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Pharmacodynamic Evaluation: Cardiovascular Methodologies

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Abstract

Cardiovascular methods to assess pharmacodynamics nowadays evolve very quickly, due to rapid progress in high technology and IT sector. Noteworthy, mathematical approach grows very fast in new algorithms to analyze the heart signal. Many areas of multiple organ damage will relay in very complex software and hardware innovations. Basics for this growth is understanding of previously unknown mechanisms of control of physiological functioning like heart stiffness and compliance. Other reasons go to research in Shannon’s entropy and derived calculations. On the other hand, some previous methods have been surpassed like arterial pulse methods when it comes to pharmacodynamics research. It is of importance also to take into account rare diseases and various channelopathies that may interfere with pharmacodynamics evaluation on large-scale clinical trials. In phases III and IV of clinical research, those factors may influence final statistical results. New tests and old proven measures of hemodynamic stabilities are required to evaluate new therapeutics during clinical studies to be able to treat more people on pharmacogenetic basis with pharmacogenomic approach. Safety to treat with new drugs comes into the first place, so many requirements in monitoring of data gathered by contract research organization (CRO) are necessary to get the approval of FDA and European Medicines Agency (EMA) is the European Union’s equivalent to the U.S. Food and Drug Administration (FDA). Those approvals mainly rely on pharmacodynamics data pooled out from clinical drug researches. To be more rapidly accessible, adverse effects are collected via wireless technologies and monitored on wider basis across multicentric studies. Therefore, guidelines on consistent methodology toward new therapeutics approach are adopted constantly.

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References and Further Reading

  • Abdelghani SA, Rosenthal TM, Morin DP (2016) Surface electrocardiogram predictors of sudden cardiac arrest. Ochsner J 16(3):280–289

    PubMed  PubMed Central  Google Scholar 

  • Abduch MC, Alencar AM, Mathias W Jr et al (2014) Cardiac mechanics evaluated by speckle tracking echocardiography. Arq Bras Cardiol 102(4):403–412

    PubMed  PubMed Central  Google Scholar 

  • Bauer A, Malik M, Schmidt G et al (2008a) Heart rate turbulence: standards of measurement, physiological interpretation, and clinical use: international society for holter and noninvasive electrophysiology consensus. J Am Coll Cardiol 52(17):1353–1365

    Article  PubMed  Google Scholar 

  • Bauer A, Malik M, Schmidt G et al (2008b) Heart rate turbulence: standards of measurement, physiological interpretation, and clinical use: international society for holter and noninvasive electrophysiology consensus. J Am Coll Cardiol 52(17):1353–1365

    Article  PubMed  Google Scholar 

  • Butlin M, Qasem A (2017) Large artery stiffness assessment using sphygmoCor technology. Pulse 4(4):180–192

    Article  PubMed  Google Scholar 

  • Chia YC, Buranakitjaroen P, Chen CH et al (2017) Current status of home blood pressure monitoring in Asia: statement from the HOPE Asia network. J Clin Hypertens. https://doi.org/10.1111/jch.13058. [Epub ahead of print]

  • Chiang CE, Wang TD, Lin TH et al (2017) The 2017 focused update of the guidelines of the Taiwan society of cardiology (TSOC) and the Taiwan hypertension society (THS) for the management of hypertension. Acta Cardiol Sin 33(3):213–225

    PubMed  PubMed Central  Google Scholar 

  • Claus P, Omar AMS, Pedrizzetti G et al (2015) Tissue tracking technology for assessing cardiac mechanics: principles, normal values, and clinical applications. JACC Cardiovasc Imaging 8(12):1444–1460

    Article  PubMed  Google Scholar 

  • Coris EE, Moran BK, De Cuba R et al (2016) Left ventricular non-compaction in athletes: to play or not to play. Sports Med 46(9):1249–1259

    Article  PubMed  Google Scholar 

  • Fung E, Järvelin MR, Doshi RN (2015) Electrocardiographic patch devices and contemporary wireless cardiac monitoring. Front Physiol 6:149

    Article  PubMed  PubMed Central  Google Scholar 

  • Garcia EV, Pastore CA, Samesima N et al (2011) T-wave alternans: clinical performance, limitations and analysis methodologies. Arq Bras Cardiol 96(3):e53–e61

    Article  PubMed  Google Scholar 

  • Gimeno-Blanes FJ, Blanco-Velasco M, Barquero-Pérez Ó et al (2016) Sudden cardiac risk stratification with electrocardiographic indices – a review on computational processing, technology transfer, and scientific evidence. Front Physiol 7:82

    Article  PubMed  PubMed Central  Google Scholar 

  • Gulizia MM, Casolo G, Zuin G et al (2016) ANMCO/AIIC/SIT consensus document: definition, precision and appropriateness of the electrocardiographic signal of electrocardiographic recorders, ergometry systems, Holter systems, telemetry and bedside monitors. G Ital Cardiol 17(6):393–415

    Google Scholar 

  • Haugaa KH, Smedsrud MK, Steen T et al (2010) Mechanical dispersion assessed by myocardial strain in patients after myocardial infarction for risk prediction of ventricular arrhythmia. JACC Cardiovasc Imaging 3(3):247–256

    Article  PubMed  Google Scholar 

  • Haugaa KH, Grenne BL, Eek CH et al (2013) Strain echocardiography improves risk prediction of ventricular arrhythmias after myocardial infarction. JACC Cardiovasc Imaging 6(8):841–850

    Article  PubMed  Google Scholar 

  • Huikuri HV, Stein PK (2013) Heart rate variability in risk stratification of cardiac patients. Prog Cardiovasc Dis 56(2):153–159

    Article  PubMed  Google Scholar 

  • Huikuri HV, Perkiömäki JS, Maestri R et al (2009) Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics. Philos Trans A Math Phys Eng Sci 367(1892):1223–1238

    Article  PubMed  Google Scholar 

  • Iwano H, Yamada S, Watanabe M et al (2011) Novel strain rate index of contractility loss caused by mechanical dyssynchrony. A predictor of response to cardiac resynchronization therapy. Circ J 75(9):2167–2175

    Article  PubMed  Google Scholar 

  • James PA, Oparil S, Carter BL et al (2014) 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the eighth joint National Committee (JNC 8). JAMA 311(5):507–520

    Article  CAS  PubMed  Google Scholar 

  • Klaeboe LG, Haland TF, Leren IS et al (2017) Prognostic value of left ventricular deformation parameters in patients with severe aortic stenosis: a pilot study of the usefulness of strain echocardiography. J Am Soc Echocardiogr 30(8):727–735

    Article  PubMed  Google Scholar 

  • Kocabay G, Muraru D, Peluso D et al (2014) Normal left ventricular mechanics by two-dimensional speckle-tracking echocardiography. Reference values in healthy adults. Rev Esp Cardiol (Engl Ed) 67(8):651–658

    Article  Google Scholar 

  • Lee PY, Liew SM, Abdullah A et al (2015) Healthcare professionals’ and policy makers’ views on implementing a clinical practice guideline of hypertension management: a qualitative study. PLoS One 10(5):e0126191. https://doi.org/10.1371/journal.pone.0126191. eCollection 2015

    Article  PubMed  PubMed Central  Google Scholar 

  • Leren IS, Saberniak J, Haland TF et al (2017) Combination of ECG and echocardiography for identification of arrhythmic events in early ARVC. JACC Cardiovasc Imaging 10(5):503–513

    Article  PubMed  Google Scholar 

  • Liu J, McKenna TM, Gribok A et al (2008) A fuzzy logic algorithm to assign confidence levels to heart and respiratory rate time series. Physiol Meas 29(1):81–94

    Article  PubMed  Google Scholar 

  • Luebbert J, Auberson D, Marchlinski F (2016) Premature ventricular complexes in apparently normal hearts. Card Electrophysiol Clin 8(3):503–514

    Article  PubMed  Google Scholar 

  • Mc Kinstry B, Hanley J, Lewis S (2015) Telemonitoring in the management of high blood pressure. Curr Pharm Des 21(6):823–827

    Article  CAS  PubMed  Google Scholar 

  • O’Brien E, Sheridan J, O’Malley K (1988) Dippers and non-dippers. Lancet 2(8607):397

    Article  PubMed  Google Scholar 

  • O’Brien E, Petrie J, Littler W et al (1993) An outline of the revised British hypertension society protocol for the evaluation of blood pressure measuring devices. J Hypertens 11(6):677–679

    Article  PubMed  Google Scholar 

  • O’Brien E, Coats A, Owens P et al (2000) Use and interpretation of ambulatory blood pressure monitoring: recommendations of the British hypertension society. BMJ 320(7242):1128–1134

    Article  PubMed  PubMed Central  Google Scholar 

  • Olsen FJ, Biering-Sørensen T, Krieger DW (2015) An update on insertable cardiac monitors: examining the latest clinical evidence and technology for arrhythmia management. Futur Cardiol 11(3):333–346

    Article  CAS  Google Scholar 

  • Pincus SM (1991) Approximate entropy as a measure of system complexity. Proc Natl Acad Sci U S A 88(6):2297–2301

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shibao C, Lipsitz LA, Biaggioni I (2013) Evaluation and treatment of orthostatic hypotension. J Am Soc Hypertens 7(4):317–324

    Article  PubMed  PubMed Central  Google Scholar 

  • Shrout T, Rudy DW, Piascik MT (2017) Hypertension update, JNC8 and beyond. Curr Opin Pharmacol 33:41–46

    Article  CAS  PubMed  Google Scholar 

  • Sokolow M, Werdegar D, Kain HK et al (1966) Relationship between level of blood pressure measured casually and by portable recorders and severity of complications in essential hypertension. Circulation 34(2):279–298

    Article  CAS  PubMed  Google Scholar 

  • Thomas GP, Daichi S, Haas D (2006) Ambulatory blood-pressure monitoring. N Engl J Med 354:2368–2374

    Article  Google Scholar 

  • Verdecchia P, Angeli F, Gattobigio R (2004) Clinical usefulness of ambulatory blood pressure monitoring. J Am Soc Nephrol 15(Suppl 1):S30–S33

    Article  PubMed  Google Scholar 

  • Verrier RL, Ikeda T (2013) Ambulatory ECG-based T-wave alternans monitoring for risk assessment and guiding medical therapy: mechanisms and clinical applications. Prog Cardiovasc Dis 56(2):172–185

    Article  PubMed  Google Scholar 

  • Voss A, Kurths J, Kleiner HJ et al (1996) The application of methods of non-linear dynamics for the improved and predictive recognition of patients threatened by sudden cardiac death. Cardiovasc Res 31(3):419–433

    Article  CAS  PubMed  Google Scholar 

  • Watanabe MA (2003) Heart rate turbulence: a review. Indian Pacing Electrophysiol J 3(1):10–22

    PubMed  PubMed Central  Google Scholar 

  • Wood PW, Boulanger P, Padwal RS (2017) Home blood pressure telemonitoring: rationale for use, required elements, and barriers to implementation in Canada. Can J Cardiol 33(5):619–625

    Article  PubMed  Google Scholar 

  • Zhou JC, Zhang N, Zhang ZH et al (2017) Intensive blood pressure control in patients with acute type B aortic dissection (RAID): study protocol for randomized controlled trial. J Thorac Dis 9(5):1369–1374

    Article  PubMed  PubMed Central  Google Scholar 

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Correspondence to Ivana I. Vranic .

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Vranic, I.I. (2018). Pharmacodynamic Evaluation: Cardiovascular Methodologies. In: Hock, F., Gralinski, M. (eds) Drug Discovery and Evaluation: Methods in Clinical Pharmacology. Springer, Cham. https://doi.org/10.1007/978-3-319-56637-5_31-1

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  • DOI: https://doi.org/10.1007/978-3-319-56637-5_31-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56637-5

  • Online ISBN: 978-3-319-56637-5

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