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Heart rate variability and falls in Huntington’s disease

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Persons with Huntington's disease (HD) have a high incidence of falls. Autonomic nervous system dysfunction has been reported even in early stages of this disease. To date, there has been no analysis of the relationship between heart rate variability (HRV) and falls in this patient population. The aim of the study reported here was to evaluate the relationship between HRV and falls in persons with HD.


Huntington's disease patients enrolled in a prospective study on fear of falling and falls were assessed using short-term HRV analyses and blood pressure measures in both the resting and standing states. Time–frequency domains and nonlinear parameters were calculated. Data on falls, the risk of falling (RoF) and disease-specific scales were collected at baseline and at the end of the 6-month follow-up.


Of the 24 HD patients who were invited to participate in the study, 20 completed the baseline analysis and 18 completed the 6-month follow-up. At baseline, seven (35%) HD patients reported at least one fall (single fallers) and 13 (65%) reported ≥ 2 falls (recurrent fallers) in the previous 12 months. At baseline, recurrent fallers had lower RMSSD (root mean square of successive RR interval differences) in the resting state (RMSSD-resting), higher LF/HF (low/high frequency) ratio in both states and higher DFA-α1 parameter (detrended fluctuation analyses over the short term) in both states. This association was similar at the 6-month follow-up for recurrent fallers, who showed lower RMSSD-resting and higher LF/HF ratio in the standing state (LF/HF-standing) than single fallers. Significant correlations were found between the number of falls, RMSSD-resting and LF/HF-standing. No differences were found between recurrent and single fallers for any blood pressure measures.


The observed HRV pattern is consistent with a higher sympathetic prevalence associated with a higher RoF. Reduced parasympathetic HRV values in this patient population predict being a recurrent faller at 6 months of follow-up, independently of orthostatic phenomena.

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  1. Jernigan TL, Salmon DP, Butters N, Hesselink JR (1991) Cerebral structure on MRI, part II: specific changes in Alzheimer’s and Huntington’s diseases. Biol Psychiatry 29(1):68–81

    Article  CAS  PubMed  Google Scholar 

  2. Vuong K, Canning CG, Menant JC, Loy CT (2018) Gait, balance, and falls in Huntington disease. Handbook of clinical neurology. Elsevier, Amsterdam

    Google Scholar 

  3. Grimbergen YAM, Knol MJ, Bloem BR, Kremer BPH, Roos RAC, Munneke M (2008) Falls and gait disturbances in Huntington’s disease. Mov Disord 23(7):970–976

    Article  PubMed  Google Scholar 

  4. Busse ME, Khalil H, Quinn L, Rosser AE (2008) Physical therapy intervention for people with Huntington disease. Phys Ther 88(7):820–831

    Article  PubMed  Google Scholar 

  5. Wheelock VL, Tempkin T, Marder K, et al (2003) Predictors of nursing home placement in huntington disease. Neurology 60(6):998–1001

    Article  CAS  PubMed  Google Scholar 

  6. Nocua R, Noury N, Gehin C, Dittmar A, McAdams E (2009) Evaluation of the autonomic nervous system for fall detection. In: EMBC 2009: Proceedings of the 31st annual international conference of the IEEE engineering in medicine and biology society: engineering the future of biomedicine, 2–6 September 2009, Hilton Minneapolis, Minnesota. IEEE, Piscataway, NJ

  7. Stolze H, Klebe S, Zechlin C, Baecker C, Friege L, Deuschl G (2004) Falls in frequent neurological diseases: prevalence, risk factors and aetiology. J Neurol 251(1):79–84

    Article  PubMed  Google Scholar 

  8. Melillo P, Castaldo R, Izzo R, De Luca N, Pecchia L (2017) Fall prediction in hypertensive patients via short-term HRV analysis. IEEE J Biomed Health Inform 21(2):399–406

    Article  PubMed  Google Scholar 

  9. Razjouyan J, Grewal GS, Rishel C, Parthasarathy S, Mohler JNB (2012) Activity monitoring and heart rate variability as indicators of fall risk. J Gerontol Nurs 43(7):1–10

    Google Scholar 

  10. Andrich J, Schmitz T, Saft C, et al (2002) Autonomic nervous system function in Huntington’s disease. J Neurol Neurosurg Psychiatry 72(6):726–731

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sharma K (2002) Sympathetic skin response and the heart rate variability in patients with Huntington’s disease. Electroencephalogr Clin Neurophysiol 103(1):138

    Article  Google Scholar 

  12. Bär KJ, Boettger MK, Andrich J, et al (2008) Cardiovagal modulation upon postural change is altered in Huntington’s disease. Eur J Neurol 15(8):869–871

    Article  PubMed  Google Scholar 

  13. Cankar K, Melik Z, Kobal J, Starc V (2018) Evidence of cardiac electrical remodeling in patients with Huntington disease. Brain Behav 8(8):1–9

    Article  Google Scholar 

  14. Diago EB, Pérez JP, Lasaosa SS, et al (2017) Circadian rhythm and autonomic dysfunction in presymptomatic and early Huntington’s disease. Park Relat Disord 44:95–100

    Article  Google Scholar 

  15. Kobal J, Meglič B, Mesec A, Peterlin B (2004) Early sympathetic hyperactivity in Huntington’s disease. Eur J Neurol 11(12):842–848

    Article  CAS  PubMed  Google Scholar 

  16. Diago EB, Pérez JP, Lasaosa SS, et al (2018) Neurocardiovascular pathology in pre-manifest and early-stage Huntington’s disease. Eur J Neurol 25(7):956–962

    Article  Google Scholar 

  17. Benarroch EE (1993) The central autonomic network: functional organization, dysfunction, and perspective. Mayo Clin Proc 68(10):988–1001

    Article  CAS  PubMed  Google Scholar 

  18. Rosas HD, Salas DH, Lee SY, et al (2008) Cerebral cortex and the cinical expression of Huntington’s disease: complexity and heterogeneity. Brain 131(4):1057–1068

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hegde R, Sudarshan B, Kumar SCP, Hariprasad S, Satyanarayana B (2013) Technical advances in fall detection system—a review. Int J Comput Sci Mob Comput 2:152–160

    Google Scholar 

  20. Boyé NDA, Mattaceraso FUS, Van LEMM, Hartholt KA (2015) Physical performance and quality of life in single and recurrent fallers: data from the Improving Medication Prescribing to Reduce Risk of Falls study. Geriatr Gerontol Int 15:350–355

    Article  PubMed  Google Scholar 

  21. Gibson M, Andres R, Isaacs BW (1987) The prevention of falls in later life. A report of the Kellogg International Work Group on the Prevention of Falls by the Elderly. Dan Med Bull 34(S4):1–24

    Google Scholar 

  22. Berg KO, Wood-Dauphinee SL, Williams JIMB (1992) Measuring balance in the elderly: validation of an instrument. Can J Public Health 83(2):S7–91

    PubMed  Google Scholar 

  23. Mestre TA (2018) Rating scales and performance-based measures for assessment of functional ability in huntington ’s disease: critique and recommendations performance-based. Mov Disord Clin Pract 5(4):361–372

    Article  PubMed  PubMed Central  Google Scholar 

  24. Podsiadlo D, Richardson S (1991) The timed “up and go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 39:142–148

    Article  CAS  PubMed  Google Scholar 

  25. Quinn L, Khalil H, Dawes H, et al (2013) Reliability and minimal detectable change of physical performance measures in individuals with pre-manifest and manifest Huntington disease. Phys Ther 93(7):942–956

    Article  PubMed  Google Scholar 

  26. Tinetti ME (1986) Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc 34:119–126

    Article  CAS  PubMed  Google Scholar 

  27. Kloos AD, Kegelmeyer DA, Young GS, Kostyk SK (2010) Fall risk assessment using the tinetti mobility test in individuals with Huntington’s disease. Mov Dis 25(16):2838–2844

    Article  Google Scholar 

  28. Lamb SE, Jørstad-Stein EC, Hauer K, Becker C (2005) Development of a common outcome data set for fall injury prevention trials: the prevention of falls network Europe consensus. J Am Geriatr Soc 53(9):1618–1622

    Article  PubMed  Google Scholar 

  29. Freeman R, Wieling W, Axelrod FB, Benditt DG, Benarroch E (2011) Consensus statement on the definition of orthostatic hypotension, neurally mediated syncope and the postural tachycardia syndrome. Clin Auton Res 21:69–72

    Article  PubMed  Google Scholar 

  30. Tarvainen MP, Ranta-aho PO, Karjalainen PA, Lipponen JA, van Iersel MB (2013) Kubios HRV: heart rate variability analysis software. Comput Methods Programs Biomed 113(1):210–220

    Article  PubMed  Google Scholar 

  31. Ho KK, Moody GB, Peng CK, et al (1997) Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics. Circulation 96:842–848

    Article  CAS  PubMed  Google Scholar 

  32. Malik M, Bigger JT, Camm AJ et al (1996) Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Eur Heart J 17(3):354–381

    Article  Google Scholar 

  33. Tarkiainen TH, Kuusela TA, Tahvanainen KUO, et al (2007) Comparison of methods for editing of ectopic beats in measurements of short-term non-linear heart rate dynamics. Clin Physiol Funct Imaging 27(2):126–133

    Article  PubMed  Google Scholar 

  34. Seely A, Macklem P, Seeley AJE, Macklem PT (2005) Complex systems and the technology of variability analysis. Crit Care 8(6):R367–384

    Article  Google Scholar 

  35. Iyengar N, Peng CK, Morin R, Goldberger AL, Lipsitz LA (1996) Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. Am J Physiol 271(4 Pt 2):R1078–1084

    CAS  PubMed  Google Scholar 

  36. Richman JS, Moorman JR (2017) Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Circ Physiol 278(6):H2039–2049

    Article  Google Scholar 

  37. Vigo DE, Dominguez J, Guinjoan SM, et al (2010) Nonlinear analysis of heart rate variability within independent frequency components during the sleep-wake cycle. Auton Neurosci Basic Clin 154(1–2):84–88

    Article  Google Scholar 

  38. Hayano J, Yuda E (2019) Pitfalls of assessment of autonomic function by heart rate variability. J Physiol Anthrop 38:3

    Article  Google Scholar 

  39. Bird ED (1997) Neuroendocrine changes in Huntington’s disease. Adv Neurol 23:291–297

    Google Scholar 

  40. Melik Z, Kobal J, Cankar K, Strucl M (2012) Microcirculation response to local cooling in patients with Huntington’s disease. J Neurol 259(5):921–928

    Article  PubMed  Google Scholar 

  41. Kobal J, Melik Z, Cankar K, et al (2010) Autonomic dysfunction in presymptomatic and early symptomatic Huntington’s disease. Acta Neurol Scand 121(6):392–399

    Article  CAS  PubMed  Google Scholar 

  42. Sannino G, Melillo P, Stranges S, De Pietro G, Pecchia L (2015) Short term heart rate variability to predict blood pressure drops due to standing: a pilot study. BMC Med Inform Decis Maks 15(3):S2

    Article  Google Scholar 

  43. Sannino G, Melillo P, Pietro G, Stranges S, Pecchia L (2014) To what extent it is possible to predict falls due to standing hypotension by using HRV and wearable devices? Study design and preliminary results from a proof-of-concept study. In: Pecchia L, Chen LL, Nugent C, Bravo J (eds) Ambient assisted living and daily activities (Lecture Notes in Computer Science, vol 8868). International Workshop on Ambient Assisted Living (IWAAL) 2014. Springer, Berlin, pp 167–170

  44. Barbic F, Perego F, Canesi M et al (2007) Early abnormalities of vascular and cardiac autonomic control in Parkinson’s disease without orthostatic hypotension. Hypertension 49(1):120–126

    Article  CAS  PubMed  Google Scholar 

  45. Goldstein DS, Holmes CS, Dendi R et al (2002) Orthostatic hypotension from sympathetic denervation in Parkinson’s disease. Neurology 58:1247–1255

    Article  CAS  PubMed  Google Scholar 

  46. Di Pardo A, Carrizo A, Damato A et al (2017) Motor phenotype is not associated with vascular dysfunction in symptomatic Huntington's disease transgenic R6/2 (160 CAG) mice. Sci Rep 17(7):42797

    Article  CAS  Google Scholar 

  47. Park S, Colwell S (2019) Do disruptions in the circadian timing system contribute to autonomic dysfunction in Huntington’s disease? Yale J Biol Med 92(2):291–303

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Young WR, Williams AM (2015) How fear of falling can increase the risk of falls in older adults: applying psychological theory to practical observations. Gait Posture 41(1):7–12

    Article  PubMed  Google Scholar 

  49. Kreibig SD (2010) Autonomic nervous system activity in emotion: A review. Biol Psychol 84:394–421

    Article  PubMed  Google Scholar 

  50. Kim HG, Cheon EJ, Bai DS, Lee YH, Koo BH (2018) Stress and heart rate variability: a meta-analysis and review of the literature. Psychiatry Investig 15(3):235–245

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wu R, Gu R, Yang K, Luo YJ (2019) How do amusement, anger and fear influence heart rate and heart rate variability? Front Neurosci 18(13):1131

    Article  Google Scholar 

  52. Purcell NL, Goldman JG, Ouyang B, Bernard B, O’Keefe JA (2019) The effects of dual-task cognitive interference and environmental challenges on balance in Huntington’s disease. Mov Disord Clin Pract 6(3):202–212

    Article  PubMed  PubMed Central  Google Scholar 

  53. Milan-Mattos JC, Porta A, Perseguini NM, et al (2018) Influence of age and gender on the phase and strength of the relation between heart period and systolic blood pressure spontaneous fluctuations. J Appl Physiol 124(3):791–804

    Article  CAS  PubMed  Google Scholar 

  54. Vittinghof E, McCulloch CE (2006) Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol 165:710–718

    Article  Google Scholar 

  55. Pavlou M, Ambler G, Seaman SR, Guttmann O, Elliott P et al (2015) How to develop a more accurate risk prediction model when there are few events. BMJ 351:h3868

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Author contributions

CTC, VB, DEV and MM conceptualized and designed the initial project of this manuscript. CTC, VB, DEV and MM made the final research plan. CTC, VB, DEV and MM ran the statistical analyses and made a definitive interpretation of the findings. CTC, VB, DEV and MM wrote the first version of the manuscript. All authors edited and approved the final version of the manuscript.


CTC is a doctoral research fellow from CONICET and received a research award from Fundación HD Lorena Scarafiocca, Buenos Aires, Argentina. The funding agencies did not have a role in the development of the study, analysis of data, and writing of the manuscript.

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Written informed consent was obtained from all the participants after a detailed explanation of the procedures. The local Ethics Committee approved the study, which followed all of the ethical standards set out in the Declaration of Helsinki of 1964 and its later amendments.

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None of the authors have any conflicts of interest to report.

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Correspondence to Marcelo Merello.

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Terroba-Chambi, C., Bruno, V., Vigo, D.E. et al. Heart rate variability and falls in Huntington’s disease. Clin Auton Res 31, 281–292 (2021).

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