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Showing 1 to 12 of 45 entries
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Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration.

Journal of diabetes science and technology

Facchinetti A, Sparacino G, Cobelli C.
PMID: 19885129
J Diabetes Sci Technol. 2007 Sep;1(5):617-23. doi: 10.1177/193229680700100504.

BACKGROUND: Continuous glucose monitoring (CGM) sensors measure glucose concentration in the interstitial fluid (ISF). Equilibration between plasma and ISF glucose is not instantaneous. Therefore, ISF and plasma glucose concentrations exhibit different dynamic patterns, particularly during rapid changes. The purpose...

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Facchinetti A, Sparacino G, Cobelli C. Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration. J Diabetes Sci Technol. 2007;1(5):617-23doi: 10.1177/193229680700100504.
Facchinetti, A., Sparacino, G., & Cobelli, C. (2007). Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration. Journal of diabetes science and technology, 1(5), 617-23. https://doi.org/10.1177/193229680700100504
Facchinetti, Andrea, et al. "Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration." Journal of diabetes science and technology vol. 1,5 (2007): 617-23. doi: https://doi.org/10.1177/193229680700100504
Facchinetti A, Sparacino G, Cobelli C. Reconstruction of glucose in plasma from interstitial fluid continuous glucose monitoring data: role of sensor calibration. J Diabetes Sci Technol. 2007 Sep;1(5):617-23. doi: 10.1177/193229680700100504. PMID: 19885129; PMCID: PMC2769666.
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[Patient education. Adult nasopharyngolaryngoscopy].

ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses

Ruby S, Hawkshaw M, McCullagh L, Sparacino L.
PMID: 18274237
ORL Head Neck Nurs. 2008;26(1):15-6.

No abstract available.

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Ruby S, Hawkshaw M, McCullagh L, et al. [Patient education. Adult nasopharyngolaryngoscopy]. ORL Head Neck Nurs. 2008;26(1):15-6
Ruby, S., Hawkshaw, M., McCullagh, L., & Sparacino, L. (2008). [Patient education. Adult nasopharyngolaryngoscopy]. ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses, 26(1), 15-6.
Ruby, S, et al. "[Patient education. Adult nasopharyngolaryngoscopy]." ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses vol. 26,1 (2008): 15-6.
Ruby S, Hawkshaw M, McCullagh L, Sparacino L. [Patient education. Adult nasopharyngolaryngoscopy]. ORL Head Neck Nurs. 2008;26(1):15-6. Chinese. PMID: 18274237.
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[No title available]

New microbes and new infections

Torri A, Bertini S, Schiavone P, Congestrì F, Matteucci M, Sparacino M, Testa G, Pedna MF, Sambri V.
PMID: 29556408
New Microbes New Infect. 2018 Mar 12;23:39-43. doi: 10.1016/j.nmni.2018.01.002. eCollection 2018 May.

No abstract available.

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Torri A, Bertini S, Schiavone P, et al. . New Microbes New Infect. 2018;23:39-43doi: 10.1016/j.nmni.2018.01.002.
Torri, A., Bertini, S., Schiavone, P., Congestrì, F., Matteucci, M., Sparacino, M., Testa, G., Pedna, M. F., & Sambri, V. (2018). . New microbes and new infections, 2339-43. https://doi.org/10.1016/j.nmni.2018.01.002
Torri, A, et al. "." New microbes and new infections vol. 23 (2018): 39-43. doi: https://doi.org/10.1016/j.nmni.2018.01.002
Torri A, Bertini S, Schiavone P, Congestrì F, Matteucci M, Sparacino M, Testa G, Pedna MF, Sambri V. . New Microbes New Infect. 2018 Mar 12;23:39-43. doi: 10.1016/j.nmni.2018.01.002. eCollection 2018 May. PMID: 29556408; PMCID: PMC5854895.
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Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation.

Source code for biology and medicine

Rubega M, Cecchetto C, Vassanelli S, Sparacino G.
PMID: 28191033
Source Code Biol Med. 2017 Feb 07;12:3. doi: 10.1186/s13029-017-0062-5. eCollection 2017.

BACKGROUND: Local field potentials (LFPs) evoked by sensory stimulation are particularly useful in electrophysiological research. For instance, spike timing and current transmembrane current flow estimated from LFPs recorded in the barrel cortex in rats and mice are exploited to...

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Rubega M, Cecchetto C, Vassanelli S, et al. Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source Code Biol Med. 2017;12:3doi: 10.1186/s13029-017-0062-5.
Rubega, M., Cecchetto, C., Vassanelli, S., & Sparacino, G. (2017). Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source code for biology and medicine, 123. https://doi.org/10.1186/s13029-017-0062-5
Rubega, Maria, et al. "Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation." Source code for biology and medicine vol. 12 (2017): 3. doi: https://doi.org/10.1186/s13029-017-0062-5
Rubega M, Cecchetto C, Vassanelli S, Sparacino G. Algorithm and software to automatically identify latency and amplitude features of local field potentials recorded in electrophysiological investigation. Source Code Biol Med. 2017 Feb 07;12:3. doi: 10.1186/s13029-017-0062-5. eCollection 2017. PMID: 28191033; PMCID: PMC5297145.
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Obesity, Cardiac Remodeling, and Metabolic Profile: Validation of a New Simple Index beyond Body Mass Index.

Journal of cardiovascular echography

Antonini-Canterin F, Di Nora C, Poli S, Sparacino L, Cosei I, Ravasel A, Popescu AC, Popescu BA.
PMID: 29629255
J Cardiovasc Echogr. 2018 Jan-Mar;28(1):18-25. doi: 10.4103/jcecho.jcecho_63_17.

AIM: The body mass index (BMI), the most used anthropometric index of obesity, has an important limitation, not taking into consideration the distribution of body fat. We developed a new simple index: the waist-corrected BMI (wBMI), calculated as waist...

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Antonini-Canterin F, Di Nora C, Poli S, et al. Obesity, Cardiac Remodeling, and Metabolic Profile: Validation of a New Simple Index beyond Body Mass Index. J Cardiovasc Echogr. 2018;28(1):18-25doi: 10.4103/jcecho.jcecho_63_17.
Antonini-Canterin, F., Di Nora, C., Poli, S., Sparacino, L., Cosei, I., Ravasel, A., Popescu, A. C., & Popescu, B. A. (2018). Obesity, Cardiac Remodeling, and Metabolic Profile: Validation of a New Simple Index beyond Body Mass Index. Journal of cardiovascular echography, 28(1), 18-25. https://doi.org/10.4103/jcecho.jcecho_63_17
Antonini-Canterin, Francesco, et al. "Obesity, Cardiac Remodeling, and Metabolic Profile: Validation of a New Simple Index beyond Body Mass Index." Journal of cardiovascular echography vol. 28,1 (2018): 18-25. doi: https://doi.org/10.4103/jcecho.jcecho_63_17
Antonini-Canterin F, Di Nora C, Poli S, Sparacino L, Cosei I, Ravasel A, Popescu AC, Popescu BA. Obesity, Cardiac Remodeling, and Metabolic Profile: Validation of a New Simple Index beyond Body Mass Index. J Cardiovasc Echogr. 2018 Jan-Mar;28(1):18-25. doi: 10.4103/jcecho.jcecho_63_17. PMID: 29629255; PMCID: PMC5875131.
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Multicenter Evaluation of the C6 Lyme ELISA Kit for the Diagnosis of Lyme Disease.

Microorganisms

Zannoli S, Fantini M, Semprini S, Marchini B, Ceccarelli B, Sparacino M, Schiavone P, Belgrano A, Ruscio M, Gobbetti M, Nicoletti M, Robatscher E, Pagani E, Sambri V.
PMID: 32213811
Microorganisms. 2020 Mar 24;8(3). doi: 10.3390/microorganisms8030457.

Lyme disease (LD), caused by infection with

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Zannoli S, Fantini M, Semprini S, et al. Multicenter Evaluation of the C6 Lyme ELISA Kit for the Diagnosis of Lyme Disease. Microorganisms. 2020;8(3)doi: 10.3390/microorganisms8030457.
Zannoli, S., Fantini, M., Semprini, S., Marchini, B., Ceccarelli, B., Sparacino, M., Schiavone, P., Belgrano, A., Ruscio, M., Gobbetti, M., Nicoletti, M., Robatscher, E., Pagani, E., & Sambri, V. (2020). Multicenter Evaluation of the C6 Lyme ELISA Kit for the Diagnosis of Lyme Disease. Microorganisms, 8(3), . https://doi.org/10.3390/microorganisms8030457
Zannoli, Silvia, et al. "Multicenter Evaluation of the C6 Lyme ELISA Kit for the Diagnosis of Lyme Disease." Microorganisms vol. 8,3 (2020). doi: https://doi.org/10.3390/microorganisms8030457
Zannoli S, Fantini M, Semprini S, Marchini B, Ceccarelli B, Sparacino M, Schiavone P, Belgrano A, Ruscio M, Gobbetti M, Nicoletti M, Robatscher E, Pagani E, Sambri V. Multicenter Evaluation of the C6 Lyme ELISA Kit for the Diagnosis of Lyme Disease. Microorganisms. 2020 Mar 24;8(3). doi: 10.3390/microorganisms8030457. PMID: 32213811; PMCID: PMC7143974.
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Data Gap Modeling in Continuous Glucose Monitoring Sensor Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Drecogna M, Vettoretti M, Favero SD, Facchinetti A, Sparacino G.
PMID: 34892190
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4379-4382. doi: 10.1109/EMBC46164.2021.9629588.

Continuous glucose monitoring (CGM) sensors are minimally-invasive sensors used in diabetes therapy to monitor interstitial glucose concentration. The measurements are collected almost continuously (e.g. every 5 min) and permit the detection of dangerous hypo/hyperglycemic episodes. Modeling the various error...

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Drecogna M, Vettoretti M, Favero SD, et al. Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021:4379-4382doi: 10.1109/EMBC46164.2021.9629588.
Drecogna, M., Vettoretti, M., Favero, S. D., Facchinetti, A., & Sparacino, G. (2021). Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 20214379-4382. https://doi.org/10.1109/EMBC46164.2021.9629588
Drecogna, Martina, et al. "Data Gap Modeling in Continuous Glucose Monitoring Sensor Data." Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference vol. 2021 (2021): 4379-4382. doi: https://doi.org/10.1109/EMBC46164.2021.9629588
Drecogna M, Vettoretti M, Favero SD, Facchinetti A, Sparacino G. Data Gap Modeling in Continuous Glucose Monitoring Sensor Data. Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4379-4382. doi: 10.1109/EMBC46164.2021.9629588. PMID: 34892190.
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A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life.

Diabetes therapy : research, treatment and education of diabetes and related disorders

Bruttomesso D, Boscari F, Lepore G, Noaro G, Cappon G, Girelli A, Bozzetto L, Tumminia A, Grassi G, Sparacino G, Laviola L, Facchinetti A.
PMID: 33725276
Diabetes Ther. 2021 May;12(5):1313-1324. doi: 10.1007/s13300-021-01020-2. Epub 2021 Mar 16.

INTRODUCTION: In persons with type 1 diabetes (T1D) insulin dosing can be adjusted based on trend arrows derived from continuous glucose monitoring (CGM). We propose a slide rule with narrower blood glucose intervals and more classes of insulin sensitivity...

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Bruttomesso D, Boscari F, Lepore G, et al. A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life. Diabetes Ther. 2021;12(5):1313-1324doi: 10.1007/s13300-021-01020-2.
Bruttomesso, D., Boscari, F., Lepore, G., Noaro, G., Cappon, G., Girelli, A., Bozzetto, L., Tumminia, A., Grassi, G., Sparacino, G., Laviola, L., & Facchinetti, A. (2021). A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life. Diabetes therapy : research, treatment and education of diabetes and related disorders, 12(5), 1313-1324. https://doi.org/10.1007/s13300-021-01020-2
Bruttomesso, Daniela, et al. "A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life." Diabetes therapy : research, treatment and education of diabetes and related disorders vol. 12,5 (2021): 1313-1324. doi: https://doi.org/10.1007/s13300-021-01020-2
Bruttomesso D, Boscari F, Lepore G, Noaro G, Cappon G, Girelli A, Bozzetto L, Tumminia A, Grassi G, Sparacino G, Laviola L, Facchinetti A. A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life. Diabetes Ther. 2021 May;12(5):1313-1324. doi: 10.1007/s13300-021-01020-2. Epub 2021 Mar 16. PMID: 33725276; PMCID: PMC8099956.
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Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients.

Entropy (Basel, Switzerland)

Rubega M, Scarpa F, Teodori D, Sejling AS, Frandsen CS, Sparacino G.
PMID: 33285854
Entropy (Basel). 2020 Jan 09;22(1). doi: 10.3390/e22010081.

Previous literature has demonstrated that hypoglycemic events in patients with type 1 diabetes (T1D) are associated with measurable scalp electroencephalography (EEG) changes in power spectral density. In the present study, we used a dataset of 19-channel scalp EEG recordings...

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Rubega M, Scarpa F, Teodori D, et al. Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients. Entropy (Basel). 2020;22(1)doi: 10.3390/e22010081.
Rubega, M., Scarpa, F., Teodori, D., Sejling, A. S., Frandsen, C. S., & Sparacino, G. (2020). Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients. Entropy (Basel, Switzerland), 22(1), . https://doi.org/10.3390/e22010081
Rubega, Maria, et al. "Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients." Entropy (Basel, Switzerland) vol. 22,1 (2020). doi: https://doi.org/10.3390/e22010081
Rubega M, Scarpa F, Teodori D, Sejling AS, Frandsen CS, Sparacino G. Detection of Hypoglycemia Using Measures of EEG Complexity in Type 1 Diabetes Patients. Entropy (Basel). 2020 Jan 09;22(1). doi: 10.3390/e22010081. PMID: 33285854; PMCID: PMC7516516.
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Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods.

Diabetic medicine : a journal of the British Diabetic Association

Camerlingo N, Vettoretti M, Sparacino G, Facchinetti A, Mader JK, Choudhary P, Del Favero S.
PMID: 34862829
Diabet Med. 2021 Dec 04;e14758. doi: 10.1111/dme.14758. Epub 2021 Dec 04.

AIMS: Reliable estimation of the time spent in different glycaemic ranges (time-in-ranges) requires sufficiently long continuous glucose monitoring. In a 2019 paper (Battelino et al., Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on...

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Camerlingo N, Vettoretti M, Sparacino G, et al. Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods. Diabet Med. 2021;e14758doi: 10.1111/dme.14758.
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., Del Favero, S. (2021). Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods. Diabetic medicine : a journal of the British Diabetic Association, e14758. https://doi.org/10.1111/dme.14758
Camerlingo, Nunzio, et al. "Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods." Diabetic medicine : a journal of the British Diabetic Association vol. (2021): e14758. doi: https://doi.org/10.1111/dme.14758
Camerlingo N, Vettoretti M, Sparacino G, Facchinetti A, Mader JK, Choudhary P, Del Favero S. Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation-based methods. Diabet Med. 2021 Dec 04;e14758. doi: 10.1111/dme.14758. Epub 2021 Dec 04. PMID: 34862829.
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Smokeless tobacco and smoking cessation: a program evaluation.

ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses

Adams J, Krouse HJ, Sparacino L.
PMID: 11153351
ORL Head Neck Nurs. 2000;18(3):12-6.

During the 1998 mid-winter Board of Directors meeting in Tampa, Florida, the leaders of the Society of Otorhinolaryngology-Head and Neck Nurses (SOHN) discussed the vision and mission of SOHN. Part of the vision that emerged was a long-overdue educational...

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Adams J, Krouse HJ, Sparacino L. Smokeless tobacco and smoking cessation: a program evaluation. ORL Head Neck Nurs. 2000;18(3):12-6
Adams, J., Krouse, H. J., & Sparacino, L. (2000). Smokeless tobacco and smoking cessation: a program evaluation. ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses, 18(3), 12-6.
Adams, J, et al. "Smokeless tobacco and smoking cessation: a program evaluation." ORL-head and neck nursing : official journal of the Society of Otorhinolaryngology and Head-Neck Nurses vol. 18,3 (2000): 12-6.
Adams J, Krouse HJ, Sparacino L. Smokeless tobacco and smoking cessation: a program evaluation. ORL Head Neck Nurs. 2000;18(3):12-6. PMID: 11153351.
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Sleep Duration Correlates With Performance in Ultra-Endurance Triathlon.

International journal of sports physiology and performance

Kisiolek JN, Smith KA, Baur DA, Willingham BD, Morrissey MC, Leyh SM, Saracino PG, Mah CD, Ormsbee MJ.
PMID: 34627130
Int J Sports Physiol Perform. 2021 Oct 09;1-8. doi: 10.1123/ijspp.2021-0111. Epub 2021 Oct 09.

The relationship between sleep duration, sleep quality, and race completion time during each stage of a 3-day ultra-endurance triathlon (stage 1: 10-km swim, 146-km cycle; stage 2: 276-km cycle; and stage 3: 84.4-km run) was investigated. Seventeen triathletes partook...

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Kisiolek JN, Smith KA, Baur DA, et al. Sleep Duration Correlates With Performance in Ultra-Endurance Triathlon. Int J Sports Physiol Perform. 2021;1-8doi: 10.1123/ijspp.2021-0111.
Kisiolek, J. N., Smith, K. A., Baur, D. A., Willingham, B. D., Morrissey, M. C., Leyh, S. M., Saracino, P. G., Mah, C. D., & Ormsbee, M. J. (2021). Sleep Duration Correlates With Performance in Ultra-Endurance Triathlon. International journal of sports physiology and performance, 1-8. https://doi.org/10.1123/ijspp.2021-0111
Kisiolek, Jacob N, et al. "Sleep Duration Correlates With Performance in Ultra-Endurance Triathlon." International journal of sports physiology and performance vol. (2021): 1-8. doi: https://doi.org/10.1123/ijspp.2021-0111
Kisiolek JN, Smith KA, Baur DA, Willingham BD, Morrissey MC, Leyh SM, Saracino PG, Mah CD, Ormsbee MJ. Sleep Duration Correlates With Performance in Ultra-Endurance Triathlon. Int J Sports Physiol Perform. 2021 Oct 09;1-8. doi: 10.1123/ijspp.2021-0111. Epub 2021 Oct 09. PMID: 34627130.
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Showing 1 to 12 of 45 entries