilini F, Andreoni S, and Carriero A

Subjects
Adult, COVID-19, Coronavirus Infections diagnostic imaging, Female, Humans, Italy, Lung diagnostic imaging, Male, Middle Aged, Pandemics, Pneumonia, Viral diagnostic imaging, Reproducibility of Results, Retrospective Studies, SARS-CoV-2, Sensitivity and Specificity, Betacoronavirus, Coronavirus Infections diagnosis, Pneumonia, Viral diagnosis, Reverse Transcriptase Polymerase Chain Reaction methods, Tomography, X-Ray Computed methods
Abstract

Objectives: The goal of this study was to assess chest computed tomography (CT) diagnostic accuracy in clinical practice using RT-PCR as standard of reference., Methods: From March 4th to April 9th 2020, during the peak of the Italian COVID-19 epidemic, we enrolled a series of 773 patients that performed both non-contrast chest CT and RT-PCR with a time interval no longer than a week due to suspected SARS-CoV-2 infection. The diagnostic performance of CT was evaluated according to sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy, considering RT-PCR as the reference standard. An analysis on the patients with discrepant CT scan and RT-PCR result and on the patient with both negative tests was performed., Results: RT-PCR testing showed an overall positive rate of 59.8 %. CT sensitivity, specificity, PPV, NPV, and accuracy for SARS-CoV-2 infection were 90.7 % [95 % IC, 87.7%-93.2%], 78.8 % [95 % IC, 73.8-83.2%], 86.4 % [95 % IC, 76.1 %-88.9 %], 85.1 % [95 % IC, 81.0 %-88.4] and 85.9 % [95 % IC 83.2-88.3%], respectively. Twenty-five/66 (37.6 %) patients with positive CT and negative RT-PCR results and 12/245 (4.9 %) patients with both negative tests were nevertheless judged as positive cases by the clinicians based on clinical and epidemiological criteria and consequently treated., Conclusions: In our experience, in a context of high pre-test probability, CT scan shows good sensitivity and a consistently higher specificity for the diagnosis of COVID-19 pneumonia than what reported by previous studies, especially when clinical and epidemiological features are taken into account., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Published
2020
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