1. Heart Rate Variability and renal organ damage in hypertensive patients P. Melilllo 1, R. Izzo 2, N. De Luca 2, and L. Pecchia 1 1 Department of Department of Electronics, Computer Science and Systems, University of Bologna, Italy 2 Departments of Clinical Medicine, Cardiovascular and Immunological Sciences, Federico II University Hospital, Italy 3 Faculty of Engineering, University of Nottingham, United Kingdom paolo.melillo2@unibo.it

2. EMBC 2012 P. Melilllo, C. Formisano, U. Bracale, and L. Pecchia Case study: stress due university examination [1] Student’s death in Naples during university examination Stress affects Autonomous Nervous System (ANS) Heart Rate Variability (HRV) reliable marker of ANS modulation on heart 1. Dimitriev D, Dimitriev A, Karpenko Y, Saperova E (2008) Influence of examination stress and psychoemotional characteristics on the blood pressure and heart rate regulation in female students. Human Physiology 34 (5):617-624. IntroductionMethods and materialsResultsDiscussionConclusion STUDY POPULATION: Hypertensive patients METHODS and MATERIALS: Retrospective analysis on a centralized database Linear analysis of Heart Rate Variability

3. EMBC 2012 P. Melilllo, C. Formisano, U. Bracale, and L. Pecchia Case study: stress due university examination [1] Student’s death in Naples during university examination Stress affects Autonomous Nervous System (ANS) Heart Rate Variability (HRV) reliable marker of ANS modulation on heart 1. Dimitriev D, Dimitriev A, Karpenko Y, Saperova E (2008) Influence of examination stress and psychoemotional characteristics on the blood pressure and heart rate regulation in female students. Human Physiology 34 (5):617-624. IntroductionMethods and materialsResultsDiscussionConclusion STUDY POPULATION: Hypertensive patients METHODS and MATERIALS: Retrospective analysis on a centralized database Linear analysis of Heart Rate Variability

4. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia Hypertensive subjects referred to the Hypertension Clinic of the University of Naples Federico II from 2000 to 2010 Cardiac and carotid ultrasonography evaluation 24h Holter ECG after one-month antihypertensive therapy wash-out Exclusion criteria: diagnosis of secondary resistant and/or uncontrolled hypertension; previous CV disease; clinical history of cancer, liver cirrhosis and/or failure; narcotics abuse or lifestyle changes in the last 12 months Ethical issues compliance with the Human Study Committee regulations of the University of Naples "Federico II“; Informed consent by each subjects. IntroductionMethods and materialsResultsDiscussionConclusion

5. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia Glomerular filtration rate (GFR) estimated by the Modification of Diet in Renal Disease (MDRD) formula no kidney organ damage kidney organ damage Normal GFR Mild GFR Moderate GFR GFR≥90 mL/min/1.73 m 2 6 0<GFR<90 mL/min/1.73 m 2 GFR≤60 mL/min/1.73 m 2 Specifics lifestyle behaviors assessed by a detailed questionnaire Blood pressure measurement according to the current guidelines Serum creatinine, fasting plasma glucose, total-cholesterol, and triglycerides measured with the standard methods IntroductionMethods and materialsResultsDiscussionConclusion

6. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia 6 TIME DOMAIN MEAURES FREQUENCY DOMAIN MEASURES NN INTERVALS TIME SERIES SPECTRUM TP: total spectral power of all NN intervals up to 0.4 Hz [ms 2 ] ULF: spectral power of all NN intervals between 0 and 0.003 Hz [ms 2 ] VLF: spectral power of all NN intervals between 0.003 and 0.04 Hz ([ms 2 ]), LF:spectral power of all NN intervals between 0.04 and 0.15 Hz [ms 2 ] HF: spectral power of all NN intervals between 0.15 and 0.4 Hz [ms 2 ] LF/HF: ratio of low to high frequency power (LF/HF), AVNN : Average of all NN intervals [ms] SDNN : Standard Deviation of all NN intervals [ms] SDANN : Standard Deviation of the averages of NN intervals in all 5 min segments of the entire recording [ms] SDNN IDX: Mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording [ms] rMSSD: square Root of the Mean of the Sum of the Squares of Differences between adjacent NN intervals [ms pNN50: percentage of differences between adjacent NN intervals that are longer than 50 ms Automatic QRS detector HRV analysis according to International Guidelines* using PhysioNet's HRV Toolkit IntroductionMethods and materialsResultsDiscussionConclusion *Malik, M., J. T. Bigger, et al. (1996). "Heart rate variability: Standards of measurement, physiological interpretation, and clinical use." Eur Heart J 17(3): 354-381.

7. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia SDNN, TP, VLF, LF, HF, LF/HF, LF nu significantly decreased HF nu significantly increased * Wilcoxon signed rank test for paired data IntroductionMethods and materialsResultsDiscussionConclusion Overall eGFR NormalMildModerate Age (years)62.4±1256±11.463±11.669.7±9.2** Sex (male/female, %)63.5/46.564.6/35.464.2/35.859.4/40.6 Family history of hypertension (yes/no, %)57/4352.1/47.958.3/41.759.4/40.6 Family history of stroke (yes/no, %)18/8220.8/79.218.3/81.712.5/87.5 Smokers (yes/ex/no, %)17.5/20.5/6227/17/5614/23/6316/19/66 Diabetes (yes/no, %)18/8218.8/81.216.7/83.321.9/78.1 Diastolic BP (mmHg)75.6±11.973.2±13.877.3±11.4*72.6±9.6 Systolic BP (mmHg)133±22.6124±23137±20**129.5±27 Pulse pressure (mmHg)57.5±17.851.3±1460±16.8*57±23.2 Fasting blood glucose (mmHg)102.9±2499.7±31.9102.9±19.9107.4±23.5 Total Cholesterol (mg/dl)186±40.5178.9±36187.7±40.4190.3±45.2 Beta-blockers (yes/no, %)33.5/66.531.3/68.734.2/65.834.4/65.6 Alphabeta-blockers (yes/no,%)10/9010.4/89.611.7/88.33.1/96.9 Alpha-blockers (yes/no, %)8/926.3/93.76.7/93.315.6/84.4 Diuretics (yes/no, %)43/5735.4/64.640.8/59.262.5/37.5* ACE inhibitor (yes/no, %)37/6333.3/66.740/6031.3/68.7 Dihydropyridine (yes/no, %)26/7425/75 31.3/68.7 GFR77.3±18.551.5±6.274.3±8.7101.9±11.8 Kidney Involvement (1/2 /3,%)24/60/16 IMT max2.24±1.561.8±0.76**2.23±1.212.9±2.85 Vascular Involvement (no/ thickening/plague, %)13.5/11/75.519/12/6913/11/766/10/84 LVMi130.2±30.8124.3±25.9132.8±32.1128.9±30.9 Left Ventricular hypertrophy (no/yes, %)40.5/59.550/5037.5/62.5

8. Normal GFRMild GFRModerate GFR p MedianPercentilesMedianPercentilesMedianPercentiles 25 th 75 th 25 th 75 th 25 th 75 th AVNN848.9784.9915.9852.4772.6953.3876.0806.3963.40.36 SDNN119.5102.3146.0111.192.2141.3113.898.3141.10.31 SDANN108.690.2137.099.878.4129.4105.686.0132.40.33 SDNN IDX51.4343.8758.7747.1040.7861.0445.0436.8658.250.24 RMSSD30.0624.5037.7430.5322.4142.0833.6724.6742.060.50 pNN507.683.9411.747.882.7317.7110.064.0712.850.66 TOTPWR161241101223626137849042216071517510303247130.36 ULF1237988641867910708710318480120018215202170.36 VLF15921195236814229612405126081319590.11 LF711.2485.81102.0600.6370.2916.7577.2373.5925.40.15 HF471.3298.8724.5493.4201.8801.5549.728.81230.20.44 LF/HF1.441.172.101.250.911.750.870.721.25<0.001 EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia SDNN, TP, VLF, LF, HF, LF/HF, LF nu significantly decreased HF nu significantly increased * Wilcoxon signed rank test for paired data IntroductionMethods and materialsResultsDiscussionConclusion

9. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia SDNN, TP, VLF, LF, HF, LF/HF, LF nu significantly decreased HF nu significantly increased * Wilcoxon signed rank test for paired data IntroductionMethods and materialsResultsDiscussionConclusion Compared groups HRV measure, factor or covariate βpOR95% CI of OR Normal eGFR versus Moderate eGFR Intercept5.8560.020 LF/HF0.9770.0332.6551.079to6.531 Systolic BP-0.0050.6450.9950.973to1.017 Age-0.104<0.0010.9010.854to0.951 Absence of family history of hypertension 1.1530.0313.1681.109to9.050 Mild eGFR versus Moderate eGFR Intercept0.3220.885 LF/HF0.9930.0232.6991.149to6.341 Systolic BP0.0210.0401.0211.001to1.042 Age-0.0510.0340.9500.906to0.996 Absence of family history of hypertension 0.7580.0912.1340.887to5.138

10. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia Significant decreased LF/HF (marker of sympatho-vagal balance) in moderate eGFR patient group Adjustment for factor / covariate contributing to the development of renal TOD  Expected influence of age and hypertension Previous study (Gargia-Gargia, 2012) failed to show significant relationship maybe because of the lack of frequency domain analysis Consistence with findings of two recent studies: lower HRV (particularly, frequency domain measures) associated with higher risk of progression to end-stage renal disease; autonomic imbalance may lead to kidney damage Garcia-Garcia A, Gomez-Marcos MA, Recio-Rodriguez JI, Patino-Alonso MC, Rodriguez-Sanchez E, Agudo-Conde C, Garcia-Ortiz L: Office and 24-hour heart rate and target organ damage in hypertensive patients. BMC Cardiovasc Disord 2012, 12(1):19. Chandra P, Sands RL, Gillespie BW, Levin NW, Kotanko P, Kiser M, Finkelstein F, Hinderliter A, Pop-Busui R, Rajagopalan S et al: Predictors of heart rate variability and its prognostic significance in chronic kidney disease. Nephrol Dial Transplant 2012, 27(2):700-709. Brotman DJ, Bash LD, Qayyum R, Crews D, Whitsel EA, Astor BC, Coresh J: Heart rate variability predicts ESRD and CKD-related hospitalization. J Am Soc Nephrol 2010, 21(9):1560-1570. IntroductionMethods and materialsResultsDiscussionConclusion

11. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia HRV depression associated with kidney organ damage Decreased LF/HF corroborates the role of autonomic imbalance in kidney damage Autonomic imbalance may lead kidney damage The mechanisms by which abnormal autonomic balance may lead to organ damage are unclear Further studies are need ed: longitudinal and prospective to investigate causal relationship nonlinear and/or point process time-frequency analysis to extract more information from HRV other non-invasive parameters of ANS activity to provide addition information automatic machine learning to develop classifiers able to detect / assess progression of kidney disease IntroductionMethods and materialsResultsDiscussionConclusion

12. EMBC 2012 P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia Brief bibliography: Similar studies Chandra P, et al. Nephrol Dial Transplant 2012, 27(2):700-709. Brotman DJ, et al. J Am Soc Nephrol 2010, 21(9):1560-1570. Garcia-Garcia A, et al. BMC Cardiovasc Disord 2012, 12(1):19. Automatic classification Pecchia L, et al. IEEE Trans Bio Med Eng 2011, 58(3):800-804. Other ANS parameters Melillo P, Pecchia L, et al. Biomed Eng Online 2012, 11(1):40. Nonlinear and Point HRV analysis Melillo P, et al. Biomed Eng Online 2011, 10(1):96. Kodituwakku S, et al. Med Bio Eng Comput 2012, 50(3):261-275. For further details, please refer also to: “Design and assessment of disease management program for cardiac patients via enhanced telemedicine with data-mining and pattern recognition” Ph.D. Thesis by Paolo Melillo, also under press in a book edited by Lambert Academic Publishing ISBN: 978-3-659-22103-3 IntroductionMethods and materialsResultsDiscussionConclusion