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15 results on '"Livrea A."'

1. Multiple solutions of second order Hamiltonian systems

Author

Bonanno, G, Bonanno, G, Livrea, R, Schechter, M, Bonanno, G, Bonanno, G, Livrea, R, and Schechter, M

Abstract

The existence and the multiplicity of periodic solutions for a parameter dependent second order Hamiltonian system are established via linking theorems. A monotonicity trick is adopted in order to prove the existence of an open interval of parameters for which the problem under consideration admits at least two non trivial qualified solutions.

Published
2017

2. Multiple solutions of second order Hamiltonian systems

Author

Bonanno, G, Bonanno, G, Livrea, R, Schechter, M, Bonanno, G, Bonanno, G, Livrea, R, and Schechter, M

Abstract

The existence and the multiplicity of periodic solutions for a parameter dependent second order Hamiltonian system are established via linking theorems. A monotonicity trick is adopted in order to prove the existence of an open interval of parameters for which the problem under consideration admits at least two non trivial qualified solutions.

Published
2017

3. Additive Role of a Potentially Reversible Cognitive Frailty Model and Inflammatory State on the Risk of Disability: The Italian Longitudinal Study on Aging.

Author

Solfrizzi, Vincenzo, Scafato, Emanuele, Lozupone, Madia, Seripa, Davide, Giannini, Michele, Sardone, Rodolfo, Bonfiglio, Caterina, Abbrescia, Daniela I., Galluzzo, Lucia, Gandin, Claudia, Baldereschi, Marzia, Di Carlo, Antonio, Inzitari, Domenico, Daniele, Antonio, Sabbã , Carlo, Logroscino, Giancarlo, Panza, Francesco, Scafato, E., Farchi, G., Galluzzo, L., Gandin, C., Capurso, A., Panza, F., Solfrizzi, V., Lepore, V., Livrea, P., Motta, Ljanka, Carnazzo, G., Motta, M., Bentivegna, P., Bonaiuto, S., Cruciani, G., Postacchini, D., Inzitari, D., Amaducci, L., Di Carlo, A., Baldereschi, M., Gandolfo, C., Conti, M., Canal, N., Franceschi, M., Scarlato, G., Candelise, L., Scapini, E., Rengo, F., Abete, P., Cacciatore, F., Enzi, G., Battistin, L., Sergi, G., Crepaldi, G., Maggi, S., Minicucci, N., Noale, M., Grigoletto, F., Perissinotto, E., Carbonin, P., Daniele, Antonio (ORCID:0000-0003-1641-5852), Solfrizzi, Vincenzo, Scafato, Emanuele, Lozupone, Madia, Seripa, Davide, Giannini, Michele, Sardone, Rodolfo, Bonfiglio, Caterina, Abbrescia, Daniela I., Galluzzo, Lucia, Gandin, Claudia, Baldereschi, Marzia, Di Carlo, Antonio, Inzitari, Domenico, Daniele, Antonio, Sabbã , Carlo, Logroscino, Giancarlo, Panza, Francesco, Scafato, E., Farchi, G., Galluzzo, L., Gandin, C., Capurso, A., Panza, F., Solfrizzi, V., Lepore, V., Livrea, P., Motta, Ljanka, Carnazzo, G., Motta, M., Bentivegna, P., Bonaiuto, S., Cruciani, G., Postacchini, D., Inzitari, D., Amaducci, L., Di Carlo, A., Baldereschi, M., Gandolfo, C., Conti, M., Canal, N., Franceschi, M., Scarlato, G., Candelise, L., Scapini, E., Rengo, F., Abete, P., Cacciatore, F., Enzi, G., Battistin, L., Sergi, G., Crepaldi, G., Maggi, S., Minicucci, N., Noale, M., Grigoletto, F., Perissinotto, E., Carbonin, P., and Daniele, Antonio (ORCID:0000-0003-1641-5852)

Abstract

Objective Cognitive frailty is a condition recently defined by operationalized criteria describing the simultaneous presence of physical frailty and mild cognitive impairment (MCI). Two subtypes for this clinical construct have been proposed: “potentially reversible” cognitive frailty (physical frailty plus MCI) and “reversible” cognitive frailty (physical frailty plus pre-MCI subjective cognitive decline). Here the prevalence of a potentially reversible cognitive frailty model was estimated. It was also evaluated if introducing a diagnosis of MCI in older subjects with physical frailty could have an additive role on the risk of dementia, disability, and all-cause mortality in comparison with frailty state or MCI condition alone, with analyses separately performed for inflammatory state. Methods In 2,373 individuals from the population-based Italian Longitudinal Study on Aging with a 3.5-year-follow-up, we operationally categorized older individuals without dementia into four groups: non-frail/non-MCI, non-frail/MCI, frail/non-MCI, and frail/MCI. Results The prevalence of potentially reversible cognitive frailty was 1%, increasing with age and more represented in women than in men, and all groups were associated with significant increased incident rate ratios of dementia, disability, and mortality. A significant difference in rates of disability has been found between the MCI and non-MCI groups (contrasts of adjusted predictions: 0.461; 95% confidence interval: 0.187–0.735) in frail individuals with high inflammatory states (fibrinogen >339 mg/dL). Conclusion In older individuals without dementia and with elevated inflammation, a potentially reversible cognitive frailty model could have a significant additional predictive effect on the risk of disability than the single conditions of frailty or MCI.

Published
2017

4. Reversible Cognitive Frailty, Dementia, and All-Cause Mortality. The Italian Longitudinal Study on Aging

Author

Solfrizzi, Vincenzo, Scafato, Emanuele, Seripa, Davide, Lozupone, Madia, Imbimbo, Bruno P., D'Amato, Angela, Tortelli, Rosanna, Schilardi, Andrea, Galluzzo, Lucia, Gandin, Claudia, Baldereschi, Marzia, Di Carlo, Antonio, Inzitari, Domenico, Daniele, Antonio, Sabbà, Carlo, Logroscino, Giancarlo, Panza, Francesco, Farchi, Gino, Capurso, Antonio, Lepore, Vito, Livrea, Paolo, Motta, Luciano, Carnazzo, Giuseppe, Motta, Massimo, Bentivegna, Prospera, Bonaiuto, Salvatore, Cruciani, Guido, Postacchini, Demetrio, Amaducci, Luigi, Gandolfo, Carlo, Conti, Massimo, Canal, Nicola, Franceschi, Massimo, Scarlato, Guglielmo, Candelise, Livia, Scapini, Elio, Rengo, Franco, Abete, Pasquale, Cacciatore, Francesco, Enzi, Giuliano, Battistin, Leontino, Sergi, Giuseppe, Crepaldi, Gaetano, Maggi, Stefania, Minicuci, Nadia, Noale, Marianna, Grigoletto, Francesco, Perissinotto, Egle, Carbonin, Pierugo, Daniele, Antonio (ORCID:0000-0003-1641-5852), Solfrizzi, Vincenzo, Scafato, Emanuele, Seripa, Davide, Lozupone, Madia, Imbimbo, Bruno P., D'Amato, Angela, Tortelli, Rosanna, Schilardi, Andrea, Galluzzo, Lucia, Gandin, Claudia, Baldereschi, Marzia, Di Carlo, Antonio, Inzitari, Domenico, Daniele, Antonio, Sabbà, Carlo, Logroscino, Giancarlo, Panza, Francesco, Farchi, Gino, Capurso, Antonio, Lepore, Vito, Livrea, Paolo, Motta, Luciano, Carnazzo, Giuseppe, Motta, Massimo, Bentivegna, Prospera, Bonaiuto, Salvatore, Cruciani, Guido, Postacchini, Demetrio, Amaducci, Luigi, Gandolfo, Carlo, Conti, Massimo, Canal, Nicola, Franceschi, Massimo, Scarlato, Guglielmo, Candelise, Livia, Scapini, Elio, Rengo, Franco, Abete, Pasquale, Cacciatore, Francesco, Enzi, Giuliano, Battistin, Leontino, Sergi, Giuseppe, Crepaldi, Gaetano, Maggi, Stefania, Minicuci, Nadia, Noale, Marianna, Grigoletto, Francesco, Perissinotto, Egle, Carbonin, Pierugo, and Daniele, Antonio (ORCID:0000-0003-1641-5852)

Abstract

Objectives Cognitive frailty, a condition describing the simultaneous presence of physical frailty and mild cognitive impairment, has been recently defined by an international consensus group. We estimated the predictive role of a “reversible” cognitive frailty model on incident dementia, its subtypes, and all-cause mortality in nondemented older individuals. We verified if vascular risk factors or depressive symptoms could modify this predictive role. Design Longitudinal population-based study with 3.5- and 7-year of median follow-up. Setting Eight Italian municipalities included in the Italian Longitudinal Study on Aging. Participants In 2150 older individuals from the Italian Longitudinal Study on Aging, we operationalized reversible cognitive frailty with the presence of physical frailty and pre-mild cognitive impairment subjective cognitive decline, diagnosed with a self-report measure based on item 14 of the Geriatric Depression Scale. Measurements Incidence of dementia, its subtypes, and all-cause mortality. Results Over a 3.5-year follow-up, participants with reversible cognitive frailty showed an increased risk of overall dementia [hazard ratio (HR) 2.30, 95% confidence interval (CI) 1.02–5.18], particularly vascular dementia (VaD), and all-cause mortality (HR 1.74, 95% CI 1.07–2.83). Over a 7-year follow-up, participants with reversible cognitive frailty showed an increased risk of overall dementia (HR 2.12, 95% CI 1.12–4.03), particularly VaD, and all-cause mortality (HR 1.39, 95% CI 1.03–2.00). Vascular risk factors and depressive symptoms did not have any effect modifier on the relationship between reversible cognitive frailty and incident dementia and all-cause mortality. Conclusions A model of reversible cognitive frailty was a short- and long-term predictor of all-cause mortality and overall dementia, particularly VaD. The absence of vascular risk factors and depressive symptoms did not modify the predictive role of reversible cognitive frailty on th

Published
2017

5. A Multicentric Prospective Incidence Study of Guillain-Barre Syndrome in Italy. the ITANG Study

Author

Benedetti, M, Pugliatti, M, Dalessandro, R, Beghi, E, Chiò, A, Logroscino, G, Filippini, G, Galeotti, F, Massari, M, Santuccio, C, Raschetti, R, Abruzzi, L, Agazzi, E, Agostoni, E, Ambrogio, L, Amidei, S, Arbasino, C, Argentiero, V, Arnaboldi, M, Baldini, D, Barki, R, Bassi, P, Basso, F, Belcastro, V, Bellotti, M, Bersano, E, Besana, R, Bettoni, L, Bezzi, G, Bianconi, C, Bondavalli, M, Bonometti, A, Borghi, A, Borsato, C, Bortolotto, S, Bottacchi, E, Bresolin, N, Bruno, S, Burlina, A, Cafasso, G, Callegarini, C, Calvo, A, Candeloro, E, Casano, A, Cattaneo, S, Cavallo, R, Cheldi, A, Ciardo, G, Cirignotta, F, Clerici, A, Clerici, R, Comi, G, Conti, R, Coppo, F, Covelli, V, Crespi, V, Currò Dossi, M, Curtò, N, D'Adda, E, Dallocchio, C, D'Anna, S, De Massis, P, De Toni Franceschini, L, Di Vito, N, Didonè, G, Dileone, M, Donati, E, Dotta, M, Fazio, R, Federico, F, Ferrarese, C, Ferrazzini, F, Ferrero, B, Filosto, M, Frasson, E, Fusina, S, Galbussera, A, Gastaldo, E, Geda, C, Ghiglione, P, Giometto, B, Gionco, M, Giorgetti, A, Giussani, G, Gobbin, F, Grampa, G, Granieri, E, Greco, G, Guidetti, D, Guidi, C, Guidotti, M, Gusmaroli, G, Imperiale, D, Internò, S, Jann, S, La Spina, I, Leo, A, Leone, M, Leoni, S, Leotta, D, Lerario, R, Liotta, G, Livrea, P, Luda di Cortemiglio, E, Maggio, B, Magni, E, Magnoni, A, Maistrelli, J, Manca, D, Mandrioli, J, Manera, U, Marcello, N, Marchi, P, Marchini, C, Marconi, S, Mattioli, M, Mauro, A, Mazzaglia, G, Medici, D, Meineri, P, Meola, G, Micaglio, G, Michelucci, R, Michieli, G, Micieli, G, Minardi, C, Moglia, C, Monaco, S, Montanari, E, Moretto, G, Munerati, V, Mura, G, Mussutto, V, Nascimbene, C, Neri, W, Nichelli, P, Nobile Orazio, E, Oddenino, E, Onorato, S, Padovani, A, Palermo, M, Papurello, D, Passarella, B, Pavesi, G, Penza, M, Perini, M, Perini, F, Perla, F, Perlotto, N, Perrone, P, Pignatta, P, Pisano, F, Poglio, F, Polo, A, Poloni, M, Porazzi, D, Pradotto, L, Previdi, P, Quatrale, R, Rasi, F, Ravasio, A, Ravetti, C, Repaci, M, Riccardi, T, Riguzzi, P, Rinaldi, R, Riva, M, Romeo, V, Romorini, A, Rosso, T, Rotondo, G, Sacquegna, T, Sanson, F, Santamato, V, Santoro, D, Sartori, V, Sasanelli, F, Savio, K, Serena, M, Silani, V, Silvestri, L, Simioni, V, Squintani, G, Suardelli, M, Tartagla, L, Terenghi, F, Terlizzi, E, Terzano, M, Tesser, F, Testa, L, Ticca, A, Ticozzi, N, Tiriticco, M, Tola, M, Tonietti, S, Trianni, G, Trojano, M, Trotta, F, Turatti, M, Ursino, E, Vanotti, A, Vercellino, M, Villani, A, Vitelli, E, Zambito Marsala, S, Zanette, G, Zarcone, D, Zimatore, G, Zoccolella, S, BEGHI, ETTORE, Borghi, AM, Bottacchi, EF, Cattaneo, SI, Clerici, AM, Curtò, NA, FERRARESE, CARLO, Papurello, DM, Penza, MT, Squintani, GM, Tola, MR, Zoccolella, S., Benedetti, M, Pugliatti, M, Dalessandro, R, Beghi, E, Chiò, A, Logroscino, G, Filippini, G, Galeotti, F, Massari, M, Santuccio, C, Raschetti, R, Abruzzi, L, Agazzi, E, Agostoni, E, Ambrogio, L, Amidei, S, Arbasino, C, Argentiero, V, Arnaboldi, M, Baldini, D, Barki, R, Bassi, P, Basso, F, Belcastro, V, Bellotti, M, Bersano, E, Besana, R, Bettoni, L, Bezzi, G, Bianconi, C, Bondavalli, M, Bonometti, A, Borghi, A, Borsato, C, Bortolotto, S, Bottacchi, E, Bresolin, N, Bruno, S, Burlina, A, Cafasso, G, Callegarini, C, Calvo, A, Candeloro, E, Casano, A, Cattaneo, S, Cavallo, R, Cheldi, A, Ciardo, G, Cirignotta, F, Clerici, A, Clerici, R, Comi, G, Conti, R, Coppo, F, Covelli, V, Crespi, V, Currò Dossi, M, Curtò, N, D'Adda, E, Dallocchio, C, D'Anna, S, De Massis, P, De Toni Franceschini, L, Di Vito, N, Didonè, G, Dileone, M, Donati, E, Dotta, M, Fazio, R, Federico, F, Ferrarese, C, Ferrazzini, F, Ferrero, B, Filosto, M, Frasson, E, Fusina, S, Galbussera, A, Gastaldo, E, Geda, C, Ghiglione, P, Giometto, B, Gionco, M, Giorgetti, A, Giussani, G, Gobbin, F, Grampa, G, Granieri, E, Greco, G, Guidetti, D, Guidi, C, Guidotti, M, Gusmaroli, G, Imperiale, D, Internò, S, Jann, S, La Spina, I, Leo, A, Leone, M, Leoni, S, Leotta, D, Lerario, R, Liotta, G, Livrea, P, Luda di Cortemiglio, E, Maggio, B, Magni, E, Magnoni, A, Maistrelli, J, Manca, D, Mandrioli, J, Manera, U, Marcello, N, Marchi, P, Marchini, C, Marconi, S, Mattioli, M, Mauro, A, Mazzaglia, G, Medici, D, Meineri, P, Meola, G, Micaglio, G, Michelucci, R, Michieli, G, Micieli, G, Minardi, C, Moglia, C, Monaco, S, Montanari, E, Moretto, G, Munerati, V, Mura, G, Mussutto, V, Nascimbene, C, Neri, W, Nichelli, P, Nobile Orazio, E, Oddenino, E, Onorato, S, Padovani, A, Palermo, M, Papurello, D, Passarella, B, Pavesi, G, Penza, M, Perini, M, Perini, F, Perla, F, Perlotto, N, Perrone, P, Pignatta, P, Pisano, F, Poglio, F, Polo, A, Poloni, M, Porazzi, D, Pradotto, L, Previdi, P, Quatrale, R, Rasi, F, Ravasio, A, Ravetti, C, Repaci, M, Riccardi, T, Riguzzi, P, Rinaldi, R, Riva, M, Romeo, V, Romorini, A, Rosso, T, Rotondo, G, Sacquegna, T, Sanson, F, Santamato, V, Santoro, D, Sartori, V, Sasanelli, F, Savio, K, Serena, M, Silani, V, Silvestri, L, Simioni, V, Squintani, G, Suardelli, M, Tartagla, L, Terenghi, F, Terlizzi, E, Terzano, M, Tesser, F, Testa, L, Ticca, A, Ticozzi, N, Tiriticco, M, Tola, M, Tonietti, S, Trianni, G, Trojano, M, Trotta, F, Turatti, M, Ursino, E, Vanotti, A, Vercellino, M, Villani, A, Vitelli, E, Zambito Marsala, S, Zanette, G, Zarcone, D, Zimatore, G, Zoccolella, S, BEGHI, ETTORE, Borghi, AM, Bottacchi, EF, Cattaneo, SI, Clerici, AM, Curtò, NA, FERRARESE, CARLO, Papurello, DM, Penza, MT, Squintani, GM, Tola, MR, and Zoccolella, S.

Abstract

To assess Guillain-Barre syndrome (GBS) incidence we relied on the Italian Network for the study of GBS (ITANG) established in 2010 in 7 Italian regions to analyse the association between influenza vaccination and GBS. Methods: All individuals aged ≥18 years, presenting with clinical manifestations that suggested GBS according to the universally accepted Asbury's diagnostic criteria (1990) were prospectively notified to a centralised database by ITANG neurologists over the period October 1, 2010-September 30, 2011. Through a telephone survey, 9 trained interviewers followed up the cases to diagnosis and then for 1 year since hospital discharge. Validation of case reporting was performed with the support of administrative data in 5 regions. Results: We found 365 cases fulfilling the definition for GBS or one of its variants over 19,846,068 population ≥18 years of age, yielding an annual incidence rate of 1.84 per 100,000 (95% CI 1.65-2.03), 2.30 (95% CI 1.99-2.60) in men and 1.41 (95% CI 1.18-1.64) in women. A highly significant peak of incidence was observed in February 2011 as compared to reference month (September 2011, rate ratio 3.3:1, p < 0.01). Conclusions: In Italy, GBS incidence was among the highest reported in Europe and higher than previously observed in Italian studies.

Published
2015

6. Migraine-specific quality of life questionnaire and relapse of medication overuse headache

Author

Caproni, S., Bianchi, E., Cupini, L. M., Corbelli, I., Beghi, E., Calabresi, P., Sarchielli, P., Pupillo, E., Pini, L. A., Iani, C., Livrea, P., Prudenzano, M. P., Bernardi, G., Diomedi, M., Tedeschi, G., Russo, A., Pisani, F., Pisani, L. R., Bono, G., Misaggi, G., Di Piero, V., Di Clemente, L., Sandrini, G., Allena, M., Calabresi P. (ORCID:0000-0003-0326-5509), Caproni, S., Bianchi, E., Cupini, L. M., Corbelli, I., Beghi, E., Calabresi, P., Sarchielli, P., Pupillo, E., Pini, L. A., Iani, C., Livrea, P., Prudenzano, M. P., Bernardi, G., Diomedi, M., Tedeschi, G., Russo, A., Pisani, F., Pisani, L. R., Bono, G., Misaggi, G., Di Piero, V., Di Clemente, L., Sandrini, G., Allena, M., and Calabresi P. (ORCID:0000-0003-0326-5509)

Abstract

Background: The management of Medication overuse headache (MOH) represents a difficult challenge for clinicians and headache experts, particularly for the responder rate after a successful withdrawal treatment. The purpose of this study was to investigate the role of demographic and clinical characteristics as well as the score of Migraine-Specific Quality of Life Questionnaire (MSQ), Migraine Disability Questionnaire and Leeds Dependence Questionnaire in predicting a response after a successful withdrawal treatment in patients with MOH. Methods: This ancillary study is part of a randomized trial that demonstrated the safety and the efficacy of a 3-month treatment with sodium valproate (VPA) (800 mg/day vs placebo) in MOH. Demographic and clinical characteristics and questionnaire results were obtained from the entire sample. Results: A significant correlation was found only between MOH relapse and the total MSQ score, the Role Preventive sub-scale and the Emotional Function sub-scale, suggesting a poorer quality of life in non responders. Conclusion: A high MSQ score could be associated with a poor short-term outcome in MOH patients after a successful treatment with detoxification followed by a new treatment.

Published
2015

7. A Multicentric Prospective Incidence Study of Guillain-Barre Syndrome in Italy. the ITANG Study

Author

Benedetti, M. D., Pugliatti, M., Dalessandro, R., Beghi, E., Chio, A., Logroscino, G., Filippini, G., Galeotti, F., Massari, M., Santuccio, C., Raschetti R., Abruzzi L, Agazzi, E, Agostoni, E, Ambrogio, L, Amidei, S, Arbasino, C, Argentiero, V, Arnaboldi, M, Baldini, D, Barki, R, Bassi, P, Basso, F, Belcastro, V, Bellotti, M, Bersano, E, Besana, R, Bettoni, L, Bezzi, G, Bianconi, C, Bondavalli, M, Bonometti, A, Borghi, Am, Borsato, C, Bortolotto, S, Bottacchi, Ef, Bresolin, N, Bruno, S, Burlina, A, Cafasso, G, Callegarini, C, Calvo, A, Candeloro, E, Casano, A, Cattaneo, Si, Cavallo, R, Cheldi, A, Ciardo, G, Cirignotta, F, Clerici, Am, Clerici, R, Comi, G, Conti, R, Coppo, F, Covelli, V, Crespi, V, Currò Dossi, M, Curtò, Na, D'Adda, E, Dallocchio, C, D'Anna, S, De Massis, P, De Toni Franceschini, L, Di Vito, N, Didonè, G, Dileone, M, Donati, E, Dotta, M, Fazio, R, Federico, F, Ferrarese, C, Ferrazzini, F, Ferrero, B, Filosto, M, Frasson, E, Fusina, S, Galbussera, A, Gastaldo, E, Geda, C, Ghiglione, P, Giometto, B, Gionco, M, Giorgetti, A, Giussani, G, Gobbin, F, Grampa, G, Granieri, E, Greco, G, Guidetti, D, Guidi, C, Guidotti, M, Gusmaroli, G, Imperiale, D, Internò, S, Jann, S, La Spina, I, Leo, A, Leone, M, Leoni, S, Leotta, D, Lerario, R, Liotta, G, Livrea, P, Luda di Cortemiglio, E, Maggio, B, Magni, Eugenio, Magnoni, A, Maistrelli, J, Manca, D, Mandrioli, J, Manera, U, Marcello, N, Marchi, P, Marchini, C, Marconi, S, Mattioli, M, Mauro, A, Mazzaglia, G, Medici, D, Meineri, P, Meola, G, Micaglio, G, Michelucci, R, Michieli, G, Micieli, G, Minardi, C, Moglia, C, Monaco, S, Montanari, E, Moretto, G, Munerati, V, Mura, G, Mussutto, V, Nascimbene, C, Neri, W, Nichelli, P, Nobile-Orazio, E, Oddenino, E, Onorato, S, Padovani, A, Palermo, M, Papurello, Dm, Passarella, B, Pavesi, G, Penza, Mt, Perini, M, Perini, F, Perla, F, Perlotto, N, Perrone, P, Pignatta, P, Pisano, F, Poglio, F, Polo, A, Poloni, M, Porazzi, D, Pradotto, L, Previdi, P, Quatrale, R, Rasi, F, Ravasio, A, Ravetti, C, Repaci, M, Riccardi, T, Riguzzi, P, Rinaldi, R, Riva, M, Romeo, V, Romorini, A, Rosso, T, Rotondo, G, Sacquegna, T, Sanson, F, Santamato, V, Santoro, D, Sartori, V, Sasanelli, F, Savio, K, Serena, M, Silani, V, Silvestri, L, Simioni, V, Squintani, Gm, Suardelli, M, Tartagla, L, Terenghi, F, Terlizzi, E, Terzano, Mg, Tesser, F, Testa, L, Ticca, A, Ticozzi, N, Tiriticco, M, Tola, Mr, Tonietti, S, Trianni, G, Trojano, M, Trotta, F, Turatti, M, Ursino, E, Vanotti, A, Vercellino, M, Villani, A, Vitelli, E, Zambito Marsala, S, Zanette, G, Zarcone, D, Zimatore, G, Zoccolella, S., Magni E (ORCID:0000-0002-2235-2280), Benedetti, M. D., Pugliatti, M., Dalessandro, R., Beghi, E., Chio, A., Logroscino, G., Filippini, G., Galeotti, F., Massari, M., Santuccio, C., Raschetti R., Abruzzi L, Agazzi, E, Agostoni, E, Ambrogio, L, Amidei, S, Arbasino, C, Argentiero, V, Arnaboldi, M, Baldini, D, Barki, R, Bassi, P, Basso, F, Belcastro, V, Bellotti, M, Bersano, E, Besana, R, Bettoni, L, Bezzi, G, Bianconi, C, Bondavalli, M, Bonometti, A, Borghi, Am, Borsato, C, Bortolotto, S, Bottacchi, Ef, Bresolin, N, Bruno, S, Burlina, A, Cafasso, G, Callegarini, C, Calvo, A, Candeloro, E, Casano, A, Cattaneo, Si, Cavallo, R, Cheldi, A, Ciardo, G, Cirignotta, F, Clerici, Am, Clerici, R, Comi, G, Conti, R, Coppo, F, Covelli, V, Crespi, V, Currò Dossi, M, Curtò, Na, D'Adda, E, Dallocchio, C, D'Anna, S, De Massis, P, De Toni Franceschini, L, Di Vito, N, Didonè, G, Dileone, M, Donati, E, Dotta, M, Fazio, R, Federico, F, Ferrarese, C, Ferrazzini, F, Ferrero, B, Filosto, M, Frasson, E, Fusina, S, Galbussera, A, Gastaldo, E, Geda, C, Ghiglione, P, Giometto, B, Gionco, M, Giorgetti, A, Giussani, G, Gobbin, F, Grampa, G, Granieri, E, Greco, G, Guidetti, D, Guidi, C, Guidotti, M, Gusmaroli, G, Imperiale, D, Internò, S, Jann, S, La Spina, I, Leo, A, Leone, M, Leoni, S, Leotta, D, Lerario, R, Liotta, G, Livrea, P, Luda di Cortemiglio, E, Maggio, B, Magni, Eugenio, Magnoni, A, Maistrelli, J, Manca, D, Mandrioli, J, Manera, U, Marcello, N, Marchi, P, Marchini, C, Marconi, S, Mattioli, M, Mauro, A, Mazzaglia, G, Medici, D, Meineri, P, Meola, G, Micaglio, G, Michelucci, R, Michieli, G, Micieli, G, Minardi, C, Moglia, C, Monaco, S, Montanari, E, Moretto, G, Munerati, V, Mura, G, Mussutto, V, Nascimbene, C, Neri, W, Nichelli, P, Nobile-Orazio, E, Oddenino, E, Onorato, S, Padovani, A, Palermo, M, Papurello, Dm, Passarella, B, Pavesi, G, Penza, Mt, Perini, M, Perini, F, Perla, F, Perlotto, N, Perrone, P, Pignatta, P, Pisano, F, Poglio, F, Polo, A, Poloni, M, Porazzi, D, Pradotto, L, Previdi, P, Quatrale, R, Rasi, F, Ravasio, A, Ravetti, C, Repaci, M, Riccardi, T, Riguzzi, P, Rinaldi, R, Riva, M, Romeo, V, Romorini, A, Rosso, T, Rotondo, G, Sacquegna, T, Sanson, F, Santamato, V, Santoro, D, Sartori, V, Sasanelli, F, Savio, K, Serena, M, Silani, V, Silvestri, L, Simioni, V, Squintani, Gm, Suardelli, M, Tartagla, L, Terenghi, F, Terlizzi, E, Terzano, Mg, Tesser, F, Testa, L, Ticca, A, Ticozzi, N, Tiriticco, M, Tola, Mr, Tonietti, S, Trianni, G, Trojano, M, Trotta, F, Turatti, M, Ursino, E, Vanotti, A, Vercellino, M, Villani, A, Vitelli, E, Zambito Marsala, S, Zanette, G, Zarcone, D, Zimatore, G, Zoccolella, S., and Magni E (ORCID:0000-0002-2235-2280)

Abstract

To assess Guillain-Barre syndrome (GBS) incidence we relied on the Italian Network for the study of GBS (ITANG) established in 2010 in 7 Italian regions to analyse the association between influenza vaccination and GBS. Methods: All individuals aged ≥18 years, presenting with clinical manifestations that suggested GBS according to the universally accepted Asbury's diagnostic criteria (1990) were prospectively notified to a centralised database by ITANG neurologists over the period October 1, 2010-September 30, 2011. Through a telephone survey, 9 trained interviewers followed up the cases to diagnosis and then for 1 year since hospital discharge. Validation of case reporting was performed with the support of administrative data in 5 regions. Results: We found 365 cases fulfilling the definition for GBS or one of its variants over 19,846,068 population ≥18 years of age, yielding an annual incidence rate of 1.84 per 100,000 (95% CI 1.65-2.03), 2.30 (95% CI 1.99-2.60) in men and 1.41 (95% CI 1.18-1.64) in women. A highly significant peak of incidence was observed in February 2011 as compared to reference month (September 2011, rate ratio 3.3:1, p < 0.01). Conclusions: In Italy, GBS incidence was among the highest reported in Europe and higher than previously observed in Italian studies.

Published
2015

8. Tremor in primary adult-onset dystonia: prevalence and associated clinical features

Author

Defazio, Giovanni, Gigante, Angelo Fabio, Abbruzzese, Giovanni, Bentivoglio, Anna Rita, Colosimo, Carlo, Esposito, Marcello, Fabbrini, Giovanni, Guidubaldi, Arianna, Girlanda, Paolo, Liguori, Rocco, Marinelli, Lucio, Morgante, Francesca, Santoro, Lucio, Tinazzi, Michele, Livrea, Paolo, Berardelli, Alfredo, Bentivoglio, Anna Rita (ORCID:0000-0002-9663-095X), Defazio, Giovanni, Gigante, Angelo Fabio, Abbruzzese, Giovanni, Bentivoglio, Anna Rita, Colosimo, Carlo, Esposito, Marcello, Fabbrini, Giovanni, Guidubaldi, Arianna, Girlanda, Paolo, Liguori, Rocco, Marinelli, Lucio, Morgante, Francesca, Santoro, Lucio, Tinazzi, Michele, Livrea, Paolo, Berardelli, Alfredo, and Bentivoglio, Anna Rita (ORCID:0000-0002-9663-095X)

Abstract

To investigate the frequency and the main clinical features of tremor in primary adult-onset dystonia (PAOD).

Published
2013

9. Neurofilament ELISA validation

Author

Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, Teunissen, Charlotte E, Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, and Teunissen, Charlotte E

Abstract

BACKGROUND: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. METHODS: The UmanDiagnostics NF-light (R)enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. RESULTS: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R=0.60, p<0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R=0.98, p<0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. CONCLUSION: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

Published
2010
Full Text
View/download PDF

10. Neurofilament ELISA validation

Author

Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, Teunissen, Charlotte E, Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, and Teunissen, Charlotte E

Abstract

This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

Published
2010
Full Text
View/download PDF

11. Neurofilament ELISA validation.

Author

Petzold, A., Altintas, A., Andreoni, L., Bartos, A., Berthele, A., Blankenstein, M.A., Buee, L., Castellazzi, M., Cepok, S., Comabella, M., Constantinescu, C.S., Deisenhammer, F., Deniz, G., Erten, G., Espino, M., Fainardi, E., Franciotta, D., Freedman, M.S., Giedraitis, V., Gilhus, N.E., Giovannoni, G., Glabinski, A., Grieb, P., Hartung, H.P., Hemmer, B., Herukka, S.K., Hintzen, R., Ingelsson, M., Jackson, S., Jacobsen, S., Jafari, N., Jalosinski, M., Jarius, S., Kapaki, E., Kieseier, B.C., Koel-Simmelink, M.J., Kornhuber, J., Kuhle, J., Kurzepa, J., Lalive, P.H., Lannfelt, L., Lehmensiek, V., Lewczuk, P., Livrea, P., Marnetto, F., Martino, D., Menge, T., Norgren, N., Papuc, E., Paraskevas, G.P., Pirttilä, T., Rajda, C., Rejdak, K., Ricny, J., Ripova, D., Rosengren, L., Ruggieri, M., Schraen, S., Shaw, G., Sindic, C., Siva, A., Stigbrand, T., Stonebridge, I., Topcular, B., Trojano, M., Tumani, H., Twaalfhoven, H.A., Vecsei, L., Pesch, V. Van, Vanderstichele, H., Vedeler, C., Verbeek, M.M., Villar, L.M., Weissert, R., Wildemann, B., Yang, C., Yao, K., Teunissen, C.E., Petzold, A., Altintas, A., Andreoni, L., Bartos, A., Berthele, A., Blankenstein, M.A., Buee, L., Castellazzi, M., Cepok, S., Comabella, M., Constantinescu, C.S., Deisenhammer, F., Deniz, G., Erten, G., Espino, M., Fainardi, E., Franciotta, D., Freedman, M.S., Giedraitis, V., Gilhus, N.E., Giovannoni, G., Glabinski, A., Grieb, P., Hartung, H.P., Hemmer, B., Herukka, S.K., Hintzen, R., Ingelsson, M., Jackson, S., Jacobsen, S., Jafari, N., Jalosinski, M., Jarius, S., Kapaki, E., Kieseier, B.C., Koel-Simmelink, M.J., Kornhuber, J., Kuhle, J., Kurzepa, J., Lalive, P.H., Lannfelt, L., Lehmensiek, V., Lewczuk, P., Livrea, P., Marnetto, F., Martino, D., Menge, T., Norgren, N., Papuc, E., Paraskevas, G.P., Pirttilä, T., Rajda, C., Rejdak, K., Ricny, J., Ripova, D., Rosengren, L., Ruggieri, M., Schraen, S., Shaw, G., Sindic, C., Siva, A., Stigbrand, T., Stonebridge, I., Topcular, B., Trojano, M., Tumani, H., Twaalfhoven, H.A., Vecsei, L., Pesch, V. Van, Vanderstichele, H., Vedeler, C., Verbeek, M.M., Villar, L.M., Weissert, R., Wildemann, B., Yang, C., Yao, K., and Teunissen, C.E.

Abstract

Contains fulltext : 89601.pdf (publisher's version ) (Closed access), BACKGROUND: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. METHODS: The UmanDiagnostics NF-light (R)enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. RESULTS: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R=0.60, p<0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R=0.98, p<0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. CONCLUSION: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

Published
2010

12. Neurofilament ELISA validation.

Author

UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, UCL - (SLuc) Service de neurologie, Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, Teunissen, Charlotte E, UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, UCL - (SLuc) Service de neurologie, Petzold, Axel, Altintas, Ayse, Andreoni, Laura, Bartos, Ales, Berthele, Achim, Blankenstein, Marinus A, Buee, Luc, Castellazzi, Massimiliano, Cepok, Sabine, Comabella, Manuel, Constantinescu, Cris S, Deisenhammer, Florian, Deniz, Gunnur, Erten, Gaye, Espiño, Mercedes, Fainardi, Enrico, Franciotta, Diego, Freedman, Mark S, Giedraitis, Vilmantas, Gilhus, Nils Erik, Giovannoni, Gavin, Glabinski, Andrzej, Grieb, Pawel, Hartung, Hans-Peter, Hemmer, Bernhard, Herukka, Sanna-Kaisa, Hintzen, Rogier, Ingelsson, Martin, Jackson, Samuel, Jacobsen, Steve, Jafari, Naghmeh, Jalosinski, Marcin, Jarius, Sven, Kapaki, Elisabeth, Kieseier, Bernd C, Koel-Simmelink, Marleen J A, Kornhuber, Johannes, Kuhle, Jens, Kurzepa, Jacek, Lalive, Patrice H, Lannfelt, Lars, Lehmensiek, Vera, Lewczuk, Piotr, Livrea, Paolo, Marnetto, Fabiana, Martino, Davide, Menge, Til, Norgren, Niklas, Papuć, Eva, Paraskevas, George P, Pirttilä, Tuula, Rajda, Cecília, Rejdak, Konrad, Ricny, Jan, Ripova, Daniela, Rosengren, Lars, Ruggieri, Maddalena, Schraen, Susanna, Shaw, Gerry, Sindic, Christian, Siva, Aksel, Stigbrand, Torgny, Stonebridge, Iva, Topcular, Baris, Trojano, Maria, Tumani, Hayrettin, Twaalfhoven, Harry A M, Vécsei, László, Van Pesch, Vincent, Vanderstichele, Hugo, Vedeler, Christian, Verbeek, Marcel M, Villar, Luisa Maria, Weissert, Robert, Wildemann, Brigitte, Yang, Cui, Yao, Karen, and Teunissen, Charlotte E

Abstract

This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

Published
2010

13. Neurofilament ELISA validation.

Author

Petzold, A., Altintas, A., Andreoni, L., Bartos, A., Berthele, A., Blankenstein, M.A., Buee, L., Castellazzi, M., Cepok, S., Comabella, M., Constantinescu, C.S., Deisenhammer, F., Deniz, G., Erten, G., Espino, M., Fainardi, E., Franciotta, D., Freedman, M.S., Giedraitis, V., Gilhus, N.E., Giovannoni, G., Glabinski, A., Grieb, P., Hartung, H.P., Hemmer, B., Herukka, S.K., Hintzen, R., Ingelsson, M., Jackson, S., Jacobsen, S., Jafari, N., Jalosinski, M., Jarius, S., Kapaki, E., Kieseier, B.C., Koel-Simmelink, M.J., Kornhuber, J., Kuhle, J., Kurzepa, J., Lalive, P.H., Lannfelt, L., Lehmensiek, V., Lewczuk, P., Livrea, P., Marnetto, F., Martino, D., Menge, T., Norgren, N., Papuc, E., Paraskevas, G.P., Pirttilä, T., Rajda, C., Rejdak, K., Ricny, J., Ripova, D., Rosengren, L., Ruggieri, M., Schraen, S., Shaw, G., Sindic, C., Siva, A., Stigbrand, T., Stonebridge, I., Topcular, B., Trojano, M., Tumani, H., Twaalfhoven, H.A., Vecsei, L., Pesch, V. Van, Vanderstichele, H., Vedeler, C., Verbeek, M.M., Villar, L.M., Weissert, R., Wildemann, B., Yang, C., Yao, K., Teunissen, C.E., Petzold, A., Altintas, A., Andreoni, L., Bartos, A., Berthele, A., Blankenstein, M.A., Buee, L., Castellazzi, M., Cepok, S., Comabella, M., Constantinescu, C.S., Deisenhammer, F., Deniz, G., Erten, G., Espino, M., Fainardi, E., Franciotta, D., Freedman, M.S., Giedraitis, V., Gilhus, N.E., Giovannoni, G., Glabinski, A., Grieb, P., Hartung, H.P., Hemmer, B., Herukka, S.K., Hintzen, R., Ingelsson, M., Jackson, S., Jacobsen, S., Jafari, N., Jalosinski, M., Jarius, S., Kapaki, E., Kieseier, B.C., Koel-Simmelink, M.J., Kornhuber, J., Kuhle, J., Kurzepa, J., Lalive, P.H., Lannfelt, L., Lehmensiek, V., Lewczuk, P., Livrea, P., Marnetto, F., Martino, D., Menge, T., Norgren, N., Papuc, E., Paraskevas, G.P., Pirttilä, T., Rajda, C., Rejdak, K., Ricny, J., Ripova, D., Rosengren, L., Ruggieri, M., Schraen, S., Shaw, G., Sindic, C., Siva, A., Stigbrand, T., Stonebridge, I., Topcular, B., Trojano, M., Tumani, H., Twaalfhoven, H.A., Vecsei, L., Pesch, V. Van, Vanderstichele, H., Vedeler, C., Verbeek, M.M., Villar, L.M., Weissert, R., Wildemann, B., Yang, C., Yao, K., and Teunissen, C.E.

Abstract

Contains fulltext : 89601.pdf (publisher's version ) (Closed access), BACKGROUND: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. METHODS: The UmanDiagnostics NF-light (R)enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. RESULTS: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R=0.60, p<0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R=0.98, p<0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. CONCLUSION: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online.

Published
2010

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