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4. The role of the intensive care unit in real-time surveillance of emerging pandemics: the Italian GiViTI experience

Author

Bertolini, G, Nattino, G, Langer, M, Tavola, M, Crespi, D, Mondini, M, Rossi, C, Previtali, C, Marshall, J, Poole, D, Abascià, A, Acquarolo, A, Adorni, A, Agnelli, V, Agostini, F, Alampi, D, Alberti, A, Alborghetti, A, Alleva, S, Ambrosoni, S, Antonini, B, Arditi, E, Avalli, L, Babini, M, Bagalini, G, Balata, A, Balicco, B, Barbagallo, M, Bartoli, T, Bassi, G, Becarelli, S, Beck, E, Bellin, M, Bellonzi, A, Bellorini, M, Benanti, C, Bensi, M, Bernasconi, Mo, Berruto, F, Bertolini, R, Besozzi, A, Biamino, C, Bianchi, T, Bianchin, A, Boccalatte, D, Bocchi, A, Bonaccorso, G, Bonazzi, M, Balsamo, C, Bonicalzi, V, Boniotti, C, Bonizzoli, M, Bottazzi, A, Breschi, C, Brizio, E, Brunetti, B, Brunori, E, Bubbico, G, Buscaglia, G, Calicchio, G, Calligaro, P, Calva, S, Candido, M, Capitanio, G, Caroleo, S, Casagli, S, Casalini, P, Castiglione, G, Cerana, M, Chiani, C, Chierego, G, Ciani, A, Ciceri, R, Cigada, Mg, Cima, M, Cingolani, E, Cinque, E, Coletta, Rp, Colombo, L, Colombo, R, Converso, M, Corrado, A, Cortis, G, Costagli, V, Crema, L, Crestan, E, Da, D, Cero, Pd, Ferro, Md, De Blasi RA, De Blasio, E, De Cristofaro MG, De Luca, A, Di Pasquale, D, Doroni, L, Fabi, Mc, Facondini, F, Fagoni, Nazzareno, Falzetti, G, Faraldi, L, Fiore, G, Fiume, C, Galeotti, E, Galleschi, N, Gallo, M, Gamberini, E, Garelli, A, Giacomello, S, Gianni, M, Giudici, R, Giuntini, R, Gnesin, P, Gorietti, A, Grassitelli, S, Greco, M, Irpino, A, Guadagna, A, Guadagnucci, A, Guagliardi, C, Laici, C, Lain, G, Lanza, G, Lefons, U, Leggieri, C, Lembo, R, Librenti, M, Liverani, C, Longobardo, A, Madeira, Sm, Madonna, R, Magatti, Mf, Mamprin, F, Mannolini, G, Marafon, S, Marchesi, G, Marifoglou, D, Martinelli, P, Martinelli, S, Escobar, Rm, Mastroianni, A, Mastropierro, R, Mediani, Ts, Messina, M, Milan, B, Molesi, A, Alberto, Cm, Mongelli, P, Morigi, A, Mosti, G, Muttini, S, Nardini, M, Nascimben, E, Natalini, G, Negri, G, Negro, G, Neri, M, Netto, R, Nonini, S, Odetto, L, Olivieri, C, Candida, Mo, Osti, D, Palmer, M, Parnigotto, A, Parrini, V, Pasculli, M, Pasetti, G, Passafiume, M, Pastorini, S, Patrignani, L, Pedeferri, M, Pegoraro, M, Pelati, E, Pelosi, G, Pera, L, Perino, P, Pero, A, Perzolla, D, Peta, M, Pinna, C, Pizzali, M, Postiglione, M, Potalivo, A, Raffaeli, M, Randellini, R, Rech, A, Renda, B, Ricciardi, G, Rizzi, S, Romagnoli, S, Rossi, G, Rossi, M, Rutta, C, Sagliaschi, U, Salcuni, R, Salvi, G, Scalera, M, Scarrone, S, Schiavuzzi, M, Aurelio, Ps, Selvaggi, P, Sicignano, A, Sorbara, C, Spagarino, E, Sparicio, D, Spinazzola, Ar, Sucre, Mj, Terzitta, M, Tetamo, R, Tibaldi, G, Todesco, L, Tomaselli, P, Torta, M, Turriziani, I, Ughi, L, Vaccari, C, Vaj, M, Vanzino, R, Vardanega, A, Vecchiarelli, P, Vedovati, S, Zanni, V, Zappa, S, Zardin, M, Zaro, G, Zuccaro, F, Barattini, M, Chieregato, A, Fumagalli, R, Livigni, S, Mengoli, F, Nardi, G, Palma, D, Portolani, L, Radrizzani, D, Terzitta, M., Bertolini, G, Nattino, G, Langer, M, Tavola, M, Crespi, D, Mondini, M, Rossi, C, Previtali, C, Marshall, J, Poole, D, Abascia, A, Acquarolo, A, Adorni, A, Agnelli, V, Agostini, F, Alampi, D, Alberti, A, Alborghetti, A, Alleva, S, Ambrosoni, S, Antonini, B, Arditi, E, Avalli, L, Babini, M, Bagalini, G, Balata, A, Balicco, B, Barbagallo, M, Bartoli, T, Bassi, G, Becarelli, S, Beck, E, Bellin, M, Bellonzi, A, Bellorini, M, Benanti, C, Bensi, M, Bernasconi, M, Berruto, F, Besozzi, A, Biamino, C, Bianchi, T, Bianchin, A, Boccalatte, D, Bocchi, A, Bonaccorso, G, Bonazzi, M, Balsamo, C, Bonicalzi, V, Boniotti, C, Bonizzoli, M, Bottazzi, A, Breschi, C, Brizio, E, Brunetti, B, Brunori, E, Bubbico, G, Buscaglia, G, Calicchio, G, Calligaro, P, Calva, S, Candido, M, Capitanio, G, Caroleo, S, Casagli, S, Casalini, P, Castiglione, G, Cerana, M, Chiani, C, Chierego, G, Ciani, A, Ciceri, R, Cigada, M, Cima, M, Cingolani, E, Cinque, E, Coletta, R, Colombo, L, Colombo, R, Converso, M, Corrado, A, Cortis, G, Costagli, V, Crema, L, Crestan, E, Da, D, Cero, P, Ferro, M, De Blasi, R, De Blasio, E, De Cristofaro, M, De Luca, A, Di Pasquale, D, Doroni, L, Fabi, M, Facondini, F, Fagoni, N, Falzetti, G, Faraldi, L, Fiore, G, Fiume, C, Galeotti, E, Galleschi, N, Gallo, M, Gamberini, E, Garelli, A, Giacomello, S, Gianni, M, Giudici, R, Giuntini, R, Gnesin, P, Gorietti, A, Grassitelli, S, Greco, M, Irpino, A, Guadagna, A, Guadagnucci, A, Guagliardi, C, Laici, C, Lain, G, Lanza, G, Lefons, U, Leggieri, C, Lembo, R, Librenti, M, Liverani, C, Longobardo, A, Madeira, S, Madonna, R, Magatti, M, Mamprin, F, Mannolini, G, Marafon, S, Marchesi, G, Marifoglou, D, Martinelli, P, Martinelli, S, Escobar, R, Mastroianni, A, Mastropierro, R, Mediani, T, Messina, M, Milan, B, Molesi, A, Alberto, C, Mongelli, P, Morigi, A, Mosti, G, Muttini, S, Nardini, M, Nascimben, E, Natalini, G, Negri, G, Negro, G, Neri, M, Netto, R, Nonini, S, Odetto, L, Olivieri, C, Candida, M, Osti, D, Palmer, M, Parnigotto, A, Parrini, V, Pasculli, M, Pasetti, G, Passafiume, M, Pastorini, S, Patrignani, L, Pedeferri, M, Pegoraro, M, Pelati, E, Pelosi, G, Pera, L, Perino, P, Pero, A, Perzolla, D, Peta, M, Pinna, C, Pizzali, M, Postiglione, M, Potalivo, A, Raffaeli, M, Randellini, R, Rech, A, Renda, B, Ricciardi, G, Rizzi, S, Romagnoli, S, Rossi, G, Rossi, M, Rutta, C, Sagliaschi, U, Salcuni, R, Salvi, G, Scalera, M, Scarrone, S, Schiavuzzi, M, Aurelio, P, Selvaggi, P, Sicignano, A, Sorbara, C, Spagarino, E, Sparicio, D, Spinazzola, A, Sucre, M, Terzitta, M, Tetamo, R, Tibaldi, G, Todesco, L, Tomaselli, P, Torta, M, Turriziani, I, Ughi, L, Vaccari, C, Vaj, M, Vanzino, R, Vardanega, A, Vecchiarelli, P, Vedovati, S, Zanni, V, Zappa, S, Zardin, M, Zaro, G, Zuccaro, F, Barattini, M, Chieregato, A, Fumagalli, R, Livigni, S, Mengoli, F, Nardi, G, Palma, D, Portolani, L, and Radrizzani, D

Subjects
medicine.medical_specialty, Epidemiology, surveillance system, law.invention, 03 medical and health sciences, Influenza A Virus, H1N1 Subtype, 0302 clinical medicine, Public health surveillance, law, Infectious disease epidemiology, influenza, pandemic, Humans, Influenza, Human, Intensive Care Units, Italy, Public Health Surveillance, Pandemics, Pandemic, medicine, human, 030212 general & internal medicine, medicine (all), Intensive care medicine, business.industry, Public health, Outbreak, 030208 emergency & critical care medicine, Monitoring system, medicine.disease, Intensive care unit, infectious disease epidemiology, humans, influenza a virus, h1n1 subtype, intensive care units, italy, public health surveillance, pandemics, infectious diseases, epidemiology, Infectious Diseases, Human mortality from H5N1, Medical emergency, business
Abstract

SUMMARYThe prompt availability of reliable epidemiological information on emerging pandemics is crucial for public health policy-makers. Early in 2013, a possible new H1N1 epidemic notified by an intensive care unit (ICU) to GiViTI, the Italian ICU network, prompted the re-activation of the real-time monitoring system developed during the 2009–2010 pandemic. Based on data from 216 ICUs, we were able to detect and monitor an outbreak of severe H1N1 infection, and to compare the situation with previous years. The timely and correct assessment of the severity of an epidemic can be obtained by investigating ICU admissions, especially when historical comparisons can be made.

Published
2015
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5. External validation of the Simplified Acute Physiology Score (SAPS) 3 in a cohort of 28,357 patients from 147 Italian intensive care units

Author

Poole, D, Rossi, C, Anghileri, A, Giardino, M, Latronico, N, Radrizzani, D, Langer, M, Bertolini, G, Acciarri, C, Acquarolo, A, Adorni, A, Alberti, A, Alborghetti, A, Antonini, B, Archi, D, Arditi, E, Badii, F, Balata, A, Barattini, M, Barbagli, R, Barbieri, P, Baroncia, M, Bartoccini, A, Bartoli, T, Bassi, F, Beck, E, Bellato, V, Bellorini, M, Belluomo Anello, C, Benanti, C, Berardino, M, Bernasconi, Mo, Besozzi, A, Bianchin, A, Bindi, Ml, Biolino, P, Blasetti, A, Boccalatte, D, Bonaccorso, G, Bonfà, A, Bonfiglio, M, Boniotti, C, Bonizzoli, M, Bottari, V, Breschi, C, Brunori, E, Buonanno, R, Buzzetti, V, Calicchio, G, Calva, S, Capannolo, B, Caracciolo, A, Carnevale, L, Carsana, C, Casadei, E, Casagli, S, Casagrande, L, Casalini, P, Castiglione, G, Cavallo, R, Chiarello, M, Chieregato, A, Chinelli, E, Cigada, M, Coaloa, M, Colombo, R, Colombo, S, Corsini, W, Corvi, D, Cosentino, E, Costa, R, Costanzo, E, Cottignoli, T, Crema, L, Crestan, E, Da Re, D, Dal Cero, P, Dal Ferro, M, David, Antonio, De Blasi RA, De Blasio, E, De Luca, A, De Negri, P, Dei Poli, M, Del Sarto, P, Di Lorenzo, G, Di Masi, P, Di Pasquale, D, Di Serafino, G, Donato, I, Fabbri, L, Fabbri, E, Fabbri, Pg, Fabi, Mc, Faccio, L, Ferla, F, Ferri, F, Fiore, G, Fognani, G, Galeotti, E, Gamberini, E, Garelli, A, Garofalo, G, Garzilli, T, Giacopuzzi, L, Gianni, M, Giannoni, S, Giugiaro, Pm, Gorietti, A, Grassi, P, Greco, M, Guadagnucci, A, Guagliardi, C, Isetta, M, Lapolla, A, Lefons, U, Livigni, S, Madonna, R, Maestrone, C, Magatti, Mf, Maggiolo, C, Malacarne, P, Mancosu, S, Mangani, Va, Mantovani, G, Marafon, S, Martinez Escobar, R, Mastroianni, A, Mastropierro, R, Meloni, A, Messina, M, Miglioranzi, R, Molino, Fm, Morigi, A, Mosca, C, Murri, V, Nardi, G, Nascimben, E, Natalini, G, Negri, G, Negro, G, Neri, M, Nicolini, A, Nuovo, D, Odetto, L, Olivieri, C, Ortoleva, A, Pacini, Dm, Paganini, G, Paganoni, G, Palmer, M, Papiri, S, Parma, A, Parrini, V, Pastorelli, M, Pastorini, S, Pegoraro, M, Pezzi, A, Pinciroli, D, Piredda, G, Piva, S, Pizzaballa, M, Possamai, C, Postiglione, M, Potalivo, A, Pulici, M, Quattrocchi, P, Raffaeli, M, Ranzini, L, Righini, E, Rona, R, Rossi, G, Rossi, S, Rossi, M, Rottoli, F, Salcuni, R, Salvi, G, Savioli, M, Scarrone, S, Schellino, Mm, Segala, V, Segalini, Pa, Sera, G, Sforza, D, Sicignano, A, Sorbara, C, Spadini, E, Staccioli, P, Stefani, M, Sucre, Mj, Tartari, S, Tavola, M, Tetamo, R, Tibaldi, G, Tinacci, S, Todesco, L, Torta, M, Tosi, L, Tripepi, C, Ughi, L, Vaj, M, Vecchiarelli, P, Vespignani, Mg, Visconti, Mg, Vulcano, Ga, Zappa, S, Zocaro, R, and Zuccaro, F.

Subjects
Male, medicine.medical_specialty, Time Factors, genetic structures, Critical Care, Critical Illness, Critical Care and Intensive Care Medicine, law.invention, Bias, law, Predictive Value of Tests, Risk Factors, Intensive care, Anesthesiology, Outcome Assessment, Health Care, medicine, Humans, Hospital Mortality, Prospective Studies, Simplified Acute Physiology Score, Intensive care medicine, Prospective cohort study, Diagnosis-Related Groups, APACHE, Aged, Chi-Square Distribution, business.industry, Data Collection, Benchmarking, Critical care, Hospital mortality, Outcome assessment, Validation study, Discriminant Analysis, Middle Aged, Prognosis, Intensive care unit, Intensive Care Units, Logistic Models, Italy, ROC Curve, Predictive value of tests, Cohort, Calibration, Female, business, Chi-squared distribution
Abstract

To evaluate the SAPS 3 score predictive ability of hospital mortality in a large external validation cohort.Prospective observational study.A total of 28,357 patients from 147 Italian ICUs joining the Project Margherita national database of the Gruppo italiano per la Valutazione degli interventi in Terapia Intensiva (GiViTI).None.Evaluation of discrimination through ROC analysis and of overall goodness-of-fit through the Cox calibration test.Although discrimination was good, calibration turned out to be poor. The general and the South-Europe Mediterranean countries equations overestimated hospital mortality overall (SMR values 0.73 with 95% CI 0.72-0.75 for both equations) and homogeneously across risk classes. Overprediction was confirmed among important subgroups, with SMR values ranging between 0.47 and 0.82.The result strictly supported by our data is that the SAPS 3 score calibrates inadequately in a large sample of Italian ICU patients and thus should not be used for benchmarking, at least in Italian settings.

Published
2009

12. Extracorporeal Co2 removal in hypercapnic patients at risk of noninvasive ventilation failure: a matched cohort study with historical control.

Author

Del Sorbo L, Pisani L, Filippini C, Fanelli V, Fasano L, Terragni P, Dell'Amore A, Urbino R, Mascia L, Evangelista A, Antro C, D'Amato R, Sucre MJ, Simonetti U, Persico P, Nava S, and Ranieri VM

Subjects
Aged, Carbon Dioxide metabolism, Cohort Studies, Extracorporeal Membrane Oxygenation, Humans, Hypercapnia etiology, Intubation, Intratracheal statistics & numerical data, Pulmonary Disease, Chronic Obstructive complications, Risk Factors, Treatment Failure, Hypercapnia therapy, Noninvasive Ventilation methods
Abstract

Objectives: To assess efficacy and safety of noninvasive ventilation-plus-extracorporeal Co2 removal in comparison to noninvasive ventilation-only to prevent endotracheal intubation patients with acute hypercapnic respiratory failure at risk of failing noninvasive ventilation., Design: Matched cohort study with historical control., Setting: Two academic Italian ICUs., Patients: Patients treated with noninvasive ventilation for acute hypercapnic respiratory failure due to exacerbation of chronic obstructive pulmonary disease (May 2011 to November 2013)., Interventions: Extracorporeal CO2 removal was added to noninvasive ventilation when noninvasive ventilation was at risk of failure (arterial pH ≤ 7.30 with arterial PCO2 > 20% of baseline, and respiratory rate ≥ 30 breaths/min or use of accessory muscles/paradoxical abdominal movements). The noninvasive ventilation-only group was created applying the genetic matching technique (GenMatch) on a dataset including patients enrolled in two previous studies. Exclusion criteria for both groups were mean arterial pressure less than 60 mm Hg, contraindications to anticoagulation, body weight greater than 120 kg, contraindication to continuation of active treatment, and failure to obtain consent., Measurements and Main Results: Primary endpoint was the cumulative prevalence of endotracheal intubation. Twenty-five patients were included in the noninvasive ventilation-plus-extracorporeal CO2 removal group. The GenMatch identified 21 patients for the noninvasive ventilation-only group. Risk of being intubated was three times higher in patients treated with noninvasive ventilation-only than in patients treated with noninvasive ventilation-plus-extracorporeal CO2 removal (hazard ratio, 0.27; 95% CI, 0.07-0.98; p = 0.047). Intubation rate in noninvasive ventilation-plus-extracorporeal CO2 removal was 12% (95% CI, 2.5-31.2) and in noninvasive ventilation-only was 33% (95% CI, 14.6-57.0), but the difference was not statistically different (p = 0.1495). Thirteen patients (52%) experienced adverse events related to extracorporeal CO2 removal. Bleeding episodes were observed in three patients, and one patient experienced vein perforation. Malfunctioning of the system caused all other adverse events., Conclusions: These data provide the rationale for future randomized clinical trials that are required to validate extracorporeal CO2 removal in patients with hypercapnic respiratory failure and respiratory acidosis nonresponsive to noninvasive ventilation.

Published
2015
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