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188 results on '"Giancaterini, A."'

2. Optimization of the Generalized Covariance Estimator in Noncausal Processes

Author

Cubadda, Gianluca, Giancaterini, Francesco, Hecq, Alain, and Jasiak, Joann

Subjects
Economics - Econometrics
Abstract

This paper investigates the performance of the Generalized Covariance estimator (GCov) in estimating and identifying mixed causal and noncausal models. The GCov estimator is a semi-parametric method that minimizes an objective function without making any assumptions about the error distribution and is based on nonlinear autocovariances to identify the causal and noncausal orders. When the number and type of nonlinear autocovariances included in the objective function of a GCov estimator is insufficient/inadequate, or the error density is too close to the Gaussian, identification issues can arise. These issues result in local minima in the objective function, which correspond to parameter values associated with incorrect causal and noncausal orders. Then, depending on the starting point and the optimization algorithm employed, the algorithm can converge to a local minimum. The paper proposes the use of the Simulated Annealing (SA) optimization algorithm as an alternative to conventional numerical optimization methods. The results demonstrate that SA performs well when applied to mixed causal and noncausal models, successfully eliminating the effects of local minima. The proposed approach is illustrated by an empirical application involving a bivariate commodity price series.

Published
2023

3. Is climate change time reversible?

Author

Giancaterini, Francesco, Hecq, Alain, and Morana, Claudio

Subjects
Economics - Econometrics
Abstract

This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is computed with the Hodrick-Prescott filter rendering a time-reversible closed-form solution. This paper also links the concept of an environmental tipping point to the statistical property of time irreversibility and assesses fourteen climate indicators. We find evidence of time irreversibility in $GHG$ emissions, global temperature, global sea levels, sea ice area, and some natural oscillation indices. While not conclusive, our findings urge the implementation of correction policies to avoid the worst consequences of climate change and not miss the opportunity window, which might still be available, despite closing quickly.

Published
2022

4. Inference in mixed causal and noncausal models with generalized Student's t-distributions

Author

Giancaterini, Francesco and Hecq, Alain

Subjects
Economics - Econometrics
Abstract

The properties of Maximum Likelihood estimator in mixed causal and noncausal models with a generalized Student's t error process are reviewed. Several known existing methods are typically not applicable in the heavy-tailed framework. To this end, a new approach to make inference on causal and noncausal parameters in finite sample sizes is proposed. It exploits the empirical variance of the generalized Student's-t, without the existence of population variance. Monte Carlo simulations show a good performance of the new variance construction for fat tail series. Finally, different existing approaches are compared using three empirical applications: the variation of daily COVID-19 deaths in Belgium, the monthly wheat prices, and the monthly inflation rate in Brazil.

Published
2020

8. Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group

Author

Davide Masi, Rita Zilich, Riccardo Candido, Annalisa Giancaterini, Giacomo Guaita, Marco Muselli, Paola Ponzani, Pierluigi Santin, Damiano Verda, and Nicoletta Musacchio

Subjects
dyslipidemia, machine learning, artificial intelligence, type 2 diabetes, low-density lipoprotein cholesterol, Medicine
Abstract

Identifying and treating lipid abnormalities is crucial for preventing cardiovascular disease in diabetic patients, yet only two-thirds of patients reach recommended cholesterol levels. Elucidating the factors associated with lipid goal attainment represents an unmet clinical need. To address this knowledge gap, we conducted a real-world analysis of the lipid profiles of 11.252 patients from the Annals of the Italian Association of Medical Diabetologists (AMD) database from 2005 to 2019. We used a Logic Learning Machine (LLM) to extract and classify the most relevant variables predicting the achievement of a low-density lipoprotein cholesterol (LDL-C) value lower than 100 mg/dL (2.60 mmol/L) within two years of the start of lipid-lowering therapy. Our analysis showed that 61.4% of the patients achieved the treatment goal. The LLM model demonstrated good predictive performance, with a precision of 0.78, accuracy of 0.69, recall of 0.70, F1 Score of 0.74, and ROC-AUC of 0.79. The most significant predictors of achieving the treatment goal were LDL-C values at the start of lipid-lowering therapy and their reduction after six months. Other predictors of a greater likelihood of reaching the target included high-density lipoprotein cholesterol, albuminuria, and body mass index at baseline, as well as younger age, male sex, more follow-up visits, no therapy discontinuation, higher Q-score, lower blood glucose and HbA1c levels, and the use of anti-hypertensive medication. At baseline, for each LDL-C range analysed, the LLM model also provided the minimum reduction that needs to be achieved by the next six-month visit to increase the likelihood of reaching the therapeutic goal within two years. These findings could serve as a useful tool to inform therapeutic decisions and to encourage further in-depth analysis and testing.

Published
2023
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9. Clinical inertia is the enemy of therapeutic success in the management of diabetes and its complications: a narrative literature review

Author

F. Andreozzi, R. Candido, S. Corrao, R. Fornengo, A. Giancaterini, P. Ponzani, M. C. Ponziani, F. Tuccinardi, and D. Mannino

Subjects
Clinical inertia, Diabetes care, Italian association of medical diabetologists, Therapeutic inertia, Type 2 diabetes mellitus, Nutritional diseases. Deficiency diseases, RC620-627
Abstract

Abstract Diabetes mellitus is a chronic disease characterized by high social, economic and health burden, mostly due to the high incidence and morbidity of diabetes complications. Numerous studies have shown that optimizing metabolic control may reduce the risk of micro and macrovascular complications related to the disease, and the algorithms suggest that an appropriate and timely step of care intensification should be proposed after 3 months from the failure to achieve metabolic goals. Nonetheless, many population studies show that glycemic control in diabetic patients is often inadequate. The phenomenon of clinical inertia in diabetology, defined as the failure to start a therapy or its intensification/de-intensification when appropriate, has been studied for almost 20 years, and it is not limited to diabetes care, but also affects other specialties. In the present manuscript, we have documented the issue of inertia in its complexity, assessing its dimensions, its epidemiological weight, and its burden over the effectiveness of care. Our main goal is the identification of the causes of clinical inertia in diabetology, and the quantification of its social and health-related consequences through the adoption of appropriate indicators, in an effort to advance possible solutions and proposals to fight and possibly overcome clinical inertia, thus improving health outcomes and quality of care.

Published
2020
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10. Is Climate Change Time-Reversible?

Author

Francesco Giancaterini, Alain Hecq, and Claudio Morana

Subjects
mixed causal and noncausal models, time reversibility, Hodrick–Prescott filter, climate change, global warming, environmental tipping points, Economics as a science, HB71-74
Abstract

This paper proposes strategies to detect time reversibility in stationary stochastic processes by using the properties of mixed causal and noncausal models. It shows that they can also be used for non-stationary processes when the trend component is computed with the Hodrick–Prescott filter rendering a time-reversible closed-form solution. This paper also links the concept of an environmental tipping point to the statistical property of time irreversibility and assesses fourteen climate indicators. We find evidence of time irreversibility in greenhouse gas emissions, global temperature, global sea levels, sea ice area, and some natural oscillation indices. While not conclusive, our findings urge the implementation of correction policies to avoid the worst consequences of climate change and not miss the opportunity window, which might still be available, despite closing quickly.

Published
2022
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11. Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Author

Musacchio, Nicoletta, Giancaterini, Annalisa, Guaita, Giacomo, Ozzello, Alessandro, Pellegrini, Maria A, Ponzani, Paola, Russo, Giuseppina T, Zilich, Rita, and de Micheli, Alberto

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are not limited anymore to a descriptive analysis of the data, as we can obtain greater value by identifying and predicting patterns resulting from inductive reasoning. Machine learning software programs that disclose the reasoning behind a prediction allow for “what-if” models by which it is possible to understand if and how, by changing certain factors, one may improve the outcomes, thereby identifying the optimal behavior. Currently, diabetes care is facing several challenges: the decreasing number of diabetologists, the increasing number of patients, the reduced time allowed for medical visits, the growing complexity of the disease both from the standpoints of clinical and patient care, the difficulty of achieving the relevant clinical targets, the growing burden of disease management for both the health care professional and the patient, and the health care accessibility and sustainability. In this context, new digital technologies and the use of artificial intelligence are certainly a great opportunity. Herein, we report the results of a careful analysis of the current literature and represent the vision of the Italian Association of Medical Diabetologists (AMD) on this controversial topic that, if well used, may be the key for a great scientific innovation. AMD believes that the use of artificial intelligence will enable the conversion of data (descriptive) into knowledge of the factors that “affect” the behavior and correlations (predictive), thereby identifying the key aspects that may establish an improvement of the expected results (prescriptive). Artificial intelligence can therefore become a tool of great technical support to help diabetologists become fully responsible of the individual patient, thereby assuring customized and precise medicine. This, in turn, will allow for comprehensive therapies to be built in accordance with the evidence criteria that should always be the ground for any therapeutic choice.

Published
2020
Full Text
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12. Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group

Author

Masi, Davide, primary, Zilich, Rita, additional, Candido, Riccardo, additional, Giancaterini, Annalisa, additional, Guaita, Giacomo, additional, Muselli, Marco, additional, Ponzani, Paola, additional, Santin, Pierluigi, additional, Verda, Damiano, additional, and Musacchio, Nicoletta, additional

Published
2023
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13. The burden of obesity in type 1 diabetic subjects: a sex-specific analysis from the AMD Annals Initiative

Author

Giandalia, Annalisa, primary, Russo, Giuseppina Tiziana, additional, Ruggeri, Patrizia, additional, Giancaterini, Annalisa, additional, Brun, Elisabetta, additional, Cristofaro, Mariarosaria, additional, Bogazzi, Anna, additional, Rossi, Maria Chiara, additional, Lucisano, Giuseppe, additional, Rocca, Alberto, additional, Manicardi, Valeria, additional, Di Bartolo, Paolo, additional, Di Cianni, Graziano, additional, Giuliani, Chiara, additional, and Napoli, Angela, additional

Published
2023
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15. Uncovering Predictors of Lipid Goal Attainment in Type 2 Diabetes Outpatients Using Logic Learning Machine: Insights from the AMD Annals and AMD Artificial Intelligence Study Group

Author

Musacchio, Davide Masi, Rita Zilich, Riccardo Candido, Annalisa Giancaterini, Giacomo Guaita, Marco Muselli, Paola Ponzani, Pierluigi Santin, Damiano Verda, and Nicoletta

Subjects
dyslipidemia, machine learning, artificial intelligence, type 2 diabetes, low-density lipoprotein cholesterol
Abstract

Identifying and treating lipid abnormalities is crucial for preventing cardiovascular disease in diabetic patients, yet only two-thirds of patients reach recommended cholesterol levels. Elucidating the factors associated with lipid goal attainment represents an unmet clinical need. To address this knowledge gap, we conducted a real-world analysis of the lipid profiles of 11.252 patients from the Annals of the Italian Association of Medical Diabetologists (AMD) database from 2005 to 2019. We used a Logic Learning Machine (LLM) to extract and classify the most relevant variables predicting the achievement of a low-density lipoprotein cholesterol (LDL-C) value lower than 100 mg/dL (2.60 mmol/L) within two years of the start of lipid-lowering therapy. Our analysis showed that 61.4% of the patients achieved the treatment goal. The LLM model demonstrated good predictive performance, with a precision of 0.78, accuracy of 0.69, recall of 0.70, F1 Score of 0.74, and ROC-AUC of 0.79. The most significant predictors of achieving the treatment goal were LDL-C values at the start of lipid-lowering therapy and their reduction after six months. Other predictors of a greater likelihood of reaching the target included high-density lipoprotein cholesterol, albuminuria, and body mass index at baseline, as well as younger age, male sex, more follow-up visits, no therapy discontinuation, higher Q-score, lower blood glucose and HbA1c levels, and the use of anti-hypertensive medication. At baseline, for each LDL-C range analysed, the LLM model also provided the minimum reduction that needs to be achieved by the next six-month visit to increase the likelihood of reaching the therapeutic goal within two years. These findings could serve as a useful tool to inform therapeutic decisions and to encourage further in-depth analysis and testing.

Published
2023
Full Text
View/download PDF

16. The burden of obesity in type 1 diabetic subjects: a sex-specific analysis from the AMD Annals Initiative

Author

Annalisa Giandalia, Giuseppina Tiziana Russo, Patrizia Ruggeri, Annalisa Giancaterini, Elisabetta Brun, Mariarosaria Cristofaro, Anna Bogazzi, Maria Chiara Rossi, Giuseppe Lucisano, Alberto Rocca, Valeria Manicardi, Paolo Di Bartolo, Graziano Di Cianni, Chiara Giuliani, and Angela Napoli

Subjects
Endocrinology, Endocrinology, Diabetes and Metabolism, Biochemistry (medical), Clinical Biochemistry, Biochemistry
Abstract

Objective Obesity is a growing emergency also in type 1 diabetes (T1D). Sex-differences in obesity prevalence and its clinical consequences in adult T1D subjects have been poorly investigated. The aim of this study was to investigate the prevalence of obesity and severe obesity, clinical correlates and potential sex-differences in a large cohort of T1D subjects, participating to the AMD Annals Initiative in Italy. Research design and methods The prevalence of obesity (BMI ≥30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2) according to sex and age, as well as obesity-associated clinical variables, long-term diabetes complications, pharmacological treatment, process indicators and outcomes, and overall quality of care (score Q) were evaluated in 37,436 T1D subjects (45.3% women) attending 282 Italian diabetes clinics during 2019. Results Overall, the prevalence of obesity was similar in the two gender (13.0% in men and 13.9% in women; mean age 50 years), and it increased with age, affecting 1 out of 6 subjects aged >65 years. Only severe obesity (BMI >35 Kg/m2) was more prevalent among women, who showed a 45% higher risk of severe obesity, compared with men at multivariate analysis. CVD risk factors (lipid profile, glucose and blood pressure control), and the overall quality of diabetes care were worse in obese subjects, with no major sex-related differences. Also, micro- and macrovascular complications were more frequent among obese than non-obese T1D men and women. Conclusions Obesity is a frequent finding in T1D adult subjects, and it is associated with a higher burden of CVD risk factors, micro- and macrovascular complications, and a lower quality of care, with no major sex-differences. T1D women are at higher risk of severe obesity.

Published
2023

22. Inference in mixed causal and noncausal models with generalized Student’s t-distributions

Author

Francesco Giancaterini, Alain Hecq, RS: GSBE other - not theme-related research, QE Econometrics, RS: FSE DACS Mathematics Centre Maastricht, RS: GSBE Theme Learning and Work, and RS: GSBE Theme Data-Driven Decision-Making

Subjects
Statistics and Probability, Economics and Econometrics, robust inference, Single Equation Models, Single Variables: Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, MLE, Noncausal models, generalized Student's t-distribution, Statistics, Probability and Uncertainty, c22 - "Single Equation Models, Dynamic Treatment Effect Models"
Abstract

The properties of Maximum Likelihood estimator in mixed causal and noncausal models with a generalized Student’s t error process are reviewed. Several known existing methods are typically not applicable in the heavy-tailed framework. To this end, a new approach to make inference on causal and noncausal parameters in finite sample sizes is proposed. It exploits the empirical variance of the generalized Student’s t, without the existence of population variance. Monte Carlo simulations show a good performance of the new variance construction for fat tail series. Finally, different existing approaches are compared using three empirical applications: the variation of daily COVID-19 deaths in Belgium, the monthly wheat prices, and the monthly inflation rate in Brazil.

Published
2022

25. Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists (Preprint)

Author

Nicoletta Musacchio, Annalisa Giancaterini, Giacomo Guaita, Alessandro Ozzello, Maria A Pellegrini, Paola Ponzani, Giuseppina T Russo, Rita Zilich, and Alberto de Micheli

Abstract

UNSTRUCTURED Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are not limited anymore to a descriptive analysis of the data, as we can obtain greater value by identifying and predicting patterns resulting from inductive reasoning. Machine learning software programs that disclose the reasoning behind a prediction allow for “what-if” models by which it is possible to understand if and how, by changing certain factors, one may improve the outcomes, thereby identifying the optimal behavior. Currently, diabetes care is facing several challenges: the decreasing number of diabetologists, the increasing number of patients, the reduced time allowed for medical visits, the growing complexity of the disease both from the standpoints of clinical and patient care, the difficulty of achieving the relevant clinical targets, the growing burden of disease management for both the health care professional and the patient, and the health care accessibility and sustainability. In this context, new digital technologies and the use of artificial intelligence are certainly a great opportunity. Herein, we report the results of a careful analysis of the current literature and represent the vision of the Italian Association of Medical Diabetologists (AMD) on this controversial topic that, if well used, may be the key for a great scientific innovation. AMD believes that the use of artificial intelligence will enable the conversion of data (descriptive) into knowledge of the factors that “affect” the behavior and correlations (predictive), thereby identifying the key aspects that may establish an improvement of the expected results (prescriptive). Artificial intelligence can therefore become a tool of great technical support to help diabetologists become fully responsible of the individual patient, thereby assuring customized and precise medicine. This, in turn, will allow for comprehensive therapies to be built in accordance with the evidence criteria that should always be the ground for any therapeutic choice.

Published
2019

26. Artificial Intelligence and Big Data in Diabetes Care: A Position Statement of the Italian Association of Medical Diabetologists

Author

Nicoletta Musacchio, A. Ozzello, Giuseppina T. Russo, Annalisa Giancaterini, Alberto de Micheli, Paola Ponzani, Giacomo Guaita, Rita Zilich, and Maria A Pellegrini

Subjects
Big Data, Computer science, diabetes management, Big data, Clinical Decision-Making, 030209 endocrinology & metabolism, Health Informatics, Context (language use), lcsh:Computer applications to medicine. Medical informatics, clinical decision making, Association, Machine Learning, 03 medical and health sciences, Technical support, 0302 clinical medicine, Viewpoint, Diabetes management, Physicians, Health care, Diabetes Mellitus, Humans, 030212 general & internal medicine, Precision Medicine, Descriptive statistics, business.industry, lcsh:Public aspects of medicine, lcsh:RA1-1270, big data analytics, Inductive reasoning, artificial intelligence, Digital health, health care, Italy, Artificial intelligence, Big data analytics, Clinical decision making, Artificial Intelligence, lcsh:R858-859.7, business
Abstract

Since the last decade, most of our daily activities have become digital. Digital health takes into account the ever-increasing synergy between advanced medical technologies, innovation, and digital communication. Thanks to machine learning, we are not limited anymore to a descriptive analysis of the data, as we can obtain greater value by identifying and predicting patterns resulting from inductive reasoning. Machine learning software programs that disclose the reasoning behind a prediction allow for “what-if” models by which it is possible to understand if and how, by changing certain factors, one may improve the outcomes, thereby identifying the optimal behavior. Currently, diabetes care is facing several challenges: the decreasing number of diabetologists, the increasing number of patients, the reduced time allowed for medical visits, the growing complexity of the disease both from the standpoints of clinical and patient care, the difficulty of achieving the relevant clinical targets, the growing burden of disease management for both the health care professional and the patient, and the health care accessibility and sustainability. In this context, new digital technologies and the use of artificial intelligence are certainly a great opportunity. Herein, we report the results of a careful analysis of the current literature and represent the vision of the Italian Association of Medical Diabetologists (AMD) on this controversial topic that, if well used, may be the key for a great scientific innovation. AMD believes that the use of artificial intelligence will enable the conversion of data (descriptive) into knowledge of the factors that “affect” the behavior and correlations (predictive), thereby identifying the key aspects that may establish an improvement of the expected results (prescriptive). Artificial intelligence can therefore become a tool of great technical support to help diabetologists become fully responsible of the individual patient, thereby assuring customized and precise medicine. This, in turn, will allow for comprehensive therapies to be built in accordance with the evidence criteria that should always be the ground for any therapeutic choice.

Published
2019

30. Efficacy of self-monitoring blood glucose as a key component of a chronic care model versus usual care in type 2 diabetes patients treated with oral agents: results of a randomized trial

Author

Musacchio, N, Ciullo, I, Scardapane, M, Giancaterini, A, Pessina, L, Maino, S, Gaiofatto, R, Nicolucci, A, Rossi, Mc, Valentini, U, Cimino, A, Agosti, B, Zarra, E, Magri, A, Pellegrini, Ma, Pellarini, L, Sciangula, L, Nappi, F, Ciucci, A, Grassa, B, De Marco, R, Olivo, Es, Trevisan, R, Frosio, I, Morlini, C, Corsi, A, Dodesini, Ar, Grassi, G, Calvi, E, Capello, E, Gramaglia, E, Ramella, V, De Rossi, C, Mengozzi, G, Orsi, E, Lunati, Me, Palmieri, E, Resi, V, Grancini, V, Giarratana, L, Ragonese, M, Slongo, R, Scoponi, C, Tonolo, G, Amadori, G, Becciu, A, Canu, L, Cherchi, S, Paciotti, V, Alfidi, P, Babini, A, Ripani, R, Cantelli, R, Rossi, P, Di Cianni, G, Russo, L, Lemmi, P, Sannino, C, Marconi, S, Di Bartolo, P, Pellicano, F, Scolozzi, P, Annese, S, Lorizzo, F, Coppolino, A, Peditto, Gc, De Feo ME, Piscopo, G, Varriale, A, De Candia, L, Ceci, A, Elia, G, Falzone, G, Schembari, R, Citro, G, Di Mauro, M, D’Urso, C, Caruso, C, on behalf of Self-Care Study Group, Musacchio, N, Ciullo, I, Scardapane, M, Giancaterini, A, Pessina, L, Maino, S, Gaiofatto, R, Nicolucci, A, Rossi, M, Valentini, U, Cimino, A, Agosti, B, Zarra, E, Magri, A, Pellegrini, M, Pellarini, L, Sciangula, L, Nappi, F, Ciucci, A, Grassa, B, De Marco, R, Olivo, E, Trevisan, R, Frosio, I, Morlini, C, Corsi, A, Dodesini, A, Grassi, G, Calvi, E, Capello, E, Gramaglia, E, Ramella, V, De Rossi, C, Mengozzi, G, Orsi, E, Lunati, M, Palmieri, E, Resi, V, Grancini, V, Giarratana, L, Ragonese, M, Slongo, R, Scoponi, C, Tonolo, G, Amadori, G, Becciu, A, Canu, L, Cherchi, S, Paciotti, V, Alfidi, P, Babini, A, Ripani, R, Cantelli, R, Rossi, P, Di Cianni, G, Russo, L, Lemmi, P, Sannino, C, Marconi, S, Di Bartolo, P, Pellicano, F, Scolozzi, P, Annese, S, Lorizzo, F, Coppolino, A, Peditto, G, De Feo, M, Piscopo, G, Varriale, A, De Candia, L, Ceci, A, Elia, G, Falzone, G, Schembari, R, Citro, G, Di Mauro, M, D'Urso, C, and Caruso, C

Subjects
medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, oral antidiabetic agent, Type 2 diabetes, law.invention, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Randomized controlled trial, law, Diabetes mellitus, Internal medicine, Internal Medicine, medicine, hemoglobin A1c lipid, 030212 general & internal medicine, Intensive care medicine, Chronic care, business.industry, Mellitus, General Medicine, medicine.disease, Management, Oral agents, Usual care, Self-monitoring, Empowerment, business
Published
2018

31. Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes 11 Medical and Health Sciences 1103 Clinical Sciences

Author

Mirijello, Antonio, Viazzi, Francesca, Fioretto, Paola, Giorda, C. B., Ceriello, Antonio, Russo, Giuspina T., Guida, Pietro, Pontremoli, Roberto, De Cosmo, S., Cimino, Antonino, Fava, Danila, Meloncelli, Illidio, Nicolucci, Antonio, Pellegrini, Fabio, Rossi, Maria Chiara, Turco, Salvatore, Vespasiani, Giacomo, Graziano, G., Lucisano, G., Memmo, R., Pellicciotta, E., Paciotti, V., Pupillo, M., Armentano, G., Giovannini, C., Armentano, V., Laudato, M., Acquati, S., Ciardullo, A. V., Laffi, G., Felace, G., Taboga, C., Tortul, C., Santantonio, G., Suraci, C., Ghisoni, G., Raffa, M., Genovese, S., Lovagnini-Scher, C. A., Rampini, P., Rocca, A., Ruggeri, P., Tortato, E., Cotti, L., Cristofaro, M. R., Tagliaferri, M., Comoglio, M., Fornengo, R., Gentile, F. M., Gigante, Antonio, Mastinu, F., Di Benedetto, A., Pata, P., Arcangeli, A., Orsini, P., Acler, P., De Blasi, G., Cicioni, G., Pocciati, S., Marangoni, A., Nogara, A., Lanero, M., Bertero, M. G., Damassino, R., Bergonzini, C., Schumtz, L., Seksich, L., Pipitone, A., Boaretto, M., Manfroi, I., Parmesan, L., Conte, B., Soccol, F., Pagano, A., Papini, E., Rinaldi, R., Petrucci, L., Graziano, F., Chianelli, M., Silvagni, S., Rosco, M., Ansaldi, E., Malvicino, F., Battezzati, M., Maresca, P., Palenzona, C., Boemi, M., Rabini, R. A., Brandoni, G., Lanari, L., Gatti, C., Testa, I., Cherubini, V., Doveri, G., Pecorelli, L., Ciccarelli, A., Gallardini, M. B., Courthoud, R., Sara Bredy, S., Ricciardi, G. P., Vitalone, G., Setti, D., Contrini, P., Corsi, A., Ghigliotti, V., Oddone, G., Ponzani, P., Valbonesi, G., Mazzini, V., Di Berardino, P., Colleluori, P., Montani, V., Trosini, V., Velussi, M., Alfidi, P., Verdecchia, B., Baliva, L., Di Pietro, A., Franchi, G., Luce, R. P., Pianta, A., Ferrari, M., Balzano, S., Beltranello, G., Dal Fabbro, S., Aricò, C. N., Cervo, L., Zanon, R., Rossa, S., Di Pace, M. C., Ciavarella, A., Giangiulio, S., Grimaldi, M., Mustacchio, A., Fattor, B., Monauni, T., Cristini, M., Orion, G., Crazzolara, D., Amor, F., Eisath, J. E., Lintner, S., Garavelli, S., Calari, T., Marini, P., Sandri, O., Scala, M., Stroppa, C., Trentin, A., Carlin, R., Carli, B., Sandonà, M., Zortea, C., Bonet, L., Pradel, L., Reato, S., Buschini, M., Bonfiglioli, D., Mones, D., Beldì, F., Morea, A., Bondesan, L., Perbellini, S., Valentini, U., Agosti, B., Corsini, R., Girelli, A., Zarra, E., Rocca, L., Bergmann, M., Pradi, I., Unterkircher, S., Piok, M., Pichler, M., Trinchera, A., Palamà, G., Palma, P., Carboni, L., Murtas, M. G., Mudadu, T., Turco, M. P., Floris, M., Delogu, A., Farris, L., Songini, M., Piras, G., Seguro, R., Floris, R., Corona, G., Lai, M., Piras, E., Contini, P. P., Cocco, S., Pilosu, R. M., Sannia, M. C., Spanu, F., Busciantella Ricci, N., Cartechini, M. G., Agostinelli, G., Fiorelli, C., Nuzzi, A., Ballauri, C., Lesina, A., Romeo, F., Giudici, G., Maciejewska, E. G., Deroma, A., Paduano, M., Rossi, L., Vagnini, C., Dolci, M., Mori, M., Baccetti, F., Gregori, G., Straface, E., Pozzuoli, G., Barone, M., Stasio, G. B., Tondini, S., Borgoni, F., Grosso, J., Scarsellato, C., Sciulli, A., De Marco, F., Confortin, L., Marin, N., Lamonica, M., Gialdino, S., Borzì, V., Gatta, C., Rapisard, R., Strano, S., Calabrò, M., Puccio, L., Zolli, M., Coracina, A., Starnone, V., Del Buono, A., Terracciano, A. M., Monda, M. V., Castro, F., Guaglianone, A., Maccari, V., Corsi, L., Versari, G., Falivene, M. R., Boletto, N., Corsi, S., Marafetti, L., Vitacolonna, E., Capani, F., Caputo, L., Di Nisio, L., Simonetti, F., Boscolo Bariga, A., Ballarin, G., De Boni, S., Di Benedetto, S., Chiambretti, A. M., Di Vito, L., Pascuzzo, M. D., Urli, P., Rumi, P., Balzarini, B., Galli, P., Castellan, M., Giannetti, A., Russotti, C., De Blasi, A., Perna, A., Campanelli, C., Ranchelli, A., Biccheri, D., Dadi, G., Massa, L., Baldi, G. P., Sciacca, F., Costanzo, E., Spada, M., Paolini, G., Ziller, P., Portolan, F., Pasolini, G., Ghilardi, G., Fiorina, P., Grata, M. L., Capretti, L., Speroni, G., Fugazza, L., Massafra, C., Lovagnini Scher, A., Cimicchi, M. C., Percudani, C., Risolo, T., Saccò, P., Gidoni Guarnieri, G. L., Piccolo, D., Bravin, C., De Noni, E., Scarpel, M., Marcon, M., Giacon, F., Panebianco, G., Tadiotto, F., Da Tos, V., D'Ambrosio, M., Pellizzola, D., Zampini, M. A., Frezzati, E., Mari, E., Raminelli, E., Gaiti, D., Bosi, E. A., Chierici, G., Pilla, S., Copelli, M., Zanichelli, P., Bertelli, L., Caretta, P., Vezzani, V., Bodecchi, S., Longobucco, A., Di Lembo, S., Spotti, E., Carrai, E., Degli Innocenti, A., Manini, L., Persico, R., Rossi, C., Magro, G., Marelli, G., Vilei, V., Andrioli, M., Bellato, L., Fedeli, M., Merlini, A., Pinelli, G., Marin, G., Contin, M. L., Gallo, A., Parlato, P., Pecchielan, W., Jacovacci, J., Placentino, G., Richini, D., Molinari, S., Strazzeri, R., Fabbri, T., Di Bartolo, P., Garrapa, G., D'Incau, F., Lagomanzini, P., Conte, P., Todesco, F., Foglini, P., Pantanetti, P., Bedetta, C., Maricotti, R., Tomasi, F., Monesi, M., Graziani, R., Beretta, F., Penna, L., Guberti, A., Dazzi, D., Forte, E., Gasbarrone, A., Marrocco, T., Moschetta, R., Tuccinardi, F., De Meo, F., Coppola, A., Pirolozzi, P., Placitelli, E., Vallefuoco, R., Catone, B., Ceschia, S., Urban, M., Fabbri, F., Torresani, M., Crovetto, R., Battistini, M., Carosia, P., Viviani, G. L., Durante, A., Pais, F., Lilliu, V., Quieto, C., D'Ugo, E., Squadrone, M., Amenduni, T., Iovannisci, M. M., Della Penna, L., Potente, F., Delle Donne, T., Massa, C., Ulisse, M. A., De Berardinis, F., Guarnieri, I., Pace, S., Splendiani, M., Di Giuseppe, R., Brunato, B., Assaloni, R., Muraro, R., Loro, R., Bucciol, S., Lavacca, C., Rossi, M., Sabbatini, G., Quadri, F., Sambuco, L., Santacroce, C., Paola Caretta, D., Marino, C., Micheletti, A., Petrelli, A., Corda, A., Pisano, L., Guaita, G., Deias, C., Trevisan, G., Coletti, I., Iannarelli, R., De Luca, A., Minnucci, A., Antenucci, D., Di Florio, C., Angelicola, G., Bosco, A., Fresco, R., Di Marco, G., Ugolotti, D., Cadossi, T., Di Caro, P., Mazzocchetti, M., Buzzetti, R., Leto, G., Gnessi, C., Cipolloni, L., Foffi, C., Moretti, C., Venditti, C., Meniconi, R., Bertoli, S., Cosimi, S., Di Cianni, G., Turco, A., Richini, A., Marconi, S., Sannino, C., Lemmi, P., Giuntoli, S., Manfrè, N., Giannini, F., Di Carlo, A., Casadidio, I., Melandri, P., Maolo, G., Polenta, B., Piccinini, N., Vincenti, C., Pastore, N., Mega, P., Magurano, E., Cananiello, A., Francescutto, C. A., Brussa Toi, E., Gaspardo, G., Angeli, L., Ronchese, L., Sciangula, L., Ciucci, A., Contartese, A., Banfi, E., Castelli, E., Tatti, P., Bloise, D., Di Mauro, P., Masselli, L., Lo Presti, A., Scarpitta, A. M., Gambina, F., Venezia, A., Morea, R., Lagonigro, G., Copeta, G., Iannucci, V., Milano, V., Trupo, M., Lochmann, A., Marchetto, P. E., Incelli, G., De Paola, G., Steiger, M. M., Gamper, M. A., Breitenberger, S., Holzner, M., Frischmann, J., Lambiase, C., Di Vece, T., D'Aniello, M., Fezza, M., Giordano, C., Leo, F., Saitta, G., Cucinotta, D., Di Vieste, G., Pintaudi, B., Mancuso, T., Musacchio, N., Giancaterini, A., Pessina, L., Salis, G., Schivalocchi, F., Testori, G., Cerutti, N., Morpugo, P. S., Cavaletto, M. L., Bonino, G., Morreale, F., Mariani, G., Ragonesi, P. D., Bollati, P., Colapinto, P., Falqui, L., Bortolato, L., Cosma, A., Pistolato, P., Centenaro, B., Ceccato, A., Campobasso, G., Zaurino, F., Mazzotta, G., Manti, R., Da Ros, R., Carlucci, S., Narduzzi, L., Bortolotto, D., D'Acunto, L., Stanic, L., Volpi, A., Cospite, A. M., Manicardi, V., Michelini, M., Finardi, L., Borghi, F., Manicardi, E., Lombardi, S., Tommasi, C., Iaccarino, M., Cozza, S., Binotto, M., Marini, F., Mecenero, I., Massignani, S., Stecco, P., Urbani, E., Massariol, W., Parolin, R., Gatti, A., Bonavita, M., Creso, E., Giannettino, R., Gobbo, M., Turco, S., Iovine, C., Riccardi, G., Iazzetta, N., Giannattasio, C., Egione, O., Galdieri, S., Velotti, A., Azzolina, A., Annicelli, G., Sorrentino, T., Gaeta, I., Zenari, L., Bertolini, L., Sorgato, C., Grippaldi, F., Stroppiana, M., Popolizio, R., Carbone, N., Grasso, S., Abate, S., Gaggero, G. C., Strazzabosco, M., Brun, E., Carlesi, G. P., Garrone, S., Cicalò, A. M., Clausi, C., Cau, R., Manconi, A., Carboni, A., Angius, M. F., Pinna, A. A., Caria, S., Filigheddu, G. D., Tonolo, G., Carta, I., Calebich, S., Burlotti, C., Saglietti, G., Schellino, A., Madau, G., Cossu, M., Mulas, F., Zoccheddu, S., Balsanelli, M., Fetonti, M., Rotolo, A., Sambo, P., Secchi, E., Angotzi, M. A., Loddoni, S., Brundu, I., Careddu, F., Becciu, A., Gabriella Piras, G., Novara, F., Cipro, F., Torchio, G., Palumbo, P., Bianchi, A., Colucci, G., La Motta, G., Tiengo, A., Avogaro, A., Bruttomesso, D., Crepaldi, C., Fadini, G., Guarnieri, G., Lavagnini, M. T., Maran, A., Vedovato, M., De Kreutzenberg, V., Fedele, D., Lapolla, A., Sartore, G., Bax, G., Cardone, C., Dalfrà, M. G., Masin, M., Toniato, R., Piarulli, Francesco, Mattina, G., Fulantelli, M. A., Gioia, D., Conti, M., Ridola, G., D'Agati, F., Grossi, G., Zavaroni, I., Dei Cas, A., Franzini, L., Usberti, E., Antonimi, M., Anelli, N., Poli, R., Ridolfi, V., Michela, M., Haddoub, S., Prampolini, G., Muoio, A., Filippi, D., Bucci, F., Tardio, S. M., Calderini, M. C., Magotti, M. G., Quarantelli, C., Vernazza, M. A., Carolfi, A., Saracca, R., Picchio, E., Del Sindaco, P., Spalluto, A., Maggiulli, L., Torreggiani, V., Rastelletti, S., Ugolini, C., Pucci, N., Magi, S., Muratori, S., La Penna, G., Consoli, A., Galeone, F., Magiar, A. V., Gherardini, V., Moretti, L., Bientinesi, M., Landi, L., Bernardi, A., Del Prato, S., Miccoli, R., Bianchi, C., Penno, G., Venditti, F., Anichini, R., De Bellis, A., Bruschi, T., Butelli, L., Gioffredi, M., Gori, R., Picciafuochi, R., Malagoli, R., Bernini, A., Gelisio, R., Zanon, M., Del Bianco, A., Bamiston, A., Signorato, M., Citro, G., Calabrese, M., Ianni, L., Lorenzetti, M., Marsocci, A., Guizzotti, S., Memoli, G., Cabasino, F., Farci, F., Atzori, A., Sanna, A., Ghiani, M., Siotto, I., Sedda, M., Manis, A., Loddo, C., Loddo, I., Seguro, P., Cuomo, A., Orlando, L., Olanda, G. B., Pucci, A., Massenzo, M., Sardu, C., Perrone, G., Corazziere, F., La Puzza, I., Tripodi, P. F., Riggio, S., Giampaolo, A., Mannino, D., Aleandri, A. R., Guidi, M. V., Battisti, B., Faraglia, M. R., Lilli, V., Leotta, S., Visalli, N., Gagliardi, A., Fontana, L., Altomare, M., Carletti, S., Abbruzzese, S., Chiaramonte, F., Giordano, R., Rossini, M., Migneco, G., Cappelloni, D., Urbani, A., Piergiovanni, F., Simonetta, A., Massimiani, F., Bulzomì, R., Giuliano, M., Pennafina, M. G., Di Perna, P., D'Accinni, M. P., Paolucci, D., D'Ubaldi, A., D'Angelo, M. T., Masaro, G., Pietrantoni, M., Fratini, M., La Rosa, R., Poggi, M., Piccirilli, F., Pisano, R., Saponara, C., Conforti, I., Penza, A., Scalpone, R., Lo Pinto, S., Iacovella, L., Caccamo, C., Sposito, S., Teodonio, C., Restuccia, M. G., Mirto, G., Girardello, R., Gennaro, R., De Moliner, L., Bettini, E., Mattuzzi, A., Speese, K., Frisinghelli, F., Locatelli, F., Nicoletti, M., Trojan, N., Centis, R., L Volsi, P., Levis, E., Zanette, G., Comba, G., Ballatore, L., Cattaneo, A., Aglialoro, A., Guido, R., Patrone, M., Zecchini, M., Clementi, L., Galetta, M., Marconi, V., Bordin, P., Perale, L., Vinci, C., Sira Zanon, M., Geretto, L., Toffolo, C., Furlan, M. G., Mazzanti, G., Vinci, M., Sica, V., Armeni, M., Derai, R., Ennas, O., Mamusa, S., Pisano, M. A., Carreras, L., Rauseo, A., Cervone, S., Leggieri, A., Pontonio, M., Sturaro, R., Quattrocchi, F., Molinaro, M., Trasatti, M., Ferretti, B., Labarile, G., Baule, G. M., Gentilini, A., Spanu, M. A., Fancellu, A., Bianco, P., Lione, L., Massazza, G., Bocchio, G., Bosco, E., Monachesi, M., Carta, G., Boschetti, M., Ceresola, E., Venier, E., Calcaterra, F., Cataldi, F., Miola, M., Manfrini, S., Lai, A., Locci, B., Putzu, D., Tanganelli, I., Leonini, M., Egger, K., Marchiotto, W., Vincis, L., Orlandini, V., Pilloni, C., Farci, R., Pelligra, I., Renier, G., Mameli, M., Pala, A., Devigus, E., Fumagalli, I., Lalli, C., Leandri, M., Agliani, M., De Pascalis, L., Malci, F., De Ciocchis, A., Diodati, M. B., Macerola, B., Davì, S., Caccavale, A., Brocato, L., Pognant Gros, M., Borla, S., Lattanzi, E., Piersanti, C., Piersanti, A., Spinelli, I., Tuzzoli, L., Tulini, V., Quaranta, G., Iorio, V., Tirabovi, M., De Terlizi, Candia, Massarelli, M. G., Venturi, S., Travaglini, A., Draghi, P., Pomante, P., Richiardi, L., Clerico, A., Bruno, A., Cavallo Perin, P., Ghigo, E., Porta, M., Scuntero, P., Arcari, R., Bertaina, S., Bo, S., Broglio, F., Bruno, G., Degiovanni, M., Fornengo, P., Grassi, G., Inglese, V., Maccario, M., Maghenzani, G., Marena, S., Martina, V., Passera, P., Ruiu, G., Tagliabue, M., Zanone, M., Monge, M., Boffano, G. M., Macrì, K., Maio, P., Ozzello, A., Pergolizzi, E., Gaia, D., Gennari, P., Micali, G., Rossetto, E., Dalmazzo, C., Oreglia, M., Stefani, T., Dossena, C., Paglia, P., Bosoni, S., Romanelli, T., Inchiostro, S., Dauriz, M., Bossi, C. A., Meregalli, G., Balini, A., Berzi, D., Filippini, B., Crotto, G., Paccagnella, A., Orrasch, M., Sambataro, M., Citro, T., Kiwanuka, E., Bagolin, E., Almoto, B., Macchia, A., Branca, M. T., Filesi, M., Candido, R., Caroli, E., Manca, E., Petrucco, A., Tommasi, E., Jagodnik, G., Baskar, B., Daris, N., Dal Col, P., Pellegrini, M. A., Tonutti, L., Venturini, G., Andreani, M., Turchi, F., Fedrighelli, F., Martinelli, G., Rongioletti, R., Candidi, M., Pais, M., Moro, E., Cervellino, F., Sinisi, R., Zampino, A., Mingardi, R., Lora, L., Reitano, R., Stocchiero, C., Simoncini, M., Mesturino, C. A., Zen, F., Di Pietro, S., Scoponi, C., Tilaro, L., Pelliccioni, S., Slongo, R., Vita, E., Garofalo, A., Vitale, F., Campanella, B., Mastrilli, V., Borrelli, T., D'Avino, A., Perbellini, A., Mirijello, A, Viazzi, F, Fioretto, P, Giorda, C, Ceriello, A, Russo, G, Guida, P, Pontremoli, R, De Cosmo, S, Cimino, A, Fava, D, Meloncelli, I, Nicolucci, A, Pellegrini, F, Rossi, M, Turco, S, Vespasiani, G, Graziano, G, Lucisano, G, Memmo, R, Pellicciotta, E, Paciotti, V, Pupillo, M, Armentano, G, Giovannini, C, Armentano, V, Laudato, M, Acquati, S, Ciardullo, A, Laffi, G, Felace, G, Taboga, C, Tortul, C, Santantonio, G, Suraci, C, Ghisoni, G, Raffa, M, Genovese, S, Lovagnini-Scher, C, Rampini, P, Rocca, A, Ruggeri, P, Tortato, E, Cotti, L, Cristofaro, M, Tagliaferri, M, Comoglio, M, Fornengo, R, Gentile, F, Gigante, A, Mastinu, F, Di Benedetto, A, Pata, P, Arcangeli, A, Orsini, P, Acler, P, De Blasi, G, Cicioni, G, Pocciati, S, Marangoni, A, Nogara, A, Lanero, M, Bertero, M, Damassino, R, Bergonzini, C, Schumtz, L, Seksich, L, Pipitone, A, Boaretto, M, Manfroi, I, Parmesan, L, Conte, B, Soccol, F, Pagano, A, Papini, E, Rinaldi, R, Petrucci, L, Graziano, F, Chianelli, M, Silvagni, S, Rosco, M, Ansaldi, E, Malvicino, F, Battezzati, M, Maresca, P, Palenzona, C, Boemi, M, Rabini, R, Brandoni, G, Lanari, L, Gatti, C, Testa, I, Cherubini, V, Doveri, G, Pecorelli, L, Ciccarelli, A, Gallardini, M, Courthoud, R, Sara Bredy, S, Ricciardi, G, Vitalone, G, Setti, D, Contrini, P, Corsi, A, Ghigliotti, V, Oddone, G, Ponzani, P, Valbonesi, G, Mazzini, V, Di Berardino, P, Colleluori, P, Montani, V, Trosini, V, Velussi, M, Alfidi, P, Verdecchia, B, Baliva, L, Di Pietro, A, Franchi, G, Luce, R, Pianta, A, Ferrari, M, Balzano, S, Beltranello, G, Dal Fabbro, S, Arico, C, Cervo, L, Zanon, R, Rossa, S, Di Pace, M, Ciavarella, A, Giangiulio, S, Grimaldi, M, Mustacchio, A, Fattor, B, Monauni, T, Cristini, M, Orion, G, Crazzolara, D, Amor, F, Eisath, J, Lintner, S, Garavelli, S, Calari, T, Marini, P, Sandri, O, Scala, M, Stroppa, C, Trentin, A, Carlin, R, Carli, B, Sandona, M, Zortea, C, Bonet, L, Pradel, L, Reato, S, Buschini, M, Bonfiglioli, D, Mones, D, Beldi, F, Morea, A, Bondesan, L, Perbellini, S, Valentini, U, Agosti, B, Corsini, R, Girelli, A, Zarra, E, Rocca, L, Bergmann, M, Pradi, I, Unterkircher, S, Piok, M, Pichler, M, Trinchera, A, Palama, G, Palma, P, Carboni, L, Murtas, M, Mudadu, T, Turco, M, Floris, M, Delogu, A, Farris, L, Songini, M, Piras, G, Seguro, R, Floris, R, Corona, G, Lai, M, Piras, E, Contini, P, Cocco, S, Pilosu, R, Sannia, M, Spanu, F, Busciantella Ricci, N, Cartechini, M, Agostinelli, G, Fiorelli, C, Nuzzi, A, Ballauri, C, Lesina, A, Romeo, F, Giudici, G, Maciejewska, E, Deroma, A, Paduano, M, Rossi, L, Vagnini, C, Dolci, M, Mori, M, Baccetti, F, Gregori, G, Straface, E, Pozzuoli, G, Barone, M, Stasio, G, Tondini, S, Borgoni, F, Grosso, J, Scarsellato, C, Sciulli, A, De Marco, F, Confortin, L, Marin, N, Lamonica, M, Gialdino, S, Borzi, V, Gatta, C, Rapisard, R, Strano, S, Calabro, M, Puccio, L, Zolli, M, Coracina, A, Starnone, V, Del Buono, A, Terracciano, A, Monda, M, Castro, F, Guaglianone, A, Maccari, V, Corsi, L, Versari, G, Falivene, M, Boletto, N, Corsi, S, Marafetti, L, Vitacolonna, E, Capani, F, Caputo, L, Di Nisio, L, Simonetti, F, Boscolo Bariga, A, Ballarin, G, De Boni, S, Di Benedetto, S, Chiambretti, A, Di Vito, L, Pascuzzo, M, Urli, P, Rumi, P, Balzarini, B, Galli, P, Castellan, M, Giannetti, A, Russotti, C, De Blasi, A, Perna, A, Campanelli, C, Ranchelli, A, Biccheri, D, Dadi, G, Massa, L, Baldi, G, Sciacca, F, Costanzo, E, Spada, M, Paolini, G, Ziller, P, Portolan, F, Pasolini, G, Ghilardi, G, Fiorina, P, Grata, M, Capretti, L, Speroni, G, Fugazza, L, Massafra, C, Lovagnini Scher, A, Cimicchi, M, Percudani, C, Risolo, T, Sacco, P, Gidoni Guarnieri, G, Piccolo, D, Bravin, C, De Noni, E, Scarpel, M, Marcon, M, Giacon, F, Panebianco, G, Tadiotto, F, Da Tos, V, D'Ambrosio, M, Pellizzola, D, Zampini, M, Frezzati, E, Mari, E, Raminelli, E, Gaiti, D, Bosi, E, Chierici, G, Pilla, S, Copelli, M, Zanichelli, P, Bertelli, L, Caretta, P, Vezzani, V, Bodecchi, S, Longobucco, A, Di Lembo, S, Spotti, E, Carrai, E, Degli Innocenti, A, Manini, L, Persico, R, Rossi, C, Magro, G, Marelli, G, Vilei, V, Andrioli, M, Bellato, L, Fedeli, M, Merlini, A, Pinelli, G, Marin, G, Contin, M, Gallo, A, Parlato, P, Pecchielan, W, Jacovacci, J, Placentino, G, Richini, D, Molinari, S, Strazzeri, R, Fabbri, T, Di Bartolo, P, Garrapa, G, D'Incau, F, Lagomanzini, P, Conte, P, Todesco, F, Foglini, P, Pantanetti, P, Bedetta, C, Maricotti, R, Tomasi, F, Monesi, M, Graziani, R, Beretta, F, Penna, L, Guberti, A, Dazzi, D, Forte, E, Gasbarrone, A, Marrocco, T, Moschetta, R, Tuccinardi, F, De Meo, F, Coppola, A, Pirolozzi, P, Placitelli, E, Vallefuoco, R, Catone, B, Ceschia, S, Urban, M, Fabbri, F, Torresani, M, Crovetto, R, Battistini, M, Carosia, P, Viviani, G, Durante, A, Pais, F, Lilliu, V, Quieto, C, D'Ugo, E, Squadrone, M, Amenduni, T, Iovannisci, M, Della Penna, L, Potente, F, Delle Donne, T, Massa, C, Ulisse, M, De Berardinis, S, Guarnieri, I, Pace, S, Splendiani, M, Di Giuseppe, R, Brunato, B, Assaloni, R, Muraro, R, Loro, R, Bucciol, S, Lavacca, C, Sabbatini, G, Quadri, F, Sambuco, L, Santacroce, C, Paola Caretta, D, Marino, C, Micheletti, A, Petrelli, A, Corda, A, Pisano, L, Guaita, G, Deias, C, Trevisan, G, Coletti, I, Iannarelli, R, De Luca, A, Minnucci, A, Antenucci, D, Di Florio, C, Angelicola, G, Bosco, A, Fresco, R, Di Marco, G, Ugolotti, D, Cadossi, T, Di Caro, P, Mazzocchetti, M, Buzzetti, R, Leto, G, Gnessi, C, Cipolloni, L, Foffi, C, Moretti, C, Venditti, C, Meniconi, R, Bertoli, S, Cosimi, S, Di Cianni, G, Turco, A, Richini, A, Marconi, S, Sannino, C, Lemmi, P, Giuntoli, S, Manfre, N, Giannini, F, Di Carlo, A, Casadidio, I, Melandri, P, Maolo, G, Polenta, B, Piccinini, N, Vincenti, C, Pastore, N, Mega, P, Magurano, E, Cananiello, A, Francescutto, C, Brussa Toi, E, Gaspardo, G, Angeli, L, Ronchese, L, Sciangula, L, Ciucci, A, Contartese, A, Banfi, E, Castelli, E, Tatti, P, Bloise, D, Di Mauro, P, Masselli, L, Lo Presti, A, Scarpitta, A, Gambina, F, Venezia, A, Morea, R, Lagonigro, G, Copeta, G, Iannucci, V, Milano, V, Trupo, M, Lochmann, A, Marchetto, P, Incelli, G, De Paola, G, Steiger, M, Gamper, M, Breitenberger, S, Holzner, M, Frischmann, J, Lambiase, C, Di Vece, T, D'Aniello, M, Fezza, M, Giordano, C, Leo, F, Saitta, G, Cucinotta, D, Di Vieste, G, Pintaudi, B, Mancuso, T, Musacchio, N, Giancaterini, A, Pessina, L, Salis, G, Schivalocchi, F, Testori, G, Cerutti, N, Morpugo, P, Cavaletto, M, Bonino, G, Morreale, F, Mariani, G, Ragonesi, P, Bollati, P, Colapinto, P, Falqui, L, Bortolato, L, Cosma, A, Pistolato, P, Centenaro, B, Ceccato, A, Campobasso, G, Zaurino, F, Mazzotta, G, Manti, R, Da Ros, R, Carlucci, S, Narduzzi, L, Bortolotto, D, D'Acunto, L, Stanic, L, Volpi, A, Cospite, A, Manicardi, V, Michelini, M, Finardi, L, Borghi, F, Manicardi, E, Lombardi, S, Tommasi, C, Iaccarino, M, Cozza, S, Binotto, M, Marini, F, Mecenero, I, Massignani, S, Stecco, P, Urbani, E, Massariol, W, Parolin, R, Gatti, A, Bonavita, M, Creso, E, Giannettino, R, Gobbo, M, Iovine, C, Riccardi, G, Iazzetta, N, Giannattasio, C, Egione, O, Galdieri, S, Velotti, A, Azzolina, A, Annicelli, G, Sorrentino, T, Gaeta, I, Zenari, L, Bertolini, L, Sorgato, C, Grippaldi, F, Stroppiana, M, Popolizio, R, Carbone, N, Grasso, S, Abate, S, Gaggero, G, Strazzabosco, M, Brun, E, Carlesi, G, Garrone, S, Cicalo, A, Clausi, C, Cau, R, Manconi, A, Carboni, A, Angius, M, Pinna, A, Caria, S, Filigheddu, G, Tonolo, G, Carta, I, Calebich, S, Burlotti, C, Saglietti, G, Schellino, A, Madau, G, Cossu, M, Mulas, F, Zoccheddu, S, Balsanelli, M, Fetonti, M, Rotolo, A, Sambo, P, Secchi, E, Angotzi, M, Loddoni, S, Brundu, I, Careddu, F, Becciu, A, Gabriella Piras, G, Novara, F, Cipro, F, Torchio, G, Palumbo, P, Bianchi, A, Colucci, G, La Motta, G, Tiengo, A, Avogaro, A, Bruttomesso, D, Crepaldi, C, Fadini, G, Guarnieri, G, Lavagnini, M, Maran, A, Vedovato, M, De Kreutzenberg, V, Fedele, D, Lapolla, A, Sartore, G, Bax, G, Cardone, C, Dalfra, M, Masin, M, Toniato, R, Piarulli, F, Mattina, G, Fulantelli, M, Gioia, D, Conti, M, Ridola, G, D'Agati, F, Grossi, G, Zavaroni, I, Dei Cas, A, Franzini, L, Usberti, E, Antonimi, M, Anelli, N, Poli, R, Ridolfi, V, Michela, M, Haddoub, S, Prampolini, G, Muoio, A, Filippi, D, Bucci, F, Tardio, S, Calderini, M, Magotti, M, Quarantelli, C, Vernazza, M, Carolfi, A, Saracca, R, Picchio, E, Del Sindaco, P, Spalluto, A, Maggiulli, L, Torreggiani, V, Rastelletti, S, Ugolini, C, Pucci, N, Magi, S, Muratori, S, La Penna, G, Consoli, A, Galeone, F, Magiar, A, Gherardini, V, Moretti, L, Bientinesi, M, Landi, L, Bernardi, A, Del Prato, S, Miccoli, R, Bianchi, C, Penno, G, Venditti, F, Anichini, R, De Bellis, A, Bruschi, T, Butelli, L, Gioffredi, M, Gori, R, Picciafuochi, R, Malagoli, R, Bernini, A, Gelisio, R, Zanon, M, Del Bianco, A, Bamiston, A, Signorato, M, Citro, G, Calabrese, M, Ianni, L, Lorenzetti, M, Marsocci, A, Guizzotti, S, Memoli, G, Cabasino, F, Farci, F, Atzori, A, Sanna, A, Ghiani, M, Siotto, I, Sedda, M, Manis, A, Loddo, C, Loddo, I, Seguro, P, Cuomo, A, Orlando, L, Olanda, G, Pucci, A, Massenzo, M, Sardu, C, Perrone, G, Corazziere, F, La Puzza, I, Tripodi, P, Riggio, S, Giampaolo, A, Mannino, D, Aleandri, A, Guidi, M, Battisti, B, Faraglia, M, Lilli, V, Leotta, S, Visalli, N, Gagliardi, A, Fontana, L, Altomare, M, Carletti, S, Abbruzzese, S, Chiaramonte, F, Giordano, R, Rossini, M, Migneco, G, Cappelloni, D, Urbani, A, Piergiovanni, F, Simonetta, A, Massimiani, F, Bulzomi, R, Giuliano, M, Pennafina, M, Di Perna, P, D'Accinni, M, Paolucci, D, D'Ubaldi, A, D'Angelo, M, Masaro, G, Pietrantoni, M, Fratini, M, La Rosa, R, Poggi, M, Piccirilli, F, Pisano, R, Saponara, C, Conforti, I, Penza, A, Scalpone, R, Lo Pinto, S, Iacovella, L, Caccamo, C, Sposito, S, Teodonio, C, Restuccia, M, Mirto, G, Girardello, R, Gennaro, R, De Moliner, L, Bettini, E, Mattuzzi, A, Speese, K, Frisinghelli, F, Locatelli, F, Nicoletti, M, Trojan, N, Centis, R, L Volsi, P, Levis, E, Zanette, G, Comba, G, Ballatore, L, Cattaneo, A, Aglialoro, A, Guido, R, Patrone, M, Zecchini, M, Clementi, L, Galetta, M, Marconi, V, Bordin, P, Perale, L, Vinci, C, Sira Zanon, M, Geretto, L, Toffolo, C, Furlan, M, Mazzanti, G, Vinci, M, Sica, V, Armeni, M, Derai, R, Ennas, O, Mamusa, S, Pisano, M, Carreras, L, Rauseo, A, Cervone, S, Leggieri, A, Pontonio, M, Sturaro, R, Quattrocchi, F, Molinaro, M, Trasatti, M, Ferretti, B, Labarile, G, Baule, G, Gentilini, A, Spanu, M, Fancellu, A, Bianco, P, Lione, L, Massazza, G, Bocchio, G, Bosco, E, Monachesi, M, Carta, G, Boschetti, M, Ceresola, E, Venier, E, Calcaterra, F, Cataldi, F, Miola, M, Manfrini, S, Lai, A, Locci, B, Putzu, D, Tanganelli, I, Leonini, M, Egger, K, Marchiotto, W, Vincis, L, Orlandini, V, Pilloni, C, Farci, R, Pelligra, I, Renier, G, Mameli, M, Pala, A, Devigus, E, Fumagalli, I, Lalli, C, Leandri, M, Agliani, M, De Pascalis, L, Malci, F, De Ciocchis, A, Diodati, M, Macerola, B, Davi, S, Caccavale, A, Brocato, L, Pognant Gros, M, Borla, S, Lattanzi, E, Piersanti, C, Piersanti, A, Spinelli, I, Tuzzoli, L, Tulini, V, Quaranta, G, Iorio, V, Tirabovi, M, De Terlizi, C, Massarelli, M, Venturi, S, Travaglini, A, Draghi, P, Pomante, P, Richiardi, L, Clerico, A, Bruno, A, Cavallo Perin, P, Ghigo, E, Porta, M, Scuntero, P, Arcari, R, Bertaina, S, Bo, S, Broglio, F, Bruno, G, Degiovanni, M, Fornengo, P, Grassi, G, Inglese, V, Maccario, M, Maghenzani, G, Marena, S, Martina, V, Passera, P, Ruiu, G, Tagliabue, M, Zanone, M, Monge, M, Boffano, G, Macri, K, Maio, P, Ozzello, A, Pergolizzi, E, Gaia, D, Gennari, P, Micali, G, Rossetto, E, Dalmazzo, C, Oreglia, M, Stefani, T, Dossena, C, Paglia, P, Bosoni, S, Romanelli, T, Inchiostro, S, Dauriz, M, Bossi, C, Meregalli, G, Balini, A, Berzi, D, Filippini, B, Crotto, G, Paccagnella, A, Orrasch, M, Sambataro, M, Citro, T, Kiwanuka, E, Bagolin, E, Almoto, B, Macchia, A, Branca, M, Filesi, M, Candido, R, Caroli, E, Manca, E, Petrucco, A, Tommasi, E, Jagodnik, G, Baskar, B, Daris, N, Dal Col, P, Pellegrini, M, Tonutti, L, Venturini, G, Andreani, M, Turchi, F, Fedrighelli, F, Martinelli, G, Rongioletti, R, Candidi, M, Pais, M, Moro, E, Cervellino, F, Sinisi, R, Zampino, A, Mingardi, R, Lora, L, Reitano, R, Stocchiero, C, Simoncini, M, Mesturino, C, Zen, F, Di Pietro, S, Scoponi, C, Tilaro, L, Pelliccioni, S, Slongo, R, Vita, E, Garofalo, A, Vitale, F, Campanella, B, Mastrilli, V, Borrelli, T, D'Avino, A, and Perbellini, A

Subjects
Albuminuria, Diabetic kidney disease, GFR, Albuminuria, Diabetic kidney disease, GFR, Nephrology
Abstract

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage ≥3 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage ≥3 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage ≥3 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 ± 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage ≥3 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage ≥3 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening.

Published
2018

33. Bruising: A Neglected, Though Patient-Relevant Complication of Insulin Injections Coming to Light from a Real-Life Nationwide Survey.

Author

Gentile, Sandro, Guarino, Giuseppina, Della Corte, Teresa, Marino, Giampiero, Satta, Ersilia, Romano, Carmine, Alfrone, Carmelo, lmberti, Clelia, Strollo, Felice, AMD-OSDI Study Group, Armentano, Vincenzo, Cucco, Lia, De-Rosa, Nicoletta, Gentile, Luigi, Giancaterini, Annalisa, Grassi, Giorgio, Lalli, Carlo, Lo-Grasso, Giovanni, Sudano, Maurizio, and Tatti, Patrizio

Subjects
INSULIN, INJECTIONS, QUALITY of life, GLYCOSYLATED hemoglobin, PATIENT surveys
Abstract

Introduction: Despite the availability of sophisticated devices and suitable recommendations on how to best perform insulin injections, lipohypertrophy (LH) and bruising (BR) frequently occur as a consequence of improper injection technique. Aim: The purpose of this nationwide survey was to check literature-reported LH risk factors or consequences for any association with BR Method: This was a cross-sectional, observational, multicenter study based on the identification of skin lesions at all patient-reported insulin injection sites in 790 subjects with diabetes. General and injection habit-related elements were investigated as possible BR risk factors. Results: While confirming the close relationship existing between LH and a full series of factors including missed injection site rotation, needle reuse, long-standing insulin treatment, frequent hypoglycemic events (hypos), and great glycemic variability (GV), the observed data could find no such association with BR, which anyhow came with high HbA1c levels, missed injection site rotation, and long-standing insulin treatment. Conclusion: BR most likely depends on the patient's habit of pressing the injection pen hard onto the skin. Despite being worrisome and affecting quality of life, BR seems to represent a preliminary stage of LH but does not affect the rate of hypos and GV. Trial Registration: 207/19.09.2017 [ABSTRACT FROM AUTHOR]

Published
2021
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34. Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Author

Mirijello, Antonio, Viazzi, Francesca, Fioretto, Paola, Giorda, Carlo, Ceriello, Antonio, Russo, Giuspina T., Guida, Pietro, Pontremoli, Roberto, De Cosmo, Salvatore, Cimino, Antonino, Fava, Danila, Giorda, Carlo Bruno, Meloncelli, Illidio, Nicolucci, Antonio, Pellegrini, Fabio, Rossi, Maria Chiara, Turco, Salvatore, Vespasiani, Giacomo, Pellegrini, F., Graziano, G., Lucisano, G., Memmo, R., Pellicciotta, E., Paciotti, V., Pupillo, M., Armentano, G., Giovannini, C., Armentano, V., Laudato, M., Turco, S., Acquati, S., Ciardullo, A. V., Laffi, G., Felace, G., Taboga, C., Tortul, C., Santantonio, G., Suraci, C., Ghisoni, G., Raffa, M., Genovese, S., Lovagnini-Scher, C. A., Rampini, P., Rocca, A., Ruggeri, P., Tortato, E., Cotti, L., Cristofaro, M. R., Tagliaferri, M., Comoglio, M., Fornengo, R., De Cosmo, S., Gentile, F. M., Gigante, A., Mastinu, F., Di Benedetto, A., Pata, P., Arcangeli, A., Orsini, P., Acler, P., De Blasi, G., Cicioni, G., Pocciati, S., Marangoni, A., Nogara, A., Lanero, M., Bertero, M. G., Damassino, R., Bergonzini, C., Schumtz, L., Seksich, L., Pipitone, A., Boaretto, M., Manfroi, I., Parmesan, L., Conte, B., Soccol, F., Pagano, A., Papini, E., Rinaldi, R., Petrucci, L., Graziano, F., Chianelli, M., Silvagni, S., Rosco, M., Ansaldi, E., Malvicino, F., Battezzati, M., Maresca, P., Palenzona, C., Boemi, M., Rabini, R. A., Brandoni, G., Lanari, L., Gatti, C., Testa, I., Cherubini, V., Doveri, G., Pecorelli, L., Ciccarelli, A., Gallardini, M. B., Courthoud, R., Sara Bredy, S., Ricciardi, G. P., Vitalone, G., Setti, D., Contrini, P., Corsi, A., Ghigliotti, V., Oddone, G., Ponzani, P., Valbonesi, G., Mazzini, V., Di Berardino, P., Colleluori, P., Montani, V., Trosini, V., Velussi, M., Alfidi, P., Verdecchia, B., Baliva, L., Di Pietro, A., Franchi, G., Luce, R. P., Pianta, A., Ferrari, M., Balzano, S., Beltranello, G., Dal Fabbro, S., Aricò, C. N., Cervo, L., Zanon, R., Rossa, S., Di Pace, M. C., Ciavarella, A., Giangiulio, S., Grimaldi, M., Mustacchio, A., Santacroce, G., Fattor, B., Monauni, T., Cristini, M., Orion, G., Crazzolara, D., Amor, F., Eisath, J. E., Lintner, S., Garavelli, S., Calari, T., Marini, P., Sandri, O., Scala, M., Stroppa, C., Trentin, A., Carlin, R., Carli, B., Sandonà, M., Zortea, C., Bonet, L., Pradel, L., Reato, S., Buschini, M., Bonfiglioli, D., Mones, D., Beldì, F., Morea, A., Bondesan, L., Perbellini, S., Cimino, A., Valentini, U., Agosti, B., Corsini, R., Girelli, A., Zarra, E., Rocca, L., Bergmann, M., Pradi, I., Unterkircher, S., Piok, M., Pichler, M., Trinchera, A., Palamà, G., Palma, P., Carboni, L., Murtas, M. G., Mudadu, T., Turco, M. P., Floris, M., Delogu, A., Farris, L., Songini, M., Piras, G., Seguro, R., Floris, R., Corona, G., Lai, M., Piras, E., Contini, P. P., Cocco, S., Pilosu, R. M., Sannia, M. C., Spanu, F., Busciantella Ricci, N., Cartechini, M. G., Agostinelli, G., Fiorelli, C., Nuzzi, A., Ballauri, C., Giorda, C. B., Lesina, A., Romeo, F., Giudici, G., Maciejewska, E. G., Deroma, A., Paduano, M., Rossi, L., Vagnini, C., Dolci, M., Mori, M., Baccetti, F., Gregori, G., Straface, E., Pozzuoli, G., Barone, M., Stasio, G. B., Tondini, S., Borgoni, F., Grosso, J., Scarsellato, C., Sciulli, A., De Marco, F., Confortin, L., Marin, N., Lamonica, M., Gialdino, S., Borzì, V., Gatta, C., Rapisard, R., Strano, S., Calabrò, M., Puccio, L., Zolli, M., Coracina, A., Starnone, V., Del Buono, A., Terracciano, A. M., Monda, M. V., Castro, F., Guaglianone, A., Maccari, V., Corsi, L., Versari, G., Falivene, M. R., Boletto, N., Corsi, S., Marafetti, L., Vitacolonna, E., Capani, F., Caputo, L., Di Nisio, L., Simonetti, F., Boscolo Bariga, A., Ballarin, G., De Boni, S., Di Benedetto, S., Chiambretti, A. M., Di Vito, L., Pascuzzo, M. D., Urli, P., Rumi, P., Balzarini, B., Galli, P., Castellan, M., Giannetti, A., Russotti, C., De Blasi, A., Perna, A., Campanelli, C., Ranchelli, A., Biccheri, D., Dadi, G., Massa, L., Baldi, G. P., Sciacca, F., Costanzo, E., Spada, M., Paolini, G., Ziller, P., Portolan, F., Pasolini, G., Ghilardi, G., Fiorina, P., Grata, M. L., Capretti, L., Speroni, G., Fugazza, L., Massafra, C., Lovagnini Scher, A., Cimicchi, M. C., Percudani, C., Risolo, T., Saccò, P., Gidoni Guarnieri, G. L., Piccolo, D., Bravin, C., De Noni, E., Scarpel, M., Marcon, M., Giacon, F., Panebianco, G., Tadiotto, F., Da Tos, V., D'Ambrosio, M., Pellizzola, D., Zampini, M. A., Frezzati, E., Mari, E., Raminelli, E., Gaiti, D., Bosi, E. A., Chierici, G., Pilla, S., Copelli, M., Zanichelli, P., Bertelli, L., Caretta, P., Vezzani, V., Bodecchi, S., Longobucco, A., Di Lembo, S., Spotti, E., Carrai, E., Degli Innocenti, A., Manini, L., Persico, R., Rossi, C., Magro, G., Marelli, G., Vilei, V., Andrioli, M., Bellato, L., Fedeli, M., Merlini, A., Pinelli, G., Marin, G., Contin, M. L., Gallo, A., Parlato, P., Pecchielan, W., Jacovacci, J., Placentino, G., Richini, D., Molinari, S., Strazzeri, R., Fabbri, T., Di Bartolo, P., Garrapa, G., D'Incau, F., Lagomanzini, P., Conte, P., Todesco, F., Foglini, P., Pantanetti, P., Bedetta, C., Maricotti, R., Tomasi, F., Monesi, M., Graziani, R., Beretta, F., Penna, L., Guberti, A., Dazzi, D., Forte, E., Gasbarrone, A., Marrocco, T., Moschetta, R., Tuccinardi, F., De Meo, F., Coppola, A., Pirolozzi, P., Placitelli, E., Vallefuoco, R., Catone, B., Ceschia, S., Urban, M., Fabbri, F., Torresani, M., Crovetto, R., Battistini, M., Carosia, P., Viviani, G. L., Durante, A., Pais, F., Lilliu, V., Quieto, C., D'Ugo, E., Squadrone, M., Amenduni, T., Iovannisci, M. M., Della Penna, L., Potente, F., Delle Donne, T., Massa, C., Ulisse, M. A., De Berardinis, S., Guarnieri, I., Pace, S., Splendiani, M., Di Giuseppe, R., Brunato, B., Assaloni, R., Muraro, R., Loro, R., Bucciol, S., Lavacca, C., Rossi, M., Sabbatini, G., Quadri, F., Sambuco, L., Santacroce, C., Paola Caretta, D., Marino, C., Micheletti, A., Petrelli, A., Corda, A., Pisano, L., Guaita, G., Deias, C., Trevisan, G., Coletti, I., Iannarelli, R., De Luca, A., Minnucci, A., Antenucci, D., Di Florio, C., Angelicola, G., Bosco, A., Fresco, R., Di Marco, G., Ugolotti, D., Cadossi, T., Di Caro, P., Mazzocchetti, M., Buzzetti, R., Leto, G., Gnessi, C., Cipolloni, L., Foffi, C., Moretti, C., Venditti, C., Meniconi, R., Bertoli, S., Cosimi, S., Di Cianni, G., Turco, A., Richini, A., Marconi, S., Sannino, C., Lemmi, P., Giuntoli, S., Manfrè, N., Giannini, F., Di Carlo, A., Casadidio, I., Melandri, P., Maolo, G., Polenta, B., Piccinini, N., Vincenti, C., Pastore, N., Mega, P., Magurano, E., Cananiello, A., Francescutto, C. A., Brussa Toi, E., Gaspardo, G., Angeli, L., Ronchese, L., Sciangula, L., Ciucci, A., Contartese, A., Banfi, E., Castelli, E., Tatti, P., Bloise, D., Di Mauro, P., Masselli, L., Lo Presti, A., Scarpitta, A. M., Gambina, F., Venezia, A., Morea, R., Lagonigro, G., Copeta, G., Iannucci, V., Milano, V., Trupo, M., Lochmann, A., Marchetto, P. E., Incelli, G., De Paola, G., Steiger, M. M., Gamper, M. A., Breitenberger, S., Holzner, M., Frischmann, J., Lambiase, C., Di Vece, T., D'Aniello, M., Fezza, M., Giordano, C., Leo, F., Saitta, G., Cucinotta, D., Di Vieste, G., Pintaudi, B., Mancuso, T., Musacchio, N., Giancaterini, A., Pessina, L., Salis, G., Schivalocchi, F., Testori, G., Rampini, P. A., Cerutti, N., Morpugo, P. S., Cavaletto, M. L., Bonino, G., Morreale, F., Mariani, G., Ragonesi, P. D., Bollati, P., Colapinto, P., Bosi, E., Falqui, L., Bortolato, L., Cosma, A., Pistolato, P., Centenaro, B., Ceccato, A., Campobasso, G., Zaurino, F., Mazzotta, G., Manti, R., Da Ros, R., Carlucci, S., Narduzzi, L., Bortolotto, D., D'Acunto, L., Stanic, L., Volpi, A., Cospite, A. M., Manicardi, V., Michelini, M., Finardi, L., Borghi, F., Manicardi, E., Lombardi, S., Tommasi, C., Iaccarino, M., Cozza, S., Binotto, M., Marini, F., Mecenero, I., Massignani, S., Stecco, P., Urbani, E., Massariol, W., Parolin, R., Gatti, A., Bonavita, M., Creso, E., Giannettino, R., Gobbo, M., Iovine, C., Turco, A. A., Riccardi, G., Iazzetta, N., Giannattasio, C., Egione, O., Galdieri, S., Velotti, A., Azzolina, A., Annicelli, G., Sorrentino, T., Gaeta, I., Zenari, L., Bertolini, L., Sorgato, C., Grippaldi, F., Stroppiana, M., Popolizio, R., Carbone, N., Grasso, S., Abate, S., Gaggero, G. C., Strazzabosco, M., Brun, E., Carlesi, G. P., Garrone, S., Cicalò, A. M., Clausi, C., Cau, R., Manconi, A., Carboni, A., Angius, M. F., Pinna, A. A., Caria, S., Filigheddu, G. D., Tonolo, G., Carta, I., Calebich, S., Burlotti, C., Saglietti, G., Schellino, A., Madau, G., Cossu, M., Mulas, F., Zoccheddu, S., Balsanelli, M., Fetonti, M., Rotolo, A., Sambo, P., Secchi, E., Angotzi, M. A., Loddoni, S., Brundu, I., Careddu, F., Becciu, A., Gabriella Piras, G., Novara, F., Cipro, F., Torchio, G., Palumbo, P., Bianchi, A., Colucci, G., La Motta, G., Tiengo, A., Avogaro, A., Bruttomesso, D., Crepaldi, C., Fadini, G., Guarnieri, G., Lavagnini, M. T., Maran, A., Vedovato, M., De Kreutzenberg, V., Fedele, D., Lapolla, A., Sartore, G., Bax, G., Cardone, C., Dalfrà, M. G., Masin, M., Toniato, R., Piarulli, Francesco, Mattina, G., Fulantelli, M. A., Gioia, D., Conti, M., Ridola, G., D'Agati, F., Grossi, G., De Berardinis, F., Zavaroni, I., Dei Cas, A., Franzini, L., Usberti, E., Antonimi, M., Anelli, N., Poli, R., Ridolfi, V., Michela, M., Haddoub, S., Prampolini, G., Muoio, A., Filippi, D., Bucci, F., Tardio, S. M., Calderini, M. C., Magotti, M. G., Quarantelli, C., Vernazza, M. A., Carolfi, A., Saracca, R., Picchio, E., Del Sindaco, P., Spalluto, A., Maggiulli, L., Torreggiani, V., Rastelletti, S., Ugolini, C., Pucci, N., Magi, S., Muratori, S., La Penna, G., Consoli, A., Galeone, F., Magiar, A. V., Gherardini, V., Moretti, L., Bientinesi, M., Landi, L., Bernardi, A., Del Prato, S., Miccoli, R., Bianchi, C., Penno, G., Venditti, F., Anichini, R., De Bellis, A., Bruschi, T., Butelli, L., Gioffredi, M., Gori, R., Picciafuochi, R., Malagoli, R., Bernini, A., Gelisio, R., Zanon, M., Del Bianco, A., Bamiston, A., Signorato, M., Citro, G., Calabrese, M., Ianni, L., Lorenzetti, M., Marsocci, A., Guizzotti, S., Memoli, G., Cabasino, F., Farci, F., Atzori, A., Sanna, A., Ghiani, M., Siotto, I., Sedda, M., Manis, A., Loddo, C., Loddo, I., Seguro, P., Cuomo, A., Orlando, L., Olanda, G. B., Pucci, A., Massenzo, M., Sardu, C., Perrone, G., Corazziere, F., La Puzza, I., Tripodi, P. F., Riggio, S., Giampaolo, A., Mannino, D., Aleandri, A. R., Guidi, M. V., Battisti, B., Faraglia, M. R., Lilli, V., Leotta, S., Visalli, N., Gagliardi, A., Fontana, L., Altomare, M., Carletti, S., Abbruzzese, S., Chiaramonte, F., Giordano, R., Rossini, M., Migneco, G., Cappelloni, D., Urbani, A., Piergiovanni, F., Fava, D., Simonetta, A., Massimiani, F., Bulzomì, R., Giuliano, M., Pennafina, M. G., Di Perna, P., D'Accinni, M. P., Paolucci, D., D'Ubaldi, A., D'Angelo, M. T., Masaro, G., Pietrantoni, M., Fratini, M., La Rosa, R., Poggi, M., Piccirilli, F., Pisano, R., Saponara, C., Conforti, I., Penza, A., Scalpone, R., Lo Pinto, S., Iacovella, L., Caccamo, C., Sposito, S., Teodonio, C., Restuccia, M. G., Mirto, G., Girardello, R., Gennaro, R., De Moliner, L., Bettini, E., Mattuzzi, A., Speese, K., Frisinghelli, F., Locatelli, F., Nicoletti, M., Trojan, N., Centis, R., L Volsi, P., Levis, E., Zanette, G., Comba, G., Ballatore, L., Cattaneo, A., Aglialoro, A., Guido, R., Patrone, M., Zecchini, M., Vespasiani, G., Meloncelli, I., Clementi, L., Galetta, M., Marconi, V., Bordin, P., Perale, L., Vinci, C., Sira Zanon, M., Geretto, L., Toffolo, C., Furlan, M. G., Mazzanti, G., Vinci, M., Sica, V., Armeni, M., Derai, R., Ennas, O., Mamusa, S., Pisano, M. A., Carreras, L., Rauseo, A., Cervone, S., Leggieri, A., Pontonio, M., Sturaro, R., Quattrocchi, F., Molinaro, M., Trasatti, M., Ferretti, B., Labarile, G., Baule, G. M., Gentilini, A., Spanu, M. A., Fancellu, A., Bianco, P., Lione, L., Massazza, G., Bocchio, G., Bosco, E., Monachesi, M., Carta, G., Boschetti, M., Ceresola, E., Venier, E., Calcaterra, F., Cataldi, F., Miola, M., Manfrini, S., Lai, A., Locci, B., Putzu, D., Tanganelli, I., Leonini, M., Egger, K., Marchiotto, W., Vincis, L., Orlandini, V., Pilloni, C., Farci, R., Pelligra, I., Renier, G., Mameli, M., Pala, A., Devigus, E., Fumagalli, I., Lalli, C., Leandri, M., Agliani, M., De Pascalis, L., Malci, F., De Ciocchis, A., Diodati, M. B., Macerola, B., Davì, S., Caccavale, A., Brocato, L., Pognant Gros, M., Borla, S., Lattanzi, E., Piersanti, C., Piersanti, A., Spinelli, I., Tuzzoli, L., Tulini, V., Quaranta, G., Iorio, V., Tirabovi, M., De Terlizi, Candia, Massarelli, M. G., Venturi, S., Travaglini, A., Draghi, P., Pomante, P., Richiardi, L., Clerico, A., Bruno, A., Cavallo Perin, P., Ghigo, E., Porta, M., Scuntero, P., Arcari, R., Bertaina, S., Bo, S., Broglio, F., Bruno, G., Degiovanni, M., Fornengo, P., Grassi, G., Inglese, V., Maccario, M., Maghenzani, G., Marena, S., Martina, V., Passera, P., Ruiu, G., Tagliabue, M., Zanone, M., Monge, M., Boffano, G. M., Macrì, K., Maio, P., Ozzello, A., Pergolizzi, E., Gaia, D., Gennari, P., Micali, G., Rossetto, E., Dalmazzo, C., Oreglia, M., Stefani, T., Dossena, C., Paglia, P., Bosoni, S., Romanelli, T., Inchiostro, S., Dauriz, M., Bossi, C. A., Meregalli, G., Balini, A., Berzi, D., Filippini, B., Crotto, G., Paccagnella, A., Orrasch, M., Sambataro, M., Citro, T., Kiwanuka, E., Bagolin, E., Almoto, B., Macchia, A., Branca, M. T., Filesi, M., Candido, R., Caroli, E., Manca, E., Petrucco, A., Tommasi, E., Jagodnik, G., Baskar, B., Daris, N., Dal Col, P., Pellegrini, M. A., Tonutti, L., Venturini, G., Andreani, M., Turchi, F., Fedrighelli, F., Martinelli, G., Rongioletti, R., Candidi, M., Pais, M., Moro, E., Cervellino, F., Sinisi, R., Zampino, A., Mingardi, R., Lora, L., Reitano, R., Stocchiero, C., Simoncini, M., Mesturino, C. A., Zen, F., Di Pietro, S., Scoponi, C., Tilaro, L., Pelliccioni, S., Slongo, R., Vita, E., Garofalo, A., Vitale, F., Campanella, B., Mastrilli, V., Borrelli, T., D'Avino, A., Perbellini, A., Mirijello, Antonio, Viazzi, Francesca, Fioretto, Paola, Giorda, Carlo, Ceriello, Antonio, Russo, Giuspina T, Guida, Pietro, Pontremoli, Roberto, and De Cosmo, Salvatore, Giordano, Carla

Subjects
Adult, Male, Nephrology, medicine.medical_specialty, endocrine system diseases, Renal function, 030209 endocrinology & metabolism, 030204 cardiovascular system & hematology, lcsh:RC870-923, Kidney, urologic and male genital diseases, GFR, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Diabetes mellitus, medicine, Humans, Albuminuria, Diabetic kidney disease, Type 1 diabetes, urogenital system, business.industry, Incidence (epidemiology), Middle Aged, lcsh:Diseases of the genitourinary system. Urology, medicine.disease, female genital diseases and pregnancy complications, Albuminuria, Diabetic kidney disease, GFR, Nephrology, Diabetes Mellitus, Type 1, medicine.anatomical_structure, Italy, Disease Progression, Female, medicine.symptom, business, Research Article, Follow-Up Studies, Glomerular Filtration Rate, Kidney disease
Abstract

Background Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage ≥3 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage ≥3 CKD in a large cohort of patients affected by T1DM. Methods A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage ≥3 CKD (eGFR 30% from baseline was evaluated. Results The mean estimated GFR was 98 ± 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions Albuminuria and eGFR reduction represent independent risk factors for incident stage ≥3 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening. Electronic supplementary material The online version of this article (10.1186/s12882-018-1136-6) contains supplementary material, which is available to authorized users.

Published
2018

37. Au and Pt Nanoparticles Effects on the Optical and Electrical Gas Sensing Properties of Sol–Gel-Based ZnO Thin-Film Sensors

Author

Carlo Cantalini, L. Giancaterini, Marco Sturaro, Umberto Anselmi-Tamburini, Michela Cittadini, Alessandro Martucci, Alessandro Resmini, and Massimo Guglielmi

Subjects
Materials science, Annealing (metallurgy), Scanning electron microscope, Analytical chemistry, Crystal structure, engineering.material, Catalysis, engineering, Noble metal, Crystallite, Electrical and Electronic Engineering, Thin film, Instrumentation, Sol-gel
Abstract

The optical and conductometric responses of sol-gel-based ZnO thin films with embedded 5% mol. Au or Pt nanoparticles (NPs) have been compared at different operating temperatures, to assess the effect of noble metal additions on to H 2 , CO and NO 2 gases sensors response. The scanning electron microscopy and X-ray diffraction techniques have been utilized for morphological characterization of the crystal structures of the films after annealing at 400°C for 30 min and the effect of Au and Pt NPs additions on crystallite growth is discussed. Au NPs additions is effective to enhance the optical response to H 2 and CO at 390 nm and in the 500-700-nm wavelength range at 300- °C temperature. No optical response to NO 2 gas, even at low concentrations has been measured in the optical mode. The catalytic action of Pt NPs additions powerfully improves both the optical to H 2 and CO at 390 nm, and the conductometric gas responses. Detection limits as low as 20-ppb NO 2 and 50-ppm H 2 , in line with the best performances reported to the best of our knowledge in literature for ZnO-based sensors, have been measured in the conduction mode. Response times have been also compared, highlighting the positive effects played by Pt additions.

Published
2015

38. Response to NO2 and other gases of resistive chemically exfoliated MoS2-based gas sensors

Author

M. Donarelli, L. Giancaterini, Carlo Cantalini, Michele Nardone, Francesco Perrozzi, Luca Ottaviano, Federico Bisti, and S. Prezioso

Subjects
Materials Chemistry2506 Metals and Alloys, X-ray photoelectron spectroscopy, Materials science, Annealing (metallurgy), Scanning electron microscope, Analytical chemistry, NO2 sensing, GAS SENSING, Coatings and Films, MOLYBDENITE, XPS, RAMAN, SEM, symbols.namesake, Electronic, Materials Chemistry, Optical and Magnetic Materials, Electrical and Electronic Engineering, Spectroscopy, Instrumentation, Resistive touchscreen, Few-layers MoS2, Doping, Metals and Alloys, Condensed Matter Physics, Resistive sensing, Surfaces, Coatings and Films, Electronic, Optical and Magnetic Materials, Surfaces, Raman spectroscopy, Scanning electron microscopy, 2506, Electrode, symbols
Abstract

We report on the fabrication, the morphological, structural, and chemical characterization, and the study of the electrical response to NO 2 and other gases of resistive type gas sensors based on liquid chemically exfoliated (in N-methyl pyrrolidone, NMP) MoS 2 flakes annealed in air either at 150 °C or at 250 °C. The active material has been analyzed by scanning electron microscopy (SEM), and micro Raman and X-ray core level photoemission spectroscopies. SEM shows that MoS 2 exfoliated flakes are interconnected between electrodes of the sensing device to form percolation paths. Raman spectroscopy of the flakes before annealing demonstrates that the flakes are constituted by crystalline MoS 2 , while, annealing at 250 °C, does not introduce a detectable bulk contamination in the expected form of MoO 3 . The sensor obtained by thermal annealing in air at 150 °C exhibits a peculiar p -type response under exposure to NO 2 . In line with core level spectroscopy evidences, this behavior is potentially ascribed to nitrogen substitutional doping of S vacancies in the MoS 2 surface (nitrogen atoms being likely provided by the intercalated NMP). Thermal annealing the MoS 2 flakes in air at 250 °C irreversibly sets an n -type behavior of the gas sensing device, with a NO 2 detection limit of 20 ppb. This behavior is assigned, in line with core level spectroscopy data, to a significant presence of S vacancies in the MoS 2 annealed flakes and to the surface co-existence of MoO 3 arising from the partial oxidation of the flakes surface. Both p- and n -type sensors have been demonstrated to be sensitive also to relative humidity. The n -type sensor shows good electrical response under H 2 exposure.

Published
2015

39. A simple all-solution approach to the synthesis of large ZnO nanorod networks

Author

L. Giancaterini, Alessandro Resmini, Daniele Bajoni, Umberto Anselmi-Tamburini, E. Rondanina, Carlo Cantalini, Ilenia G. Tredici, F. De Angelis, and Maddalena Patrini

Subjects
Fabrication, Materials science, Renewable Energy, Sustainability and the Environment, Electrode, Interdigitated electrode, Process (computing), General Materials Science, Nanotechnology, Nanorod, General Chemistry, Piezoelectricity, Environmentally friendly
Abstract

ZnO nanorods present great potential for application in optical, sensing and piezoelectric devices; thanks to their nanometric diameter and large surface area. In some of these applications a probing current must flow directly through the nanorods, requiring each nanorod to be directly connected to two electrodes. To attain this architecture a few solutions have been proposed in the past, mostly involving the use of complex and time-consuming procedures, but the large-scale production of such devices represents still a major challenge. We present here a new all-solution approach that allows the fabrication of extensive self-assembled, bi-dimensional networks of ZnO nanorods. Such networks can be easily produced on interdigitated electrodes with no need for any alignment, resulting directly in the formation of very robust devices. The entire process is fast, does not require any complex experimental apparatus and involves only the use of inexpensive and environmentally friendly chemical reagents. We demonstrate the potentiality of such networks in a gas sensing application, where these networks were able to detect NO2 at trace levels, at low temperatures, using UV-visible activation.

Published
2015

40. NO 2 Gas Response of WO 3 Nanofibers by Light and Thermal Activation

Author

L. Giancaterini, Carlo Cantalini, A. De Marcellis, Elia Palange, and S.M. Emamjomeh

Subjects
Metal oxide, Materials science, Nano fibers, business.industry, Analytical chemistry, Response time, General Medicine, Atmospheric temperature range, NO2, Light activation, Light source, Electrospun nanofibers, Nanofiber, WO3, Thermal, Light induced, Optoelectronics, business, Engineering(all), Blue light
Abstract

Aim of this paper is to compare the electrical responses to sub-ppm NO2 gas concentrations of WO3 electrospun nanofibers both activated by thermal (in the temperature range 25 °C - 150 °C) and/or light-radiating conditions (Red λ=670 nm, Green λ=550 nm, and Purple Blue λ=430 nm). Blue light resulted the most effective light source with respect to the others. Light illumination at room temperature improves the base line recovery and response time, whereas temperature enhances relative response, with a maximum at 75 °C. Light-radiating room temperature gas detection yields a satisfactory response despite the reduction of sensor gas sensitivity. Light induced electrical response mechanisms are presented and discussed.

Published
2015

41. High GADA titer increases the risk of insulin requirement in LADA patients: a 7-year follow-up (NIRAD study 7)

Author

Zampetti, S., Campagna, G., Tiberti, C., Songini, M., Arpi, Ml., De Simone, G., Cossu, E., Cocco, L., Osborn, J., Bosi, E., Giorgino, F., Spoletini, M., Buzzetti, R., NIRAD Study Group, Adda, G, Di Lembo, S, Aglialoro, A, Cattaneo, A, Scassi, V, Anichini, R, Arcangeli, A, Arpi, Ml, Bardini, Rg, Basciano, P, Bracaccia, M, Pistoni, S, Bracaglia, D, Borzı, V, Emanuele, V 2nd, Cannata, F, Capitano, G, Cignarelli, M, Piemontese, S, Capuano, G, Carro, S, Cazzalini, C, Cocco, L, Ciccarone, Am, Cicioni, G, Cossu, E, Sano, F, Cucinotta, D, Di Benedetto, A, De Mattia, G, Mollica, Mr, De Cosmo, S, Minenna, A, Dei Cas, A, De Simone, G, Di Berardino, P, Dotta, F, Contini, V, Franzetti, I, Frontoni, S, Gadaleta, G, Galeone, G, Magiar, Av, Garofano, Mr, Gentile, S, Guarino, G, Giansanti, R, Genovese, S, Giancaterini, A, Leotta, S, Gianni, E, Burrafato, S, Giordano, C, Gigante, A, Cicalo, A, Giorgino, F, Gnasso, A, Fiaschi, E, Grossi, G, Deverardinis, F, Ianni, L, Iovine, C, Lauro, R, Federici, M, Spallone, V, Lo Presti, A, Scarpetta, Am, Lunari, R, Manna, R, Margotta, A, Mantovani, E, Matteoli, Mc, Matteucci, E, Chiesi, F, Maran, A, Mascetti, P, Quintana, T, Mazzucca, P, Melga, P, Cordera, R, Meloncelli, I, Morano, S, Morviducci, L, Nannipieri, M, Parillo, M, Pacifico, A, Pascal, G, Papini, E, Graziano, F, Passaro, A, Pata, P, Pontiroli, Ae, Pozzilli, P, Cipolloni, L, Guglielmi, C, Puccio, L, Raffa, Lm, Richini, D, Romano, R, Rotella, C, Santantonio, G, Sbriglia, Ms, Songini, M, Cau, V, Scorsone, A, Taboga, C, Tatti, P, Turco, A, Trovati, M, Fiori, E, Vasta, M, Vitale, F, Zavaroni, D, Buzzetti, R, Bosi, E, Giaccari, A, Di Pietro, S, Suraci, C, Locatelli, M, Bazzigaluppi, E, Falorni, A, Tiberti, C, Capizzi, M, Marandola, L, and Petrone, A.

Subjects
Male, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Type 2 diabetes, Logistic regression, LADA, Settore MED/13 - Endocrinologia, Endocrinology, Insulin, Glutamate Decarboxylase, Medicine (all), Diabete di tipo 1, autoanticorpi, GADA, LADA, Titrimetry, General Medicine, Middle Aged, Diabetes and Metabolism, Titer, Female, Type 2, Type 1, Adult, Risk, medicine.medical_specialty, medicine.drug_class, autoanticorpi, Socio-culturale, GADA, Diabete di tipo 1, Internal medicine, Diabetes mellitus, Diabetes Mellitus, medicine, Humans, Hypoglycemic Agents, Aged, Autoantibodies, Case-Control Studies, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Follow-Up Studies, business.industry, Autoantibody, Case-control study, medicine.disease, Sulfonylurea, business
Abstract

ObjectiveThe aim of this study was to determine whether glutamic acid decarboxylase antibody (GADA) titer and other clinical parameters could define the risk of progression to insulin therapy in latent autoimmune diabetes in adults (LADA) patients during a 7-year follow-up.MethodsThis study involved 220 LADA and 430 type 2 diabetes subjects followed up for 7 years from the time of GADA screening to evaluate their progression toward insulin therapy. Kaplan–Meier curves and multivariate logistic regression analysis were performed to identify the markers capable of influencing this progression.ResultsDuring the follow-up, the drop out was 4% in both groups. A total of 119 (56.1%) out of 212 LADA patients required insulin during the 7 years of follow-up. The Kaplan–Meier plots showed that 74/104 (71.1%) of high GADA titer required insulin compared with 45/108 (41.6%) of low GADA titer and with 86/412 (20.9%) of type 2 diabetes (P2and IA-2ICand zinc transporter 8 (ZnT8) positivity were also shown as the markers of faster progression (PPPConclusionsHigh GADA titer, BMI ≤ 25, ZnT8 and IA-2ICpositivity and sulfonylurea treatment, in the first year from diagnosis, significantly increase the progression toward insulin requirement in LADA patients.

Published
2014

43. Inference in mixed causal and noncausal models with generalized Student’s t-distributions

Author

Giancaterini, Francesco and Hecq, Alain

Abstract

The properties of Maximum Likelihood estimator in mixed causal and noncausal models with a generalized Student’s terror process are reviewed. Several known existing methods are typically not applicable in the heavy-tailed framework. To this end, a new approach to make inference on causal and noncausal parameters in finite sample sizes is proposed. It exploits the empirical variance of the generalized Student’s t, without the existence of population variance. Monte Carlo simulations show a good performance of the new variance construction for fat tail series. Finally, different existing approaches are compared using three empirical applications: the variation of daily COVID-19 deaths in Belgium, the monthly wheat prices, and the monthly inflation rate in Brazil.

Published
2024
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44. A suitable palpation technique allows to identify skin lipohypertrophic lesions in insulin-treated people with diabetes

Author

Annalisa Giancaterini, Giuseppina Guarino, Felice Strollo, Sandro Gentile, and Piero Guida

Subjects
Injection, Pediatrics, medicine.medical_specialty, medicine.medical_treatment, 030209 endocrinology & metabolism, Bioinformatics, Palpation, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, medicine, Insulin, 030212 general & internal medicine, Major complication, Multidisciplinary, medicine.diagnostic_test, business.industry, Diabetes, Ultrasound, Methodology, Lipohypertrophy, Gold standard (test), medicine.disease, Lesions, business, Patient education
Abstract

Background Lipohypertrophy (LH) is a major complication of subcutaneous insulin treatment brought about by multiple overlapping injections and/or needle reuse. It is responsible for unacceptable glucose oscillations due to a high rate of hypoglycaemic episodes and rebound glucose spikes. Skin ultrasound scans (USS), the gold standard for its detection, is too expensive for screening purposes. Aims To define a structured method allowing health professionals (HPs) to identify LH lesions as inexpensively and correctly as possible. Methods Out of 129 insulin-treated people with diabetes identified by USS as having LH lesions, only 40 agreed to participate in the study (24 females, age 54 ± 15 years, daily insulin dosage 57 ± 12 IU). Each was blindly examined by four well trained and four non-trained HPs according to a standard method involving repeated well codified maneuvers. Results A specific training allowed inexperienced HPs to acquire high diagnostic accuracy in identifying LH lesions independent of site, size, shape, and even BMI. This kind of training also allowed to reach a 97 % consistency rate among HPs as compared to USS, while the lack of training was associated with a wide variability and inconsistency of identification results. Conclusions Diabetes teams should follow systematically the simple procedure reported in this paper for the diagnosis of LH and try to get it further implemented and progressively refined in large scale studies. This would have a major impact on patient education in terms of (1) correct injection technique and (2) ability to identify lesions early enough to prevent poor metabolic outcome.

Published
2016

45. Factors Hindering Correct Identification of Unapparent Lipohypertrophy

Author

Speese K, Gentile S, Strauss K, Guida P, G. Guarino, Ames Prj, Felice Strollo, and Giancaterini A

Subjects
Pediatrics, medicine.medical_specialty, Type 1 diabetes, Adrenal disorder, business.industry, Lipohypertrophy, 030209 endocrinology & metabolism, medicine.disease, Gestational diabetes, Lesion, Impaired glucose tolerance, 03 medical and health sciences, 0302 clinical medicine, Immunology, medicine, Glucose homeostasis, Hormone metabolism, 030212 general & internal medicine, medicine.symptom, business
Abstract

i. Introduction:A correct injection technique is essential to prevent lipohypertrophy (LH) in people with diabetes mellitus (DM) and related glucose oscillations. However, features associated with missed LH identification are mostly unknown. ii. Aim of the study: to find out how lesion features influence LH identification and to assess patients’ awareness of the problem. iii. Materials and Method: 60 patients with LH lesions (36 F, 24 M, 56 ± 13 years of age) treated with four insulin shots per day were enrolled. All were blindly examined by four non-trained (NT) and four well trained (WT) health professionals (HPs) and filled in a questionnaire concerning their own experience. iv. Results:WT HPs were better at identifying LH lesions (OR 10.52 [4.34-25.50], p

Published
2016

46. The influence of thermal and visible light activation modes on the NO2 response of WO3 nanofibers prepared by electrospinning

Author

S.M. Emamjomeh, L. Giancaterini, A. De Marcellis, Alessandro Resmini, Umberto Anselmi-Tamburini, Carlo Cantalini, and Elia Palange

Subjects
Materials Chemistry2506 Metals and Alloys, Materials science, Analytical chemistry, Nanofibers, 02 engineering and technology, 010402 general chemistry, Gas sensors, 01 natural sciences, Coatings and Films, chemistry.chemical_compound, Operating temperature, WO3, Materials Chemistry, medicine, Electronic, Optical and Magnetic Materials, Electrical and Electronic Engineering, Instrumentation, Room temperature, Visible light, Polyvinylpyrrolidone, business.industry, Metals and Alloys, 021001 nanoscience & nanotechnology, Microstructure, Condensed Matter Physics, Electronic, Optical and Magnetic Materials, 2506, Surfaces, Coatings and Films, Electrospinning, 0104 chemical sciences, Surfaces, Wavelength, chemistry, Nanofiber, Dimethylformamide, Optoelectronics, 0210 nano-technology, business, Visible spectrum, medicine.drug
Abstract

The paper reports on the influence of visible light at different wavelengths (red, λ = 630 nm; green, λ = 570 nm; purple–blue, λ = 430 nm), light irradiance conditions (from 30 to 770 μW/cm 2 ) and operating temperatures (from 25 °C to 100 °C) on the electrical response of WO 3 electrospun nanofibers (NFs) to 100–400 ppb NO 2 gas in dry air. WO 3 NFs were prepared by mixing a W–O sol–gel transparent solution (WCl 6 in ethanol) with a polymeric solution made of polyvinylpyrrolidone (PVP) and dimethylformamide (DMF). Electrospun NFs were annealed between 300 °C and 500 °C and the their microstructures features investigated by SEM and XRD. Room temperature (25 °C) gas responses of the 450 °C annealed NFs have shown that, beside a slight reduction of the relative gas response (RRs), a decrease of the light wavelength (toward the purple–blue) and an increase of its irradiance, greatly improve the base line recovery and the response time with respect to dark conditions. At operating temperatures ranging from 25 °C to 100 °C, sensor relative responses in dark always resulted to be higher as respect to the ones displayed under purple–blue light illumination. The combined action of purple-blue light with an irradiance of 770 μW/cm 2 and of mild operating temperature of 75 °C, relative responses (RRs) of 12.4 and base line recovery percentages (RPs) of 97% were attained at 400 ppb NO 2 . The capability to tune the response of WO 3 NFs to NO 2 by combining light and mild thermal gas sensors activations is addressed and discussed also considering the involved response mechanisms.

Published
2016

47. AMD-OSDI Consensus on Injection Techniques for People with Diabetes Mellitus

Author

De Rosa N, Speese K, Gentile S, Sudano M, etti R, Branca Mt, Marcone Tam, Cucco L, Grassi G, Lalli C, Strollo F, Armentano, L. Tonutti, Chi, Giancaterini A, De Riu S, Tatti P, Garrapa G, Lo Grasso G, Gentile L, and Botta A

Subjects
High rate, medicine.medical_specialty, business.industry, Insulin, medicine.medical_treatment, Alternative medicine, Lipohypertrophy, Library science, Evidence-based medicine, medicine.disease, National guideline, Open access publishing, Family medicine, Diabetes mellitus, medicine, business
Abstract

It goes without saying that all people with diabetes should be taught the best injection technique before starting insulin treatment. Nevertheless the extremely high rate of local injection-related skin reactions-i.e., lipodysthrophic lesions-described in literature, proves otherwise. We are hereby presenting a Consensus Document on Injecting Techniques which highlights 18 key points based on a thorough analysis of the available literature and ranked by "Level of evidence" and "Strength of recommendation" according to our National Guideline System. It is meant at providing all professionals involved in diabetes care with a practical guide on how to help patients on insulin perform well.

Published
2016

48. Exfoliated black phosphorus gas sensing properties at room temperature

Author

Carlo Cantalini, M. Donarelli, Giulia Fioravanti, Luca Ottaviano, L. Giancaterini, and Francesco Perrozzi

Subjects
Materials science, Scanning electron microscope, Analytical chemistry, Nanotechnology, 02 engineering and technology, 010402 general chemistry, NO2, 01 natural sciences, Black phosphorus, X-ray photoelectron spectroscopy, Oxidizing agent, XPS, General Materials Science, Detection limit, Gas sensing, H2, NH3, Mechanics of Materials, Mechanical Engineering, Materials Science (all), Chemistry (all), Condensed Matter Physics, Drop (liquid), General Chemistry, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Electrode, Interdigitated electrode, 0210 nano-technology
Abstract

Room temperature gas sensing properties of chemically exfoliated black phosphorus (BP) to oxidizing (NO2, CO2) and reducing (NH3, H2, CO) gases in a dry air carrier have been reported. To study the gas sensing properties of BP, chemically exfoliated BP flakes have been drop casted on Si3N4 substrates provided with Pt comb-type interdigitated electrodes in N2 atmosphere. Scanning electron microscopy and x-ray photoelectron spectroscopy characterizations show respectively the occurrence of a mixed structure, composed of BP coarse aggregates dispersed on BP exfoliated few layer flakes bridging the electrodes, and a clear 2p doublet belonging to BP, which excludes the occurrence of surface oxidation. Room temperature electrical tests in dry air show a p-type response of multilayer BP with measured detection limits of 20 ppb and 10 ppm to NO2 and NH3 respectively. No response to CO and CO2 has been detected, while a slight but steady sensitivity to H2 has been recorded. The reported results confirm, on an experimental basis, what was previously theoretically predicted, demonstrating the promising sensing properties of exfoliated BP.

Published
2016

49. Il gioco del silenzio: il segreto familiare come ostacolo alle funzioni coniugali e genitoriali

Author

Antonella Giancaterini, Claudia Di Gregorio Zitella, and Alessandro Celli

Subjects
Mechanical Engineering, Energy Engineering and Power Technology, Management Science and Operations Research
Abstract

Questo lavoro analizza gli effetti del segreto sul funzionamento familiare e le conseguenze che questo comporta, sia sul piano coniugale che genitoriale. Si analizzerŕ la connessione tra segreto e mito familiare e gli aspetti legati alle loro funzioni protettive e difensive dell'identitŕ dei membri della famiglia. Sul piano coniugale e genitoriale saranno presentate delle ipotesi sull'influenza del segreto nella definizione della relazione tra gli individui e sulla natura patogena di tale stile relazionale familiare. Sarŕ trattata, infine, la figura del terapeuta, sia come fattore di cambiamento rispetto allo svelamento del segreto in terapia che come aiuto alla famiglia nel connettere il suo "tempo".

Published
2011

50. Impact of a chronic care model based on patient empowerment on the management of Type 2 diabetes: effects of the SINERGIA programme

Author

Fabio Pellegrini, Antonio Nicolucci, A. Lovagnini Scher, N. Musacchio, F. Schivalocchi, Maria Chiara Rossi, A. Giancaterini, L. Pessina, and G. Salis

Subjects
Chronic care, medicine.medical_specialty, business.industry, Endocrinology, Diabetes and Metabolism, Repeated measures design, Type 2 diabetes, medicine.disease, Obesity, Surgery, Endocrinology, Patient satisfaction, Blood pressure, Metabolic control analysis, Internal medicine, Diabetes mellitus, Internal Medicine, medicine, business
Abstract

Diabet. Med. 28, 724–730 (2011) Abstract Aims Several chronic care models for diabetes have been implemented in Italy, although conclusive data on their effectiveness are lacking. In the Cusano-Milanino diabetes clinic, patients with Type 2 diabetes with a stable disease/therapy (i.e. a steady level of HbA1c without need for therapy changes) are included in the SINERGIA programme: diabetologists, nurses and dietitians empower patients and telemedicine resources are utilized efficiently. Methods Clinical outcomes measured in the year before and after the initiation of SINERGIA were compared. A generalized hierarchical linear regression model for repeated measures was used. Results Altogether, 1004 patients were included; baseline characteristics were (mean ± sd): age 66.6 ± 6.2 years, 54.1% male, diabetes duration 10.8 ± 7.7 years, BMI 29.5 ± 4.8 kg/m2, HbA1c 6.9 ± 0.9% (52 ± 14 mmol/mol); 72.9% of patients were treated with anti-hypertensive drugs; 32.7% were treated with lipid-lowering drugs. After a median follow-up of 12 months (range 6–24 months), the proportion of patients with HbA1c≤ 7.0% (≤ 53 mmol/mol) increased from 32.7 to 45.8% (P

Published
2011

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