Boris P Kovatchev

Summary

Affiliation: University of Virginia
Country: USA

Publications

  1. ncbi request reprint Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 4:295-303. 2002
  2. ncbi request reprint Quantifying temporal glucose variability in diabetes via continuous glucose monitoring: mathematical methods and clinical application
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 7:849-62. 2005
  3. ncbi request reprint Bio-behavioral control, glucose variability, and hypoglycemia-associated autonomic failure in type 1 diabetes (T1DM)
    Marc D Breton
    School of Medicine, University of Virginia, USA
    Conf Proc IEEE Eng Med Biol Soc 1:315-8. 2006
  4. ncbi request reprint Is glycemic variability important to assessing antidiabetes therapies?
    Boris P Kovatchev
    University of Virginia Health System, Box 800137, Charlottesville, VA 22908, USA
    Curr Diab Rep 6:350-6. 2006
  5. doi request reprint Comparison of the numerical and clinical accuracy of four continuous glucose monitors
    Boris Kovatchev
    University of Virginia, Charlottesville, Virginia, USA
    Diabetes Care 31:1160-4. 2008
  6. pmc Safety of outpatient closed-loop control: first randomized crossover trials of a wearable artificial pancreas
    Boris P Kovatchev
    Center for Diabetes Technology and Department of Medicine, Division of Endocrinology, University of Virginia, Charlottesville, VA
    Diabetes Care 37:1789-96. 2014
  7. pmc In silico Models of Alcohol Dependence and Treatment
    Boris Kovatchev
    Computational Neuroscience Section, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health System Charlottesville, VA, USA
    Front Psychiatry 3:4. 2012
  8. pmc Feasibility of outpatient fully integrated closed-loop control: first studies of wearable artificial pancreas
    Boris P Kovatchev
    Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA
    Diabetes Care 36:1851-8. 2013
  9. ncbi request reprint A psychophysiological marker of attention deficit/hyperactivity disorder (ADHD)--defining the EEG consistency index
    B Kovatchev
    Center for Behavioral Medicine Research, University of Virginia Health System, Box 800137, Charlottesville, Virginia 22908, USA
    Appl Psychophysiol Biofeedback 26:127-40. 2001
  10. pmc In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes
    Boris P Kovatchev
    University of Virginia, Charlottesville, Virginia 22908 4888, USA
    J Diabetes Sci Technol 3:44-55. 2009

Research Grants

  1. MODULAR BIO-BEHAVIORAL CLOSED-LOOP CONTROL OF TYPE 1 DIABETES
    Boris P Kovatchev; Fiscal Year: 2010
  2. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris P Kovatchev; Fiscal Year: 2010
  3. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2009
  4. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2007
  5. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2006
  6. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2005
  7. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2003
  8. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2002
  9. BIOBEHAVIORAL IRREGULARITY AND CONTROL OF IDDM
    Boris Kovatchev; Fiscal Year: 2000
  10. BIOBEHAVIORAL IRREGULARITY AND CONTROL OF IDDM
    Boris Kovatchev; Fiscal Year: 1999

Collaborators

Detail Information

Publications70

  1. ncbi request reprint Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 4:295-303. 2002
    ..0001). SMBG data allow for computing and frequent updating of various idiosyncratic diabetes characteristics and risk factors. The use of such computations may assist in optimizing patients' glycemic control...
  2. ncbi request reprint Quantifying temporal glucose variability in diabetes via continuous glucose monitoring: mathematical methods and clinical application
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 7:849-62. 2005
    ..As a result, important information about the temporal structure of the data is lost during the translation of raw sensor readings into clinically interpretable statistics and images...
  3. ncbi request reprint Bio-behavioral control, glucose variability, and hypoglycemia-associated autonomic failure in type 1 diabetes (T1DM)
    Marc D Breton
    School of Medicine, University of Virginia, USA
    Conf Proc IEEE Eng Med Biol Soc 1:315-8. 2006
    ....
  4. ncbi request reprint Is glycemic variability important to assessing antidiabetes therapies?
    Boris P Kovatchev
    University of Virginia Health System, Box 800137, Charlottesville, VA 22908, USA
    Curr Diab Rep 6:350-6. 2006
    ..Thus, temporal variability methods are discussed for the analysis and interpretation of CGM output...
  5. doi request reprint Comparison of the numerical and clinical accuracy of four continuous glucose monitors
    Boris Kovatchev
    University of Virginia, Charlottesville, Virginia, USA
    Diabetes Care 31:1160-4. 2008
    ..The purpose of this study was to compare the numerical and clinical accuracy of four continuous glucose monitors (CGMs): Guardian, DexCom, Navigator, and Glucoday...
  6. pmc Safety of outpatient closed-loop control: first randomized crossover trials of a wearable artificial pancreas
    Boris P Kovatchev
    Center for Diabetes Technology and Department of Medicine, Division of Endocrinology, University of Virginia, Charlottesville, VA
    Diabetes Care 37:1789-96. 2014
    ..We estimate the effect size of hypoglycemia risk reduction on closed-loop control (CLC) versus open-loop (OL) sensor-augmented insulin pump therapy in supervised outpatient setting...
  7. pmc In silico Models of Alcohol Dependence and Treatment
    Boris Kovatchev
    Computational Neuroscience Section, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health System Charlottesville, VA, USA
    Front Psychiatry 3:4. 2012
    ....
  8. pmc Feasibility of outpatient fully integrated closed-loop control: first studies of wearable artificial pancreas
    Boris P Kovatchev
    Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA
    Diabetes Care 36:1851-8. 2013
    ..To evaluate the feasibility of a wearable artificial pancreas system, the Diabetes Assistant (DiAs), which uses a smart phone as a closed-loop control platform...
  9. ncbi request reprint A psychophysiological marker of attention deficit/hyperactivity disorder (ADHD)--defining the EEG consistency index
    B Kovatchev
    Center for Behavioral Medicine Research, University of Virginia Health System, Box 800137, Charlottesville, Virginia 22908, USA
    Appl Psychophysiol Biofeedback 26:127-40. 2001
    ..Post hoc analysis indicated that the classification utility of the CI diminished with age. A CI below 40% could be a discriminating, reliable, and reproducible marker of ADHD in young boys...
  10. pmc In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes
    Boris P Kovatchev
    University of Virginia, Charlottesville, Virginia 22908 4888, USA
    J Diabetes Sci Technol 3:44-55. 2009
    ....
  11. pmc Graphical and numerical evaluation of continuous glucose sensing time lag
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia, USA
    Diabetes Technol Ther 11:139-43. 2009
    ..This study introduces a new method for graphical and numerical evaluation of time lags typically associated with subcutaneous glucose sensing, based on Poincaré-type plot and a maximum statistical agreement criterion...
  12. pmc Pramlintide reduces the risks associated with glucose variability in type 1 diabetes
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22901, USA
    Diabetes Technol Ther 10:391-6. 2008
    ..This study was designed to determine whether pramlintide added to insulin therapy reduced the risks associated with extreme blood glucose (BG) fluctuations in patients with type 1 diabetes...
  13. ncbi request reprint Evaluation of a new measure of blood glucose variability in diabetes
    Boris P Kovatchev
    University of Virginia Health System, Box 800137, Charlottesville, VA 22908, USA
    Diabetes Care 29:2433-8. 2006
    ..It is therefore important to design variability measures that are equally predictive of low and high blood glucose excursions...
  14. pmc The accuracy of a new real-time continuous glucose monitoring algorithm: an analysis
    Boris Kovatchev
    Diabetes Technology Program, University of Virginia, Charlottesville, Virginia 22909, USA
    J Diabetes Sci Technol 4:119-22. 2010
    ..However, the presented results should be interpreted cautiously because they are based on retrospective analysis and are heavily dependent on the distribution of blood glucose levels observed in a particular data set...
  15. ncbi request reprint Algorithmic evaluation of metabolic control and risk of severe hypoglycemia in type 1 and type 2 diabetes using self-monitoring blood glucose data
    Boris P Kovatchev
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 5:817-28. 2003
    ..SMBG data allow for accurate estimation of the two most important markers of metabolic control in T1DM and T2DM - HbA(1c) and risk for hypoglycemia...
  16. ncbi request reprint Evaluating the accuracy of continuous glucose-monitoring sensors: continuous glucose-error grid analysis illustrated by TheraSense Freestyle Navigator data
    Boris P Kovatchev
    Department of Psychiatric Medicine, University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Care 27:1922-8. 2004
    ....
  17. ncbi request reprint Sample asymmetry analysis of heart rate characteristics with application to neonatal sepsis and systemic inflammatory response syndrome
    Boris P Kovatchev
    Department of Psychiatric Medicine, University of Virginia Health System, Charlottesville, VA 22908, USA
    Pediatr Res 54:892-8. 2003
    ..002). We conclude that SAA is a useful new mathematical technique for detecting the abnormal heart rate characteristics that precede neonatal sepsis and SIRS...
  18. pmc Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results
    Boris Kovatchev
    Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia 22908, USA
    J Diabetes Sci Technol 4:1374-81. 2010
    ..In 2008-2009, the first multinational study was completed comparing closed-loop control (artificial pancreas) to state-of-the-art open-loop therapy in adults with type 1 diabetes mellitus (T1DM)...
  19. pmc Effect of automated bio-behavioral feedback on the control of type 1 diabetes
    Boris P Kovatchev
    Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA
    Diabetes Care 34:302-7. 2011
    ..To test the effect of an automated system providing real-time estimates of HbA(1c), glucose variability, and risk for hypoglycemia...
  20. ncbi request reprint Relationships between hyperglycemia and cognitive performance among adults with type 1 and type 2 diabetes
    Daniel J Cox
    Center for Behavioral Medicine Research, University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Care 28:71-7. 2005
    ..This study prospectively and objectively assessed the effects of hyperglycemia on cognitive-motor functioning in subjects' natural environment...
  21. pmc Control to range for diabetes: functionality and modular architecture
    Boris Kovatchev
    Department of Psychiatry and Neurobehavioral Sciences and Department of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia, USA
    J Diabetes Sci Technol 3:1058-65. 2009
    ....
  22. pmc Nonlinear metabolic effect of insulin across the blood glucose range in patients with type 1 diabetes mellitus
    Alice Chan
    Diabetes Technology Center, University of Virginia Health System, Charlottesville, Virginia 22908 4888, USA
    J Diabetes Sci Technol 4:873-81. 2010
    ..For insulin therapy to successfully maintain blood glucose (BG) levels of patients with type 1 diabetes mellitus (T1DM) in normoglycemia, it is necessary to understand if the metabolic effect of insulin across the BG range is linear or not...
  23. ncbi request reprint Prediction of severe hypoglycemia
    Daniel J Cox
    Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Care 30:1370-3. 2007
    ..Prevention of severe hypoglycemia (SH) is premised partially on the ability to accurately anticipate its occurrence. This study prospectively tests methods for predicting SH using blood glucose meter readings...
  24. pmc Type 1 diabetic drivers with and without a history of recurrent hypoglycemia-related driving mishaps: physiological and performance differences during euglycemia and the induction of hypoglycemia
    Daniel J Cox
    Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health SciencesCenter, Charlottesville, Virginia, USA
    Diabetes Care 33:2430-5. 2010
    ..This increased risk appears to be attributable to a subgroup of drivers with type 1 diabetes. The hypothesis tested is that this vulnerable subgroup is more at risk for hypoglycemia and its disruptive effects on driving...
  25. ncbi request reprint A novel analytical method for assessing glucose variability: using CGMS in type 1 diabetes mellitus
    Anthony L McCall
    Division of Endocrinology and Center for Diabetes and Hormone Excellence, Department of Internal Medicine, University of Virginia, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 8:644-53. 2006
    ....
  26. ncbi request reprint Clinical assessment and mathematical modeling of the accuracy of continuous glucose sensors (CGS)
    Boris P Kovatchev
    University of Virginia School of Medicine, Charlottesville, Virginia, USA
    Conf Proc IEEE Eng Med Biol Soc 1:71-4. 2006
    ..The continuous glucose error-grid analysis (CG-EGA) was used to evaluate sensor inaccuracy from a clinical point of view...
  27. doi request reprint Cardiovascular oscillations at the bedside: early diagnosis of neonatal sepsis using heart rate characteristics monitoring
    J Randall Moorman
    Department of Internal Medicine, Cardiovascular Division, University of Virginia, Charlottesville, VA, USA
    Physiol Meas 32:1821-32. 2011
    ..This review focuses on the mathematical and statistical time series approaches used to detect these abnormal heart rate characteristics and present predictive monitoring information to the clinician...
  28. ncbi request reprint Numerical estimation of HbA(1c) from routine self-monitoring data in people with type 1 and type 2 diabetes mellitus
    Boris P Kovatchev
    University of Virginia Health System, Center for Behavioral Medicine Research, Charlottesville, Virginia 22908, USA
    Methods Enzymol 384:94-106. 2004
  29. ncbi request reprint The metabolic demands of driving for drivers with type 1 diabetes mellitus
    Daniel J Cox
    University of Virginia Health System, Charlottesville, VA 22908, USA
    Diabetes Metab Res Rev 18:381-5. 2002
    ..Conversely, symptoms caused by the stress of driving may be confused with hypoglycemia and lead to false alarms. This study examined the metabolic demand and the physiological stress of driving on type 1 diabetes mellitus (T1DM) drivers...
  30. pmc Systematic method to assess microvascular recruitment using contrast-enhanced ultrasound. Application to insulin-induced capillary recruitment in subjects with T1DM
    Alice Chan
    Diabetes Technology Center, University of Virginia Health System, P O 400 888, Charlottesville, VA 22908 4888, USA
    Comput Methods Programs Biomed 102:219-26. 2011
    ....
  31. pmc Impact of blood glucose self-monitoring errors on glucose variability, risk for hypoglycemia, and average glucose control in type 1 diabetes: an in silico study
    Marc D Breton
    University of Virginia, Charlottesville, Virginia 22908 4888, USA
    J Diabetes Sci Technol 4:562-70. 2010
    ....
  32. pmc Hypoglycemia prevention via pump attenuation and red-yellow-green "traffic" lights using continuous glucose monitoring and insulin pump data
    Colleen S Hughes
    Department of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia 22904, USA
    J Diabetes Sci Technol 4:1146-55. 2010
    ..More specifically, the algorithm presented here is formulated as a component of the independent safety system module proposed in the modular control-to-range architecture...
  33. pmc Association of Basal hyperglucagonemia with impaired glucagon counterregulation in type 1 diabetes
    Leon S Farhy
    Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia Charlottesville, VA, USA
    Front Physiol 3:40. 2012
    ..Our findings support the hypothesis that basal hyperglucagonemia contributes to the GCR impairment in T1DM and show that the predictive power of our GCR animal model applies to human pathophysiology in T1DM...
  34. pmc Metabolic Demand of Driving Among Adults with Type 1 Diabetes Mellitus (T1DM)
    Daniel J Cox
    University of Virginia Health System, Charlottesville, Virginia, USA
    Ann Adv Automot Med 54:367-72. 2010
    ..Driving a virtual reality simulator is associated with increased glucose utilization rates suggesting that driving per se has a metabolic cost and that BG should be measured prior to driving and periodically during long drives...
  35. pmc Modeling of Calibration Effectiveness and Blood-to-Interstitial Glucose Dynamics as Potential Confounders of the Accuracy of Continuous Glucose Sensors during Hyperinsulinemic Clamp
    Christopher King
    University of Virginia Health System, Charlottesville, Virginia
    J Diabetes Sci Technol 1:317-22. 2007
    ..These effects could have a significant effect on the cross-interpretation of nonidentical accuracy studies...
  36. pmc A behavior change model for internet interventions
    Lee M Ritterband
    Department of Psychiatry and Neurobehavioral Sciences, Behavioral Health and Technology, University of Virginia Health System, PO Box 801075, Charlottesville, VA 22908, USA
    Ann Behav Med 38:18-27. 2009
    ..To date, however, many of these interventions have not been grounded in theory or developed from behavior change models, and no overarching model to explain behavior change in Internet interventions has yet been published...
  37. ncbi request reprint Unequal autonegative feedback by GH models the sexual dimorphism in GH secretory dynamics
    Leon S Farhy
    Division of Endocrinology and Metabolism, Department of Internal Medicine, The University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Am J Physiol Regul Integr Comp Physiol 282:R753-64. 2002
    ..3-h-interval, multiphasic, volleylike male GH pattern into a femalelike profile with irregular pulses of higher frequency...
  38. pmc Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience
    William L Clarke
    Division of Pediatric Endocrinology, Department of Pediatrics, University of Virginia Health Sciences Center, Charlottesville, Virginia 22908, USA
    J Diabetes Sci Technol 3:1031-8. 2009
    ..The use of a new personalized model predictive control (MPC) algorithm to determine insulin doses to achieve and maintain BG levels between 70 and 140 mg/dl overnight and to control postprandial BG levels is presented...
  39. ncbi request reprint Treatment of childhood constipation by primary care physicians: efficacy and predictors of outcome
    Stephen M Borowitz
    Department of Pediatrics, University of Virginia, Charlottesville, Virginia 22908, USA
    Pediatrics 115:873-7. 2005
    ..With this study, we prospectively examined which treatments primary care physicians prescribe to children who present for the first time with constipation and how effective those treatments are...
  40. ncbi request reprint Hypoglycemia anticipation, awareness and treatment training (HAATT) reduces occurrence of severe hypoglycemia among adults with type 1 diabetes mellitus
    Daniel J Cox
    University of Virginia Health Sciences Center, Charlottesville, Virginia, USA
    Int J Behav Med 11:212-8. 2004
    ..These findings suggest that a structured, specialized psycho-educational treatment program (HAATT) can be highly effective in managing hypoglycemia...
  41. ncbi request reprint Treatment of childhood encopresis: a randomized trial comparing three treatment protocols
    Stephen M Borowitz
    Department of Pediatrics, University of Virginia, Charlottesville, Virginia 22908, USA
    J Pediatr Gastroenterol Nutr 34:378-84. 2002
    ..To compare short- and long-term effectiveness of three additive treatment protocols in children experiencing chronic encopresis...
  42. ncbi request reprint Controlled-release methylphenidate improves attention during on-road driving by adolescents with attention-deficit/hyperactivity disorder
    Daniel J Cox
    University of Virginia, Department of Psychiatric Medicine, Charlottesville, 22908, USA
    J Am Board Fam Pract 17:235-9. 2004
    ..This study investigated whether a once-daily, long-acting, osmotic, controlled-release MPH formulation improves the driving performance of ADHD adolescents while driving their own car on an actual road segment...
  43. ncbi request reprint An Internet intervention as adjunctive therapy for pediatric encopresis
    Lee M Ritterband
    Department of Psychiatric Medicine, Center for Behavioral Medicine Research, University of Virginia Health System, Charlottesville, VA 22908 USA
    J Consult Clin Psychol 71:910-7. 2003
    ..Internet interventions may be an effective way of delivering sophisticated behavioral interventions to a large and dispersed population in a convenient format...
  44. ncbi request reprint Impact of methylphenidate delivery profiles on driving performance of adolescents with attention-deficit/hyperactivity disorder: a pilot study
    Daniel J Cox
    Department of Psychiatric Medicine, University of Virginia Health System, Charlottesville, VA 22908, USA
    J Am Acad Child Adolesc Psychiatry 43:269-75. 2004
    ..5 hours post-dose. However, little is known about the effects of different MPH delivery profiles on driving performance throughout the day...
  45. ncbi request reprint Manual transmission enhances attention and driving performance of ADHD adolescent males: pilot study
    Daniel J Cox
    University of Virginia Health System, Charlottesville, VA 22908, USA
    J Atten Disord 10:212-6. 2006
    ..This study tests the hypotheses that manual transmission, compared to automatic transmission, would be associated with better attention and performance on a driving simulator...
  46. ncbi request reprint The artificial pancreas: how close are we to closing the loop?
    William L Clarke
    Division of Pediatric Endocrinology, Box 800386, University of Virginia School of Medicine, Charlottesville, Virginia 22908, USA
    Pediatr Endocrinol Rev 4:314-6. 2007
  47. ncbi request reprint Rebound effects with long-acting amphetamine or methylphenidate stimulant medication preparations among adolescent male drivers with attention-deficit/hyperactivity disorder
    Daniel J Cox
    Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, VA 22908, USA
    J Child Adolesc Psychopharmacol 18:1-10. 2008
    ..04), suggesting possible rebound. During both late simulator and on-road testing, driving performance variance was approximately 300% greater during the se-AMPH ER compared to the OROS MPH condition...
  48. ncbi request reprint Evaluating readiness and treatment seeking effects in a pharmacotherapy trial for alcohol dependence
    J Kim Penberthy
    Center for Addiction Research and Education, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia Health System, Charlottesville, Virginia 22908 0623, USA
    Alcohol Clin Exp Res 31:1538-44. 2007
    ..Our goal was to evaluate drinking behavior before initiating a randomized, double-blind pharmacotherapy clinical trial for alcohol dependence...
  49. ncbi request reprint Detection of hypoglycemia by children with type 1 diabetes 6 to 11 years of age and their parents: a field study
    Linda Gonder-Frederick
    Department of Psychiatry and Neurobehavioral Sciences, Behavioral Medicine Center, University of Virginia, Charlottesville, VA 22908, USA
    Pediatrics 121:e489-95. 2008
    ....
  50. ncbi request reprint Relative benefits of stimulant therapy with OROS methylphenidate versus mixed amphetamine salts extended release in improving the driving performance of adolescent drivers with attention-deficit/hyperactivity disorder
    Daniel J Cox
    Department of Psychiatric Medicine, University of Virginia, Charlottesville, Virginia, USA
    Pediatrics 118:e704-10. 2006
    ..Studies have demonstrated that stimulants improve driving performance. This study compared 2 long-acting stimulant medications during daytime and evening driving evaluations...
  51. ncbi request reprint Does "stubbornness" have a role in pediatric constipation?
    Roger C Burket
    University of Virginia Health Sciences Center, Charlottesville, VA, USA
    J Dev Behav Pediatr 27:106-11. 2006
    ....
  52. ncbi request reprint Evaluating clinical accuracy of continuous glucose monitoring systems: Continuous Glucose-Error Grid Analysis (CG-EGA)
    William L Clarke
    Department of Pediatrics, Box 800386, University of Virginia, Charlottesville, VA 22908, USA
    Curr Diabetes Rev 4:193-9. 2008
    ..Information is presented on how to obtain assistance with the use of CG-EGA...
  53. ncbi request reprint Effects of blood glucose rate of changes on perceived mood and cognitive symptoms in insulin-treated type 2 diabetes
    Daniel J Cox
    Psychiatry and Neurobehavioral Sciences, University of Virginia Health Sciences Center, Charlottesville, VA, USA
    Diabetes Care 30:2001-2. 2007
  54. ncbi request reprint Using the internet to provide information prescriptions
    Lee M Ritterband
    Department of Psychiatric Medicine, University of Virginia Health System, PO Box 800223, Charlottesville, VA 22908, USA
    Pediatrics 116:e643-7. 2005
    ..As with any health care intervention, patients' lack of compliance is a barrier to the effectiveness of Web-based information prescriptions (WebIPs). WebIPs cannot be helpful if patients do not review the information prescribed for them...
  55. ncbi request reprint Evaluating the clinical accuracy of two continuous glucose sensors using continuous glucose-error grid analysis
    William L Clarke
    Division of Pediatric Endocrinology, Department of Pediatrics, University of Virginia Health System, Box 800386, Charlottesville, VA 22908, USA
    Diabetes Care 28:2412-7. 2005
    ..To compare the clinical accuracy of two different continuous glucose sensors (CGS) during euglycemia and hypoglycemia using continuous glucose-error grid analysis (CG-EGA)...
  56. ncbi request reprint Calibration of ADHD assessments across studies: a meta-analysis tool
    Jennifer Kim Penberthy
    Center for Behavioral Medicine Research, Department of Psychiatric Medicine, University of Virginia Health System, PO Box 800137, Charlottesville, Virginia 22908, USA
    Appl Psychophysiol Biofeedback 30:31-51. 2005
    ....
  57. pmc Reduced daily risk of glycemic variability: comparison of exenatide with insulin glargine
    Anthony L McCall
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 11:339-44. 2009
    ..In the present study, variability parameters were used to assess effects of exenatide and insulin glargine on risk of acute blood glucose extremes...
  58. pmc Statistical tools to analyze continuous glucose monitor data
    William Clarke
    Division of Pediatric Endocrinology, Department of Pediatrics, and Section on Computational Neuroscience, University of Virginia Health Sciences Center, Charlottesville, Virginia 22908, USA
    Diabetes Technol Ther 11:S45-54. 2009
    ..These methods should facilitate the extraction of information from, and the interpretation of, complex and voluminous CGM time series...
  59. pmc Adding Heart Rate Signal to a Control-to-Range Artificial Pancreas System Improves the Protection Against Hypoglycemia During Exercise in Type 1 Diabetes
    Marc D Breton
    Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia
    Diabetes Technol Ther 16:506-11. 2014
    ....
  60. pmc Average daily risk range as a measure of glycemic risk is associated with mortality in the intensive care unit: a retrospective study in a burn intensive care unit
    Leon S Farhy
    University of Virginia Health System, Charlottesville, Virginia 22908, USA
    J Diabetes Sci Technol 5:1087-98. 2011
    ..The main goal of the study was to relate blood glucose (BG) variability of burn ICU patients to outcomes using a sensitive measure of glycemic variability, the average daily risk range (ADRR)...
  61. pmc The median is not the only message: a clinician's perspective on mathematical analysis of glycemic variability and modeling in diabetes mellitus
    Anthony L McCall
    Department of Medicine, University of Virginia, Charlottesville, Virginia 22908, USA
    J Diabetes Sci Technol 3:3-11. 2009
    ..For the clinician, the incursion of mathematical models that simulate normal and pathophysiological mechanisms of glycemic control is a reality and should be also gradually incorporated into clinical practice...
  62. pmc Historical data enhances safety supervision system performance in T1DM insulin therapy risk management
    Colleen Hughes-Karvetski
    Psychiatry and Neurobehavioral Sciences, University of Virginia, United States
    Comput Methods Programs Biomed 109:220-5. 2013
    ..Through the use of available real-time data supplemented with historical glucose information to assess hypoglycemic risk, we are able to better anticipate and prevent hypoglycemia...
  63. pmc Effects of pulsatile subcutaneous injections of insulin lispro on plasma insulin concentration levels
    Alice Chan
    Diabetes Technology Center, University of Virginia Health System, Charlottesville, Virginia
    J Diabetes Sci Technol 2:844-52. 2008
    ..The purpose of this work is to analyze the effects of pulsatile injections of modern insulins on plasma insulin levels compared with a continuous insulin infusion...
  64. ncbi request reprint Assessment of behavioral mechanisms maintaining encopresis: Virginia Encopresis-Constipation Apperception Test
    Daniel J Cox
    Behavioral Medicine Center, University of Virginia Health System, Charlottesville 22908, USA
    J Pediatr Psychol 28:375-82. 2003
    ..In addition, mothers were also believed to be more discerning than children...
  65. pmc Accuracy and robustness of dynamical tracking of average glycemia (A1c) to provide real-time estimation of hemoglobin A1c using routine self-monitored blood glucose data
    Boris P Kovatchev
    1 University of Virginia, Charlottesville, Virginia
    Diabetes Technol Ther 16:303-9. 2014
    ..However, self-monitored blood glucose (SMBG) readings offer the possibility for real-time estimation of HbA1c. We present a new dynamical method tracking changes in average glycemia to provide real-time estimation of A1c (eA1c)...
  66. pmc DiAs user interface: a patient-centric interface for mobile artificial pancreas systems
    Patrick Keith-Hynes
    Center for Diabetes Technology Research, University of Virginia, 617 West Main St, 4th Floor, Charlottesville, VA 22903
    J Diabetes Sci Technol 7:1416-26. 2013
    ..This work is an initial inquiry involving a relatively small number of potential users, many of whom had never seen an AP system before, and the results should be understood in that light...
  67. pmc Resolving the conundrum of islet transplantation by linking metabolic dysregulation, inflammation, and immune regulation
    Xiaolun Huang
    Department of Surgery, University of Virginia, Charlottesville, Virginia 22908, USA
    Endocr Rev 29:603-30. 2008
    ..This review focuses on interactions between the technical, immunological, and metabolic barriers that must be overcome to optimize the success of this important therapeutic approach...
  68. doi request reprint Analytical methods for the retrieval and interpretation of continuous glucose monitoring data in diabetes
    Boris Kovatchev
    University of Virginia Health System, Charlottesville, Virginia, USA
    Methods Enzymol 454:69-86. 2009
    ..The use of such methods has the potential to enable optimal glycemic control in diabetes and, in the future, artificial pancreas systems...

Research Grants15

  1. MODULAR BIO-BEHAVIORAL CLOSED-LOOP CONTROL OF TYPE 1 DIABETES
    Boris P Kovatchev; Fiscal Year: 2010
    ..A modular approach will also permit incremental testing and deployment of system features, which will structure and facilitate the progress towards the automated closed-loop control commonly known as artificial pancreas. ..
  2. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris P Kovatchev; Fiscal Year: 2010
    ..abstract_text> ..
  3. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2009
    ..abstract_text> ..
  4. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2007
    ..abstract_text> ..
  5. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2006
    ..abstract_text> ..
  6. Bio-Behavioral Feedback and Control of Type 1 Diabetes
    Boris Kovatchev; Fiscal Year: 2005
    ..abstract_text> ..
  7. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2003
    ..Provide dynamic interpretation of continuous BG monitoring data with the goal to forecast the BG fluctuations, and especially the risk for hypoglycemia, within 30 minutes. ..
  8. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2002
    ..Provide dynamic interpretation of continuous BG monitoring data with the goal to forecast the BG fluctuations, and especially the risk for hypoglycemia, within 30 minutes. ..
  9. BIOBEHAVIORAL IRREGULARITY AND CONTROL OF IDDM
    Boris Kovatchev; Fiscal Year: 2000
    ..Phase 3 will validate these protocols using data from ongoing studies at the University of Virginia, the Joslin Diabetes Center, and Amylin Pharmaceuticals. ..
  10. BIOBEHAVIORAL IRREGULARITY AND CONTROL OF IDDM
    Boris Kovatchev; Fiscal Year: 1999
    ..Phase 3 will validate these protocols using data from ongoing studies at the University of Virginia, the Joslin Diabetes Center, and Amylin Pharmaceuticals. ..
  11. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2004
    ..Provide dynamic interpretation of continuous BG monitoring data with the goal to forecast the BG fluctuations, and especially the risk for hypoglycemia, within 30 minutes. ..
  12. Bio-Behavioral Monitoring and Control of IDDM
    Boris Kovatchev; Fiscal Year: 2001
    ..Provide dynamic interpretation of continuous BG monitoring data with the goal to forecast the BG fluctuations, and especially the risk for hypoglycemia, within 30 minutes. ..
  13. MODULAR BIO-BEHAVIORAL CLOSED-LOOP CONTROL OF TYPE 1 DIABETES
    Boris Kovatchev; Fiscal Year: 2009
    ..A modular approach will also permit incremental testing and deployment of system features, which will structure and facilitate the progress towards the automated closed-loop control commonly known as artificial pancreas. ..